Authors:
Dr Mirko Winkler, Mr Christian Nyaundi, Ms Astrid Knoblauch,
Mr Zakari Madougou, Dr Mark Divall
February 2012, Final Report
Address all correspondence to Dr Mark Divall
mdivall@shapeconsulting.org
This report has been prepared by Shape Consulting, with all reasonable skill, care and
diligence within the terms of the contract with the client, and taking account of the resources
devoted to it by agreement with the client. We disclaim any responsibility to the client and
others in respect of any matters outside the scope of the above. This report is confidential to
the client and we accept no responsibility of whatsoever nature to third parties to whom this
report, or any part thereof, is made known. Any such party relies on the report at their own
risk.
© Shape Consulting Limited. 2011. All rights reserved.
This report is prepared solely for the benefit of, and use by, SNC-Lavalin Environnement and Rio Tinto Iron
ore Atlantic Limited and Simfer S.A. and may not be sold, reproduced or in any other way copied or transferred
by the customer to anyone else, whether in whole or in part. Shape Consulting owns and retains all intellectual
property rights in this report including, without limiting the generality of foregoing, all copyrights.
Rio Tinto Iron Ore Atlantic Ltd, Simfer SA
Port Site – Forécariah, Kaback
Baseline Health Survey
February 2012
Acknowledgements
Shape Consulting Limited would like to acknowledge the following individuals for the support
provided in planning and performing this baseline health survey in conjunction with the Rio
Tinto Simandou Project, which was carried out in October 2011.
Rio Tinto- Simfer S.A.
Community manager
Superintendant communities
Community liaison officer
SNC Lavalin Environnement
Guy Poirier
Logistics manager
Michel Bureau
Logistics manager
Richard Fontaine
Vice-president special projects
Chantal Roy
Project Manager
Claudia Paz-Miller
Project Assistant
Clinique Ambroise Paré
Dr Mohamed Magassouba
Country Director, HKI-Guinea
Ministère de la Santé et de l’Hygiène Publique
Dr Alpha Ahmadou Diallo
Responsible of Research and Documentation Department
Members of the ‘Comité National d’Ethique pour la Recherche en Santé’
Helen Keller International
Zakari Madougou
Country Director, HKI-Guinea
Ibrahim Fofanah
Field and Laboratory Services Coordinator
Idrissa Diallo
Laboratory Technician
Soumah Kadiatou
Laboratory Technician
Lansana Mansadouno
Data Analyst
Folahan Esther Tolulope
Survey preparation and data analysis support
Clinical Field Unit Team
Dr Bangaly Douno
Treatment Officer
Dr Lamine Keita
Nutritional Officer
Dr Mory Sangaré
Nutritional Officer
Moustapha Touré
Phlebotomy Haematologist
Sékouba Souaré
Phlebotomy Haematologist
Interview Team
Deen Touré
Interviewer
Kémoko Cissoko
Interviewer
Mabinty Camara
Interviewer
Dr Mafoundia Soumaré
Interviewer
Dr Nouman Diakité
Interviewer
Tamba Célestin Millimono
Interviewer
SHAPE Consulting Limited
Dr Mark Divall
Project Director
Dr Mirko Winkler
Field Project Director and Manager
Christian Nyaundi
Epidemiologist
Astrid Knoblauch
Epidemiologist
Joan Angel
Project Administrator
Catherine Garcia
Frédéric Chenais
Dr Kékoura Camara
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While each individual cannot be named, the communities surrounding the Port Site
Development project in Kaback and Forécariah area also deserve special mention for
participating in the survey.
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Executive Summary
Introduction
Rio Tinto Iron Ore Atlantic Ltd (Rio Tinto) through their local entity in Guinea, Simfer S.A. is
in the process of conducting feasibility studies to develop the world class Simandou Iron Ore
Project (Project) in the Republic of Guinea. The mining area is located in the Guinée
Forestière and Haute Guinée regions of Guinea some 700 km to the east of the capital,
Conakry. As part of the Project, Rio Tinto is planning to develop a deep-water port 40 km
south of Conakry, in Forécariah prefecture1. The development will include a stockyard (~600
ha) for the iron ore that will arrive via the 700 km railroad and a conveyor (~25 km) that will
cross the island of Kaback to the deep-water port.
The Project follows its own community relation standards with the stated goal to support
regional and local community based projects that contribute to sustainable development.
Furthermore, International Finance Corporation (IFC) is a partner in the Project, holding a
share of 5% and thus the project is being development according to the IFC social and
environmental sustainability performance standards as good international industry practice
(GIIP).
Consistent with IFC and corporate standards, a health impact assessment (HIA) of the
proposed deep-water port development project was commissioned as part of the feasibility
studies with a formal, detailed community health management plan (CHMP) as an ultimate
deliverable and management tool. The principal goals of the HIA are as follows:
•
to align and benchmark the current operations and future project developments with
GIIP and standards and such as the environmental and social performance standards
(PS) of the IFC, and more specifically PS4 which addresses community health, safety
and security;
•
to provide the operations with evidence based recommendations to manage potential
community health impacts related to the Project and also determine opportunities for
1
The names of some of the villages mentioned in this report may differ from the official name list established by
the project.
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voluntary contributions (social investment programme) that can enhance community
health in the potentially affected communities; and
•
use the process to develop relationships with a broad range of stakeholders to
support community health programmes based on the following sustainability criteria:
o
align community health activities to ensure that they are based on risk and priority
but also so that community health interventions or programmes are appropriately
scoped, planned, resourced and measured; and
o
measure and report on community health activities based not only on outcomes
but also on impacts.
In order to define the terms of reference (ToR) for the HIA, a HIA scoping study of the Port
development was performed in September 2010. In this process it was concluded that
additional primary baseline data should be collected by conducting a baseline health survey
(BHS). This report presents this outcome.
Baseline Health Survey
The BHS in the zone of influence of the proposed Port Development Project in Forécariah
prefecture had the following objectives:
•
describe an improved knowledge of the existing health conditions and health status of
the communities surrounding the Port Development Project by means of a descriptive
study;
•
provide the required evidence to support the modelling of potential health impacts on
the communities who may be affected by the project; and
•
provide information that the Project can consider for the development and
surveillance (monitoring and evaluation) of community health interventions, either as
part of the mitigation strategy of project-related impacts or as negotiated
commitments/ voluntary contributions that the company may consider as social
investment related to community health.
Methodology
The applied methodology has been specifically developed for HIA of industrial development
projects and is based on a modular, cross-sectional study design. The modular nature of the
methodology facilitates the adaptation of the BHS to the prevailing eco-epidemiological
characteristics of the project setting, covering a multiplicity of health outcomes and
determinants at different levels and scales. The sample selection was based on a three
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staged sampling procedure with the stratification of the project affected population into
potentially affected communities (PACs) in the first stage, the selection of primary sampling
units (sentinel sites) within the PACs in the second stage and a random selection of
households, individuals, community or environmental determinants in the third stage.
This methodology will support easily reproducible surveillance at either individual areas or
when pooled across the whole community. It will also allow for measurement of specific
elements of the study based on interventions or pure surveillance of impacts.
The BHS for the Port Development Project included the following data collection modules:
•
Household questionnaire survey to assess knowledge, attitude and practices
(KAPs) in relation to specific public health topics at the individual level in the adult
male and female population (questionnaire survey). This was performed using a pretested questionnaire in defined population groups at the selected sentinel sites (SS).
The questionnaires included a wide variety of subjects which addressed both biophysical and social determinants of health.
•
Clinical field unit where specific samples were taken from individuals linked to
households selected in the KAP study. This included: (i) determination of the
prevalence of malaria in children aged 6-59 months; (ii) determination of the
prevalence and intensity of anaemia in children aged 6-59 months and in women of
reproductive age (aged 15-49 years); (iii) determination of anthropometric
measurements in children aged 6-59 months; (iv) determination of blood pressure in
adults; and (v) determination of present or past syphilis infection in women of
reproductive age.
•
Parasitological survey in schoolchildren (aged 10-15 years) to determine the
prevalence and intensity of schistosomiasis and soil-transmitted helminth infections.
Stool and urine samples were collected among children in schools that were readily
linked to the selected SS for this purpose.
•
Drinking water source and end-user water quality analysis to determine the level
and origin of biological contamination in drinking water. Drinking water samples were
collected at functioning community drinking water sources and at the end user points
in selected households. These water samples were subsequently analysed for the
presence of thermo-tolerant coliform bacteria to provide an indication of faecal
contamination.
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•
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Service and infrastructure assessment to assess key parameters facilities in the
wider project area. This included the evaluation of available services, availability of
essential drugs and consumables, general infrastructure, human resources and
patient load.
Specific tools and strategies were developed for the respective surveys. The topics and
questionnaire guides were selected based on the data gaps and surveillance requirements
identified in the HIA scoping study. The questionnaires were developed combining a variety
of validated questionnaires that have been used in similar settings in sub-Saharan Africa, as
well as those that have been utilised in Guinea, such as the National Demographic and
Health Surveys (DHS)
Survey Activities
As an initial step, a formal study protocol was developed for submission to the National
Ethics Committee for Health Research (‘Le Comité National d’Ethique pour la Recherche en
Santé’) for ethical approval. SHAPE Consulting Limited (SHAPE) developed and submitted
the study protocol for review and approval. The final ethics review committee approval is
attached in Appendix A.
Stakeholder sensitisation and consultation activities were carried out prior to the field survey
to promote prior and informed consent as well as to ensure appropriate support. This
included information sessions with the national (Ministry of Health (MoH), Conakry) and local
health authorities (Directeur Préfectoral de Santé de Forécariah) who authorised the
activities in the form of an ‘Ordre de Mission’ as attached in Appendix B. Furthermore, the
sensitisation and consultation activities were extended to the communities in the proposed
sampling area. These activities were supported by the Rio Tinto community department and
included meetings with village leaders and community members to inform them about survey
objectives, activities and the planned sampling schedule in the selected communities. Preprepared posters of the activities were used to support these activities so that the community
could have an idea what to expect from the survey and to note some frequently asked
questions. These were posted in key visible areas in the community along with the proposed
sampling schedule.
The survey team was trained prior to the initiation of the survey. This included sessions on
the objectives of the survey, community code of conduct, planned activities and then on their
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specific tasks, document control and quality assurance. The team were also induced on the
Rio Tinto health, safety, environment and community policy.
The field component of the survey was conducted from the 11th of October 2011 to the 20th of
October 2011.
The following samples were collected in the survey activities:
•
384 questionnaires were conducted in the questionnaire surveys, representing 31.4%
of the households of the 8 selected SS, with women serving as primary respondents
as per the inclusion criteria. Overall, 254 women and 130 men participated in the
questionnaire survey.
•
769 individuals were sampled at the clinical field unit. This represents approximately
8.9% of the selected population (i.e. children <5 years and adults >15 years).
•
240 urine and 240 stool samples were collected from schoolchildren (aged 10-15
years);
•
a total of 26 community drinking water collection points and 79 households were
sampled for water quality testing; and
•
3 health facilities were assessed.
As part of the ethical requirements, health conditions identified in the course of the BHS that
needed interventions were treated. This included treatment at the clinical field unit or referral
to the local health facilities.
Key Findings
The key findings of the BHS are summarized in Table 1.
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Table 1: Key findings
Malaria
The malaria sample only considered Plasmodium falciparum infection as the most common
parasite expected to occur in the area. The mean point prevalence for malaria infection was
recorded at 32.7% in children aged 6-59 months across the 8 SS. The range was between 12.2%
and 67.4%, with the highest value recorded in Tèrin. This rate by definition represents a mesoendemic state; with rates between 10-50%.
30.9% of the children had haemoglobin levels below 8 g/dl as an indicator for malaria related
anaemia. This was highest in Soungaya at 39.0%.
All male and 96.1% of female respondents had heard of malaria. However, knowledge that
mosquitoes are the only malaria transmission mode was low, with 12.3% of men and 7.5% of
women supporting this consistent knowledge. The most common misconceptions were malaria
transmission through a dirty environment and through drinking dirty water.
Ownership and use of insecticide-treated nets (ITN) in the area was moderate with 58.3% of
households reporting to owning at least one ITN, and of these, 50.1% reported that a child had
slept under an ITN the previous night.
The coverage of intermittent preventive treatment of malaria in pregnancy was high with 79.4% of
women saying that they received at least 2 doses of medication during their last pregnancy.
Nutrition and anaemia
A number of nutritional indicators were evaluated clinically to provide an indication of levels of
acute and chronic malnutrition as well as micronutrient deficiency.
Wasting (weight-for-height), as an indicator for acute malnutrition, showed that 1.9% of children
were severely wasted, with 6.2% as moderately wasted. This was more common in boys. The midupper arm circumference (MUAC) levels of 3.0% and 13.7% for severe and moderate acute
malnutrition, respectively, support this finding related to wasting. Again boys had a lower mean
MUAC value.
Stunting (height-for-age), as an indicator for chronic malnutrition, showed that 14.5% and 36.2% of
children were severely and moderately stunted, respectively. This may reflect that state of past
periods of malnourishment in the area and the burden from the past levels of acute malnutrition
which were discussed in the HIA scoping study.
6.2% and 16.7% of children were severely and moderately underweight (weight-for-age)
respectively, which provides an indication of general food availability/security in the communities.
Children under the age of 5 years were evaluated for anaemia by determining their haemoglobin
levels. The majority (88.6%) of the children were reported as having anaemia (<11g/dl) with
14.4% classified as having severe anaemia (<7g/dl), 60.1% classified as having moderate
anaemia (7-9.9 g/dl) and 14.1% classified as having mild anaemia (10-10.9 g/dl). Girls were more
affected by mild and moderate anaemia, while boys were more affected by severe anaemia. Tèrin
(97.8%) and Matakang (97.4%) had the highest rates of anaemia.
Blood pressure
71.9% of men and 48.4% of women showed some form of hypertension. However, while there
were significantly more women than men who presented to the clinical field lab (83.4% female and
16.6% male) the prevalence of hypertension in men was significantly higher than in women.
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Schistosomiasis and Soil-transmitted helminthiases
The overall prevalence of any soil-transmitted helminth (STH) infection was 66.7%, which
classifies the area as highly endemic for STH. The mean level of STH infection was higher on
Kaback Island (77.5%) compared to the mainland areas of the sample (55.7%). Hookworm
infection was the most prevalent STH with an overall prevalence of 45.4%, followed by whipworm
(T. trichiura) at 15.0% and roundworm (A. lumbricoides) at 25.4%.
Schistosoma haematobium (urogenital bilharzia) infection was found in 0.4% of the children
surveyed and S. mansoni (intestinal schistosomiasis) infection was found in 1.7%. Thus, for
schistosomiasis the overall prevalence is classified as low at each individual site. Interestingly,
schistosomiasis was reported only on the mainland and completely absent on the Island, while
STH were reported both geographic zones.
Syphilis
Syphilis was found in 2 out of 285 women (aged 15-49 years) representing a point prevalence of
0.7%. Both women were living in Bossimiya. Upon investigation as part of the study protocol it was
discovered that in both cases the women had previously resided in a city and their
husbands/partners travel regularly to others parts of Guinea.
HIV/AIDS
Nearly all men (98.5%) and women (98.4%) had heard of HIV/AIDS. However, knowledge on
HIV/AIDS transmission and prevention methods was generally poor with only 6.3% of men and
only 2.0% of women showing consistent knowledge.
Stigma related to the disease was very high with only 9.5% of men and 2.9% of women reporting
that they would buy fruits or vegetables from a hypothetical shop-keeper known to be HIV positive.
In contrast, 79.5% of men and 82.9% of women would not keep it a secret if one of their family
members was HIV positive.
Uptake of voluntary counselling and testing (VCT) was low with 11.8% of men and 9.8% of women
reporting to have ever undergone a HIV test.
Condom use was low, with only 26.6 % of men and 7.6% of women reporting that they had ever
used a condom. Just over a half of men (55%) and 19.8% of women knew a place where they
could find condoms.
Tuberculosis
99.2% of men and 91.3% of women had heard of tuberculosis (TB), but only 8.6% of men a 9.1%
of women knew that TB is transmitted only through air when a person coughs or sneezes. About a
third (32.8%) of men and almost a half of women (47.8%) did not know how TB was transmitted.
Human African Trypanosomiasis
83.7% of men and 59.5% of women reported that they had heard of Human African
Trypanosomiasis (HAT). However, almost two-thirds of the men (65.7%) and 87.3% of women did
not know what the cause of HAT is.
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Maternal and child health
Anaemia in women of reproductive age showed that 48.9% of women who were not pregnant at
the time of the survey were anaemic, compared to 58.9% who were pregnant. The highest rates of
anaemia were in Tèrin, Sahrata and Konimodiya.
When their last child was sick, the majority of the mothers (73.1%) went to the pharmacy to seek
health care. Only 12.2% of the mothers went to a health facility. The most common reason (73%)
for not attending a health facility was lack of money for services at the health facility. Three in four
mothers (75.5%) admitted to having ever taken their child to a traditional healer.
Almost all mothers (97.6%) reported that they attended an antenatal clinic during their last
pregnancy. The mean attendance rate was four, which complies with the World Health
Organisation (WHO) standard.
Almost three-quarters (74.6%) of mothers said that they delivered their last child in a health facility
with the remaining 25.4% of the women reporting that they delivered their child at home. 76.5% of
women received delivery assistance from a skilled provider.
Although almost all women (98.4%) in the BHS said they breastfed their child, only 47% of
mothers reported exclusive breastfeeding for more than 1 month. The WHO recommends
exclusive breastfeeding for at least 6 months.
82.6% of mothers reported that they have a vaccination card for their child, which confirms followup visits after birth as an indicator that child health support is provided.
About two-thirds (68.1%) of children under the age of 5 years showed reported signs of acute
respiratory infections during the two weeks preceding the survey.
Social determinants of health and quality of life
64.6% of men and 76.7% of women reported that they did not have any formal education. Primary
school was attended by 18.5% of men and 19.8% of women. A higher level of education than
primary school was only achieved by 16.8% of men and 3.6% of women.
Asset ownership was evaluated to determine the socio-economic status of the participants,. The
most commonly owned asset was a radio (66.9%) and more than half of the respondents (57.1%)
also reported ownership of a cell-phone. 40.2% and 37% of the households owned a bicycle
and/or a motorcycle, respectively. Only 20.1% reported ownership of a television set with a vehicle
at 5.5%.
Only 7.7% of men and 0.4% of women reported that they drink alcohol, whereas 45.4% of men
reported that they smoke. The median number of cigarettes smoked in the last 24 hours was 10.
Only 2.4% of women said they smoke with 5 the median number of cigarettes smoked in the last
24 hours.
About three-quarters of all respondents thought that transactional sex work was a problem in their
community.
Noise and air pollution
About half of men (50.8%) and 66.3% of women thought that air pollution was a problem in their
community. The most commonly cited causes were malodours and dust. Similarly, 48.5% of men
and 65.9% of women thought that noise pollution was a problem in their community. General
community noises were cited as the main reason for noise pollution.
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Water and sanitation
A large majority (86.2%) of households had unimproved sanitation facilities. Sahrata had the
highest proportion (35.3%) of households with improved sanitation facilities. 6.3% reported that
they practice indiscriminate defecation in the bush while 4.3% reported using a water body (lake,
river, and ocean). The latter which was particularly high in Konimodiya at 35.5%.
Access to improved water sources varied between SS and seasons, with 58.7% and 47% of
households having access to improved water sources during the wet and dry seasons,
respectively. Access to improved water sources was highest in Manké and Sahrata, while
Farmoriya-Yindi village had the lowest number of households with improved water sources.
About a quarter (23.2%) of households said that they do not treat their water before drinking. The
most common methods of treatment were by using a water filter (46.5%) or by chlorination
(26.4%).
The number of thermo-tolerant coliform (TTC) bacteria colonies per 100ml was the applied
outcome measure for the drinking water quality testing. 65.4% of the 26 samples collected from
the main water collection points in the communities were classified as unsuitable for drinking
without treatment and 26.9% were classified as ‘requires treatment’. Consequently, only 7.7% of
the drinking water samples collected at community drinking water points could be classified as
compliant/tolerant.
At household level, almost 9 out of 10 drinking water samples collected (88.6%) were classified as
unsuitable for drinking without treatment and an additional 8.9% were classified as ‘requires
treatment’.
These findings do not only show that available drinking water infrastructure for the communities
covered under the present BHS is of poor quality but also that treatment of drinking water at
household level is not well practiced.
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Next Steps in the HIA Process
As the HIA is a dynamic iterative process, the following activities are planned to complete the
initial assessment activities:
•
complete the modelling of potential health impacts based on the findings from the
BHS, the secondary data that is available from a variety of sources and also from
project-related activities and data;
•
develop recommendations based on the recognised health impacts and develop a
framework community health management plan (CHMP);
•
stakeholder engagement and communication, which needs to include:
o
disclosure and dissemination of the results related to the key findings from the
BHS; and
o
•
discussions related to the CHMP and subsequent activities; and
develop a monitoring and evaluation programme to monitor community health
impacts and activities from baseline and related to proposed and planned
interventions.
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Table of Contents
Executive Summary .................................................................................................III Table of Contents .................................................................................................. XIII List of Figures ........................................................................................................ XVI List of Tables ........................................................................................................ XVII Acronyms ............................................................................................................. XVIII Glossary .................................................................................................................. XX 1 Introduction ........................................................................................................1 1.1 Project Location and Description ............................................................................... 1 1.2 Health Impact Assessment ........................................................................................ 2 1.2.1 Methodology and Benefits .................................................................................. 3 1.2.2 Health Impact Assessment Process ................................................................... 4 2 Baseline Health Survey Methodology ..............................................................7 2.1 Study Design.............................................................................................................. 7 2.1.1 Selected Sentinel Sites ....................................................................................... 9 2.2 Data Collection Modules .......................................................................................... 11 2.2.1 Survey Teams and Organization ...................................................................... 13 2.3 Field Procedures and Survey Tools ......................................................................... 14 2.3.1 Questionnaire Survey ....................................................................................... 14 2.3.2 Clinical Field Unit .............................................................................................. 16 2.3.2.1 Height, Weight and MUAC of Children <5 Years ....................................... 17 2.3.2.2 Blood Pressure Measurement .................................................................... 18 2.3.2.3 Malaria, Anaemia and Syphilis Testing ...................................................... 18 2.3.3 Parasitological Survey in Schoolchildren .......................................................... 20 2.3.3.1 Field Procedures for School Survey ........................................................... 20 2.3.3.2 Laboratory Procedures ............................................................................... 21 2.3.4 Drinking Water Quality Assessment ................................................................. 22 2.3.5 Health Facility Assessment .............................................................................. 24 2.4 Training of Field Workers ......................................................................................... 25 2.4.1 Interviewer Training .......................................................................................... 25 2.4.2 Training of Medical Staff ................................................................................... 25 2.5 Data Management and Statistical Analysis .............................................................. 26 2.6 Ethical Considerations ............................................................................................. 27 2.6.1 Treatment ......................................................................................................... 27 2.7 Stakeholder and Community Consultation and Sensitization .................................. 28 3 Findings of the Baseline Health Survey ......................................................... 30 3.1 Demographics and Sample Sizes ............................................................................ 30 3.1.1 Number of Participants Treated ........................................................................ 32 3.2 Clinical Field Unit ..................................................................................................... 33 3.2.1 Prevalence of Malaria in Children Aged 6-59 Months ...................................... 33 3.2.2 Malaria-Related Anaemia in Children Aged 6-59 Months ................................ 37 3.2.3 Nutritional Indicators ......................................................................................... 39 3.2.3.1 Wasting (Weight-for-Height) ....................................................................... 41 3.2.3.2 MUAC-for-Age ............................................................................................ 43 3.2.3.3 Stunting (Height-for-Age) ........................................................................... 45 3.2.3.4 Underweight (Weight-for-Age) .................................................................... 46 3.2.4 Anaemia ........................................................................................................... 48 3.2.4.1 Prevalence and Intensity of Anaemia in Children Aged 6-59 Months ........ 48 Shape Consulting Limited
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3.2.4.2 Prevalence and Intensity of Anaemia in Women of Reproductive Age ...... 51 3.2.5 Syphilis in Women of Reproductive Age .......................................................... 53 3.2.6 Blood Pressure in Adults .................................................................................. 54 3.3 Parasitological Survey in Schoolchildren ................................................................. 56 3.3.1 Prevalence and Intensity of Schistosomiasis Infection ..................................... 57 3.3.2 Prevalence and Intensity of STH Infections ...................................................... 58 3.3.3 Discussion and Recommendations .................................................................. 60 3.4 Questionnaire Survey .............................................................................................. 61 3.4.1 Household Composition ................................................................................... 61 3.4.1.1 Age and Marital Status ............................................................................... 61 3.4.1.2 Education
61 3.4.1.3 Socio-economic Status............................................................................... 62 3.4.2 Health Services and Behaviours ...................................................................... 64 3.4.2.1 Health Seeking Behaviour .......................................................................... 64 3.4.2.2 Maternal and Child Health .......................................................................... 67 3.4.2.2.1 Access to Antenatal Care ........................................................................ 67 3.4.2.2.2 Place of Delivery and Assistance ............................................................ 67 3.4.2.2.3 Breastfeeding Practices .......................................................................... 69 3.4.2.2.4 Ownership of a Vaccination Card ............................................................ 70 3.4.2.2.5 Acute Respiratory Infections ................................................................... 71 3.4.3 Social Determinants of Health .......................................................................... 72 3.4.3.1 Substance Abuse ....................................................................................... 72 3.4.3.2 Transactional Sex Work ............................................................................. 72 3.4.3.3 Domestic Gender Based Violence ............................................................. 72 3.4.4 KAP Related to Malaria .................................................................................... 74 3.4.4.1 Knowledge, Attitudes and Practices ........................................................... 74 3.4.4.2 Ownership and Use of Insecticide-Treated Nets ........................................ 75 3.4.4.3 Intermittent Preventive Treatment for Malaria ............................................ 77 3.4.5 KAP Related to HIV/AIDS ................................................................................. 80 3.4.5.1 HIV Knowledge and Awareness ................................................................. 81 3.4.5.1.1 HIV/AIDS Knowledge in Men .................................................................. 81 3.4.5.1.2 HIV/AIDS Knowledge in Women ............................................................. 83 3.4.5.2 Consistent Knowledge of HIV/AIDS Transmission and Prevention ............ 84 3.4.5.3 Attitudes and Beliefs Related to HIV/AIDS ................................................. 86 3.4.5.4 HIV Prevention Practices ........................................................................... 88 3.4.5.4.1 HIV Testing .............................................................................................. 88 3.4.5.4.2 Condom Use ........................................................................................... 89 3.4.6 KAP Pertaining to Tuberculosis ........................................................................ 91 3.4.7 KAP Related to Nutrition ................................................................................... 93 3.4.8 KAP pertaining to Trypanosomiasis ................................................................. 95 3.4.9 Household and Environmental Indicators ......................................................... 97 3.4.9.1 Construction Material of Floor, Walls and Roof .......................................... 97 3.4.9.2 Cooking Area and Fuel............................................................................... 99 3.4.9.3 Air and Noise Pollution ............................................................................. 100 3.4.9.3.1 Air Pollution ........................................................................................... 100 3.4.9.3.2 Noise Pollution ...................................................................................... 102 3.4.9.4 Utilisation of Sanitation Facilities .............................................................. 103 3.4.9.5 Utilisation of Drinking Water Sources ....................................................... 105 3.4.9.5.1 Rainy Season ........................................................................................ 106 3.4.9.5.2 Dry Season ............................................................................................ 107 3.4.9.6 Treatment of Drinking Water at Household Level .................................... 108 3.5 Drinking Water Quality Assessment ...................................................................... 110 3.6 Health Facilities Assessment ................................................................................. 113 Shape Consulting Limited
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Limitations of the Study ................................................................................ 116 References ...................................................................................................... 117 Appendices .....................................................................................................121 6.1 6.2 6.3 Appendix A: Ethical Approval ................................................................................. 121 Appendix B: Ordre de mission ............................................................................... 122 Appendix C: Questionnaire .................................................................................... 123 Shape Consulting Limited
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List of Figures
Figure 1: Project map ............................................................................................................... 1 Figure 2: HIA flow chart ............................................................................................................ 5 Figure 3: Three-stage sampling strategy.................................................................................. 7 Figure 4: Determination of directions using a top ..................................................................... 8 Figure 5: Location of selected sentinel sites .......................................................................... 10 Figure 6: Modular cross-sectional baseline health survey framework .................................... 11 Figure 7: Survey teams and their respective staff members .................................................. 13 Figure 8: Simandou Port BHS survey team ........................................................................... 13 Figure 9: Setup of the clinical field unit................................................................................... 16 Figure 10: Height, weight and MUAC measurements ............................................................ 17 Figure 11: Blood pressure measurement at the clinical field unit ........................................... 18 Figure 12: Finger pricking in adults and children aged 6-59 months ...................................... 19 Figure 13: Turbidity testing of drinking water samples ........................................................... 23 Figure 14: Drinking water testing with the DelAgua water quality testing kit .......................... 23 Figure 15: TTC (yellow dots) on the filter membrane after the incubation period .................. 24 Figure 16: Training of medical staff ........................................................................................ 26 Figure 17: Posters as part of community sensitization activities ............................................ 29 Figure 18: Predicted P. Falciparum endemicity in Guinea ..................................................... 33 Figure 19: Prevalence of malaria across the SS .................................................................... 35 Figure 20: Prevalence of malaria stratified by age group and gender.................................... 36 Figure 21: Prevalence of malaria-related anaemia across the SS ......................................... 37 Figure 22: Prevalence of malaria-related anaemia stratified by age group and gender ......... 38 Figure 23: Nutritional status in children under 5 years by age group ..................................... 40 Figure 24: Odds ratio for mortality based on wasting ............................................................. 42 Figure 25: Weight-for-age distribution in children <5 years compared to WHO standards .... 43 Figure 26: MUAC-for-age distribution in children <5 years compared to WHO standards ..... 44 Figure 27: Height-for-age distribution in children <5 years compared to WHO standards ..... 46 Figure 28: Weight-for-age distribution in children <5 years compared to WHO standards .... 47 Figure 29: Anaemia intensity in children aged 6-59 months by age group ............................ 49 Figure 30: Prevalence and intensity of anaemia across the SS ............................................. 51 Figure 31: Prevalence of any STH across the SS .................................................................. 59 Figure 32: Education level in male and female respondents .................................................. 62 Figure 33: Reported ownership of household assets ............................................................. 63 Figure 34: Availability of health facilities in the surveyed SS ................................................. 64 Figure 35: Reasons for not going to a health facility (n=37) ................................................... 65 Figure 36: Hindrances to obtaining medical treatment ........................................................... 66 Figure 37: Place of delivery .................................................................................................... 68 Figure 38: Percentage of children <six months old exclusively breastfed in 2006 ................. 70 Figure 39: Actions allowing a man to beat his wife (according to women) ............................. 73 Figure 40: Proportion of children under 5 years who slept under an ITN by SS .................... 77 Figure 41: IPTp use in women during their last pregnancy ..................................................... 78 Figure 42: HIV prevalence in Guinea by administrative region in 2005 ................................. 80 Figure 43: Causes of malnutrition as reported by male respondents ..................................... 93 Figure 44: Causes of malnutrition as reported by female respondents .................................. 94 Figure 45: Causes of HAT according to male respondents .................................................... 95 Figure 46: Causes of HAT according to female respondents ................................................. 96 Figure 47: Type of material used on floor............................................................................... 98 Figure 48: Type of material used on walls .............................................................................. 98 Figure 49: Type of material used on roof ............................................................................... 98 Figure 50: Type of cooking fuel used ................................................................................... 100 Figure 51: Distribution of sanitation facilities ........................................................................ 104 Shape Consulting Limited
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List of Tables
Table 1: Key findings ............................................................................................................ VIII Table 2: Selected sentinel sites................................................................................................ 9 Table 3: WHO classification of drinking water samples ......................................................... 24 Table 4: Demographics and sample sizes at the different sentinel sites ................................ 31 Table 5: Malaria prevalence in children aged 6-59 months, stratified by SS ......................... 34 Table 6: Summary of nutritional indicators ............................................................................. 40 Table 7: Prevalence of wasting in children under 5 years ...................................................... 42 Table 8: Prevalence of low MUAC in children aged 4-59 months .......................................... 44 Table 9: Prevalence of stunting in children under 5 years ..................................................... 45 Table 10: Prevalence of underweight in children under 5 years ............................................ 47 Table 11: Proportion of children with anaemia by intensity, age group and gender ............... 49 Table 12: Proportion of children with anaemia by intensity, age group and gender ............... 50 Table 13: Proportion of children with anaemia by intensity and sentinel site ......................... 50 Table 14: Anaemia in women (15-49 years) by sentinel site (n=287) .................................... 52 Table 15: Syphilis prevalence in women (15-49 years) by sentinel site ................................. 53 Table 16: Classification of BP for adults................................................................................. 54 Table 17: Percentage distribution of BP in adults .................................................................. 54 Table 18: Sampling locations and elevations ......................................................................... 56 Table 19: Prevalence of S. mansoni and S. haematobium .................................................... 57 Table 20: Intensities of S. mansoni and S. haematobium infections ...................................... 57 Table 21: Prevalence of STH by sentinel site ........................................................................ 58 Table 22: Intensity of STH infections...................................................................................... 59 Table 23: Locality of medical advice at the last instance when the child was sick ................. 65 Table 24: Assistance during delivery...................................................................................... 69 Table 25: Children (%) that showed symptoms of ARI 2 weeks preceding the survey .......... 71 Table 26: Malaria knowledge in men...................................................................................... 74 Table 27: Malaria knowledge in women ................................................................................. 75 Table 28: Insecticide-treated net ownership and reasons for not owning one ....................... 76 Table 29: Intermittent preventive treatment in pregnancy per sentinel site ............................ 79 Table 30: HIV/AIDS knowledge in men .................................................................................. 81 Table 31: HIV/AIDS knowledge in women ............................................................................. 83 Table 32: Proportion of respondents with consistent HIV knowledge .................................... 85 Table 33: Proportion of respondents with correct knowledge of HIV prevention .................... 86 Table 34: Attitudes towards HIV positive people .................................................................... 87 Table 35: Proportion of respondents who had ever taken an HIV test ................................... 88 Table 36: Condom use among men and women ................................................................... 90 Table 37: TB knowledge in men ............................................................................................. 91 Table 38: TB knowledge in women ........................................................................................ 92 Table 39: Cooking area during wet and dry season ............................................................... 99 Table 40: Perception on air pollution by men ....................................................................... 101 Table 41: Perception on air pollution by women .................................................................. 101 Table 42: Perceptions on noise pollution by men................................................................. 102 Table 43: Perceptions on noise pollution by women ............................................................ 103 Table 44: Type of sanitation facilities in each sentinel site................................................... 105 Table 45: Sources of drinking water at household level during the rainy season ................ 107 Table 46: Sources of drinking water at household level during the dry season ................... 108 Table 47: Water treatment methods in each sentinel site .................................................... 109 Table 48: Drinking water quality at community and household level .................................... 110 Table 49: Water quality at drinking water collection points .................................................. 112 Table 50: Key indicators on health infrastructure ................................................................. 115 Shape Consulting Limited
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Acronyms
ACT
Artemisinin-Based Combination Therapy
AIDS
Acquired Immunodeficiency Syndrome
ANC
Antenatal Care
ART
Antiretroviral Treatment
BHS
Baseline Health Survey
BP
Blood Pressure
CHIS
Community Health Information System
CHMP
Community Health Management Plan
CI
Confidence Interval
CNERS
Le Comité National d’Ethique pour la Recherche en Santé’
DHS
Demographic Health Survey
DPS
Directeur Préfectoral de Santé
epg
Eggs per Gram of Stool
e/10ml
Eggs per 10ml of urine
GDHS
Guinea Demographic and Health Survey
GPN
Good Practice Note
GPS
Global Positioning System
HAT
Human African Trypanosomiasis
Hb
Haemoglobin
HDP
Health Development Plan
HIA
Health Impact Assessment
HIV
Human Immunodeficiency Virus
HMP
Health Management Plan
LLIN
Long-Lasting Insecticidal Net
ICMM
International Council on Mining and Metals
IEC
Information, Education and Communication
IFC
International Finance Corporation
IPTp
Intermittent Preventive Treatment in Pregnancy
IQR
Inter-Quartile Range
ITN
Insecticide-Treated Net
KAP
Knowledge, Attitude and Practices
KPI
Key Performance Indicator
MDA
Mass Drug Administration
MoH
Ministry of Health
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MUAC
Mid-Upper Arm Circumference
NGO
Non-Governmental Organization
NTD
Neglected Tropical Disease
NTU
Turbidity Units
OR
Odds Ratio
PAC
Potentially Affected Community
PO
Per Os
RBM
Roll Back Malaria Partnership
RDT
Rapid Diagnostic Tests
SD
Standard Deviation
SP
Sulphadoxine-Pyrimethamine
SS
Sentinel Site
STH
Soil-Transmitted Helminthiasis
STI
Sexually-Transmitted Infection
TB
Tuberculosis
TM
Traditional Medicine
ToR
Terms of Reference
TTC
Thermo-Tolerant Coliform Bacteria
UNICEF
United Nations Children’s Fund
VCT
Voluntary Counselling and Testing
VIP
Ventilated Improved Latrine
WHO
World Health Organization
WLP
Women’s Learning Partnership
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Glossary
Antenatal care: Pregnant women are supposed to attend at least three sessions by skilled
health personnel (doctors, nurses or midwives) during their last pregnancy.
Baseline health survey: A cross-sectional study aiming at identifying and quantifying
relevant health, environmental and socio-cultural characteristics of the population living in a
certain population group or geographical area.
Community: A group of individuals broader than the household, who identify themselves as
a common unit because of shared locality, or because of recognized social, religious,
economic or traditional ties.
95% confidence interval: It is that interval which one may be 95% confident contains the
true (population) value that is being estimated.
Demographic and Health Survey (DHS): Nationally-representative household surveys that
provide data for a wide range of monitoring and impact evaluation indicators in the areas of
population, health and nutrition. DHS have large sample sizes (usually between 5,000 and
30,000 households) and are typically conducted every 5 years to allow comparisons over
time.
Health: A state of complete physical, mental and social and spiritual well-being and not
merely the absence of disease or infirmity.
Health determinants: The range of personal, social, economic and environmental factors
which determine the health status of individuals or populations.
Health impacts: Changes in community health which are attributable to a policy, programme
or project. A health impact can be both positive and negative.
Health impact assessment (HIA): HIA is a combination of procedures, methods and tools
that systematically judge the potential, and sometimes unintended, effects of a project,
programme or policy on the health of a population and the distribution of those effects within
the population. HIA identifies appropriate actions to manage those effects.
Health outcomes: A change in the health status of an individual, group or population which
is attributable to a planned intervention or series of interventions, regardless of whether such
an intervention was intended to change health status.
HIV adult prevalence rate: Percentage of adults (15-49 years) living with HIV/AIDS.
Household: A person or a group of persons, related or unrelated, who live together and
share a common source of food and livelihood, and recognize one person as a head.
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Indicator: Data which provide information about, and will allow surveillance of, the overall
health and/or socio-economic status of an individual or family.
Insecticide-treated nets (ITN): An ITN is a bed net that was treated with insecticide within
the past 12 months or that was pre-impregnated as a long-lasting insecticidal net (LLIN)
(effective for approximately 5 years).
Inter-quartile range (IQR): A measure of statistical dispersion, being equal to the difference
between the upper and lower quartiles.
Knowledge, attitude and practice (KAP): Describes an individual’s or household’s
knowledge, attitude and practices towards different determinants, in this case health. These
variables can outline any gaps in individual or community knowledge and practices and can
inform the development of information, education and communication (IEC) strategies to
support behavioural change.
Mean: The mean is the most commonly used measure of the central value of a distribution. It
is also defined as the arithmetic mean or the average. It is the sum of the observations
divided by the number of observations.
Median: The median is described as the numeric value separating the higher half of a
sample from the lower half.
Potentially affected community (PAC): A community (i.e. single village or a group of
settlements) within a sensible geographical boundary which will potentially be equally
exposed to the project in terms of the magnitude and nature of anticipated impacts. This can
include directly who may be affected by proximity and operations of the project and indirectly
affected populations that may be influenced by transport routes, local economic changes and
changes in culture and lifestyles.
Prevalence: Total number of existing cases of a disease at a given time divided by the total
population surveyed. It thus measures the rate of people in a population who have a specific
condition at a given time. This was the most common measure in the survey.
Primary health care: Affordable, practical methods of delivering essential health care that
are scientifically sound and socially acceptable.
Safe water: Safe drinking water includes treated surface water and untreated water from
protected springs, boreholes, and sanitary wells, which complies with drinking water
standards given by the World Health Organization (WHO). The definition of what constitutes
"access" to safe water varies from country to country. Generally, walking distance or time
from household to water source is the principal criterion, particularly in rural areas. Access to
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safe water is essential in preventing water-borne diseases, and it is a minimum requirement
for human health and well-being.
Sanitation: Access to sanitation is essential in preventing diseases spread by unsanitary
conditions or by water contaminated by solid human waste. WHO and UNICEF in their joint
monitoring programme provide the following definitions:
Improved sanitation facilities:
• Flush or pour–flush to:
Unimproved sanitation facilities:
• Flush or pour–flush to elsewhere;
o
piped sewer system;
•
Pit latrine without slab or open pit;
o
septic tank; and
•
Bucket;
o
pit latrine.
•
Hanging toilet or hanging latrine; and
•
No facilities (e.g. bush or field).
•
Ventilated improved pit latrine;
•
Pit latrine with slab; and
•
Composting toilet.
Sampling: Procedure by which some members of a given population are selected as
representative for the entire population.
Sexually-transmitted infections (STIs): Diseases that have a significant probability of
transmission between humans by means of human sexual behaviour, including vaginal
intercourse, oral sex, and anal sex (e.g. gonorrhoea, chlamydia, syphilis). These infections
increase the risk for the transmission of HIV/AIDS.
Skilled attendance at delivery: Percentage of births attended by skilled health personnel
(i.e. doctor, nurse or trained midwife).
Stakeholders: Stakeholders are all those who have rights or interests in the project and/or
are directly or indirectly affected by the project. Stakeholders can be individuals,
communities, social groups, organizations or administrative bodies.
Standard deviation (SD): Is the measure of spread used in conjunction with the mean. It is
based on the deviations of the observations from the mean; that is on the difference between
each observation and the mean.
Stunting: Stunting is defined as having a height-for-age of more than -2 SD below the
median of a healthy population.
Traditional medicine (TM): Refers to health practices, approaches, knowledge and beliefs,
incorporating plant, animal and mineral based medicines, spiritual therapies, manual
techniques and exercises, applied singularly or in combination to treat, diagnose and prevent
illnesses or maintain well-being.
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Underweight: Underweight is defined as having a weight-for-age more than -2 SD below the
median of the healthy population.
VCT: Voluntary counselling and testing for HIV.
Wasting: Wasting is defined as having a weight-for-height of more than -2 SD below the
median of the healthy population.
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1 Introduction
1.1 Project Location and Description
Rio Tinto Iron Ore Atlantic Ltd (Rio Tinto) through their local entity in Guinea, Simfer S.A. is
in the process of conducting feasibility studies to develop the world class Simandou Iron Ore
Project (Project) in the Republic of Guinea. The mining area is located in the Guinée
Forestière and Haute Guinée regions of Guinea some 700 km to the east of the capital,
Conakry. As part of the Project, Rio Tinto is planning to develop a deep-water port 40 km
south of Conakry, in Forécariah prefecture. The Port area will serve as both a Marine
offloading facility (MOF) and an iron ore export facility. The proposed development area is
shown in Figure 1. A 700km railway line will connect the Port development with the mine
development. At present the Project in the stage of advanced feasibility and when developed
it will have a life of mine that exceeds 50 years.
Maférinya
Conakry
Forécariah
Kaback
Island
Figure 1: Project map
The baseline health survey (BHS) described in this document is focussed at assessing the
health conditions for the Port Development Project. Based on current feasibility studies it is
anticipated that the development will include (i) a stockyard (~600 ha) for the iron ore that will
arrive via the railroad (purple line in Figure 1); (ii) a conveyor (~25 km, black lines) that will
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cross the island of Kaback to the (iii) deep water export facility. However, while it is
anticipated that Kaback Island and communities between the island and Maférinya will be the
major zone of influence for this proposed development the final designs and decisions have
not been completed as yet. More detailed Project descriptions and activities are described in
the comprehensive health impact assessment (HIA) document which is being developed to
support the Project development.
Kaback Island is very densely developed along three parallel roads that cross the island from
south to north and composed of several independent villages. On the eastern side of the
inhabited belt, small hamlets exist in patches of higher grounds with oil palms, and along the
roads. These hamlets are numerous, but most are quite small, between a <5 houses to
15‐20 in the biggest ones. The land used to be more occupied, and villages have been
abandoned during the past 100 years [1].
Agriculture is the main livelihood source in the Kaback area with rice as the major crop. Also
horticulture of market garden crops such as red pepper, eggplant, water melon, okra, and
others has become a major source of income which can be practiced using relatively small
surfaces of high quality land. Though close to the sea, channels and rivers, only a minority of
the households practices fishing. This is different in Matakang, a village at the tip of the
island where fishing is the major source of income. The region is rich in oil palms, and oil
extraction activities are frequently observed in the villages2 [1].
1.2 Health Impact Assessment
Although the HIA scoping study performed for the Project outlined the HIA methodology and
approach in detail [2], it is considered beneficial to briefly re-introduce the HIA approach as a
reference in the BHS report so that the reader can understand the specific context.
2
The names of some of the villages mentioned in this report may differ from the official name list
established by the Project.
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1.2.1 Methodology and Benefits
The Project follows its own community relation standards with the stated goal to support
regional and local community based projects that contribute to sustainable development.
This is in spite of the fact that there are no specific regulations that legally require the
assessment of community health, or the completion of a HIA for mining project developments
in Guinea. Furthermore, International Finance Corporation (IFC) is a partner in the Project,
holding a share of 5%, and thus the Project is being development according to the IFC social
and environmental sustainability performance standards (PS) as good international industry
practice (GIIP).
Against this background, the HIA process follows the approach and methodology outlined in
the Good Practice Note (GPN) on HIA developed by the IFC to support environmental and
social sustainability in new project developments [3]. This is often considered the default best
practice in the absence of local host country guidance, and aligns to the IFC Performance
Standards and specifically Performance Standard 4 which considers Community Health and
Safety [4]. The good practice note developed by the International Council on Mining and
Metals (ICMM) was also considered as Rio Tinto is a member company [5].
The reasons and benefits for commissioning a HIA include the following:
•
benchmarking the operation against GIIP required by industry (e.g. ICCM), partners
and lenders (e.g. IFC) as well as corporate standards;
•
improved stakeholder engagement and alignment through the assessment process
allows for improved partnerships for supporting community health and well-being.
Furthermore, this supports the definition of roles and responsibilities and thus
promotes sustainability of future interventions including mitigation measures as well
as negotiated commitments;
•
supporting the definition of a robust baseline of the health status of the potentially
affected communities (PAC) and the broader area, both through the activities of the
BHS and data collected from secondary sources at scoping. This information can be
used to support communication related to any criticisms related to changes in the
health status of the PACs and support subsequent monitoring;
•
support the understanding of the potential vulnerabilities from a health perspective of
the PACs, and ultimately how the Project may influence these health outcomes and
determinants;
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based on a systematic risk assessment and prioritization process develop evidencebased recommendations for the mitigation of potential adverse health impacts, and
the promotion of positive health impacts. Hence, targeted programmes and
interventions related to community health can be developed based on these
principles. This allows a risk- and evidence-based approach to prioritise interventions
and not to simply respond to requests or address seemingly obvious interventions;
•
support the basis for the development of a monitoring and evaluation programme to
assess the impact of the Project per se, as well as of community health programmes
which are planned or being implemented. This is essential for regular auditing of
programmes to establish their weakness and success and also assist in developing
budgets;
•
improved social licence to operate in the PAC and other stakeholders due to
participative planning for any planned negotiated commitments linked to health
programmes. These can be aligned to sustainability criteria and developing
partnerships with the local community, non-governmental organisations (NGOs) and
health authorities.
1.2.2 Health Impact Assessment Process
The major framework that is commonly used for HIA and which follows a 6-step process is
depicted in Figure 2 [6]. A HIA scoping study was initiated in September 2010. The activities
served to outline potential health impacts of concern, their spatial and temporal effects, what
evidence was available to support the modelling of potential health impacts, and what was
required to address any data gaps. This outlined the terms of reference (ToR) for the HIA for
the ultimate development of a community health management plan and associated
monitoring tools [2].
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Figure 2: HIA flow chart
Data gaps or additional evidence required for the definition of the characterisation of health
impacts or community health surveillance was addressed in the scoping phase of the HIA
and formed the framework to develop the study protocols for the current BHS. As mentioned,
it was anticipated that the BHS will provide the necessary data to develop the following
elements:
•
Comprehensive HIA, which will include the findings of the scoping study and
consider the most recent Project design and proposed Project related activities. The
impacts assessment will address areas that require impact mitigation. This may be to
avoid or prevent negative health impacts which may in turn result in positive impacts,
or specific enhancement activities.
•
Based on the significance ranking of the assessment process, a prioritised
Community Health Management Plan (CHMP) will be developed and divided into
the following sections:
o
A Health Management Plan (HMP) that is specifically related to impact mitigation
and which is required by the Project.
o
A Health Development Programme (HDP) as part of the Project’s negotiated
and voluntary contributions to community health in the Project area. These
negotiated commitments are likely to enhance the social license to operate and
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may not be tied to a specific project impact, but may be selected because the
Project sees long-term benefits in measures that enhance overall community wellbeing.
•
A Community Health Information System (CHIS) linked to specific outcome
indicators either from health impact mitigation or from an enhancement perspective.
The BHS will support this through the development of a baseline to enable future
monitoring and evaluation of defined health indicators distributed across the Project
concession and PACs.
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2 Baseline Health Survey Methodology
The applied BHS methodology has been specifically developed for HIA of industrial
development projects and is based on a modular, cross-sectional study design [7]. The
modular nature of the methodology facilitates the adaptation of the BHS to the prevailing
eco-epidemiological characteristics of the project setting, covering a multiplicity of health
outcomes and determinants at different levels and scales.
2.1 Study Design
The study design of a BHS is governed by the fact that it should reflect the heterogeneity of
health characteristics and potential project-related impacts (beneficial or detrimental) among
different communities and/or population groups. Hence, a central feature of BHS for
industrial projects is that data collection methods need to be fine-tuned to conditions at a
micro level, or at communities who may be impacted by the proposed project development.
Against this background, we applied a three-stage sampling strategy, which is purposive in
the first two stages and randomised in the third stage (see Figure 3).
Figure 3: Three-stage sampling strategy
At the first stage, the population was stratified into PACs, which was done as part of the
scoping study. A PAC is a defined community within a clear geographical boundary where
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project-related health impacts may reasonably be expected to occur. For instance,
communities along a major access road of a project, or communities to be resettled, or
communities not directly affected by a project are examples of PACs.
At the second stage, primary sampling units were defined and selected within a PAC,
referred to as sentinel sites (SS). A SS is defined as a geographically constructed area (e.g.,
sentinel village), or a part of an area (e.g., neighbourhood in a town), with up to 300
households. The number and selection procedure (i.e., purposive or random) of SS is
governed by the magnitude and heterogeneity of the project area, financial and human
resources, operational issues and technical considerations. The SS were selected based on
the following considerations:
•
the potential for high level health impacts as defined by the scoping HIA;
•
geographical and demographic considerations;
•
information obtained from the environmental, social and associated specialist studies;
•
information from the project development and designs; and
•
the legacy of past activities on the project site and the broader area.
At the third stage, with data collection at the SS level, a quota sampling method was applied,
involving random sampling of households. For this, a top was spun at a strategically selected
point(s) within the SS (depending on the structure of the SS) to determine randomly selected
directions. This is illustrated in Figure 4. Subsequently, households along these directional
lines to the border of the SS were counted, and one in each direction was selected at
random. Proximity sampling was then adopted, with interviewers moving from one household
to the next, until the pre-determined number of households was completed.
Figure 4: Determination of directions using a top
The optimal sample size at SS level is usually a trade-off between practical economics, the
desired survey precision and reproducibility. Demographic and Health Survey (DHS)
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experience suggests that, for an average cluster size of 100-300 households, to achieve
moderate intra-cluster correlation and an acceptable cost ratio, the optimal second-stage
sample size for gathering data on most of the survey indicators is about 20-30 women per
cluster [8]. DHS are similar in terms of field procedures and the type of indicators which are
measured and therefore this range is used as reference for individuals and households
selected per SS.
Overall, this methodology was chosen because it allows for a broad sample among the
different PACs and can be easily reproduced and, if need be, adapted as the project evolves.
Additional SS can simply be added, and as communities are relocated to the host site the
sentinel surveillance can simply shift to these areas without challenges regarding
proportional sizes or cluster selections. Moreover, this study design will allow for comparison
between the different SS on an individual basis, and also allow for data to be pooled across
all the SS according to similar characteristics to improve the statistical significance for
analysis and surveillance purposes.
2.1.1 Selected Sentinel Sites
Based on the outlined methodology, 8 SS were selected in the zone of influence of the
planned Port Development Project (4 on the mainland and 4 on Kaback Island), which are
shown in Figure 5 and roughly described Table 2. As no precise data on household numbers
from the socio-economic baseline studies was available prior to the field work in the BHS, the
number of households per SS are based on estimations that were obtained in the field.
Table 2: Selected sentinel sites
Estimated
number of
household
40
Sentinel Site
District
Tèrin
Fanyé
Sahrata
Maférinya
80
Soungaya
Maférinya
100
Farmoriya-Yindi village
Yindi
110
Matakang
Matakang
200
Bossimiya
Bossimiya
40
Manké Centre
Manké
90
Konimodiya
Yélibanet
150
Total
8 sentinel sites
810
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Reason for selection
Control site
Central community of Maférinya, which is the
closest town to the Port Development
Community on the road from Kaback Island to
Maférinya
Community is located close to the planned rail
loop and stockyard
Important community on Kaback Island which
may be impacted by the conveyor
Average community on Kaback Island
Central community on Kaback Island where
the main health centre is located
Average community on Kaback Island
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Figure 5: Location of selected sentinel sites
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2.2 Data Collection Modules
Key performance indicators (KPIs) are measures of project inputs, outputs, outcomes and
impacts that are defined at project design and implementation and monitored during on-going
programme activities.
Figure 6: Modular cross-sectional baseline health survey framework
From a practical point of view, three general data collection levels have been defined, each
of contain different sets of indicators: (i) individual level (e.g., age and sex, indicators on
knowledge, attitude and practice (KAP) and biomedical indicators); (ii) household level (e.g.,
structural indicators, such as durable housing characteristics, asset indicators (e.g.,
possession of a radio or bicycle) and environmental indicators); and (iii) community level
(e.g., health systems, infrastructure indicators and environmental indicators). Based on the
scope of planned data collection at individual projects different data collection tools and
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methods (referred to as ‘modules’) can be considered from the different levels described
above. Figure 6 shows the inter-linkages between the different data collection levels, the
indicator groups and the data collection modules, including a broad, but focused set of
potential KPIs [7].
The final design of the BHS is determined by selecting KPIs and then data modules of
interest and applying them to the local setting. Based on the outcomes of the scoping report
and on discussions with Rio Tinto and SNC Lavalin the following data collection modules
have been selected for the BHS of the Port Development Project:
•
Household questionnaire survey to assess KAP in relation to specific public health
concerns of individuals (questionnaire survey). This included the determination of the
current status of health-related KAP in the adult male and female population. This
was performed using a pre-tested questionnaire in defined population groups at the
selected SS. The questionnaires included a wide variety of topics which addressed
both bio-physical and social determinants of health.
•
Clinical field unit where specific samples were taken from individuals linked to
households selected in the KAP study. This included: (i) determination of the
prevalence of malaria in children aged 6-59 months; (ii) determination of the
prevalence and intensity of anaemia in children aged 6-59 months and in women of
reproductive age (aged 15-49 years); (iii) determination of anthropometric measures
of children aged 6-59 months; (iv) determination of blood pressure in adults; and (v)
determination of present or past syphilis infection in women of reproductive age.
•
Parasitological survey in schoolchildren (aged 10-15 years) to determine the
prevalence and intensity of schistosomiasis and soil-transmitted helminth (STH)
infections. Stool and urine samples were collected among children in schools that
were readily linked to the selected SS.
•
Drinking water source and end-user water quality analysis to determine the level
and origin of biological contamination in drinking water. Drinking water samples were
collected at functioning community drinking water points and at selected households
and analysed for the presence of thermo-tolerant coliform bacteria as indicators for
faecal contamination of water.
•
Service and infrastructure assessment to assess key parameters at health posts
and centres in the wider Project area. This included the evaluation of available
services, availability of essential drugs and consumables, general infrastructure,
human resources and patient load.
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2.2.1 Survey Teams and Organization
The BHS was organized along different teams and their respective staff members as
illustrated in the following Figure 7.
Figure 7: Survey teams and their respective staff members
Figure 8: Simandou Port BHS survey team
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2.3 Field Procedures and Survey Tools
2.3.1 Questionnaire Survey
The questionnaire survey at household level was based on a structured questionnaire (see
Appendix C) comprising: (i) an informed consent sheet; (ii) a clinical form to enter the date of
birth and names of household members; (iii) observational indicators on household
infrastructure; (iv) socio-demographic indicators and (v) questions pertaining to KAP
addressing the following public health issues:
•
health seeking behaviour;
•
maternal and child health;
•
malaria;
•
HIV/AIDS;
•
tuberculosis;
•
neglected tropical diseases (NTDs);
•
nutrition;
•
social determinants of health and quality of life; and
•
water and sanitation practices.
Well established standard indicators that have been used for many years by different
organisations and programmes, such as WHO, UNAID, MEASURE DHS and The Global
Fund, as well as indicators used in national Guinean surveys, were selected in the
development of the survey questionnaires. The rationale in using these indicators is that they
allow for comparison of the data collected at the local level with reported data from a district,
regional and even national level. This thus allows benchmarking across a broad set of
indicators and allows for monitoring and surveillance at the Project level compared to these
different areas.
The questionnaire was split into three sections; (i) a description of the general household
characteristics as well as water and sanitation practices of the household members; (ii) a
man’s questionnaire dedicated to an individual man in the household (who was above the
age of 18 years and generally the head of the household); and (iii) a woman’s questionnaire
for a mother in the household who had at least one child who was aged between 6-59
months. If no man was at home, the interviewer was allowed to skip the man’s questionnaire
(section 2) and interview the woman only.
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At SS level, sample selection of houses was based on the stage sampling procedure
described above. The targeted sampling unit was a ‘household’, which was defined as
follows: “A person or a group of persons, related or unrelated, who live together and share a
common source of food and livelihood, and recognize one person as a head.” Once a
household was selected, the two following inclusion criteria applied:
¾ presence of at least one mother; and
¾ presence of at least one child <5 years.
If one or both criteria were not met, the interviewer proceeded to the next house until a
household was identified that met these criteria. If more than one mother was present in the
same household, all mothers with a child <5 years of age were asked to draw a card from a
set of playing cards. The woman with the highest card was then selected to participate in the
survey.
As the initial step, the interviewer explained the aim and procedures of the study to the
household head or, if absent, the person who would be representing the head of the
household at that time. The questionnaire content and the procedures for the biological
sampling activity were also explained and the household head was invited to sign an
informed consent sheet. If the head of the household refused, then this was noted, the
respondent thanked for their time, and the interviewer would move to the next household as
per the aforementioned methodology.
After written informed consent was obtained, the interviewer recorded the global positioning
system (GPS) coordinates of the household, completed the clinical form with the names and
dates of birth of the household members and assessed the behavioural and observational
indicators using a pretested questionnaire. Thereafter, the interviewer would request the
household members registered on the clinical form to go to the clinical field unit.
In addition, every third household was asked to provide a sample of their drinking water.
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2.3.2 Clinical Field Unit
The clinical field unit was located at a well-known, central place of the SS. This was selected
to ensure it was appropriate for the collection of biological samples. The unit was set up in a
structured manner to ensure a smooth flow and consisted of three different posts (as shown
in Figure 9):
•
first post: initial reception, nutritional measurements and blood pressure for adults;
•
second post: field laboratory (malaria status, haemoglobin (Hb) level and blood
syphilis status); and
•
third post: treatment (malaria and nutritional supplements).
Second post: Field
laboratory (malaria status,
haemoglobin level and
presence of syphilis)
First post: Reception,
anthropometric
measurements and blood
pressure
Third post: Treatment
(antimalarial drugs and
nutritional supplements)
Figure 9: Setup of the clinical field unit
Once household members arrived at the clinical field unit, they handed over the clinical form
to the medical staff at the reception. The clinical form contained the details of the household
members that were requested to visit the clinical field unit (adults aged above 15 years and
children below the age of 5 years) but was also used as a control by the medical staff to
ensure that the household had been selected as part of the survey and thus eligible for the
sampling. This was crucial as informed consent was obtained prior to laboratory entry by the
household survey team.
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The clinical form was designed in such a way that the measurement requirements for each
individual household member were defined so that unnecessary tests would not be
performed.
2.3.2.1 Height, Weight and MUAC of Children <5 Years
The height and weight measurements were based on WHO standards [9]. For children <2
years the recumbent length was measured while for children aged 2-5 years the standing
height was measured. Weight was measured in children below the age of 5 years using
digital ‘Seca’ scales that had a tared function which allowed for easy weighing of small
children [10].
In addition to the height and weight, the middle upper arm circumference (MUAC) of children
aged 6-59 months was measured according to WHO/UNICEF guidelines [11].
Figure 10: Height, weight and MUAC measurements
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2.3.2.2 Blood Pressure Measurement
Blood pressure (BP) of adults was taken using an automated sphygmomanometer (Topcom,
BPM Arm 1480). The reading was taken from the left upper arm with the participant in a
sitting position. The arm was placed in relaxed manner with the cuff at the level of the heart
(Figure 11).
Figure 11: Blood pressure measurement at the clinical field unit
2.3.2.3 Malaria, Anaemia and Syphilis Testing
A standard finger prick blood sampling method was used to obtain a capillary blood sample
from children aged 6-59 months and from adults above >15 years. This was performed using
universal protection and according to best practices. The following tests were performed in
the respective age groups:
•
in children aged 6-59 months, the sample was analysed for the presence of malaria
parasites and for anaemia (haemoglobin [Hb]);
•
in women of reproductive age (15-49 years) the sample was analysed for anaemia;
and
•
in women of reproductive age (15-49 years) the sample was screened for syphilis
antibodies that are present in people who have, or have had, the disease.
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Malaria diagnosis in children aged 6-59 months was performed using a malaria rapid
diagnostic test (RDT). In the survey protocol it was concluded that the sole use of RDTs was
acceptable for the BHS. RDT for malaria are highly sensitive and allow for easy
reproducibility in subsequent surveys in comparison to blood slides. Thus blood slides were
not selected as an analysis strategy. The RDTs used were ICT® kits (Global Diagnostics)
which are WHO approved for their high sensitivity and specificity [12]. The tests are based on
the detection of histidine rich protein-II (HRP-II) which is specific for Plasmodium falciparum,
which is the most common form of human malaria parasite in the Project region and which
also causes the most severe form of malaria. The tests were performed using standard
protocols provided by the manufacturer and guidelines from the WHO [13].
Figure 12: Finger pricking in adults and children aged 6-59 months
The HemoCue® test was used to assess Hb levels in women of the reproductive age group
(15-49 years) and children aged 6-59 months [14]. This is a highly reliable and accurate field
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test device, which is used by organisations such as UNICEF and MEASURE DHS for large
scale studies. The HemoCue® device is highly accurate when compared to formal laboratory
tests [15]. The tests were performed according to standard protocols as defined by the
manufacturer.
Women of reproductive age (15-49 years) were screened for syphilis antibodies that are
present in people who have, or have had, the disease. This was done using the Alere
DetermineTM Syphilis TP test, an in-vitro, visually read, qualitative immunoassay for the
detection of antibodies to Treponema pallidum, which is the bacteria that causes syphilis
infection, in human blood. The tests were performed according to standard protocols as
defined by the manufacturer.
All the blood samples were analysed in the field and results were available within 1-15 min,
which supported the ethical requirements of the survey in providing rapid treatment.
2.3.3 Parasitological Survey in Schoolchildren
The parasitological survey had per aim to determine the prevalence and intensity of
schistosomiasis and STH in schoolchildren aged 10-15 years. Schools were sampled in the
framework of the SS. Schools that were closer to any water-body or riverside were given
preference if there was more than one school in the selected sites. Both clinical and
laboratory studies were conducted. GPS references of selected schools were recorded.
2.3.3.1 Field Procedures for School Survey
Prior to any activity, information about the aim of the study was provided and permission to
proceed was obtained from community leaders and head teachers. Informed written consent
from the head teachers was recorded by the investigating field team. Only children aged 1015 years were selected. A maximum of 65 children were selected per school depending on
the setting as described earlier.
A questionnaire was given to each head teacher to ask children about the presence of visible
haematuria (bloody urine). In large schools with more than 30 children one class was
selected at random. Fresh stool samples were collected from a minimum of 30 children per
site. Fresh, terminal urine samples were collected around midday from a minimum of 30
children after exercise.
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Due to logistics constrains on the Island, distance and other difficulties, the stool samples
collected on the Island were preserved in 10% formalin and examined at Forécariah on the
fourth and fifth day of the survey.
Terminal urine samples were collected after 30 min moderate exercise around midday, fresh
from a minimum of 30 children per site and inspected for visible haematuria.
Each stool and urine sample had a unique ID number that was linked to the name, age and
sex of the child on a specific form. The height and weight as well as any visible haematuria in
the urine samples were recorded on the same form.
2.3.3.2 Laboratory Procedures
The stool sample was labelled and examined within 24 hours of collection by Kato Katz as
recommended by WHO [16]. A 50 µm template was used (Vestergard Asia, PVT Ltd). The
results were expressed in prevalence (%) and intensity of infection in eggs per gram (epg).
Urine samples were examined the same day by the filtration method for S. haematobium
eggs. The volume of urine samples was measured and urine containers were filtered. The
sediment of urine was transferred onto a slide. These were examined under a light
microscope and the number of S. haematobium eggs was recorded. The intensity of infection
was expressed as number of eggs per 10ml of urine (e/10ml).
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2.3.4 Drinking Water Quality Assessment
It was recognized as important to get a baseline indication of the quality of potable water at
each SS. Therefore, the most common community drinking water collection points in each
SS that were in use at the time of the survey were sampled (e.g. tube wells, open wells or
unprotected sources). In addition, drinking water samples were taken by the interviewers (10
randomly selected households at each SS) to support the determination of water quality at
the end-user level.
Finally, the comparison of the drinking water quality at community level with the samples
obtained at household level had the objective of providing an indication of the challenges
which the community faces in collecting, transporting and storing water safely, including any
treatment/purification (e.g. chlorination).
At community drinking water collection points, water was poured into a sterile testing bottle,
either from the collection container or directly from the standpipe while avoiding the use of
any interim container. At the household level water was taken directly from the drinking water
container. Care was taken not to contaminate the lid or the container by following a sterile
procedure.
The WHO has developed standards for drinking water and these were applied in the water
testing conducted in the survey so that a referenced and internationally accepted benchmark
could be applied [17, 18]. In the frame of the present study, the primary indicator for drinking
water quality was recent faecal contamination. In addition, the pH and turbidity was
determined as both parameters can adversely affect the efficiency of disinfection. Turbidity
was measured using a turbidity tube (see Figure 13) and expressed in turbidity units (NTU)
[17].
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Figure 13: Turbidity testing of drinking water samples
In the field laboratory water was tested for the presence and number of thermo-tolerant
coliforms (TTC), which indicate recent faecal contamination. For this purpose, collected
samples were analysed by means of the DelAgua® portable water quality testing kit as shown
in Figure 14 [19].
Figure 14: Drinking water testing with the DelAgua water quality testing kit
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The 100ml water samples were filtered using a membrane and incubated for 16-18 hours at
a temperature of 44.5°. In case of high turbidity, samples were diluted using distilled water.
After the incubation period the number of TTC that grew on the filter membrane was counted
(see Figure 15) and samples classified according to the degree of health concern as per
WHO guidelines (see Table 3).
Figure 15: TTC (yellow dots) on the filter membrane after the incubation period
Table 3: WHO classification of drinking water samples
TTC per 100ml
Acceptability
0
Compliant
1-10
Tolerable
11-100
Requires treatment
>100
Unsuitable for consumption without treatment
2.3.5 Health Facility Assessment
Health posts and centres in the wider Project area were assessed in regard to services
provided, availability of essential drugs and supplies, general infrastructure, human
resources and case load. The assessment was carried at the health facilities using a
standardized check list.
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2.4 Training of Field Workers
2.4.1 Interviewer Training
As interviewers played a critical role in the survey, emphasis was placed on training in order
to ensure a standardized interview technique. Once the interviewers were familiar with
general interview-techniques, the focus was shifted to the specific (health) content of the
questionnaires. Training was managed by two field supervisors and included participatory
methodologies to refine the techniques for conducting interviews as well as handling of GPS
devices (Garmin eTrex Summit HC).
2.4.2 Training of Medical Staff
The medical staff designated to work in the clinical field unit and in the parasitological
laboratory was trained in laboratory techniques prior to the commencement of field work.
This included specific training on the following topics:
•
survey methodology;
•
use of data entry forms and eligibility for the survey and different laboratory
components;
•
height and weight measurements – multimedia tools available from WHO and specific
training protocols on the measuring equipment (Seca scales) was performed;
•
use of ICT malaria RDTs based on a specific protocol with additional practical training
with a cheat sheet of common mistakes.
•
use of the HemoCue® device based on the multimedia tools provided by the supplier,
including practical training using standard specific protocols as well as a cheat sheet
with common mistakes;
•
use of Alere DetermineTM Syphilis TP test, including practical training using standard
specific protocols;
•
sharps handling and medical waste disposal;
•
stool and urine collection and transferring procedures;
•
sample preparation and examination; and
•
treatment protocol and escalation procedures.
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Figure 16: Training of medical staff
2.5 Data Management and Statistical Analysis
Quality assurance was initiated in the field at the clinical laboratory and in the questionnaire
teams. In the questionnaires the project manager and the epidemiologist supported various
individual interviewers in the initial stages and then based on need. All questionnaires were
checked in the field and signed off by either the epidemiologist or the project manager. The
clinical laboratory team was supervised by the field project director.
To ensure real-time capturing and reporting, the database was managed in the field by an
epidemiologist, using EpiData version 3.1 (EpiData Association; Odense, Denmark) and MS
Excel (Microsoft Office 2007). If any inconsistency was found at the data entry point, this was
clarified with the interviewer and if required the interviewer was returned to the respective
household to rectify any inconsistency.
Statistical analysis was carried out using STATA 10 (Stata Corp LP; Texas, USA). Frequency
tables were generated for most of the variables and summary statistics. Means (with
standard deviations) and medians (with inter-quartiles ranges) were described for (numerical)
continuous variables.
For the parasitological survey, data were analyzed using Excel, SPSS and Epi info
software. A frequency table with 95% CIs was used. Arithmetic mean intensity of infection
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was used in the analysis. Degree of intensity of infection for individual parasites was
categorised according to WHO recommendations. Differences in terms of sex were
determined using Chi square (X2) test.
2.6 Ethical Considerations
As an initial step a formal study protocol was developed for submission to the National Ethics
Committee for Health Research (‘Le Comité National d’Ethique pour la Recherche en Santé’
(CNERS)) for ethical approval. SHAPE Consulting Limited (SHAPE) developed and
submitted the study protocol for review and approval. The final ethics review committee
approval is attached in Appendix A.
At household level, written informed consent was obtained from all the study participants
before interviews began. This included the consent for the clinical field unit laboratory.
For the school survey the local education authorities and headmasters of the surveyed
schools were informed about the aim of the study and the need to seek informed consent
from parents. The head teachers provided consent for the children sampled in the school
survey, where prior consent had been obtained from parents/legal guardians of the children
selected to participate.
All participants were informed of their results in the field and a commitment was made to
feedback other data at a later stage. Individuals who tested positive for any of the tested
diseases were treated according to national treatment guidelines, free of charge. If a
participant was found ill in the survey and requires care the survey team provided transport
to the closest appropriate government health facility and supported with initial care.
2.6.1 Treatment
As part of the ethical requirements, each child tested positive for Plasmodium malaria was
treated with an artemisinin-based combination (ACT) therapy, using the national first-line
drug, i.e. artesunate-amodiaquine. Treatment was administered according to the child’s
weight.
Additionally, all children under the age of 5 years and women in reproductive age (15-49
years) were provided with nutritional supplements according to their level of anaemia.
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Women that tested positive for syphilis obtained treatment (azithromycin 2,000 mg as one
single dose PO) for themselves, their husband and additional spouses if there were any.
All children in the school survey were empirically treated with mebendazole 500 mg as one
single directly-observed dose. Schistosomiasis was treated based upon a positive result with
praziquantel 40mg/kg in a directly-observed dose after eating biscuits that were provided.
Adults found with hypertension and/or high blood sugar levels were counselled regarding
lifestyle modification and referred to the local health facilities.
2.7 Stakeholder and Community Consultation and Sensitization
Community consultation and sensitization was considered an essential initial activity. It had
the objective of informing the village authorities and communities of the activity to ensure
community participation, while also providing the opportunity for the community to address
their concerns about the survey. Conducting health surveys requires detailed community
information explaining the purpose and procedures, potential risks and benefits. This is to
allay expectations and misconceptions of the survey and its objectives.
In a first stage, information sessions were held at the level of national (Ministry of Health
(MoH), Conakry) and local health authorities (Directeur Préfectoral de Santé (DPS) de
Forécariah). In this process a formal authorisation for the planned BHS could be obtained
from the MoH in the form of an ‘Ordre de Mission’ (Appendix B).
In a second stage, the sensitisation and consultation activities were extended to the
potentially impacted communities in the proposed study area. This was supported by the Rio
Tinto community department and included meetings with village leaders and community
members where they were informed of the following:
•
the purpose of the proposed survey;
•
exact locations where the survey will be conducted;
•
strategy for community selection to participate in the survey and planned schedule;
•
procedures on how the households will be selected;
•
details on how the survey will be conducted and what kind of samples will be taken;
•
the extent of their individual involvement;
•
analytical plan on how the test results will be used;
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•
their right to be treated free of charge if found positive for a disease;
•
ethical considerations; and
•
reporting of results.
It was also pointed out that participation is voluntary and that the individuals may withdraw
from the survey at any time. Besides the community sensitization meetings the information
was also made available on pre-prepared posters which were posted in key visible areas for
all community members as illustrated in Figure 17.
Figure 17: Posters as part of community sensitization activities
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3 Findings of the Baseline Health Survey
3.1 Demographics and Sample Sizes
This BHS survey sampled 8 SS across the wider Project region as outlined in section 2.1.1.
Overall, the following samples were collected in the survey activities:
•
384 questionnaires were conducted in the questionnaire surveys, representing 31.4%
of the households of the 8 SS, with women serving as primary respondents as per the
inclusion criteria. Overall, 254 women and 130 men participated in the questionnaire
survey.
•
769 individuals were sampled at the clinical field unit. This represents approximately
8.9% of the selected population (i.e. children <5 years and adults >15 years).
•
240 urine and 240 stool samples were collected from schoolchildren (aged 10-15
years);
•
A total of 26 community drinking water collection points and 79 households were
sampled for water quality testing; and
•
3 health facilities were assessed.
Overall, 1,393 individuals participated in the different survey modules of the BHS at the 8
selected SS, as summarised in Table 4. As no precise data on household numbers from the
socio-economic baseline studies were available at the time of the BHS the number of
households per SS are estimations that were obtained in the field.
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Table 4: Demographics and sample sizes at the different sentinel sites
Sentinel site
Estimated
number of
HH*
Questionnaire survey at HH level
Number of
Children
HH
aged 0-6
sampled (% Number of Number of
months
of total HH)
women
men
(male:female)
Mainland
Clinical field unit
Children aged
6-59 months
(male:female)
Adults aged
≥15 years
(male:female)
Total
individuals
at clinical
field unit
School Survey
Total children
aged 10-15
years
(male:female)
40
26 (65.0%)
26
10
6 (3:3)
46 (23:23)
41 (6:35)
93
30
Sahrata
80
34 (42.5%)
34
16
4 (4:0)
50 (30:20)
39 (4:35)
93
30
Soungaya
100
33 (33.0%)
33
18
3 (1:2)
49 (32:17)
41 (5:36)
93
30
Farmoriya-Yindi village
Sub-Total
110
30 (27.3%)
20
9 (6:3)
42 (16:26)
40 (9:31)
91
30
330
123 (37.3%)
30
123
64
22 (14:8)
187 (101:86)
161 (24:137)
370
120
37 (6:31)
84
30
Tèrin
Kaback Island
Matakang
200
30 (15.0%)
30
11
8 (2:6)
39 (17:22)
Bossimiya
40
33 (82.5%)
33
17
6 (3:3)
53 (30:23)
47 (6:41)
106
30
Manké Centre
90
37 (41.1%)
37
20
5 (3:2)
56 (24:32)
54 (13:41)
115
30
Konimodiya
150
31 (20.7%)
31
18
7 (3:4)
42 (25:17)
45 (11:34)
94
30
Sub-Total
480
131 (27.3%)
131
66
26 (11:15)
190 (96:94)
183 (36:147)
399
120
Total
810
254 (31.4%)
254
130
48 (25:23)
377 (197:180)
344 (60:284)
769
240
* Estimate based on numbers given by the village head during field work (socio-economic baselines not yet available at the time of the survey)
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3.1.1 Number of Participants Treated
As part of the ethical requirements of the survey, treatment was provided to those who were
diagnosed with specific conditions in the survey:
•
ACT was provided to approximately 140 children who tested positive for Plasmodium
falciparum malaria. Health education was provided to the primary care-giver on
treatment schedule and the need to complete the full course. The first dose was
provided under direct observation;
•
240 schoolchildren were empirically treated for STH with mebendazole (single dose
500 mg PO);
•
5 schoolchildren were treated with a single dose of praziquantel for schistosomiasis
(40 mg/kg PO) after a meal;
•
approximately 450 children and 200 women in reproductive age (15-49 years) were
provided with nutritional supplements and health education;
•
two women and her husbands were treated with azithromycin (2g PO) for syphilis and
informed about transmission and prevention of the disease;
•
approximately 450 children and 200 women in reproductive age (15-49 years) were
provided with nutritional supplements and health education;
•
approximately 50 children were found with symptoms for acute respiratory infection
and treated with amoxicillin (500 mg tds PO for a minimum of 5 days);
•
mothers or caregivers of underweight children were given health education on how to
improve the nutritional status of their children;
•
adults found with high BP were advised on lifestyle changes and referred for further
medical investigations to the nearest health facilities.
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3.2 Clinical Field Unit
3.2.1 Prevalence of Malaria in Children Aged 6-59 Months
Introduction
Malaria, a protozoan infection transmitted by Anopheles mosquitoes, is the most important
parasitic disease of humans. Malaria is one of the most serious public-health issues in many
parts of the developing world, but especially so in sub-Saharan Africa. This holds true for
Guinea, where malaria is a major public health concern as it significantly contributes to the
burden of disease. In 2006, the annual malaria incidence was estimated at 164 cases per
1,000 people and was implicated as a contributing cause of up to 24% of causes of infant
mortality in 2008. Therefore, malaria is a major public health concern for all Guineans, but
especially for children under the age of 5. This is also reflected at the local level, where
malaria was reported to be the most important disease by the local health authorities,
accounting for the bulk of consultations in the study area [2]. The proposed Port
Development Project is situated within an area classified moderately endemic for P.
falciparum endemicity as shown in Figure 18. Based on this modelling the prevalence was
expected to be lower than the mine area in the East of the country [20].
Figure 18: Predicted P. Falciparum endemicity in Guinea
In 2007 and 2008 malaria was the leading cause of morbidity at the health facilities in
Forécariah prefecture with 39.7% (n=32,380) and 36.1% (n=18,004) of the consultations that
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were related to malaria, respectively [2]. In addition, in the first term of 2010 malaria was
clearly the leading cause of morbidity (n=16,485). However, these numbers do not reflect the
true malaria prevalence in the communities impacted by the Port Development Project. Thus,
the establishment of the baseline malaria prevalence before the Project commences or any
interventions were performed was considered as crucial.
In the present BHS, samples were collected from children (aged 6-59 months) at the
households that had been randomly selected for the questionnaire survey. Of note, the
malaria prevalence status was reported according to the RDT (positive/negative for P.
falciparum) and not based on clinical symptoms for malaria. Most of the participating children
were asymptomatic at the time of the survey.
The endemicity of malaria can be classified according to the following commonly used
categories by means of parasite rates in children aged 6-59 months:
•
Hypo-endemic: parasite rate 0-10%;
•
Meso-endemic: parasite rate 10-50%;
•
Hyper-endemic: parasite rate 50-75%; and
•
Holo-endemic: parasite rate >75% and parasite count high in first year of life.
Findings
A total of 376 children were tested for P. falciparum infection of which 123 tested positive.
This represents a mean point prevalence rate of 32.7% across the surveyed SS. The malaria
endemicity in the port site area can therefore be described as meso-endemic. Table 5
summarizes the malaria prevalence in each SS.
Table 5: Malaria prevalence in children aged 6-59 months, stratified by SS
Malaria
prevalence (%)
67.4
Number of
children
46
Sahrata
28.0
50
Soungaya
12.2
49
Farmoriya-Yindi village
26.2
42
Matakang
56.4
39
Bossimiya
15.1
53
Manké Centre
16.1
56
Konimodiya
53.7
41
Total
32.7
376
Sentinel Site
Tèrin
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Malaria prevalence was highest in Tèrin (67.4%), followed by Matakang (56.4%) and
Konimodiya (53.7%). The other SS had a point prevalence below 30.0%. The lowest
prevalence was found in Soungaya (12.2%). There was no significant difference in malaria
prevalence between the SS surveyed on the mainland and on Kaback Island (p=0.86).
The variation in prevalence across the SS is spatially depicted in Figure 19.
Figure 19: Prevalence of malaria across the SS
Figure 20 shows the differences in malaria prevalence by age group and by gender. Malaria
prevalence was almost the same in boys (32.5%) and in girls (33.0%), with no statistically
significant difference (p=0.55). Malaria prevalence was highest in the 48-59 month-old males
(59.3%) and lowest in the 6-11 month-old males at 13.2%. Malaria prevalence in females
was highest in the 36-47 month age group (43.2%) and also lowest in the 6-11 month age
group (18.2%). The most severely affected group were children aged 48-59 months, where
their odds of being malaria positive increased by 7 times compared to a child less than 11
months (OR=6.97; 95%CI: 2.59-18.79, p<0.01).
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100,0
80,0
59,3
60,0
50,0
%
29,3
24,5
18,2
20,0
13,2
47,1
43,2
41,9
40,0
46,4
33,3
32,9
27,0
33,0
32,5
32,7
23,8
15,0
0,0
6-11 (n=61)
12-23 (n=111)
24-35 (n=85)
36-47 (n=69)
48-59 (n=51)
6-59 (n=376)
Age in months
Male
Female
Total
Figure 20: Prevalence of malaria stratified by age group and gender
Discussion
There is considerable variation in malaria prevalence in the study area (range 12.2 – 67.4%),
which may be based on the size of communities and access to malaria prevention modalities
and effective treatment. However, no obvious cause for this variation could be determined.
The low prevalence levels in children aged 6-11 months is not abnormal, as these children
may still have some of their mother’s immunity which they acquired during pregnancy that
may provide protection against malaria. This acquired immunity is generally lost as the child
gets older, and with repeated inoculation, the child starts to develop its own immunity [21].
Insecticide-treated nets (ITN) are an important tool for controlling malaria. Preferential
provision of ITN coverage to the younger age groups remains the most beneficial distribution
of scarce resources as the burden of malaria-associated deaths and morbidity is likely to
remain highest in younger children. The continued long-term provision of ITNs holds promise
for effective malaria control in rural malaria endemic areas [22, 23]. Ownership and use of
ITNs in the surveyed communities is further outlined in section 3.4.4.2.
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3.2.2 Malaria-Related Anaemia in Children Aged 6-59 Months
More than half of all young children and pregnant women are affected by anaemia worldwide
[24]. Malaria causes anaemia through the constant haemolysis of red blood cells and comorbid effects linked to nutrition and other infectious diseases. The Global Fund to Fight
AIDS, Tuberculosis and Malaria uses malaria-related anaemia as an impact indicator, with a
Hb threshold value of below 8 g/dl regarded as the measure for severe-to-moderate anaemia
[25]. For purposes of the survey, malaria-related anaemia was defined as children who had
an Hb level of less than 8 grams/decilitre (g/dl).
Findings
A total of 376 children (aged 6-59 months) were analysed for presence of malaria-related
anaemia. 116 children (30.9%) were found to have moderate-to-severe anaemia (Hb less
than 8g/dl).
Figure 21 depicts the prevalence of malaria-related anaemia in different SS. The lowest
prevalence was found in Manké Centre (17.9%) and highest in Konimodiya where 39.0% of
the children were found with an Hb level less than 8 g/dl. There was no significant difference
regarding malaria-related anaemia between settings, i.e. the SS sampled on the mainland
and the SS sampled on Kaback Island (p=0.99).
Figure 21: Prevalence of malaria-related anaemia across the SS
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There was a significant association between malaria and malaria-related anaemia (p<0.01).
The odds of a child having an Hb level of less than 8g/dl increased by 3.1 times if the child
had malaria (Odds Ratio (OR) = 3.14, 95%CI: 1.89-5.26, p<0.01) whereas the model was
adjusted for gender and age.
Prevalence of malaria-related anaemia was highest in 12-23 month-olds for both genders
(44.8% in males and 43.4% in females, respectively) as shown in Figure 22. The lowest
prevalence was found in females aged 48-59 months (20.8%). Logistic regression revealed
no significant difference in malaria-related anaemia after stratifying by gender (p=0.91) but
children in the 12-23 month-old age group were 2.3-2.6 times more likely to be found with
malaria-related anaemia compared to children of other age groups.
100,0
80,0
60,0
44,8
%
40,0
43,4
44,1
30,7
27,9
31,8
21,1
25,0
25,9
23,8
26,1
31,3
23,5
25,9
21,6
20,8
36-47 (n=69)
48-59 (n=51)
31,0
30,9
20,0
0,0
6-11 (n=60)
12-23 (n=111)
24-35 (n=85)
6-59 (n=376)
Age in months
Male
Female
Total
Figure 22: Prevalence of malaria-related anaemia stratified by age group and gender
Discussion
There was a clear and significant association between malaria and anaemia (p<0.01),
where children found to be malaria positive were 3.5 times more likely to have an Hb level
below 8 g/dl. Therefore it is important to follow trends of anaemia prevalence as it is an
important indicator of malaria morbidity in children aged <5 years. Malaria control
interventions have been associated with a 60% reduction in the risk of moderate anaemia
and more especially in severe anaemia [26-28].
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3.2.3 Nutritional Indicators
The fourth report on global nutrition showed that the challenge of malnutrition is still very high
and that progress to reduce it in most parts of the world is slow. It was estimated that in the
year 2000, 182 million preschool-aged children, or one-third of children below the age of 5
years in developing countries were stunted, while about 27% were underweight, which
underscored long-term cumulative inadequacies of health and/or nutrition [29]. According to
the 2005 Guinean Demographic and Health Survey (GDHS), 34.5% of the children in Kindia
region were stunted, 6.2% were wasted and 16.7% were underweight [30].
Malnutrition has been known to not only result from, but also perpetuate poverty and
undermines socio-economic growth in the affected communities. It remains one of the
greatest concerns in public health and the largest contributing factor to child mortality in
developing countries, where the majority of children who are malnourished are concentrated.
Malnutrition links into more than half the deaths of children, as a co-morbid factor, as
malnourished children are more likely to acquire infections through low levels of inherent
resistance. They are more likely to die from common childhood illnesses, such as diarrhoea
and respiratory tract infections, and if they survive these initial insults, they often enter a
continuous cycle of illness until they do eventually succumb to an infection. It is very
important to understand that ¾ of children that die with a link to malnutrition only have
moderate levels of under-nourishment thus not making this very visible in general
communities.
Findings
In the BHS, four global indicators of malnutrition were assessed: stunting, wasting,
underweight and MUAC. A total of 420 children under the age of 5 years had their
height/length and weight measured and age recorded. The WHO reference anthropometric
standards were used to determine stunting (height-for-age), wasting (weight-for-height),
underweight (weight-for-age) and MUAC-for-age (middle-upper-arm-circumference) among
the children [31].
Table 6 summarises the nutritional indicators found from the survey and compares them,
where possible, to the findings of the 2005 GDHS [32]. The data was pooled across all SS.
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Table 6: Summary of nutritional indicators
Severely
wasted
(% <-3SD)
2.8
Wasted
(% <-2SD)
9.2
Stunted
(% <-2SD)
37.2
Underweight
(% <-2SD)
17.4
MUAC
(% <-2SD)
15.6
Total
number of
children
218
Female
Total
1.0
3.0
35.1
15.8
11.6
202
1.9
6.2
36.2
16.7
13.7
420
2005 GDHS
1.8
9.4
34.8
25.8
-
2,786
2005 GDHS Kindia
0.8
8.0
34.5
25.2
-
419
Background
characteristic
Male
The prevalence of severe wasting (1.9%) was significantly higher than that found in the
GDHS for the Kindia region (0.8%) but is comparable to the national average (1.8%). The
percentage of children who were stunted (36.2%) was slightly higher than that found in the
2005 GDHS both nationally (34.8%) and regionally (34.5%). The percentage of children
found underweight (16.7%) was however lower than that found in the 2005 GDHS nationally
(25.8%) and regionally (25.2%). Boys showed higher rates of malnutrition across all four
nutritional indicators compared to girls.
Important age variations can be observed in nutritional indicators as shown in Figure 23. All
indicators are highest and thus worst in children in their 3rd year of life (aged 24-35 months).
100
% < -2 SD
80
60
Wasting
40
Stunting
Underweight
20
MUAC-for-age
0
0-5
(n=49)
6-11
(n=60)
12-23
(n=111)
24-35
(n=90)
36-47
(n=71)
48-59
(n=39)
Age in months
Figure 23: Nutritional status in children under 5 years by age group
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Discussion
Anaemia, malaria and malnutrition as discussed, all contribute significantly to the
morbidity/mortality of children under 5 years of age in sub-Saharan Africa, but it is generally
agreed that the individual roles for conferring disease is complex. In a study completed in
Ghana in 2002 all three components (stunting, underweight and wasting) were evaluated in
areas of hyper-endemic malaria transmission (i.e. malaria prevalence of >50%). Anaemia
was noted in 64% of the children and was not only associated with young age and
seasonality, but also with nutrition. In addition to this, malnutrition was also associated
independently from fever and malaria. The conclusion of this study was that malnutrition was
a fundamental factor contributing to malaria-associated anaemia and morbidity and that
malaria control programmes will not have the desired impact in childhood mortality without
supporting concurrent nutritional programmes [33].
The different nutritional indicators will be described in more detail in the following sections.
3.2.3.1 Wasting (Weight-for-Height)
Children, who are wasted, are those that have a low weight-for-height/length z-score which is
below -2 SD from the median weight-for-height of the WHO reference population.
Wasting, also referred to as acute malnutrition, is a widely used measure to determine food
availability or burden of disease estimation in affected populations. It can thus identify
significant seasonal variations associated with food availability or increases in disease
prevalence. The situation can change rapidly. It is often a consequence of low intake of
energy and high loss of nutrients due to concurrent infection. Follow-up surveys should
therefore preferably be conducted at the same time of the year to facilitate comparison.
When using weight-for-height, WHO and UNICEF recommend the use of a cut-off for weightfor height of below -3 SD to identify infants and children who have severe acute malnutrition
[10]. This cut-off value has been selected for the following reasons:
•
children below this cut-off have a higher risk of death. Figure 24 shows the increasing
OR for mortality where children with a weight-for-height below -3 SD have a risk of
death that is more than 9-fold higher compared to children with a weight-for-height
above -1 SD;
•
children show a higher weight gain when receiving a therapeutic diet compared to
other diets, which results in faster recovery; and
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•
Baseline Health Survey
February 2012
in a well-nourished population there are virtually no children below -3 SD (<1%).
Figure 24: Odds ratio for mortality based on wasting
Children who were moderately wasted (< -2 SD) represented 6.2% of the study population,
while 1.9% of the children were found to be severely wasted (< -3 SD). Table 7 stratifies
rates of wasting according to different age groups. None of the children aged 0-5 months
were severely wasted as they were likely to still be breastfeeding. However, the rates of
severe and moderate wasting were highest in children aged 24-35 months (4.4% and 13.3%,
respectively) and decrease markedly after this. Boys were found more affected by wasting
than girls in this BHS.
Table 7: Prevalence of wasting in children under 5 years
Severely
wasted
(%<-3SD)
0.0
Moderately
wasted
(%<-2SD)
6.1
Total number
of children
49
6-11
1.7
8.3
60
12-23
2.7
4.5
111
24-35
4.4
13.3
90
36-47
0.0
1.4
71
48-59
0.0
0.0
39
Total
1.9
6.2
420
Male
2.8
9.2
218
Female
1.0
3.0
202
Total
1.9
6.2
420
2005 GDHS
1.8
9.4
2,786
2005 GDHS Kindia
0.8
8.0
419
Background
characteristics
0-5
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Findings of this survey were compared and plotted against WHO standards (Figure 25). The
green line outlines the WHO standards and the red line the findings from the BHS. This
figure shows a slight shift of the curve to the left, showing that acute malnutrition is a not a
major health concern in the area at this time of the year. It is important to note that numbers
of severe and moderate wasting are highly dependent on seasonal fluctuations, and hence
these findings need to be interpreted with care.
Figure 25: Weight-for-age distribution in children <5 years compared to WHO standards
3.2.3.2 MUAC-for-Age
MUAC-for-age is, similar to wasting, a sensitive indicator for acute malnutrition in the
population. It is recognised that MUAC is a more precise indicator for mortality risk than
weight-for-height (wasting). Therefore, to complete the picture of (acute) malnutrition in the
community, MUAC was measured for all children under the age of 5 years, whereas MUAC
is not calculated for children 0-3 months of age. Although MUAC excludes older children with
low weight-for-age, together they provide a comprehensive picture of malnutrition in the
community [34].
In a well-nourished population, there are very few children aged 4-59 months with a MUAC
less than 115 mm. Children with MUAC <115 mm have a significantly increased risk of
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morbidity, with malnutrition as a co-morbid factor, compared to those with values above this
threshold [11].
3.0% of children had MUAC values below -3 Z-scores which indicate severe acute
malnutrition. The prevalence of MUAC-for-age for moderate malnutrition of 13.7% was higher
than the prevalence of moderate wasting (6.2%). Table 8 shows the percentage of children
aged 4-59 months with low MUAC-for-age stratified by age group. As for wasting, boys were
found more affected by low MUAC than girls.
Table 8: Prevalence of low MUAC in children aged 4-59 months
Severely low
MUAC
(%<-3SD)
4.3
Moderately
low MUAC
(%<-2SD)
4.3
Total number
of children
23
6-11
1.7
15.0
60
12-23
3.6
17.1
111
24-35
5.6
16.7
90
36-47
1.4
7.0
71
48-59
0.0
12.8
39
Total
3.0
13.7
394
Male
3.4
15.6
205
Female
2.6
11.6
189
Total
3.0
13.7
394
Background
characteristics
0-5
Figure 26: MUAC-for-age distribution in children <5 years compared to WHO standards
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Figure 26 depicts the MUAC distribution curve of the survey children, which shows a shift to
the left when compared to the WHO standard distribution. The average for the BHS
population is -1.0 SD below the WHO predicted values of the reference population.
3.2.3.3 Stunting (Height-for-Age)
Stunting is also referred to as chronic malnutrition. It reflects a deficit in the consumption of
micro- and macro-nutrients and also potentially exposure to infections, poor water and
sanitary conditions. Low Z-scores indicate long-term chronic malnutrition in children under
the age of 5 years. Affected children are shorter than expected and experience long-term
sequelae such as poor physical growth, cognitive and general development which is often
irreversible. Poor productivity is a likely long-term effect.
Table 9 shows the number percentages of children who were moderately and severely
stunted in each age group. A little over a third of the children (36.2%) were moderately
stunted while 14.5% of the children were severely stunted. The prevalence of stunting was
highest in children aged 24-35 months, where almost a quarter (22.2%) of the children were
severely stunted and almost half (48.9%) were moderately stunted.
Table 9: Prevalence of stunting in children under 5 years
Severely
stunted
(%<-3SD)
8.2
Moderately
stunted
(%<-2SD)
12.2
Total number
of children
49
6-11
5.0
15.0
60
12-23
18.0
45.0
111
24-35
22.2
48.9
90
36-47
14.1
39.4
71
48-59
10.3
38.5
39
Total
14.5
36.2
420
Male
14.7
37.2
218
Female
14.4
35.1
202
Total
14.5
36.2
420
2005 GDHS
15.3
34.8
2,786
2005 GDHS Kindia
11.2
24.5
419
Background
characteristics
0-5
Boys were more stunted than girls at the both levels of severe and moderate stunting (Table
9). Studies have shown that this is often the case in sub-Saharan Africa although the causes
are multi-factorial [35].
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The comparison of the BHS findings to the WHO height-for-age standards revealed that
there is a big shift to the left (Figure 27) in the BHS population which emphasizes the high
prevalence of stunting in the project area. This will be an important indicator to monitor as the
project progresses.
Figure 27: Height-for-age distribution in children <5 years compared to WHO standards
3.2.3.4 Underweight (Weight-for-Age)
Underweight reflects both, the poor past (chronic) and/or present (acute) under nutrition of
the (under 5 years of age) population. This has a particular reference to food availability in
the community over time.
The prevalence of severe underweight was 6.2% while the prevalence of moderate
underweight was 16.7% (Table 10). Prevalence of both severe and moderate underweight
was highest in the 24-35-month age group. More boys were underweight compared to girls.
Overall, the results found in this BHS were lower than the national and regional averages
found during the 2005 GDHS.
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Table 10: Prevalence of underweight in children under 5 years
Severely
underweight
(%<-3SD)
8.2
Moderately
underweight
(%<-2SD)
8.2
Total number
of children
49
6-11
6.7
13.3
60
12-23
3.6
19.8
111
24-35
11.1
22.2
90
36-47
4.2
15.5
71
48-59
2.6
12.8
39
Total
6.2
16.7
420
Male
7.3
17.4
218
Female
5.0
15.8
202
Total
6.2
16.7
420
2005 GDHS
7.1
25.8
2,786
2005 GDHS Kindia
7.0
25.2
419
Background
characteristics
0-5
Accordingly, when compared to the WHO reference population, the curve in Figure 28 is
skewed to the left, which indicates the presence of underweight children in the population.
Figure 28: Weight-for-age distribution in children <5 years compared to WHO standards
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3.2.4 Anaemia
3.2.4.1 Prevalence and Intensity of Anaemia in Children Aged 6-59 Months
Iron deficiency and anaemia are public health problems in both the developing and
developed countries, where it is predicted that more than 2 billion people around the world
are anaemic. Anaemia adversely affects health, cognitive development, school achievement
and work performance. Young children and pregnant women are the most vulnerable groups,
and this holds true for Guinea [36, 37].
Anaemia is a common cause of morbidity and mortality in resource-poor settings in the
tropics, especially with the high burden of disease from malaria, intestinal parasites (e.g.
hookworm infections) and the effects of malnutrition. Although other causes of anaemia,
such as haemorrhage, infections, genetic disorders, and chronic diseases play a role,
nutritional deficiency (due primarily to a lack of dietary iron) accounts for the majority (half the
global burden) of anaemia cases. Iron deficiency, is caused by inadequate dietary intake of
bio-available iron, increased iron requirements during rapid growth periods (such as
pregnancy and infancy), and increased blood loss/haemolysis due to parasitic infections.
The following reference ranges based on WHO standards [12] were used to classify types of
anaemia (based on measurements of haemoglobin with the unit of g/dl), which are different
to malaria-related anaemia as described in section 0:
•
≥11 g/dl: normal;
•
10-10.9 g/dl: mild anaemia;
•
7-9.9 g/dl: moderate anaemia; and
•
<7 g/dl: severe anaemia.
Findings
A total of 376 children (aged 6-59 months) were tested for anaemia. 364 children (88.6%;
95%CI: 0.85-0.92%) were found to have some form of anaemia (Hb <11 g/dl). 14.4% of the
children had severe anaemia, 60.1% had moderate anaemia and the remaining 14.1% had
mild anaemia as reported in Table 11. The anaemia levels found during this survey are
markedly higher for moderate and severe anaemia than the levels found nationally and in the
Kindia region as reported in the 2005 GDHS [32].
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Table 11: Proportion of children with anaemia by intensity, age group and gender
Level of anaemia (%)
Background
characteristic
Mild
(10-10.9g/dl)
Any
anaemia
Moderate
Severe
(<11g/dl)
(7-9.9 g/dl)
(<7g/dl)
By age group (age in months)
Not
anaemic
(%)
Total
number of
children
5.1
60
6-11
13.3
73.3
8.3
94.9
12-23
12.6
59.5
19.8
91.9
8.1
111
24-35
15.3
58.8
11.8
85.9
14.1
85
36-47
14.5
56.5
15.9
86.9
13.1
69
48-59
15.7
52.9
11.8
80.4
19.6
51
87.8
12.2
197
By gender
Male
11.2
58.7
17.9
Female
17.2
61.7
10.5
89.4
10.6
179
Total
14.1
60.1
14.4
88.6
11.4
376
2005 GDHS
23.7
45.7
6.5
75.9
24.9
2,599
2005 GDHS Kindia
23.1
42.5
5.0
70.6
29.4
385
Trends of anaemia levels for the different age groups over time are shown in Figure 29.
94.9% of children in the youngest age group (6-11 months old) were found anaemic.
Moderate anaemia was highest in this age group, where almost three quarters were found
moderately anaemic (73.3%) and the trend then decreased with age. Severe anaemia was
most prevalent in children aged 12-23 months (19.8%).
100
80
60
%
Mild anaemia
40
Moderate anaemia
Severe anaemia
20
0
6-11
(n=60)
12-23
(n=111)
24-35
(n=85)
36-47
(n=69)
48-59
(n=51)
Age in months
Figure 29: Anaemia intensity in children aged 6-59 months by age group
Mean haemoglobin levels for the different age groups generally increased with age; it was
lowest in the 12-23 months age group (8.3±1.7 g/dl) and highest in the 48-59 month age
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group (9.3±1.9 g/dl). Therefore the oldest age group (48-59 month-old) was less likely to
have anaemia than the other age groups but not significantly (OR=0.38; p=0.065).
Gender differences, though not statistically significant (p=0.336), showed that the prevalence
of anaemia was slightly higher in girls (89.4%) than in boys (87.8%). Girls were more
affected by mild and moderate anaemia, while boys were more affected by severe anaemia.
Anaemia prevalence by age groups and gender is shown in Table 12 and prevalences and
classification of anaemia for the different SS is shown in Table 13.
Table 12: Proportion of children with anaemia by intensity, age group and gender
Level of anaemia (%)
Mild
(10-10.9g/dl)
Moderate
(7-9.9 g/dl)
Severe
(<7g/dl)
Background
characteristic
6-11
Male
Female
Male
Female
10.8
17.4
75.7
69.6
8.1
8.7
12-23
12.1
13.2
56.8
62.3
25.9
13.2
24-35
19.1
11.6
42.8
74.4
16.7
7.0
36-47
3.1
24.3
62.5
51.4
21.9
48-59
7.4
25.0
59.3
45.8
Total
11.2
17.2
58.7
61.7
Male
Female
Any anaemia
(<11g/dl)
Male
Not anaemic
(%)
Female
Male
Female
94.6
95.7
5.4
4.3
94.8
88.7
5.2
11.3
78.6
93.0
21.4
7.0
10.8
87.5
86.5
12.5
13.5
11.1
12.5
77.8
83.3
22.2
16.7
17.9
10.5
87.8
89.4
12.2
10.6
Table 13: Proportion of children with anaemia by intensity and sentinel site
Level of anaemia (%)
Mild
(10-10.9g/dl)
15.2
Moderate
(7-9.9 g/dl)
71.7
Severe
(<7g/dl)
10.9
Any
anaemia
(<11g/dl)
97.8
Sahrata
14.0
62.0
20.0
96.0
4.0
50
Soungaya
20.4
59.2
8.2
87.8
12.2
49
Farmoriya-Yindi village
16.7
54.7
16.7
88.1
11.9
42
Matakang
5.3
81.6
10.5
97.4
2.6
39
Bossimiya
17.0
49.0
20.8
86.8
13.2
53
Manké Centre
16.1
46.4
5.4
67.9
32.1
56
Konimodiya
4.8
64.3
23.8
92.9
7.1
41
Total
14.1
60.1
14.4
88.6
11.4
376
Sentinel Site
Tèrin
Not
anaemic
(%)
2.2
Total
number
of
children
46
The highest anaemia prevalence was found in Tèrin, where 97.8% of children where found
with any form of anaemia. The lowest anaemia prevalence was found in children living in
Manké Centre (67.9%), where 16.1% were found to be mildly anaemic, 46.4% moderately
anaemic and 5.4% severely anaemic. The highest anaemia prevalence for severe anaemia
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was found in Konimodiya, where almost a quarter of the children were severely anaemic
(23.8%). Moderate anaemia was highest in Matakang at 81.6%.
Figure 30 depicts the prevalence of anaemia prevalence and anaemia intensity in the
different SS.
Figure 30: Prevalence and intensity of anaemia across the SS
3.2.4.2 Prevalence and Intensity of Anaemia in Women of Reproductive Age
Anaemia in women of reproductive age is an important indicator of maternal well-being.
Anaemia in pregnancy can be a serious problem, since it can lead to premature delivery and
low birth weight of newborns. It can also increase post-partum complications leading to
higher maternal mortality rates. In the setting with high malaria rates, anaemia can be an
important co-morbid factor to the effects of malaria infection.
A total of 287 women were examined for anaemia. Of these, 17 (5.9%) were pregnant.
Similar reference ranges like those used to measure childhood anaemia were used, with any
value below 10.9 g/dl deemed as below the reference range.
Table 14 shows the frequency of anaemia in different SS, stratified by pregnancy status.
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Table 14: Anaemia in women (15-49 years) by sentinel site (n=287)
Level of anaemia (%)
Any anaemia
(<11g/dl)
Not anaemic
(%)
Yes
0.0
No
57.6
Yes
100.0
No
42.4
3.0
0.0
42.4
100.0
57.6
0.0
0.0
0.0
62.9
0.0
37.1
100.0
n.a.
0.0
n.a.
51.6
n.a.
48.4
n.a.
0.0
3.5
50.0
72.4
50.0
27.6
50.0
22.5
0.0
0.0
0.0
37.5
0.0
62.5
100.0
14.3
16.7
0.0
0.0
34.3
33.4
65.7
66.6
0.0
11.8
50.0
0.0
50.0
38.3
100.0
61.7
0.0
5.9
25.9
41.2
0.7
11.8
48.8
58.9
51.2
41.1
Sentinel Site
Mild
(10-10.9g/dl)
Moderate
(7-9.9 g/dl)
Tèrin
No
36.4
Yes
0.0
No
21.2
Yes
100.0
No
0.0
Sahrata
15.2
0.0
24.2
100.0
Soungaya
FarmoriyaYindi village
Matakang
28.6
0.0
34.3
0.0
19.3
n.a.
32.3
17.2
0.0
51.7
Bossimiya
15.0
0.0
Manké Centre
20.0
16.7
Konimodiya
26.5
Total
22.2
Severe (<7g/dl)
By pregnancy status
Yes
0.0
There was a significant association between malaria and malaria-related anaemia (p<0.01).
The odds of a child having an Hb level of less than 8g/dl increased by 3.1 times if the child
had malaria (OR=3.14, 95%CI: 1.89-5.26, p<0.01) whereas the model was adjusted for
gender and age.
Discussion
The 88.6% anaemia prevalence found in this study is a public health concern. The most
likely reasons for the high anaemia prevalence are (i) low consumption of iron due to the
limited varied diet; (ii) limited sanitation services leading to high rates of infections and
parasitic diseases; and (iii) high rates of infectious disease including malaria [36].
Anaemia prevalence in children was high in lower age groups and declined in the oldest age
group. Similar results have been found in other anaemia prevalence studies [36]. Iron
requirements are related to growth velocity and so requirements per kg of body weight
decreases with age. Therefore, there may be a physiological explanation for the fall in
anaemia prevalence with age and the general decline in anaemia prevalence with age in the
study area supports this.
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3.2.5 Syphilis in Women of Reproductive Age
Syphilis is a sexually transmitted infection (STI) caused by the bacterium Treponema
pallidum. Untreated STIs can have critical implications for reproductive, maternal and child
health. 25% of pregnancies in pregnant women with untreated early syphilis result in stillbirth
and 14% of pregnancies result in neonatal death [38]. Syphilis, like HIV, can also be
transmitted from mother to child during pregnancy and childbirth. Importantly, untreated STIs
increase the risk of both acquisition and transmission of HIV by a factor of up to 10. Prompt
treatment for STIs is thus important to reduce the risk of STI and HIV infection. Syphilis can
cause particularly severe congenital conditions in a child born to a mother that has active
syphilis infection. The disease can also cause long term cardiovascular and neurological
sequelae.
Syphilis in women of reproductive age was selected as an indicator for STIs within the study
population and results are shown in Table 15. Only 2 women were tested positive for
syphilis, both living in Bossimiya. This gives an overall point prevalence of syphilis of 0.7%.
Table 15: Syphilis prevalence in women (15-49 years) by sentinel site
Syphilis
prevalence (%)
0.0
Number of
women
35
Sahrata
0.0
36
Soungaya
0.0
36
Farmoriya-Yindi village
0.0
31
Matakang
0.0
30
Bossimiya
4.9
41
Manké Centre
0.0
41
Konimodiya
0.0
35
Total
0.7
285
Sentinel Site
Tèrin
Both women that tested positive for syphilis reported that they once lived in a town
(Forécariah and Conakry), which also accounted for their husbands. Furthermore the women
reported that their husbands travel to different parts of the country on a regular basis.
Discussion
The low prevalence of syphilis in the survey communities (only in 1 out of 8 SS syphilis cases
were identified) indicates a low level of STIs and associated activities such as commercial
sex work and exchange with areas that are likely to have higher incidence rates. At the same
time it shows that the control of sexually transmitted diseases will be important in the zone of
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influence of the Port Development as this may to trigger in-migration from areas where high
prevalences of STI are anticipated (e.g. Conakry) and the infleunces from temporary work
camps.
3.2.6 Blood Pressure in Adults
The health care services in the area have limited resources and capabilities to recognise,
diagnose and manage chronic diseases [2]. Hence, blood pressure (BP) was evaluated as
an indicator for chronic disease. In 90-95% of cases, hypertension is caused by an
interaction of genetic as well as environmental factors such as diet and physical activity.
Hypertension damages end organs and is a risk factor for stroke, heart attack, heart failure,
damage to the eye and the leading cause of chronic renal failure. High BP is a risk factor for
premature death in adults.
BP was measured in 344 participants (57 male; 287 female). Five different categories were
considered based on the criteria presented in Table 16 [39].
Table 16: Classification of BP for adults
Category
Systolic (mm Hg)
Diastolic (mm Hg)
<90
<60
Normal
90-120
and 60-80
Pre-hypertension
121-139
or 81-89
Stage 1 hypertension
140-159
or 90-99
Stage 2 hypertension
≥160
or ≥100
Hypotension
Based on this classification, 71.9% of men (n=41) and 48.4% of women (n=139) were
defined as having some form of hypertension. However, there were far more women than
men who presented for BP analysis (16.6% male and 83.4% female). There was a significant
difference in prevalence between the genders (p=0.01). The gender specific differences in
BP rates are shown in Table 17.
Table 17: Percentage distribution of BP in adults
Category
Male (%)
Female (%)
Total (%)
Hypotension
1.8
9.1
7.9
Normal
26.3
42.5
39.8
Pre-hypertension
42.1
33.1
34.6
Stage 1 hypertension
19.3
9.7
11.3
Stage 2 hypertension
10.5
5.6
6.4
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Mean BP for all adults were measured at 120/76 mm Hg with gender differences at 130/80
mm Hg for men and 118/75 mm Hg for women, respectively. Thus, the mean values showed
a prevailing normotensive state. Men had higher rates of pre-hypertension as well as stage 1
and 2 hypertension than women.
It must be emphasised that these levels may be biased (i.e. slightly increased) due to the
stress of the examination. All attempts were made to minimise this, but “white coat”
hypertension may exist. There was no option to follow up the participants that had prehypertension or overt hypertension, so this data provides a snap shot of the potential burden
of hypertension in the community. More reliable longitudinal data will be obtained from
supporting health systems strengthening and tracking hypertension as part of future
community health surveillance activities.
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3.3 Parasitological Survey in Schoolchildren
Schistosomiasis is transmitted by contact with infected freshwater and requires the
intermediate host snails, Biomphilaria spp. for S. mansoni, and Bulinus spp. for S.
haematobium. In contrast, STH are transmitted by contact with infected soil and are
prevalent in areas with poor water and sanitation practices. Hookworm is transmitted by
direct exposure to soil by skin (walking or farming barefoot) as well as exposure through the
faecal-oral route (contaminated food and water). STH and schistosomiasis often affect
school children by causing anaemia, poor weight gain, slow growth, poor concentration in
their “learning years”, finally resulting in poor school achievement and eventually reduced
adult earning capacity.
The BHS in the Simandou mining area in May 2010 found the following parasite prevalences
and intensities: S. mansoni 66.2% (462 epg); S. haematobium 21.0% (18 e/10ml); hookworm
51.2% (508 epg); Ascaris 8.1% (89 epg); and T. trichiura 2.4% (17 epg) [40].
The parasitological survey in the Port Development area followed the 8 SS that were
sampled by the other survey components. At each site, 30 school children aged 10-15
years were randomly selected from the primary schools, balancing for gender ratio where
possible. In total, 240 school children were selected, comprising 139 boys and 101 girls with
no mean age difference (11.7±1.5years). As height above sea level is important in the
distribution patterns of schistosomiasis transmission the exact GPS reference point and
elevation were recorded at each of the SS as shown in Table 18.
Table 18: Sampling locations and elevations
Village, Chiefdom, District
North
West
Elevation
Matakang
09.27255˚
013.42204˚
±4m
Soungaya
09.44206˚
013.35235˚
±3m
Farmoriya-Yindi village
09.41241˚
013.31801˚
±3m
Sahrata
09.54052˚
013.28404˚
±3m
Bossimia
09.32979˚
013.40979˚
±8m
Konimodiya
09.37517˚
013.41945˚
±3m
Manké Centre
09.33404˚
013.40368˚
±3m
Térin
09.51861˚
013.24051˚
±3m
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3.3.1 Prevalence and Intensity of Schistosomiasis Infection
The overall prevalence of S. mansoni was 1.7% (95% CI: 0.5-4.2; range 0.0-6.6%) and S.
haematobium prevalence was found to be 0.4% (95% Cl: 0.0-2.3; range 0.0-3.2%). No
visible haematuria was detected. Interestingly, none of the SS surveyed on Kaback Island
showed schistosome infections. S. mansoni prevalence was highest in Sahrata at 6-7%. S.
haematobium infections were only found in Farmoriya-Yindi village at 3.2%. Results for the
individual sites are summarized in Table 19.
Table 19: Prevalence of S. mansoni and S. haematobium
Sentinel Site
Mean age ± SD
S. mansoni (%; 95%CI)
S. haematobium (%; 95%CI)
Tèrin
11.7 ± 1.8
3.3 (0.1-17.2)
0.0 (0.0-11.6)
Soungaya
11.6 ± 1.5
0.0 (0.0-11.9)
0.0 (0.0-11.9)
Farmoriya-Yindi village
12.0 ± 0.8
3.2 (0.1-16.7)
3.2 (0.1-16.7)
Sahrata
11.8 ± 1.6
6.7 (0.8- 21.1)
0.0 (0.0-11.6)
Matakang
11.4 ± 1.5
0.0 (0.0-11.6)
0.0 (0.0-11.6)
Bossimiya
11.7 ± 1.1
0.0 (0.0-11.6)
0.0 (0.0-11.6)
Konimodiya
11.8 ± 1.4
0.0 (0.0-11.6)
0.0 (0.0-11.6)
Manké Centre
11.9 ± 1.7
0.0 (0.0-11.6)
0.0 (0.0-11.6)
Overall
11.7 ± 1.5
1.7 (0.5-4.2)
0.4 (0.0-2.3)
There were no significant differences in prevalence of S. mansoni by gender (p>0.05). All
sites are classified as having a low prevalence of Schistosomiasis with rates below <10%.
The arithmetical mean intensity was very low at 1.7 epg (95% CI: 0.5-2.8) for S. mansoni and
0.1 e/10ml (95% Cl: 0.0-0.2) for S. haematobium as shown in Table 20. The overall intensity
of schistosome infections for the surveyed SS is thus classified as light infections.
Table 20: Intensities of S. mansoni and S. haematobium infections
Intensity categories
Overall intensity (95% Cl)
epg
S. mansoni (epg)
1.7 (0.5-2.8)
S. haematobium (epg)
0.1 (0.0-0.2)
236
239
Light
2
1
Moderate
2
0
Heavy
0
0
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3.3.2 Prevalence and Intensity of STH Infections
STH infections, particularly hookworm, were widespread in the study area, as summarized in
Table 21. The overall prevalence of any STH infection (i.e. single or mixed STH infections)
was 66.7%, which classifies the area as highly endemic for STHs (i.e. >50%). The mean
level of STH infection was higher on Kaback Island (77.5%) when compared to the mainland
(55.7%). Only Sahrata (central community of Maférinya) (43.3%) and Tèrin (control village
close to Maférinya) (50.5%) had moderate prevalences of any STH (i.e. 20-50%), while the
remaining 6 SS showed high levels (>50%) as shown in Figure 31.
Table 21: Prevalence of STH by sentinel site
Sentinel Site
Tèrin
Ascaris
(%; 95% CI)
33.3 (17.3-52.8)
Hookworm
(%; 95% CI)
20.0 (7.7-38.6)
Trichuris
(%; 95% CI)
0.0 (0.0.-11.6)
Any STH
(%; 95% CI)
50.0 (31.3-68.7)
Soungaya
24.1 (10.3-43.5)
44.8 (26.4-64.3)
0.0 (0.0-11.9)
55.2 (35.7-73.6)
Farmoriya-Yindi village
16.1 (5.5-33.7)
58.1 (39.1-75.5)
0.0 (0.0-11.2)
74.2 (55.4-88.1)
Sahrata
30.0 (14.7-49.4)
23.3 (9.9-42.3)
0.0 (0.0-11.6)
43.3 (25.5-62.6)
Matakang
36.7 (19.9-56.1)
46.7 (28.3-65.7)
33.3 (17.3-52.8)
76.7 (57.7-90.1)
Bossimiya
13.3 (3.8-30.7)
60.0 (40.6-77.3)
40.0 (22.7-59.4)
83.3 (65.3-4.4)
Konimodiya
26.7 (12.3-45.9)
56.6 (37.4-74.5)
33.3 (17.3-52.8)
73.3 (54.1-87.7)
Manké Centre
23.3 (9.9-42.3)
53.3 (34.3-71.7)
13.3 (3.8-30.7)
76.7 (57.7-90.1)
Overall
25.4 (20.0-31.4)
45.4 (39.0-51.9)
15.0 (10.7-20.2)
66.7 (60.3-72.6)
Hookworm infection was the most prevalent STH with an overall prevalence of 45.4% (95%
CI: 39.0-51.9; range 20.0-60.0%). This was followed by T. trichiura with 15.0% (95% CI: 10.720.2; range 13.3-40.0%) and A. lumbricoides at 25.4% (95% CI: 20.0-31.4; range 13.336.7%). There were no significant differences in any individual parasitic infections between
gender (p>0.05).
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Figure 31: Prevalence of any STH across the SS
The arithmetical mean intensities of STH infections were low: hookworm 51.8 epg; Ascaris
11.4 epg; and Trichuris 12.4 epg. All the infections found were classified as light with the
arithmetical mean below 100 epg (see Table 20).
Table 22: Intensity of STH infections
Intensity categories
Ascaris (epg)
Hookworm (epg)
Overall intensity (95% Cl)
11.4 (9.9-12.8)
51.8 (45.3-58.2)
No epg
179
131
204
Light
61
109
36
Moderate
0
0
0
Heavy
0
0
0
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Trichuris (epg)
12.4 (9.3-15.5)
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3.3.3 Discussion and Recommendations
Schistosomiasis was discovered in only one of the geographic zones (Mainland) and
completely absent on the Island, while STH were discovered in both geographic zones
(Island and Mainland). Overall, hookworm and Ascaris show a moderate infection rate and
Trichuris shows low infection rate in terms of single prevalence. However, prevalence rate of
any STH in both geographic locations is high according to WHO guidelines [41]. Thus, mass
drug administration (MDA) of children as well as risk groups such as pregnant and lactating
mothers is indicated bi-annually [42].
For schistosomiasis, the overall prevalence is classified as low in each individual site. In
practice that means that treatment should be given on a case-by-case basis after clinical
diagnosis, not necessarily confirmed by laboratory diagnosis. Visible haematuria is sufficient
clinical data to justify treatment for schistosomiasis in these circumstances.
Apart from MDA once or twice a year, attention should be given to the other control aspects
such as water, proper sanitary/hygiene conditions and behavioural change. The primary
objective should be that each community and school has access to potable drinking water
and proper improved latrines.
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3.4 Questionnaire Survey
3.4.1 Household Composition
A total of 254 households took part in the questionnaire survey. More than half of the
households (51.2%) had a man present at home at the time of the interview.
A large majority (89.8%) of survey respondents belonged to the ethnic group Soussou. Other
ethnic groups represented in the BHS included Peulh (3.1%), Malinké (3.1%) and others
(4%).
3.4.1.1 Age and Marital Status
The median age of male respondents in the questionnaire survey was 40 years (Interquartile
range (IQR): 31-49), while the median age in female respondents was 25 (IQR: 20-31).
Almost all men (99.2%) were married or had a co-habiting partner (0.8%). Two hundred and
thirty-three women (92.1%) were married, 10 (4%) had a co-habiting partner and 5 (2%)
were widowed. Three women (1.2%) were celibate, one (0.4%) was divorced and one (0.4%)
was separated.
3.4.1.2 Education
There is a strong correlation between health and education. Basic education is important as
it equips a person to better understand and internalise relevant information and to translate
this knowledge into behaviour change [43]. This is more relevant for women who are
normally the gate-keepers for child health. According to the Women’s Learning Partnership
(WLP), it is estimated that for every year beyond fourth grade that a girl attends school,
wages rise by 20%, child mortality drops by 10% and family size drops by 20% [44].
Both adult males and females in each household were asked about their education level. It is
important to note that low education level in one household partner might impact on the
health seeking behaviour of the entire household.
Figure 32 shows the education level in men and women. Women were generally less
educated than men. Three in four women (76.7%) did not have any formal education. 50
women (19.8%) had attended primary school while 8 (3.2%) attended lower level secondary
school. Only one woman (0.4%) had attended university. Eighty-four men (64.6%) had no
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formal education, while 24 men (18.5%) had only primary school education. Twenty-four men
(16.8%) had secondary school education or higher.
100
76,7
80
64,6
60
Men
%
40
Women
19,8
18,5
20
6,1
0
None
Primary
3,2
6,1
0,0
2,3
2,3 0,4
0,0
Lower Level Higher Level Professional
Secondary Secondary
B
University
Education level
Figure 32: Education level in male and female respondents
These findings are slightly different to the results of the 2005 GDHS which found that 84.1%
of women in Kindia had no formal education. Only 8.9% of women in Kindia were found to
have some primary education, and only 7.0% were found to have some secondary
education. Furthermore, the findings in male respondents were also not very different from
what was found during the 2005 GDHS, which found that 68.2% of men in Kindia had no
formal education. However, the percentage of men in this survey (18.5%) who had some
primary education was slightly higher than the 15.3% found in Kindia during the 2005 GDHS
[32].
3.4.1.3 Socio-economic Status
The questionnaire survey also aimed at investigating the socio-economic status of the
communities in order to provide a more complete understanding of economic, social and
physical environments in which individuals live and work. The study investigated various
assets owned by the household as proxy indicators for wealth. These assets included a
radio, a TV set, a cell-phone, a bicycle, a motorcycle, a car and a boat.
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100,0
80,0
66,9
57,1
60,0
%
40,2
40,0
37,0
22,4
20,0
20,1
5,5
0,0
Radio
Cell-phone
Bicycle
Motorcycle
Boat
TV
Car
Asset
Figure 33: Reported ownership of household assets
The most commonly owned asset was a radio (66.9%). More than half of the respondents
(57.1%) also reported ownership of a cell-phone. 40.2% and 37% of the households owned a
bicycle and/or a motorcycle, respectively. The lowest owned asset was a television set
(20.1%) and a car (5.5%).
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3.4.2 Health Services and Behaviours
3.4.2.1 Health Seeking Behaviour
Health-seeking behaviour explores personal actions aimed at pursuing wellness, recovery
and rehabilitation. Information on health seeking behaviour is particularly important in
understanding and addressing the barriers individuals may face in seeking care for
themselves and for their children. Many factors can prevent individuals from getting medical
advice or treatment when they are sick or from receiving health education. Parents also face
barriers in accessing a health facility when their child is sick. Seeking medical care from
other sources other than a health facility may be risky and access to appropriate health
facilities (including affordability and geographical accessibility) should ideally be guaranteed
for all individuals in a population. Moreover, health education is closely linked to health
seeking behaviour and timely provision of professional health care. Figure 34 shows the
availability of health facilities in the surveyed SS.
Figure 34: Availability of health facilities in the surveyed SS
Women were asked to recall when their youngest (last born) child last had a fever, and
where they received medical care from during this episoide (Table 23).
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Health Facility
(%)
Pharmacy (%)
Shop/Kiosk/
market (%)
Herbal brew (%)
Parent/friend (%)
Traditional
healer (%)
Did not do
anything (%)
Other (%)
Number of
respondents
Table 23: Locality of medical advice at the last instance when the child was sick
64.0
16.0
0.0
16.0
0.0
0.0
4.0
0.0
25
Sahrata
20.6
76.5
0.0
0.0
0.0
2.9
0.0
0.0
34
Soungaya
0.0
84.9
0.0
9.1
0.0
0.0
3.0
3.0
33
Farmoriya-Yindi village
3.3
73.4
0.0
0.0
10.0
0.0
13.3
0.0
30
Matakang
6.7
83.4
0.0
0.0
3.3
3.3
3.3
0.0
30
Bossimiya
0.0
75.7
0.0
9.1
0.0
9.1
6.1
0.0
33
Manké Centre
10.8
78.4
10.8
0.0
0.0
0.0
0.0
0.0
37
Konimodiya
3.2
83.9
0.0
3.2
0.0
6.5
3.2
0.0
31
Total
12.2
73.1
1.6
4.3
1.6
2.8
4.0
0.4
253
Sentinel Site
Tèrin
Table 23 shows where mothers first went to seek medical advice the last time their last born
child was sick with a fever. Three in four women (73.1%) responded that they sought medical
advice/treatment from the pharmacy. Thirty-one women (12.2%) said that they went to the
medical facility while 7 women (2.8%) said that they went to a traditional healer. Tèrin had
the highest percentage (64.0%) of respondents who said that they took their child to a health
facility. This is despite the fact that Tèrin does not have its own health facility. Communities
that had health facilities (Sahrata, Matakang and Manké Centre) had relatively low
proportions of mothers who took their children there. None of the mothers in Soungaya and
Bossimiya reported that they took their children to a health facility. Only the respondents in
Farmoriya-Yindi village and Manké reported that they did not take their child to a traditional
healer nor did they use an herbal brew.
10,8%
2,7%
5,4%
No access to health facility
8,1%
Cannot afford the health facility
Prefer traditional healer
Prefer to self-treat
Not necessary
73,0%
Figure 35: Reasons for not going to a health facility (n=37)
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Most of the women (73%) who did not attend a health facility said that it was because they
could not afford the services at the health facility. Four women (10.8%) said that it was not
necessary for them to take their children to the health facility while 3 women (8.1%) said that
they prefer a traditional healer (Figure 35).
One hundred and ninety-one mothers (75.5%) admitted to have ever taken their child to a
traditional healer.
Female respondents were asked about the biggest hindrances to obtaining medical
treatment. Two hundred and thirty-two (91.7%) reported that obtaining money for treatment
was one of their biggest problems. Moreover, about three-quarters (73.1%) said that
obtaining money for transport was one of their biggest problems while 180 women (71.4%)
said that it was the lack of a health facility in the vicinity (Figure 36).
100
91,7
80
73,1
71,4
64,4
62,1
60
%
54,2
41,5
40
20
0
Money for
treatment
Money for
No health
Does not Don't want to
transport facility nearby know where
go alone
to go
No female
health
attendant
Obtaining
permission
Problem
Figure 36: Hindrances to obtaining medical treatment
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3.4.2.2 Maternal and Child Health
The health and well-being of women, newborns and children are closely inter-linked and
should be managed in a unified and integrated manner. Maternal and child health is
regarded as a crucial indicator to measure the health status and development of a
population. Thus indicators that support essential health and reproductive services for
women from adolescence, through pregnancy, delivery and beyond, as well as proper health
services for newborns to ensure their survival through childhood, adolescence and
adulthood, are important to investigate. The Project, per se, may not have any direct
influence on these and they remain the responsibility of the MoH, but they are useful
indicators of population well-being.
Access to antenatal care (ANC) and delivery services were used as indicators for maternal
health. Breastfeeding practices and childhood vaccination were used as indicators for child
health.
3.4.2.2.1 Access to Antenatal Care
According to the WHO standards for maternal and neonatal care, all pregnant women should
have at least four ANC visits by, or under the supervision of a skilled attendant, which have
to be spaced at regular intervals throughout pregnancy, commencing as early as possible in
the first trimester [45].
Two hundred and forty-six women (97.6%) reported that they attended an ANC the last time
they were pregnant. The median number for times of an ANC visit was 4 (IQR: 3-6).
3.4.2.2.2 Place of Delivery and Assistance
A key element of maternal and child health services is the provision of safe delivery care.
The proportion of deliveries in a health care setting, as well as the supervision of the delivery
by a trained health provider, are both important determinants to good maternal and foetal
outcomes.
Accessibility issues may hamper women from accessing a safe delivery site, particularly in
remote areas. High delivery fees and lack of trained midwives and health personnel may also
discourage women from going to a health centre and force them to deliver at home. Women
were asked where they delivered their last child, with findings shown in Figure 37.
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Figure 37: Place of delivery
Almost three-quarters (74.6%) of the respondents said that they delivered their last child in a
health facility (range: 42.4-95.8%). One hundred and sixty-three women (64.7%) said that
they delivered their last child in a public health facility while 25 women (9.9%) said that they
delivered in a private health facility. A quarter of the women (25.4%) said that they delivered
their child at home. Soungaya (42.4%) had the lowest proportion of women who delivered at
a health facility. The highest proportions of deliveries at a health facility were recorded in
Tèrin (95.8%) and Matakang (93.3%) as depicted in Figure 37.
The type of assistance during delivery is an important determinant influencing the birth
outcome and the health of the mother and infant. A skilled birth attendant can significantly
reduce the likelihood of complications during and after delivery. This is important in a setting
with limited health care services.
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Sentinel site
Tèrin
Skilled health provider
Nurse /
Any
Doctor /
Midwife /
skilled
Clinical
MCH Aide
provider
Officer (%)
(%)
(%)
95.8
4.2
91.6
Un-skilled health provider
Traditional
Family
birth
member/
attendant
friend (%)
(%)
0.0
4.2
No one
(%)
0.0
Number of
respondents
Table 24: Assistance during delivery
24
Sahrata
17.7
76.5
94.2
2.9
2.9
0.0
34
Soungaya
FarmoriyaYindi village
Matakang
0.0
42.4
42.4
6.1
42.4
9.1
33
3.3
60.0
63.3
10.0
26.7
0.0
30
13.3
80.1
93.4
3.3
3.3
0.0
30
Bossimiya
Manké
Centre
Konimodiya
3.0
75.8
78.8
3.0
15.2
3.0
33
0.0
78.4
78.4
0.0
18.9
2.7
37
6.5
64.5
71.0
3.2
25.8
0.0
31
Total
6.0
70.5
76.5
3.6
17.9
2.0
252
Table 24 shows the delivery assistance in all SS. More than three-quarters (76.5%) of
women had skilled assistance during their last delivery (range: 42.4-95.8%). Most women
(70.5%) were assisted by a nurse or midwife, while only 6% were assisted by a doctor. Fortyfive women (17.9%) were assisted by a traditional birth attendant. Soungaya (42.4%) had the
highest proportion of women whose deliveries were assisted by a traditional birth attendant.
Moreover, it also had the highest proportion of births that were assisted by nobody (9.1%).
This is likely to be due to the fact that Soungaya is located far away from any health facility.
3.4.2.2.3 Breastfeeding Practices
Exclusive breastfeeding is very important during early childhood. It not only supports the
basic nutritional needs of the child but it also boosts their immunity through transfer of
antibodies from mother to child. It also encourages maternal bonding and provides a natural
form of contraception which promotes child spacing. The WHO recommends that
breastfeeding should be provided exclusively for the first six months of life and then
supported by supplemental food up until a minimum of 2 years of age [46]. Breastfeeding of
infants has a positive impact on child survival reducing acute respiratory infections, diarrhoea
and other infectious diseases. Figure 38 shows the percentage of women above six months
old who exclusively breastfed their child according to UNICEF recommendations in 2006.
The proportion in Guinea was between 20-49% [46].
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Figure 38: Percentage of children <six months old exclusively breastfed in 2006
Almost all women (98.4%) in the BHS said they breastfed their child. 118 women (47%)
reported that they exclusively breastfed their child for more than one month before they
started giving him/her water or boiled food (median: 7 months, IQR: 6-10.5 months). Ninetyfour women (37.5%) said that they started giving the baby water or boiled food immediately
after birth, while 31 women (12.4%) said that they only breastfed their child exclusively for
one month. Eight women (3.2%) did not remember.
The implications of this early introduction of substitute food before 6 months can lead to a
halt to breastfeeding. Moreover, watered down food and supplements can lead to inadequate
calorie intake. Exposure to contaminated water or foodstuffs can predispose the young infant
to the risk of illness.
3.4.2.2.4 Ownership of a Vaccination Card
For the recording of vaccinations, post natal check-ups and growth indicators a vaccination
card (carnet de la Mère et de l’Enfant) is provided to all new-born children after birth.
Ownership of this card is a good indicator for child health monitoring and enrolment of child
health services such as vaccinations and nutritional surveillance.
Two hundred and eight women (82.6%) reported that they have a vaccination card for their
last born child. Of these, 192 women (76.2%) showed their card to the interviewer. Fourteen
women (5.6%) did not have a card, while 30 women (11.9%) did not know whether the child
had a card. The percentage of women (76.2%) who showed their vaccination cards to the
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interviewer was higher than what was found in Kindia during the 2005 GDHS (60.6%) and
thus child vaccination in the area seem to be on the increase [32].
3.4.2.2.5 Acute Respiratory Infections
Acute respiratory infections (ARI) are among the leading causes of morbidity and mortality in
Guinea. Among acute respiratory diseases, pneumonia is the most serious one for young
children. Early diagnosis and treatment with antibiotics can prevent a large proportion of
deaths resulting from pneumonia [32]. The prevalence of symptoms of ARI was estimated by
asking mothers whether their children under age 5 had been ill with a cough accompanied by
short, rapid breathing in the two weeks preceding the survey. Of note, this indicator is based
on the mother’s perception of illness and is not validated by any form of medical examination.
Two hundred and seven (81.8%) mothers reported that their child had a cough in the two
weeks preceding the survey. Furthermore, 141 mothers (68.1%) reported that their child had
an instance where his/her breathing was rapid, during the two weeks before the survey.
Konimodiya had the highest proportion of mothers (93.6%) who reported that their children
had a cough during the two weeks preceding the survey. The lowest proportion was in Tèrin,
with 60%.
Sahrata had the highest percentage of mothers (75.9%) who reported that their child was
breathing rapidly during the two weeks preceding the survey. The lowest percentage was
found in Farmoriya-Yindi village (59.1%).
Table 25: Children (%) that showed symptoms of ARI 2 weeks preceding the survey
Proportion of mothers whose child…
…had a cough (%)
60.0
…was breathing
rapidly (%)
60.0
Number of
respondents 25
Sahrata
85.3
75.9
34
Soungaya
84.9
67.9
33
Farmoriya-Yindi village
73.3
59.1
30
Matakang
86.7
73.1
30
Bossimiya
84.9
71.4
33
Manké Centre
81.1
63.3
37
Konimodiya
93.6
69.0
31
Total
81.8
68.1
253
Sentinel site
Tèrin
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The percentage of children who had symptoms of ARI during this survey (68.1%) was
considerably higher than the findings of the 2005 GDHS in Kindia (6.1%). This might be
partly explained by the time of the year when the survey was conducted (end of rainy
season) [32].
3.4.3 Social Determinants of Health
3.4.3.1 Substance Abuse
Substance misuse such as alcohol, tobacco or other drugs is not only an important health
determinant but also closely linked to mental health. Misuse is associated with crime,
transactional sex and domestic violence [2].
In the questionnaire men and women were asked about their alcohol uptake and requested
to specify the number of drinks that they consume on a daily or weekly basis. Only 10 male
participants (7.7%) reported that they consume alcohol. Of these, five men (50%) said they
drink less than once a week, 4 (40%) said they drink once a week and only one (10%) said
that he drinks multiple times a week. Only one woman (0.4%) admitted to drinking alcohol,
and she said that she drinks less than once a week.
In contrast to the low alcohol consumption, almost half of the men (45.4%) reported that they
smoke. The median number of cigarettes smoked in the last 24 hours amongst these men
was 10 (IQR: 7-15). Only 6 women (2.4%) reported that they smoke, with a median number 5
cigarettes in the last 24 hours (IQR: 2-10).
3.4.3.2 Transactional Sex Work
Transactional sex involves exchange of sex for money, favours, or gifts. Transactional sex is
associated with a high risk of contracting HIV and other STIs due to compromised power
relations and the tendency to have multiple partnerships.
About three-quarters of all respondent thought that transactional sex work was a problem
within their community. Ninety-eight men (76%) and 186 women (74.1%) reported that they
considered transactional sex work as a problem within their community.
3.4.3.3 Domestic Gender Based Violence
General inequalities in the community may impart some distinct health impacts on
communities and sections within communities. It is generally recognised that women bear
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the brunt of domestic gender based violence (GBV) which creates both a health and
psychological burden. It is recognised that in many societies that women are socialised to
accept, tolerate and even rationalise GBV and it is recognised that this has an impact on the
economy of a country [47].
Figure 39 shows the number of women who agreed when asked if a man was justified in
beating his wife if she did various actions. A large majority of women (86.1%) thought that a
man was justified to beat his wife if she neglected the children, if she went out without telling
him (83.7%) and if she argued with him (79.2%). Hence, violent behaviour of men is widely
accepted amongst women supporting the reference cited above.
100
83,7
86,1
79,4
80
78,2
63,9
60
%
40
20
0
Goes out without
telling him
Neglects the
children
Argues with him
Refuses to have
sex with him
Burns the food
Action
Figure 39: Actions allowing a man to beat his wife (according to women)
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3.4.4 KAP Related to Malaria
3.4.4.1 Knowledge, Attitudes and Practices
Malaria is a major public health concern that can impact on the health as well as the
economic development of both the community and the Project. As an indicator on malaria
awareness and knowledge among the population, causes of malaria and modes of
transmission were determined.
All male respondents said that they have heard of malaria. In addition, almost all women
(96.1%) said that they have heard of malaria. Table 26 and Table 27 show the level of
knowledge on modes of malaria transmission across the different SS, in men and women. As
answers were not prompted and more than one answer was accepted it was possible to
analyse consistent knowledge on malaria transmission (that being bitten by mosquitoes is
the only true mode).
Don’t know (%)
Number of
respondents
16
18
10.0
25.0
20
27.3
16.7
18.2
11
17.7
11.8
24.2
11.8
17
10.0
30.0
10.0
10.8
15.0
20
27.8
22.2
38.9
27.8
6.5
11.1
18
10.0
17.7
28.5
23.1
9.8
18.5
130
Drinking dirty
water (%)
6.3
44.4
Dirty
environment
(%)
0.0
6.1
When it's cold
(%)
10
Working under
the sun (%)
10.0
Mosquito bites
(%)
3.9
Consistent
knowledge (%)
Other (%)
Table 26: Malaria knowledge in men
20.0
70.0
20.0
20.0
40.0
30.0
Sahrata
6.3
50.0
0.0
12.5
56.3
43.8
Soungaya
FarmoriyaYindi village
Matakang
0.0
22.2
5.6
27.8
27.8
16.7
20.0
65.0
10.0
10.0
0.0
25.0
9.1
45.5
0.0
18.2
27.3
Bossimiya
Manké
Centre
Konimodiya
11.8
41.2
17.7
23.5
25.0
55.0
0.0
5.6
38.9
Total
12.3
47.7
Sentinel site
Tèrin
Overall, only 16 men (12.3%, range: 0.0-25%) had consistent malaria knowledge. However,
half of the male participants (47.7%) correctly identified mosquito bites as a malaria
transmission mode. The most common misconceptions among the men were malaria
transmission through a dirty environment (28.5%), drinking dirty water (23.1%) and when it is
cold (17.7%). Twenty-four men (18.5%) reported that they did not know how malaria was
transmitted.
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Dirty
environment (%)
25.0
12.5
Sahrata
8.8
55.9
11.8
17.7
47.1
Soungaya
FarmoriyaYindi village
Matakang
6.1
12.1
6.1
15.2
9.1
18.5
28.6
3.6
10.7
3.6
17.9
3.6
Bossimiya
Manké
Centre
Konimodiya
6.5
12.9
2.9
Total
Number of
respondents
When it's cold
(%)
4.2
Don’t know (%)
Working under
the sun (%)
37.5
Other (%)
Mosquito bites
(%)
12.5
Sentinel site
Tèrin
Drinking dirty
water (%)
Consistent
knowledge (%)
Table 27: Malaria knowledge in women
16.7
7.7
33.3
24
38.2
5.9
11.8
34
18.2
18.2
39.4
33
21.4
3.6
10.0
39.3
28
28.6
17.9
7.1
10.0
46.4
28
3.2
25.8
12.9
12.9
15.2
35.5
31
22.9
2.9
31.4
25.7
14.3
13.5
37.1
35
3.5
10.0
0.0
26.7
10.0
6.7
3.2
50.0
30
7.5
24.7
4.5
22.6
20.2
15.2
10.6
36.2
243
The portion of women having consistent knowledge on malaria transmission was even lower
than for the men (7.5%, range: 3.5-18.5%). Only one in four women (24.7%) could correctly
identify mosquito bites as the correct mode of transmission for malaria. The most common
misconceptions were that malaria is transmitted when it is cold (22.6%), through a dirty
environment (20.2%) and through drinking dirty water (15.2%). Although dirty surroundings
can be related to an increase in breeding sites and may be an acceptable result, 4.5% of
women reported working under the sun as a mode of transmission. Eighty-eight women
(36.2%) did not know how malaria is transmitted.
This poor knowledge of malaria transmission modes reflects the poor educational status in
the survey area, particularly in women, and the lack of any functioning malaria health
education programme that is reaching the communities.
3.4.4.2 Ownership and Use of Insecticide-Treated Nets
In areas with high malaria transmission, ITNs are one of the principal strategies for
preventing malaria. The use of ITNs is widely considered a highly effective intervention with
various community-based trials and studies that showed that ITNs use reduces malaria
transmission, malaria-related morbidity and all-cause child mortality [48, 49]. A study in
Tanzania documented that ITN distribution with a strong social marketing campaign was
associated with a 27% increase in survival, as well as 65% reduction in anaemia, among
children aged between 1-48 months [50]. The cost effectiveness of ITN use, compared to
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other prevention measures, has also been widely demonstrated, but the challenge has been
to increase ownership and use of ITNs [49, 51].
The Global Fund and the WHO Roll Back Malaria Programme (RBM) have defined a number
of indicators linked to ITN ownership and use. It was not considered practical to cover all the
outcomes and impact indicators within the scope of the survey and therefore a few key areas
were selected as shown below.
Table 28: Insecticide-treated net ownership and reasons for not owning one
Sentinel site
Tèrin
Households
owning at
least one
bednet (%)
65.4
Reasons not to have a bednet
Cannot
Not
afford
available
Other
(%)
(%)
(%)
77.8
22.2
0.0
Number of
households
26
Sahrata
70.6
60.0
30.0
10.0
34
Soungaya
36.4
76.2
0.0
23.8
33
Farmoriya-Yindi village
50.0
60.0
33.3
6.7
30
Matakang
53.3
57.1
28.6
14.3
30
Bossimiya
72.7
77.8
22.2
0.0
33
Manké Centre
70.3
72.7
27.3
0.0
37
Konimodiya
45.2
56.3
18.7
25.0
31
Total
58.3
66.7
20.1
12.3
254
One hundred and forty-eight (58.3%, range: 36.4-72.7%) of households reported that they
own an ITN. Bossimiya had the highest ITN coverage (72.7%) followed by Sahrata (70.6%).
The lowest ITN coverage was in Soungaya (36.4%), which may be due to this community’s
poor access to health care. Two-thirds of households (66.7%) said that they did not have an
ITN, because they cannot afford one. Twenty-two households (20.1%) said there are no ITNs
available in the community while 12.3% gave other reasons.
Figure 40 shows the percentage of children under 5 who slept under an ITN the night before
the survey in each SS. Just over a half (50.1%) of children slept under an ITN, although
58.3% of the households reported to own at least one. In Tèrin only 11.1% of children slept
under an ITN the night before the survey despite 65.4% households claiming to own at least
one. This was also the case in Sahrata where only 14.9% of the children slept under a
bednet despite 70.6% of households reporting to owning at least one. ITN utilisation was
highest in Bossimiya, where 66.1% of children slept under an ITN the night before the
survey. This was just lower than the 72.7% ITN ownership that was reported. The low ITN
utilisation rate might be due to lack of enough ITNs for all household members or because
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they are not aware that it is particularly the children that should sleep under the nets due to
their vulnerability to severe effects from malaria. However, there was no significant
association between malaria infection and ITN utilisation (p=0.78).
Figure 40: Proportion of children under 5 years who slept under an ITN by SS
3.4.4.3 Intermittent Preventive Treatment for Malaria
Pregnant women are more susceptible to Plasmodium and are more prone to acquire a
severe form of malaria leading to high maternal mortality as a direct consequence of the
infection and indirectly from the effects of anaemia which is often caused or exacerbated by
the disease. Anaemia often results in premature births and/or low birth weight with poor
foetal outcome.
One of the strategies for malaria control is intermittent preventive treatment in pregnancy
(IPTp) most often using sulphadoxine-pyrimethamine (SP) - commonly prescribed under the
brand name Fansidar®. Under this strategy it is recommended that all pregnant women in
malaria-endemic areas receive one full three-tablet single dose of SP at least three times
during the second and third trimester of their pregnancy. Pregnant women generally have
higher malaria prevalence and parasitaemia levels, which is often highest in weeks 20-36 of
pregnancy. Thus the aim is to eliminate the parasitaemia in this phase of pregnancy. Studies
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have shown good results in reducing parasitaemia, anaemia and low birth weight through
this intervention [52]. ANC clinics are therefore considered an important entry point to target
pregnant women and deliver this preventive medication. Thus this is also a good indicator of
the quality of ANC services. The provision of two separate doses in the last pregnancy is
used as a service delivery indicator.
Two hundred and four women (81%) said that they received IPTp during their last pregnancy.
Twenty one (8.3%) said they did not receive IPTp during their last pregnancy while 27 women
(10.7%) were not sure (Figure 41).
10,7%
8,3%
Yes
No
81,0%
Not Sure
Figure 41: IPTp use in women during their last pregnancy
IPTp use ranged from 67.6% to 94.1%. IPTp use was highest in Sahrata (94.1%) and
Matakang (90%). It was lowest in Manké Centre (67.6%). One hundred and sixty-two women
(79.4%, range: 69.6-94.4%) said that they received at least two doses of SP/Fansidar during
an ANC visit. This proportion was highest in Tèrin (94.4%) and lowest in Konimodiya
(69.6%).
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Table 29: Intermittent preventive treatment in pregnancy per sentinel site
Percentage of
women who
used IPT during
last pregnancy
(%)
75.0
Percentage who
received at
least two doses
of SP/Fansidar
during an ANC
visit (%)
94.4
Number of
households
24
Sahrata
94.1
78.1
34
Soungaya
Farmoriya-Yindi
village
Matakang
87.9
75.9
33
80.0
79.2
30
90.0
70.4
30
Bossimiya
78.8
80.8
33
Manké Centre
67.6
92.0
37
Konimodiya
74.2
69.6
31
Total
81.0
79.4
252
Sentinel site
Tèrin
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3.4.5 KAP Related to HIV/AIDS
There are an estimated 33 million people living with HIV globally, with sub-Saharan Africa
accounting for 67% of cases [53]. The 2005 GDHS found that 1.5% of all adults in Guinea
aged 15-49 years are HIV positive. HIV prevalence was higher among women than among
men (1.9% and 0.9%, respectively). The HIV prevalence rate in urban areas (2.4%) was
higher than in rural areas (1%). Kindia Region had an HIV prevalence of 0.9%.
Figure 42: HIV prevalence in Guinea by administrative region in 2005
The questionnaire survey aimed at investigating knowledge of HIV/AIDS in the study area as
well as related issues such as stigma, misconceptions and behaviour.
The results are grouped into three categories:
•
HIV knowledge and awareness – which explores awareness of the disease and
possible prevention;
•
HIV attitudes – which investigates stigma and behavioural patterns; and
•
HIV practices – which outlines the actual habits with regards to condom use and
other prevention activities.
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3.4.5.1 HIV Knowledge and Awareness
The knowledge indicators provide an indication of the level of correct knowledge related to
the disease. Although it is now accepted that knowledge in itself will not lead to change in
behaviour, knowledge is an important prerequisite for behaviour change. Increasing HIV
awareness certainly plays a major role in containing the spread of the disease.
One hundred and twenty-eight men (98.5%) and 249 women (98.4%) said that they had
heard of HIV. This was slightly higher than findings of the 2005 GDHS where 95.3% of men
and 93.4% of women in Kindia Region said that they had heard of HIV [32].
Respondents were prompted about different preventive measures related to HIV/AIDS with
the objective to obtain an understanding of comprehensive knowledge on these methods in
the study population. This was based on a prompted recognition of the correct preventive
measures as well as common misconceptions.
3.4.5.1.1 HIV/AIDS Knowledge in Men
Table 30 shows the levels of knowledge on HIV prevention methods in men. Correct
behaviours are highlighted in green while misconceptions are highlighted in pink.
Sentinel site
Tèrin
Have heard of HIV/AIDS
(%)
Think they can reduce
chances of HIV infection
by being faithful (%)
Think condoms can
reduce chances of HIV
infection (%)
Think they can reduce the
risk of HIV by abstinence
(%)
Think a healthy looking
person can have HIV (%)
Think they can get HIV
from mosquito bites (%)
Think witchcraft can
cause HIV (%)
Think they can get HIV by
sharing food with a HIVpositive person (%)
Number of respondents
Table 30: HIV/AIDS knowledge in men
100.0
80.0
90.0
50.0
40.0
60.0
20.0
40.0
10
Sahrata
100.0
93.8
75.0
80.0
26.7
31.3
6.3
26.7
16
Soungaya
Farmoriya-Yindi
village
Matakang
94.4
100.0
64.7
82.4
5.9
29.4
35.3
47.1
18
95.0
73.7
84.2
73.7
5.3
42.1
5.3
47.4
20
100.0
90.9
72.7
54.6
18.2
54.6
9.1
72.7
11
Bossimiya
100.0
94.1
85.4
82.4
23.5
52.9
11.8
58.8
17
Manké Centre
100.0
95.0
90.0
90.0
20.0
50.0
20.0
50.0
20
Konimodiya
100.0
88.9
83.3
77.8
16.7
55.6
11.1
55.6
18
Total
98.5
89.8
80.5
76.4
18.1
46.1
14.8
49.6
130
2005 GDHS
98.8
92.1
82.1
90.0
68.4
35.9
59.4
49.1
2,709
2005 GDHS - Kindia
95.3
87.2
79.3
79.8
67.4
30.9
48.6
37.9
340
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One hundred and fifteen men (89.8%, range: 73.7-100%) knew that they could reduce
chances of HIV infection by being faithful to one uninfected partner. This was highest in
Soungaya (100%) and lowest in Farmoriya-Yindi village (73.7%). One hundred and three
men (80.5%, range: 64.7-90%) agreed that using condoms every time they had sex reduced
their chances of getting infected with HIV. This proportion was lowest in Soungaya (64.7%).
Just over three-quarters of the men (76.4%, range: 50-90%) thought that they can reduce the
risk of getting HIV by abstaining from sex.
Only 18.1% (range: 5.3-40%) of men stated that a healthy-looking person can have HIV. This
proportion was lowest in Farmoriya-Yindi village (5.3%) and Soungaya (5.9%). Tèrin had the
highest percentage of men (40%) who knew that a healthy looking person can have HIV,
which was, however, still less than half of the respondents. The most popular misconception
was that you can get HIV from sharing food with an HIV positive person (49.6%, range: 26.758.8%). This misconception was highest in Bossimiya (58.8%) and lowest in Sahrata
(26.7%). Fifty-six men (46.1%, range: 29.4-60%) thought that mosquitoes can transmit HIV
while 19 men (14.8%, range: 5.3-35.3%) thought that you can get HIV from witchcraft or
supernatural powers.
The results from this survey vary with those that were found in Kindia Region during the 2005
GDHS. The proportion of men who thought that they can reduce their chances of getting HIV
by limiting sex to one uninfected partner (89.8%) was slightly lower than the 91.4% found in
Kindia Region during the 2005 GDHS. Similarly, the proportion of men who knew that
consistent condom use can reduce their chances of getting HIV (80.5%) was almost similar
to that found during the 2005 GDHS (79.3% in Kindia Region). However, there was also a
decrease in men (76.4%) who thought that abstinence from sex can reduce their chances of
getting HIV (90.8% in Kindia Region during 2005 GDHS) [32].
The number of men who knew that a healthy looking person can have HIV (18.1%) was
much lower than what was found during the 2005 GDHS (67.4%). Only 14.8% of male
respondents thought that HIV can be caused by witchcraft, which was also much lower than
the findings in the 2005 GDHS (37.9%) [32].
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3.4.5.1.2 HIV/AIDS Knowledge in Women
Table 31 shows the levels of knowledge on HIV prevention methods in women. Correct
behaviours are highlighted in green while misconceptions are highlighted in pink.
Have heard of HIV/AIDS
(%)
Think they can reduce
chances of HIV infection
by being faithful (%)
Think condoms can
reduce chances of HIV
infection (%)
Think they can reduce the
risk of HIV by abstinence
(%)
Think a healthy looking
person can have HIV (%)
Think they can get HIV
from mosquito bites (%)
Think witchcraft can
cause HIV (%)
Think they can get HIV by
sharing food with a HIVpositive person (%)
Number of respondents
Table 31: HIV/AIDS knowledge in women
96.0
66.7
58.3
66.7
34.8
37.5
16.7
39.1
25
Sahrata
100.0
79.4
73.5
70.6
6.1
32.4
20.6
47.1
34
Soungaya
Farmoriya-Yindi
village
Matakang
97.0
75.0
53.1
62.5
6.3
25.0
3.1
40.6
33
96.7
82.8
55.2
58.6
21.4
31.0
10.3
48.3
30
100.0
80.0
63.3
60.0
0.0
33.3
10.0
46.7
30
Bossimiya
100.0
87.9
75.8
84.9
12.1
36.4
18.2
54.6
33
Manké Centre
100.0
78.4
51.4
73.0
8.1
46.0
10.8
37.8
37
Konimodiya
96.8
76.7
73.3
70.0
6.7
53.3
20.0
56.7
31
Total
98.4
78.7
63.1
68.7
11.0
37.0
13.7
46.4
253
2005 GDHS
97.0
87.9
71.0
83.4
48.4
43.6
62.7
46.8
7,954
2005 GDHS - Kindia
93.4
91.7
76.8
85.0
59.7
37.1
54.2
41.0
1,155
Sentinel site
Tèrin
One hundred and ninety-six (78.7%, range: 66.7-87.9%) women knew that they can reduce
their chances for HIV infection by being faithful to one uninfected partner. This proportion
was highest in Bossimiya (87.9%) and lowest in Tèrin (66.7%). Less than two-thirds (63.1%,
range: 51.4-75.8%) of women reported that using condoms every time you have sex can
reduce your chances of getting HIV. This proportion was highest in Bossimiya and lowest in
Manké Centre. One hundred and seventy-one women (68.7%, range: 58.6-84.9%) thought
that abstaining from sex reduces your chances of getting HIV. This proportion was again
highest in Bossimiya (84.9%). Only one in ten women (11%) knew that a healthy looking
person can have HIV. None of the respondents in Matakang considered that a healthy
looking person can have HIV.
Just as in men, the most common HIV transmission misconception was that you can get HIV
from sharing food with an HIV positive person (46.4%). This belief was highest in Konimodiya
(56.7%) and lowest in Manké Centre (37.8%). Ninety-two women (37%) thought that HIV can
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be transmitted through mosquito bites (range: 25.0-53.3%). Thirty-four women (13.7%)
reported that HIV can be transmitted through witchcraft or supernatural powers. This belief
was most popular in Sahrata (20.6%) and Konimodiya (20%).
The results from this survey varied with what was found in Kindia Region during the 2005
GDHS. The percentage of women who knew that limiting sex to one uninfected partner
(78.7%) can reduce their chances of getting HIV was lower than what was found during the
2005 GDHS (91.7% in Kindia). Moreover, the proportion of women who stated that using
condoms every time they have sex (63.1%) can reduce their chances of getting HIV was
lower than the 76.8% found in Kindia Region during the 2005 GDHS. Similarly, the 68.7% of
women in this study who thought that abstaining from sex can reduce their chances of
getting HIV was also lower than the 85% found in Kindia Region during the 2005 GDHS [32].
The proportion of women (11%) who thought that a healthy looking person can have HIV was
much lower than the findings of the 2005 GDHS (59.7%).
Similarly, the percentage of female respondents (13.7%) who thought that witchcraft can
cause HIV was also lower than the findings of the 2005 GDHS (54.2%). However, the
proportion of respondents (37%) who thought that mosquitoes can cause HIV was similar to
the results of the GDHS (37.1%) [32].
3.4.5.2 Consistent Knowledge of HIV/AIDS Transmission and Prevention
It is important to analyse consistent knowledge on HIV/AIDS transmission and prevention.
This was done by evaluating the consistent correct knowledge about HIV/AIDS which is
defined according to the following four criteria:
•
acknowledgment that consistent condom use and having one faithful, uninfected
partner can reduce the chances of HIV infection;
•
acknowledgment that a healthy looking person can be HIV infected;
•
rejection of the statement that HIV can be transmitted by mosquito bites; and
•
rejection of the statement that HIV can be transmitted by sharing food with a HIVpositive person.
Table 32 shows the proportion of men and women who had consistent HIV knowledge. Only
8 men (6.3%) and 5 women (2%) had consistent HIV knowledge. Matakang stood out as the
community which did not have a single respondent (male or female) who had consistent HIV
knowledge. In addition, none of the male respondents in Bossimiya had consistent HIV
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knowledge and none of the female respondents in Sahrata, Konimodiya and Manké Centre
reported consistent HIV knowledge either. Consistent HIV knowledge in men was highest in
Sahrata (12.5%) and Konimodiya (11.1%). Amongst women, consistent HIV knowledge was
highest in Bossimiya (6.1%) and Tèrin (4.2%). Consistent HIV knowledge was found to be
significantly higher in men than in women (p=0.03).
Table 32: Proportion of respondents with consistent HIV knowledge
Proportion in
men (%)
10.0
Number of
respondents
10
Proportion in
women (%)
4.2
Number of
respondents
24
Sahrata
12.5
16
0.0
33
Soungaya
Farmoriya-Yindi
village
Matakang
5.9
17
3.1
32
5.3
19
3.5
29
0.0
11
0.0
30
Bossimiya
0.0
17
6.1
33
Manké Centre
5.0
20
0.0
37
Konimodiya
11.1
18
0.0
30
Total
6.3
128
2.0
248
Sentinel Site
Tèrin
Since HIV in sub-Saharan Africa is mainly transmitted through heterosexual contact,
HIV/AIDS prevention programmes focus their messages and efforts on three important
aspects of sexual behaviour. Good knowledge of HIV prevention methods within the
communities was assessed by measuring the percentage of respondents who correctly
identified that;
•
having one uninfected partner who is faithful can help reduce your chances of getting
HIV; and that
•
using condoms every time you have sex can reduce your chances of getting HIV.
Table 33 shows the proportion of respondents in each SS who correctly identified these two
methods as ways of reducing the chances of getting HIV. Almost three-quarters of all men
(72.7%) and 56.6% of women had correct HIV knowledge. Manké Centre had the highest
proportion of men (85%) with correct HIV knowledge. Farmoriya-Yindi village had the lowest
proportion of men (63.2%) with correct HIV knowledge. Amongst women, Konimodiya had
the highest proportion of respondents (70%) with correct HIV knowledge. Soungaya had the
lowest proportion of women (43.8%) with correct HIV knowledge. HIV prevention knowledge
was found to be significantly higher in men than in women (p=0.02).
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Table 33: Proportion of respondents with correct knowledge of HIV prevention
Proportion in
men (%)
70.0
Number of
respondents
10
Proportion in
women (%)
54.2
Number of
respondents
24
Sahrata
75.0
16
64.7
33
Soungaya
Farmoriya-Yindi
village
Matakang
64.7
17
43.8
32
63.2
19
55.2
29
72.7
11
53.3
30
Bossimiya
76.5
17
66.7
33
Manké Centre
85.0
20
46.0
37
Konimodiya
72.2
18
70.0
30
Total
72.7
128
56.6
248
2005 GDHS
78.6
2,709
67.5
7,954
2005 GHDS - Kindia
74.1
340
76.3
1,155
Sentinel Site
Tèrin
3.4.5.3 Attitudes and Beliefs Related to HIV/AIDS
Investigating the HIV attitude of respondents was aimed at exploring taboos related to the
disease, stigma and perceptions of lifestyle and behaviour. Misconceptions may increase the
risk of infection by misleading individuals who are at risk, or they may help to sustain social
stigma and discrimination. Widespread stigma and discrimination towards people infected
with HIV or living with AIDS can adversely affect both people’s willingness to be tested for
HIV and also their adherence to antiretroviral therapy. Thus, reduction of stigma and
discrimination is an important indicator of the success of programmes targeting HIV/AIDS
prevention and control.
In this survey, we asked respondents two specific questions to assess attitudes and stigma
towards HIV positive people. These are:
•
whether they would be willing to buy fruit or vegetables from someone who is known
to be HIV positive; and
•
whether they would NOT keep it a secret if one of their family members was HIV
positive.
Table 34 shows the attitudes of respondents to HIV positive people. Only 9.5% of men and
2.9% of women reported that they would be willing to buy fruit or vegetable from a
hypothetical individual who was HIV positive. This proportion was highest in Sahrata, where
it was 33.3% and 12.1% in men and women, respectively. None of the respondents in
Soungaya and Bossimiya, both male and female, said that they would buy fruit/vegetables
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from a hypothetical individual who was HIV positive, which may indicate a high level of
stigma or misconceptions in HIV transmission modes within these communities. Similarly,
none of the female respondents in Matakang or Konimodiya admitted that they would be
willing to buy fruit or vegetables from a hypothetical individual who was HIV positive.
Four in five men (79.5%) and 82.9% of women said that they would not keep it a secret if one
of their family members was HIV positive. Matakang had the lowest percentages of men
(54.6%) and women (66.7%) who agreed to the statement. The highest percentages were
found in Manké Centre, where 95% of men and 94.6% of women said they would not keep it
a secret if one of their family members had HIV.
Table 34: Attitudes towards HIV positive people
Percentage of adults who agreed with the
following statements when prompted
Sentinel Site
Would buy fruit or
vegetables from an HIV
positive person (%)
Men
Women
Would not keep it a
secret if one of their
family members was
HIV positive (%)
Men
Women
Number of
respondents
Men
Women
Tèrin
10.0
4.4
80.0
82.6
10
23
Sahrata
33.3
12.1
80.0
84.9
15
33
Soungaya
Farmoriya-Yindi
village
Matakang
0.0
0.0
76.5
90.6
17
32
10.5
3.6
84.2
82.1
19
28
9.1
0.0
54.6
66.7
11
30
Bossimiya
0.0
0.0
64.7
75.8
17
33
Manké Centre
10.0
2.7
95.0
94.6
20
37
Konimodiya
5.6
0.0
88.9
83.3
18
30
Total
9.5
2.9
79.5
82.9
127
246
2005 GHDS
20.8
8.5
72.8
71.2
2709
7,954
2005 GDHS - Kindia
18.5
5.9
66.2
85.9
340
1,155
The percentage of men (9.5%) and women (2.9%) who were willing to buy fruit or vegetable
from a hypothetical individual who was HIV positive was much lower than what was found in
Kindia during the 2005 GDHS. In men, the proportion was twice less than what was found
nationally (20.8%) or in Kindia Region (18.5%). This was also the same in women where the
proportions found nationally (8.5%) and in Kindia Region (5.9%) were almost twice the
proportion found in this survey. The proportion of men (79.5%) who would not keep it a
secret if one of their family members was HIV positive was higher than what was found both
nationally (72.8%) and regionally (66.2%) during the 2005 GDHS. In women, the proportion
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found in this survey (82.9%) was higher than what was found nationally (71.2%) but lower
than what was found regionally (85.9%) during the 2005 GDHS [32].
3.4.5.4 HIV Prevention Practices
Both men and women were asked about practices commonly associated with HIV and HIV
transmission risks and prevention strategies. Two indicators were chosen to evaluate HIV
practices:
•
whether the respondent had ever undertaken an HIV test; and
•
access to and use of condoms as this is a fundamental strategy in preventing HIV
transmission risk.
3.4.5.4.1 HIV Testing
Table 35 shows the proportion of men and women who reported that they had ever taken an
HIV test. Only 11.8% of men (range: 5-21.1%) and 9.8% of women (range: 3.1-21.2%) said
they had ever taken an HIV test. Farmoriya-Yindi village (21.1%) and Sahrata (20%) had the
highest proportion of men who said they had ever taken an HIV test. Sahrata (21.2%) also
had the highest number of women who reported that they had ever taken an HIV test. Manké
Centre (5%) had the lowest percentage of men who said that they had ever taken an HIV test
while Soungaya (3.1%) had the lowest percentage of women.
Table 35: Proportion of respondents who had ever taken an HIV test
Proportion in
men (%)
10.0
Number of
respondents
10
Proportion in
women (%)
17.4
Number of
respondents
24
Sahrata
20.0
16
21.2
33
Soungaya
11.8
17
3.1
32
Farmoriya-Yindi village
21.1
19
7.1
29
Matakang
18.2
11
3.3
30
Bossimiya
5.9
17
12.1
33
Manké Centre
5.0
20
8.1
37
Sentinel Site
Tèrin
Konimodiya
5.6
18
6.7
30
Total
11.8
128
9.8
248
2005 GDHS
6.7
2,709
2.5
7,954
2005 GDHS - Kindia
3.2
340
1.4
1,155
Nevertheless, the findings of this survey were higher than what was found during the 2005
GDHS. The proportion of men (11.8%) who took an HIV test was almost twice the proportion
found nationally (6.7%) and almost four times what was found in Kindia Region (3.2%).
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Similarly, amongst women, the proportion found in this survey (9.8%) was much higher than
what was found during the 2005 GDHS both nationally (2.5%) and regionally (1.4%). The
increase in uptake of HIV testing within the community is probably due to increased
HIV/AIDS campaigns within the country [32].
3.4.5.4.2 Condom Use
Table 36 shows the percentage of adults who agreed with different statements of condom
used when prompted. More than a half of all men interviewed (55%, range: 27.8-100%) said
that they know a place to get condoms. This proportion was highest in Tèrin, where all the
male respondents said that they knew a place where they could get condoms. The lowest
proportion was in Soungaya, where only 27.8% of men knew a place to find condoms. Only
one in five women (19.8%) reported that they know a place to find condoms. This percentage
ranged from 6.1% in Soungaya to 41.2% in Sahrata. However, despite knowing where to find
condoms, only about a half of those respondents said that they had ever used a condom
before. Only 26.6% of men reported that they had ever used a condom before (range: 1045%). This proportion was highest in Manké Centre (45%) and in Tèrin (44.4%). Similarly,
only 7.6% of women said that they had ever used a condom before, with the highest (17.7%)
proportion recorded in Sahrata and the lowest proportion (2.7%) recorded in Manké Centre.
Twenty men (21.1%, range: 0-50%) said they would have no problem using a condom. This
proportion was highest in Tèrin (50%). All male respondents in Farmoriya-Yindi village said
they would not consider using a condom. Thirty-two women (13.8%) said that they would not
mind using a condom. This ranged from 6.3% in Soungaya to 19.4% in Manké Centre.
The poor knowledge, utilisation and acceptability of condoms within these communities might
be largely attributed to the fact that most of the respondents who were interviewed were
married. Married people would be less likely to be using condoms during their sexual
relations. Moreover, most of the respondents within these communities were Muslims, who
do not advocate condom use.
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Table 36: Condom use among men and women
Percentage of adults who agreed with the following
statements when prompted
Know a place to
Have used a
Would you ever
get condoms (%)
condom before (%) use a condom (%)
Sentinel Site
Tèrin
Men
100.0
Women
20.0
Sahrata
66.7
Soungaya
FarmoriyaYindi village
Matakang
27.8
Men
44.4
Women
12.5
41.2
26.7
6.1
22.2
50.0
17.2
45.5
Bossimiya
Number of
respondents
Men
50.0
Women
19.1
Men
10
Women
25
17.7
9.1
17.9
15
34
3.0
21.4
6.3
18
33
10.0
10.3
0.0
7.7
20
29
10.0
36.4
6.7
42.9
14.3
11
30
52.9
24.2
11.8
3.0
20.0
15.6
17
33
Manké Centre
65.0
18.9
45.0
2.7
45.5
19.4
20
37
Konimodiya
50.0
19.4
27.8
6.5
15.4
10.3
18
31
Total
55.0
19.8
26.6
7.6
21.0
13.8
129
252
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3.4.6 KAP Pertaining to Tuberculosis
Tuberculosis (TB) is an infectious bacterial disease caused by Mycobacterium tuberculosis,
which most commonly affects the lungs. Individuals with active pulmonary TB produce
airborne droplet nuclei containing infectious M. tuberculosis in the course of speaking,
sneezing, and particularly coughing. Crowding, poor ventilation and duration of exposure
increase the risk of transmission. TB is endemic in Guinea, with an incidence rate of 287
cases per 100,000 population in 2007. WHO defines >200 cases per 100,000 population as
a serious epidemic [2].
Both male and female respondents were asked if they knew about TB, and how it was
transmitted. In terms of knowledge of TB transmission it was important to report against
consistent knowledge, i.e. that droplet infection is the only true mode of TB transmission.
Table 37 and Table 38 show the levels of TB knowledge amongst men and women,
respectively, stratified for each SS.
Sentinel Site
Tèrin
Have heard of TB (%)
Consistent Knowledge (%)
Through air when a person
coughs/sneezes (%)
Don't know (%)
Through smoking (%)
Through sharing dishes (%)
Other (%)
Through handshakes (%)
Untreated colds (%)
Through touching items in
public, e.g. doorknobs (%)
Number of respondents
Table 37: TB knowledge in men
100.0
10.0
10.0
10.0
60.0
10.0
7.7
0.0
0.0
0.0
10
Sahrata
100.0
0.0
20.0
26.7
53.3
33.3
5.9
0.0
6.7
0.0
15
Soungaya
FarmoriyaYindi village
Matakang
94.4
5.9
17.7
58.8
5.9
11.8
6.1
5.9
0.0
0.0
18
100.0
10.0
25.0
45.0
30.0
10.0
6.7
0.0
0.0
0.0
20
100.0
9.1
27.3
45.5
9.1
36.4
3.3
0.0
0.0
9.1
11
Bossimiya
100.0
5.9
23.5
29.4
29.4
17.7
12.1
5.9
5.9
0.0
17
Manké Centre
100.0
10.0
45.0
15.0
30.0
50.0
5.4
5.0
0.0
5.0
20
Konimodiya
100.0
16.7
27.8
27.8
16.7
38.9
6.5
5.6
5.6
0.0
18
Total
99.2
8.6
25.8
32.8
28.1
26.6
6.7
3.1
2.3
1.6
129
Almost all men (99.2%) had heard of TB. However, only 25.8% (range: 10-27.8%) mentioned
droplet transmission, via air, as the route of TB transmission. Furthermore, more men
believed that smoking (28.1%) and sharing dishes (26.6%) caused the transmission of TB.
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One in three men (32.8%) did not know how TB is transmitted. Only 8.6% of men (range: 016.7%) had consistent TB knowledge. None of the men in Sahrata had consistent TB
knowledge.
Sentinel Site
Tèrin
Have heard of TB (%)
Consistent Knowledge (%)
Through air when a person
coughs/sneezes (%)
Don't know (%)
Through smoking (%)
Through sharing dishes (%)
Other (%)
Through handshakes (%)
Untreated colds (%)
Through touching items in
public, e.g. doorknobs (%)
Number of respondents
Table 38: TB knowledge in women
96.0
4.2
8.3
58.3
12.5
16.7
7.7
4.2
0.0
4.2
26
Sahrata
100.0
5.9
26.5
32.5
0.0
55.9
20.6
2.9
2.9
0.0
34
Soungaya
Farmoriya-Yindi
village
Matakang
90.9
6.7
26.7
50.0
0.0
33.3
9.1
6.7
3.3
0.0
33
86.2
8.0
24.0
52.0
8.0
12.0
13.3
4.0
0.0
0.0
30
83.3
0.0
20.0
60.0
4.0
32.0
13.3
4.0
0.0
0.0
30
Bossimiya
90.9
20.0
36.8
46.7
3.3
26.7
6.1
0.0
0.0
3.3
33
Manké Centre
89.2
9.1
21.2
45.5
21.2
18.2
5.4
0.0
3.0
0.0
37
Konimodiya
93.6
17.2
31.0
44.8
13.8
24.1
6.5
6.9
0.0
0.0
31
Total
91.3
9.1
24.8
47.8
7.8
28.3
10.2
3.5
1.3
0.9
254
Two hundred and thirty women (91.3%) said that they had heard of TB. This knowledge
ranged from 83.3% in Matakang to 100% in Sahrata. However, almost a half of all women
(47.8%) did not know how TB was transmitted. One in four women (24.8%) correctly
identified air as a mode of TB transmission. But more women (28.3%) identified sharing
dishes as a mode of TB transmission than through air. Moreover, only 9.1% of women had
consistent knowledge. None of the women in Matakang had consistent TB knowledge.
Bossimiya (20.0%) and Konimodiya (17.2%) had the highest levels of consistent TB
knowledge.
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3.4.7 KAP Related to Nutrition
Nutritional behavioural aspects were included in the questionnaire survey to support the
baseline description and to complete the picture of clinical findings presented in section
2.3.2.1 above.
Three in four men (76%) had heard of malnutrition. In addition, 87.8% of these men think that
malnutrition is a problem within their community. Figure 43 shows the causes of malnutrition
as reported by male respondents. A large majority of the men (73.5%) thought that
malnutrition is caused by lack of money. Ten men (10.2%) thought that malnutrition is
caused by bad feeding habits, while 6.1% thought that malnutrition is caused by disease or
by other causes.
4,1%
6,1%
6,1%
10,2%
5,1%
Disease
Bad feeding habits
Lack of food
Lack of money
Don't know
Other
73,5%
Figure 43: Causes of malnutrition as reported by male respondents
One hundred and forty-five women (57.5%) had heard of malnutrition. Of these women,
90.3% thought that malnutrition was a problem within their community. One hundred and two
women (70.3%) thought that lack of money is the cause of malnutrition. Twenty-six women
(17.9%) thought that bad feeding habits were the cause of malnutrition, while 5.5% thought
that malnutrition is caused by disease of by other causes (Figure 44).
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5,5%
3,5%
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5,5%
17,9%
Disease
Bad feeding habits
7,6%
Lack of food
Lack of money
Don't know
Other
70,3%
Figure 44: Causes of malnutrition as reported by female respondents
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3.4.8 KAP pertaining to Trypanosomiasis
Human African Trypanosomiasis (HAT) is a protozoan disease (commonly referred to as
sleeping sickness) caused by Trypanosoma brucei spp. which enters the blood-stream via
the bite of blood-feeding tsetse flies (Glossina spp.). The parasite that may occur in Guinea
is T. b. gambiense which is endemic in Western Africa and is the less aggressive variant. In
2008, less than 100 cases of HAT were reported in Guinea. However, Guinea is the only one
of two countries in West Africa who is still reporting cases, and there are some focal areas of
transmission in the Forécariah Prefecture [2].
One hundred and eight men (83.7%) reported that they had heard of HAT. However, almost
two-thirds of the men (65.7%) did not know what the cause of HAT is. Only 5.6% identified
flies as the cause of HAT. Five men (4.6%) identified mosquitoes as the cause, 5.6% said
that uncleanliness (improper hygiene) was the cause while 23.2% mentioned other causes
(Figure 45).
4,6%
23,2%
5,6%
0,9%
5,6%
Mosquitoes
Flies
Witchcraft
Hygiene
Don't know
Other
65,7%
Figure 45: Causes of HAT according to male respondents
One hundred and forty-nine women (59.1%) had heard of HAT. However, only 2 women
(1.3%) of these women correctly identified flies as the cause of HAT. A large majority of the
women (87.3%) did not know what the cause of HAT is. Seven women (4.7%) said that they
thought uncleanliness (improper hygiene) was the cause, while 10.1% identified other
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causes. Figure 46 shows the responses of the women when asked what the causes of HAT
were.
1,3%
10,1%
0,7%
0,7%
4,7%
Mosquitoes
Flies
Witchcraft
Hygiene
Don't know
Other
87,3%
Figure 46: Causes of HAT according to female respondents
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3.4.9 Household and Environmental Indicators
Household characteristics, such as sanitation facilities, source of drinking water, drinking
water quality and place of cooking are important indicators of socio-economic status and also
of general well-being and health.
Observational indicators focused on housing and sanitation. Shelter has been recognised as
a basic prerequisite for health in the Ottawa Charter for Health Promotion [54]. Furthermore,
improper housing and overcrowding may favour transmission of airborne diseases such as
TB and offer favourable breeding sites for vectors such as rodents and mosquitoes.
Sanitation is a major cornerstone of public health as segregation of excreta from human
contact reduces the impact of diarrhoea, the second most important killer of children in
developing countries, and other major diseases such as cholera, schistosomiasis and
trachoma. Improving sanitation and guaranteeing access to a proper toilet prevents transfer
of bacteria, viruses and parasites, which will otherwise contaminate water sources, soil and
food. Accordingly to the WHO/UNICEF Joint Monitoring Program for Water Supply and
Sanitation, 62% of people in Africa do not have access to proper sanitation [11].
3.4.9.1 Construction Material of Floor, Walls and Roof
More than a half of the respondents (57.5%) had a natural floor (earth, sand or dung) in their
house. In addition, one in three respondents (33.1%) had houses with a finished floor
(ceramic floor plates, cement or polished wood), while 9.5% had houses with rudimentary
floors (wood, palm, bamboo or loose carpets) (Figure 47).
Figure 48 shows the type of material used by households for constructing their walls. A large
majority of households (72%) had walls that were made of a solid material (bricks, cement or
stone). The rest of the households (28%) were all made of rudimentary material (wood or
mud).
Two hundred and thirteen households (83.9%) had a roof made of a solid material
(corrugated sheets, cement, bricks or asbestos). The remaining households (16.1%) had
roofs made of rudimentary material (grass, thatch, straw or palm leaves) (Figure 49).
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33,1%
Natural floor
Rudimentary floor
57,5%
Finished floor
9,5%
Figure 47: Type of material used on floor
28,0%
Rudimentary walls
Solid walls
72,0%
Figure 48: Type of material used on walls
16,1%
Rudimentary roof
Solid roof
83,9%
Figure 49: Type of material used on roof
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3.4.9.2 Cooking Area and Fuel
It was considered important to describe the baseline environmental health conditions at the
household level and note how these may change over time. Due to seasonal variation and
potentially differing practices, it was also important to document the differences between the
wet and dry seasons.
The type of cooking arrangement is an indicator for indoor air pollution. Members of
households practicing indoor cooking are more exposed to risks of respiratory complications
than those cooking outside or in a separate building. Table 39 shows household cooking
areas during the wet and dry season at each SS. More than a half of the households (53.5%)
reported that they cook outside during the wet season. One hundred and two households
(40.2%) reported that they cook in a separate building, while 16 households (6.3%) reported
that they cook inside their house. Just over two-thirds (69.3%) of households said they cook
outside during the dry season. Seventy-three households (28.7%) said that they cook in a
separate building, while 5 households (2.0%) said that they cook inside their house.
Wet Season
In the
house
(%)
15.4
In a
separate
building
(%)
65.4
Sahrata
8.8
Soungaya
Farmoriya-Yindi
village
Matakang
3.1
Dry Season
Number of
respondents
Table 39: Cooking area during wet and dry season
Outside
(%)
19.2
In the
house
(%)
7.7
In a
separate
building
(%)
19.2
Outside
(%)
73.1
29.4
61.8
0.0
23.5
76.5
34
33.3
63.6
3.0
21.2
75.8
33
0.0
46.7
53.3
0.0
43.3
56.7
30
6.7
40.0
53.3
0.0
33.3
66.7
30
Bossimiya
6.1
33.3
60.6
0.0
27.3
72.7
33
Manké Centre
5.4
37.8
56.8
0.0
24.3
75.7
37
Konimodiya
6.5
41.9
51.6
6.5
38.7
54.8
31
Total
6.3
40.2
53.5
2.0
28.7
69.3
254
Sentinel Site
Tèrin
26
Figure 50 shows the type of cooking fuel that was used in the households. A large majority of
households (n=228, 89.8%) reported that they use firewood for cooking fuel. The remaining
households (n=26, 10.2%) reported that they use charcoal as their cooking fuel. No other fuel
was used- e.g. gas, kerosene or electricity.
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10,2%
Charcoal
Firewood
89,8%
Figure 50: Type of cooking fuel used
3.4.9.3 Air and Noise Pollution
To assess different environmental health determinants at baseline the participants were
asked questions related to perceived noise and air pollution in their community.
3.4.9.3.1 Air Pollution
Table 40 shows perceptions on air pollution amongst men in each SS. Sixty-six men (50.8%)
thought that there was air pollution in their community. This ranged from 31.1% in Sahrata to
61.1% in Konimodiya. Bad smells (36.4%) was the most commonly cited cause of air
pollution (range: 0-66.7%). One in three men (33.3%) cited dust as the most common cause
of air pollution (range: 11.1-60%). Nine men (13.6%) cited smoke as the cause of air
pollution while 11 men (16.7%) cited other different causes.
Men in Bossimiya cited bad smells (66.7%) as the most common reason for air pollution. No
men in Tèrin reported bad smells as a cause of air pollution. It is important to note that dust
was reported as a reason for air pollution in each site, with the highest percentage of men
reporting this in Soungaya (60%).
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Nature of air pollution
Number of
respondents
Table 40: Perception on air pollution by men
Proportion
that agrees
that there is
air pollution
(%)
50.0
Bad
smells (%)
0.0
Smoke (%)
20.0
Dust (%)
20.0
Other (%)
60.0
Sahrata
31.3
40.0
0.0
40.0
20.0
16
Soungaya
FarmoriyaYindi village
Matakang
55.6
20.0
20.0
60.0
0.0
18
40.0
37.5
25.0
25.0
12.5
20
54.6
50.0
0.0
33.3
16.7
11
Bossimiya
52.9
66.7
0.0
11.1
22.2
17
Manké Centre
60.0
41.6
16.7
25.0
16.7
20
Konimodiya
61.1
27.3
18.1
45.5
9.1
18
Total
50.8
36.4
13.6
33.3
16.7
130
Sentinel Site
Tèrin
10
Table 41 shows the perceptions on air pollution by women in each SS. About two-thirds
(66.3%, range: 54.2-74.2%) of women thought that there was air pollution in their community.
Fifty-one women (30.5%) said they thought bad smells were the biggest cause of air
pollution. Dust was cited as the cause of air pollution by 27.0% of the women, while 22.8%
said that smoke was the cause. Thirty-three women (19.7%) gave other different causes.
Nature of air pollution
Number of
respondents
Table 41: Perception on air pollution by women
Proportion
that agrees
that there is
air pollution
(%)
54.2
Bad
smells (%)
23.1
Smoke (%)
15.4
Dust (%)
38.4
Other (%)
23.1
Sahrata
61.8
42.8
14.3
28.6
14.3
34
Soungaya
FarmoriyaYindi village
Matakang
72.7
4.2
29.2
41.6
25.0
33
60.0
27.8
33.3
22.2
16.7
30
70.0
42.9
23.8
19.0
14.3
30
Bossimiya
69.7
34.9
21.7
21.7
21.7
33
Manké Centre
64.9
25.0
25.0
25.0
25.0
37
Konimodiya
74.2
43.5
17.4
21.7
17.4
31
Total
66.3
30.5
22.8
27.0
19.7
252
Sentinel Site
Tèrin
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3.4.9.3.2 Noise Pollution
Table 42 shows the perception on noise pollution by male respondents in each SS. Less
than half of male respondents (48.5%) thought there was noise pollution in their community.
This ranged from 20.0% in Tèrin to 62.5% in Sahrata. General community noises (like bars,
market, etc) were cited as the most common reason for noise by 87.3% of the respondents.
All men in Manké Centre and Konimodiya said community noises were the main cause of
noise pollution. Six respondents (9.5%) said noise from the road was the biggest cause while
2 men (3.2%) cited other different reasons.
Table 42: Perceptions on noise pollution by men
General
community
noises (%)
50.0
Construction
Site (%)
0.0
Noise from
the road (%)
0.0
Other (%)
50.0
Sahrata
62.5
70.0
0.0
20.0
10.0
16
Soungaya
Farmoriya-Yindi
village
Matakang
44.4
87.5
0.0
12.5
0.0
18
50.0
90.0
0.0
10.0
0.0
20
54.6
83.3
0.0
16.7
0.0
11
Bossimiya
47.1
87.5
0.0
12.5
0.0
17
Manké Centre
60.0
100.0
0.0
0.0
0.0
20
Konimodiya
38.9
100.0
0.0
0.0
0.0
18
Total
48.5
87.3
0.0
9.5
3.2
130
Sentinel Site
Tèrin
Nature of noise pollution
Number of
respondents
Proportion
that agrees
that there is
noise
pollution
(%)
20.0
10
One hundred and sixty-six women (65.9%) thought that there was noise pollution in their
community. This ranged from 53.3% in Farmoriya-Yindi village to 76.5% in Sahrata. Just like
in men, a large majority of the women (88.6%) thought that community noises were the major
cause of noise pollution. This ranged from 72% in Soungaya to 96.1% in Sahrata. Fifteen
women (9%) thought that noise from the road was the main cause of noise pollution. Only
two women (all from Matakang) thought that noise pollution from the construction was the
cause, while two women in Tèrin gave other different causes (see Table 43).
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Sentinel Site
Tèrin
Proportion
that agrees
that there is
noise
pollution
(%)
66.7
Nature of noise pollution
General
community
noises (%)
81.2
Construction
Site (%)
0.0
Noise from
the road (%)
6.3
Other (%)
12.5
Number of
respondents
Table 43: Perceptions on noise pollution by women
24
Sahrata
76.5
96.1
0.0
3.9
0.0
34
Soungaya
Farmoriya-Yindi
village
Matakang
75.7
72.0
0.0
28.0
0.0
33
53.3
93.7
0.0
6.3
0.0
30
66.7
90.0
10.0
0.0
0.0
30
Bossimiya
66.7
95.4
0.0
4.6
0.0
33
Manké Centre
62.2
87.0
0.0
13.0
0.0
37
Konimodiya
58.1
94.4
0.0
5.6
0.0
31
Total
65.9
88.6
1.2
9.0
1.2
252
3.4.9.4 Utilisation of Sanitation Facilities
WHO/UNICEF have developed definitions and a set of indicators for evaluating human
excreta disposal. The following definitions and indicators are widely used to monitor the
progress towards supporting the provision of sanitation services [11].
Improved sanitation facilities:
•
flush or pour – flush to piped sewer system, or septic tank or pit latrine (water closet);
•
ventilated improved pit latrine (VIP);
•
pit-latrine with slab; and
•
composting toilet.
Non-improved sanitation facilities:
•
flush or pour – flush to elsewhere;
•
pit-latrine without slab or open pit;
•
bucket; and
•
no facilities or bush or field.
Furthermore, only facilities which are not shared or are not for public use are considered
improved. The type of sanitation facilities were evaluated with the different types of latrines
used by the communities. The portion of households using improved/non-improved sanitation
facilities at each SS is shown in Figure 51.
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Figure 51: Distribution of sanitation facilities
The different types of sanitation facility at each SS are listed in Table 44. The majority of the
households (86.2%, range: 64.7-100%) had a non-improved sanitation facility. Thirty-five
households (13.8%, range: 0-35.3%) had improved facilities. The most common type of
sanitation facility was a pit-latrine without a slab, which was found in 68.9% (range: 2993.9%) of households. Twenty-nine households (11.4%, range: 0-30.8%) had a pit-latrine
with a slab. Seventeen households (6.7%) said they use a shared facility, 16 (6.3%) go to the
bush, while 11 (4.3%) go to a nearby water body (stream, river, lake or ocean). Only 2 (0.8%)
households had a water closet while 4 (1.6%) households had a VIP toilet.
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Table 44: Type of sanitation facilities in each sentinel site
Sentinel Site
Tèrin
Bush (%)
River/Lake/ Ocean
(%)
Pit-latrine without slab
(%)
Proportion using
facilities that are not
improved (%)
Pit-latrine with slab
(%)
VIP (%)
Water closet (%)
Proportion using
improved facility (%) Number of households Improved, non-shared
sanitation facility A shared facility (%)
Non-improved sanitation facility
7.7
7.7
0.0
53.8
69.2
30.8
0.0
0.0
30.8
26
Sahrata
5.9
0.0
0.0
58.8
64.7
20.6
8.8
5.9
35.3
34
Soungaya
Farmoriya-Yindi
village
Matakang
3.0
18.2
0.0
69.7
90.9
9.1
0.0
0.0
9.1
33
0.0
3.3
0.0
90.0
93.3
6.7
0.0
0.0
6.7
30
10.0
6.7
0.0
66.6
83.3
16.7
0.0
0.0
16.7
30
Bossimiya
0.0
0.0
0.0
93.9
93.9
6.1
0.0
0.0
6.1
33
Manké Centre
5.4
2.7
0.0
93.8
91.9
5.4
2.7
0.0
8.1
37
Konimodiya
22.6
12.9
35.5
29.0
100.0
0.0
0.0
0.0
0.0
31
Total
6.7
6.3
4.3
68.9
86.2
11.4
1.6
0.8
13.8
254
All respondents in Konimodiya reported that they use a non-improved sanitation facility. More
than a third (35.5%) of the respondents in this community reported that to the ocean, 29%
said that they use a pit-latrine without a slab, and 12.9% said that they go to the bush.
Soungaya had the highest number of respondents (18.2%) who said they go to the bush.
Sahrata had the highest number of respondents (35.3%) who had improved sanitation
facilities. Sahrata was also the only site that had water closets (n=2) and was one of the sites
that had a VIP toilet. Interestingly, Sahrata was also the village with the lowest prevalence of
STH infections (43.3%) and where no case of schistosomiasis was found.
3.4.9.5 Utilisation of Drinking Water Sources
The availability of and accessibility to potable water may be associated with the prevalence
of water-borne diseases among household members, with especially children being more
severely affected by conditions such as diarrhoea. The important indicator of water supply is
the proportion of the population with access to an adequate amount of safe drinking water
located within a convenient distance from the user’s dwelling. Lack of ready access to a
water source may limit the quantity of suitable drinking water that is available to a household.
Even if the water is obtained from an improved source, if the water must be fetched from a
source that is not immediately accessible to the household, it may be contaminated during
transport or storage.
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Ideally drinking water is collected from ‘improved drinking water sources’ as these are
supposed to be relatively free of water related pathogens. According to WHO/UNICEF,
improved and non-improved water sources are defined as follows [11]:
Improved drinking water sources:
•
household connection;
•
protected dug well;
•
public standpipe;
•
protected spring; and
•
borehole;
•
rainwater collection.
Non-improved drinking water sources:
•
unprotected well;
•
rivers or ponds;
•
unprotected spring;
•
street vendor-provided water;
•
bottled water (bottled water is not considered improved due to limitations in the
potential quantity, not quality, of the water).
With regards to seasonal variations, the main drinking water source for each household
during the dry and wet season was investigated.
3.4.9.5.1 Rainy Season
Table 45 shows the sources of drinking water for each household during the rainy season.
More than a half of the respondents (58.7%) reported that they get their drinking water from
an improved source. Seventy-one households (28%) reported that they collect their drinking
water from a protected well, while 67 households (26.4%) reported that they get their drinking
water from rainfall. Only 11 households (4.3%) said that they had tap water. One in four
households (25.5%) reported that they get their drinking water from an unprotected well.
Forty households (15.8%) reported that they get their drinking water from a river/lake or
spring.
Manké Centre had the highest proportion of households (94.6%) that said they get their
drinking water from an improved source during the rainy season. It had the highest
proportion of households with a protected well (46%). Bossimiya had the highest percentage
of households that get their drinking water from rainfall (51.6%) during the rainy season.
Almost a quarter (23.5%) of households in Sahrata gets their water from a tap, which was the
highest percentage of households with tap water. Farmoriya-Yindi village had the highest
percentage (76.7%) of households that get their water from an unimproved source. Most of
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the respondents here get their water from a spring (46.6%) or an unprotected well (30%).
Soungaya had the highest percentage of respondents (51.6%) who get their water from a
river/spring. Matakang had the highest number of unprotected wells (70%).
Table 45: Sources of drinking water at household level during the rainy season
Improved drinking
water source
Lake, river, spring
(%)
Proportion using
a non-improved
source (%)
Rain (%)
Protected well/
Tube borehole (%)
Tap water (%)
Proportion using
an improved
source (%)
Number of
respondents
Unprotected well
(%)
Non-improved drinking
water source
19.2
26.9
46.2
3.9
50.0
0.0
53.8
26
Sahrata
26.5
0.0
26.5
5.9
44.1
23.5
73.5
34
Soungaya
FarmoriyaYindi village
Matakang
12.1
51.6
63.6
3.0
33.3
0.0
36.4
33
30.0
46.6
76.7
6.7
16.7
0.0
23.3
30
70.0
3.3
73.3
13.4
3.3
10.0
26.7
30
Bossimiya
21.2
3.0
24.2
51.6
24.2
0.0
75.8
33
Manké Centre
5.4
0.0
5.4
48.6
46.0
0.0
94.6
37
Sentinel Site
Tèrin
Konimodiya
25.8
0.0
25.8
71.0
3.2
0.0
74.2
31
Total
25.5
15.8
41.3
26.4
28.0
4.3
58.7
254
3.4.9.5.2 Dry Season
Table 46 shows the drinking water sources for households during the dry season in each
sentinel site. More than a half of the households (53%, range: 14.7-80%) get their drinking
water from an unimproved source during the dry season. Ninety-two households (36.2%)
said that they get their drinking water from an unprotected well while 40 (15.8%) said that
they get their drinking water from a river/spring. However, 42.1% of households said they get
their drinking water from a protected well. Five households (2%) said that they get their
drinking water from a water tanker (all in Farmoriya-Yindi village) while 10 (3.9%) households
said they get their drinking water from tap water.
Sahrata had the lowest percentage (14.7%) of households who said they get their drinking
water from an unimproved source during the dry season. Sahrata had the highest
percentage (26.5%) of respondents who said that they get their drinking water from tap
water. Four in five (80%) of respondents in Matakang said that they get their drinking water
from an unimproved source, mainly unprotected wells (73.3%). Farmoriya-Yindi village had
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the highest percentage of households (43.3%) who get their drinking water from a
lake/river/spring. Manké Centre had the highest percentage (78.4%) of households who get
their drinking water from a protected well.
Table 46: Sources of drinking water at household level during the dry season
Improved drinking
water source
Lake, river, spring
(%)
Proportion using
a non-improved
source (%)
Protected
well/Tube borehole
(%)
Water Tanker (%)
Piped water/Public
tap (%)
Proportion using
an improved
source (%)
Number of
respondents
Unprotected well
(%)
Non-improved drinking
water source
23.1
30.8
53.8
46.1
0.0
0.0
46.2
26
Sahrata
14.7
0.0
14.7
58.8
0.0
26.5
85.3
34
Soungaya
FarmoriyaYindi village
Matakang
18.2
33.3
51.5
48.5
0.0
0.0
48.5
33
33.3
43.3
76.7
23.4
0.0
0.0
23.3
30
73.3
6.7
80.0
16.7
0.0
3.3
20.0
30
Bossimiya
60.6
9.1
69.7
30.3
0.0
0.0
30.3
33
Manké Centre
21.6
0.0
21.6
78.4
0.0
0.0
78.4
37
Sentinel Site
Tèrin
Konimodiya
48.4
9.7
69.2
25.8
16.1
0.0
30.8
31
Total
36.2
15.8
53.0
42.1
2.0
3.9
47.0
254
3.4.9.6 Treatment of Drinking Water at Household Level
Almost a quarter of households (n=59, 23.2%) reported that they do not treat their water
before drinking it (see Table 47). One hundred and eighteen households (46.5%) said that
they use a water filter to treat their water. Sixty-seven households (26.4%) said they use
chlorine to treat their water, 9 households (3.5%) said they let the water stand/settle, while
only 1 (0.4%) households said that they boil it.
Soungaya had the highest proportion of households (60.6%) who said they do not treat their
water. The lowest proportion of households that said they do not treat their water was in
Manké Centre (2.7%) and Tèrin (3.9%). More than a half (51.3%) of respondents in Manké
Centre said they use chlorine to treat their water which may be an indication of the
programme which is supported in the area. The majority of household in Tèrin (69.1%),
Matakang (66.7%) and Bossimiya (60.6%) said they use a water filter to treat their drinking
water.
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23.1
Sahrata
14.7
0.0
44.1
Soungaya
Farmoriya-Yindi
village
Matakang
60.6
0.0
9.1
56.8
3.3
3.3
23.3
0.0
Bossimiya
6.1
Manké Centre
Konimodiya
Total
23.2
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Number of
households
Chlorine (%)
0.0
Let it stand and
settle (%)
Boiling (%)
3.9
Water filter
(ceramic, sand)
(%)
Sentinel Site
Tèrin
No treatment (%)
Table 47: Water treatment methods in each sentinel site
69.1
3.9
25
41.2
0.0
29
18.2
12.1
13
33.3
3.3
13
6.7
66.7
3.3
24
0.0
30.3
60.6
3.0
31
2.7
0.0
51.3
46.0
0.0
36
19.4
0.0
35.5
41.9
3.2
25
0.4
26.4
46.5
3.5
196
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3.5 Drinking Water Quality Assessment
A total of 105 water samples were analysed based on biological criteria for drinking water. 26
samples were taken from the most commonly utilised community water collection points, i.e.
wells, hand pumps or rivers and springs. In addition to these, 79 samples were taken at
household level to determine end-user water quality. This methodology was chosen as it
provides an indication of the quality of water from source to final consumption as outlined in
section 2.3.4.
Table 3 summarises the results of the drinking water testing at community and household
level. Seventeen (65.4%) of the 26 samples collected from the main water collection points
were classified as unsuitable for drinking without treatment and 7 (26.9%) were classified as
‘requires treatment’. Consequently only 7.7% of the drinking water samples collected at
community drinking water points could be classified as compliant/tolerant. This shows poor
drinking water quality at community level, which is partly explained by the fact that only 7
(26.9%) of the sampled drinking water collection points were protected wells, while all the
other available drinking water collection points were uncovered wells, open sources or
rivers/ponds. Of note, 5 (71.4%) of the 7 protected wells were also classified as unsuitable
for drinking/requires treatment. In summary, the available drinking water infrastructure for the
communities in the survey is of poor quality (i.e. open wells), badly maintained (i.e.
contaminated protected wells) or simply non-existent (i.e. people get their drinking water form
rivers/ponds).
Table 48: Drinking water quality at community and household level
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The comparison with water samples collected at household level to those at end user at the
households was analysed to determine how the quality of water was affected through the
collection to use chain. Almost 9 out of 10 drinking water samples collected at household
level (88.6%) were classified as unsuitable for drinking without treatment and an additional
8.9% were classified as ‘requires treatment’. Only one sample from Sahrata did not present
any contamination with TTC. Sahrata is also the community that had the best water quality at
community level with one protected well showing only 1 TTC per 100ml. Furthermore, one
tolerable sample was found in Soungaya. In summary, 97.5% of the drinking water samples
collected at household level showed more than 10 TTC per 10 ml and thus require treatment
prior to drinking.
The fact that the household water showed a higher degree of contamination (only 2.6% of
samples were classified as compliant or tolerable) than the community drinking water points
(7.7% of samples were classified as tolerable) underpins the findings of section 3.4.9.6 that
only few households (26.4%) chlorinate their drinking water and that collection to end use is
a source of potential contamination which require support from improved hygiene measures.
Only two water collection points (one in Matakang and one in Manké Centre) showed a slight
degree of turbidity (8 NTU). Hence, in general turbidity of the water samples was very low
which favours any disinfection efforts.
Bossimiya was the only SS where water samples where alkaline (pH >7), though only to
minor degree (pH 7-7.8). Thus, almost all the drinking water samples collected could be
classified as acidic with a pH of below 6.8. Hence, it is assumed that water disinfection with
chlorine would be highly effective in the study area due to low pH and low turbidity.
A detailed list of the location, type and measured parameters of the different community
drinking water collection points is provided in Table 49.
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Table 49: Water quality at drinking water collection points
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3.6 Health Facilities Assessment
Three health facilities were visited during the BHS and an interview and some focussed
observational assessments were completed in each of these facilities. Key parameters were
accessed in terms of the functionality of the facility, services provided, availability of essential
drugs and consumables, human resource component, case load and availability of essential
services. These are presented in Table 50. More background information on the local health
system can be found in the HIA scoping study [2].
In the surveyed SS, 2 health centres (Maférinya and Manké Centre) and 1 health post
(Matakang) were present. The facilities assessed all offer basic health care services
including primary health care, maternal health care and vaccination services. According to
the level and scope of service, the health centres only offered rudimentary emergency care
services and none had an ambulance. Only the health centre in Maférinya had laboratory
services with a microscope for haematological and parasitological investigations. At the time
of the survey all these health facilities had run out of stock of RDTs for malaria diagnosis.
The same was true to many of the essential drugs including ACT for malaria treatment. In
Manké Centre during the assessment the clinician responsible for community health reported
that this was due to the fact that the facility had run out of internally generated funds to
restock the facility. This was due to the change in policy to provide health care services free
of charge to children under the age of 5 years and pregnant women. The facility was
sponsored with an initial stock from UNICEF which was to be sustained through revenue
collected during consultations, but this was now depleted.
None of the health centres had a functioning water supply system (water tank feeding a
piped water supply system) and solar panels supplying the fridge that contained vaccines
were the only available electricity supply. Lighting at night was thus not available and many
procedures including deliveries are conducted by candlelight.
Staffing was acceptable for patient load of 15-30 consultations per day.
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Figure 52: Candle wax in delivery room in Manké health centre
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Dr Cissé (Médecin),
Director of Maférinya X X X
health centre
X
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X
X
X
X X
X
Diassy Amadou,
Director of Matakang
X X
health post
X
a
X
b
X
Aguibou Diallo
(Médecin) Director of
Kaback health centre X X X
X
X
b
X X
a
Staff from Kaback health centre arrives once a month for vaccination services
b
Sputum for TB testing is send to Maférinya
c
TB treatment is provided from Forécariah in case of a confirmed TB case
c
X
X
c
X
X
X
X X
3
2
30
2
X X X
4
1
15
2
Infrastructure
2
20
1
3 8 1
1
3
3
2
5
TOTAL Staff
TOTAL beds
Number of beds
Medical doctor
Medical specialist
Medical assistant
Nurses
Technical assistants
Midwife (educated)
Agent communautaire
Laboratory technician
Traditional birth attendant
Environmental health technologist
Nurse assistant
c
∅ outpatient consultations per day
X X X X
Post-natal care
Essential drugs and supplies that are
always in stock
Outpatient
Laboratory services
Inpatient
Services Provided
TB diagnostic
Haematology
Biochemistry
Parasitology
ACTs(Arthermeter/amiodiaquine)
Quinine
IPTp (Fansidar/SP)
Antiretroviral drugs
TB drugs
EPI vaccinations
Antihelmintic drugs
Oral rehydration solution
Oxytocin √
Penicillin/Ampicillin
Erythromycin
Doxycycline
Vitamin A
Vitamin K
Iron supplements
Folic acids
Insecticide treated nets
Piped potable water available
Reliable electricity supply available
Primary health care
Maternal health care
Emergency care
Ambulance service
Intensive care
Laboratory services
General surgery
Orthopaedic surgery
Specialist care
Radiology
Vaccination service
Blood transfusion
Microscopy
Malaria testing
RDT
ELISA
Rapid Tests
HIV/AIDS testing
CD4 count
Name of interviewed person
and health facility
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Table 50: Key indicators on health infrastructure
Human resources
4 21
4
8
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4 Limitations of the Study
It is generally recognised that any epidemiological study will present some limitations in the
scope and study design. The intent of the BHS reported here was not to conduct a controlled
trial or to present detailed research, but rather to describe a robust baseline in the selected
PACs and establish an evidence-base to inform the overall HIA and to support the
development of a community health management plan and associated surveillance system.
Some of the limitations include:
•
findings of the present study are not directly applicable to communities that were
not sampled within the BHS and do not represent a broader district or area
average due to the strategic and high focussed selections of the SS that were
focussed on the PACs;
•
some of the SS cannot be directly compared to each other for certain indicators
due to limited sample sizes required for direct comparison (e.g. nutrition);
•
while the survey had an extensive scope, it is nevertheless limited and not all
indicators for all the disease profiles could be obtained, hence indicators that can
be easily obtained and are reproducible were chosen that had a higher
importance than others;
•
like any other cross-sectional study design, exposures and outcomes were
collected at the same time, which leads to difficulties in determining causality;
•
surveys are normally based on respondents’ self-declaration which may be prone
to recall bias. Moreover, when it comes to questions on one’s private life, study
participants tend to be affected by a social desirability bias, where they choose to
give answers that are socially acceptable; and
•
the project area and the general health status of the community will change over
time. At present the Project has a long life cycle and the present health priorities
are likely to change. Thus, as the Project moves ahead, the surveillance activities
may need to have new indicators added and others may not be relevant anymore.
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6 Appendices
6.1 Appendix A: Ethical Approval
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6.2 Appendix B: Ordre de mission
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6.3 Appendix C: Questionnaire
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