TANA RIVER COUNTY
SMART NUTRITION SURVEY REPORT
By
International Medical Corps
and
Ministry of Public Health and Sanitation
With Support from UNICEF
February 2012
Submitted to:
International Medical Corps, Kenya
Report compiled by:
Martin Meme
Consultant Nutritionist
Department of Foods, Nutrition & Dietetics
Kenyatta University
P.O. Box 43844 (00100)
Nairobi
Cell: 0722-306607
Email: mmmeeme@yahoo.com
TABLE OF CONTENTS
ACRONYMS AND ABBREVIATIONS……………………………………………………….
EXECUTIVE SUMMARY ……………………………………………………………………...
1.0 INTRODUCTION …………………………………………………………………………...
1.1 Background to the Survey and Rationale……………………………………….........
1.2 Objectives …………………………………………………………………………………...
2.0 METHODOLOGY …………………………………………………………………….........
2.1 Geographic Target Area and Population Group…………………………………….......
2.2 Type of Survey............................................................................................................
2.3 Sampling Methodology and Sample Size ………………………………………………
2.4 Data Collection Tools and variables measured..........................................................
2.4.1 The Household Questionnaire.................................................................................
2.4.2 Child (6-59 months old) and maternal questionnaire...............................................
2.4.3 Under 6 months old questionnaire...........................................................................
2.4.4 Mortality questionnaire.............................................................................................
2.4.5 IYCF questionnaire.............................................................................................
2.4.6 Focus group discussion (FGD) guide.....................................................................
2.5 Training and Supervision…………………………………………………………………
2.6 Data Entry and Analysis..............................................................................................
2.7 Nutritional Status Cut-off Points..................................................................................
2.7.1 Weight-for-height (WFH) and MUAC – Wasting for Children …………………........
2.7.2 Weight-for-age (WFA) – Underweight ……………………………………………........
2.7.3 Height-for-age (HFA) – Stunting ………………………………………………………..
2.7.4 Maternal MUAC …………………………………………………………………………..
2.8 Data Quality Control....................................................................................................
3.0 RESULTS AND DISCUSSIONS ………………………………………………………...
3.1 Demographic Characteristics of Study population and Households…………….........
3.2 Nutritional Status of Children 6-59 Months ……………………………………………...
3.2.1 Prevalence of Global Acute Malnutrition (WHO Standards)....................................
3.2.2 Prevalence of Acute malnutrition by MUAC.............................................................
3.2.3 Prevalence of Underweight by Weight-for-age Z-scores (WHO-GS)……………….
3.2.4 Prevalence of Stunting by height-for-age (HFA) z-scores (WHO-GS)………….......
3.3 Adult Nutritional Status ………………………………………………………………........
3.4 Child Feeding, Care and Health ……………………………………………………….....
3.4.1 Infant and young Child Feeding Practices ……………………………………………
3.4.2 Child Immunization, Vitamin A Supplementation and Deworming ……………........
3.4.3 Child Morbidity …………………………………………………………………………....
3.5 Access to Health Facilities and Maternal Health Care................................................
3.6 Insecticide Treated Mosquito Nets (ITN) Holding Rates and Utilization …………......
3.7 Water, Sanitation and Hygiene Practices………………………………………………...
3.8 Household Food Security Indicators ……………………………………………………..
3.8.1 Sources of income………………………………………………………………………..
3.8.2 Food Aid …………………………………………………………………………………..
3.8.3 Household Dietary Diversity and Food Sources ……………………………………...
3.8.4 Coping Strategies…………………………………………………………………………
3.9 Mortality …………………………………………………………………………………......
3.10 Association between GAM and Important Public Health variables...........................
4.0 CONCLUSIONS AND RECOMMENDATIONS ………………………………………...
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LIST OF TABLES
Table 1: Maternal MUAC Cut-off Points …………………………………………………….
Table 2: Age and sex distribution of sample children ……………………………………..
Table 3: Overall prevalence of acute malnutrition by WFH z-scores (WHO-GS)............
Table 4: Child nutritional status based on MUAC…........................................................
Table 5: Prevalence of underweight by weight-for-height z-scores (WHO-GS)………...
Table 6: Prevalence of stunting by height-for-age z-scores (WHO-GS)………..............
Table 7: Adult nutritional status by MUAC …………………………………………............
Table 8: Sources of water and treatment of drinking water ……………………………....
Table 9: Quantities of food aid received by households …………………………………..
Table 10: Underfive and crude mortality rates ………………………………....................
Table 11: Association between GAM and other variables ………………………………..
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LIST OF FIGURES
Figure 1: Overall prevalence of GAM by child age................……………………………..
Figure 2: Distribution of W/H Z-scores for sampled children...........................................
Figure 3: Wasting by MUAC and Child Age ………………………………………………..
Figure 4: Breast feeding practices.................................................................................
Figure 5: Food groups taken by children in the previous 24 hours................................
Figure 6: Immunization, vitamin A supplementation and deworming coverage ………..
Figure 7: Child morbidity.................................................................................................
Figure 8: Management of diarrhoea................................................................................
Figure 9: Time taken to access health facilities..............................................................
Figure 10: Sources of ITNs.............................................................................................
Figure 11: ITN utilization by household members...........................................................
Figure 12: Handwashing………………………………………………………………………
Figure 13: Food groups taken by mothers......................................................................
Figure 14: Main household food sources........................................................................
Figure 15: Household food stress coping mechanisms……………………………………
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LIST OF APPENDICES
Appendix 1: Local events calendar………………………………………………………….. 32
Appendix 2: Survey tools……………………………………………………………………... 33
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ACRONYMS AND ABBREVIATIONS
ARI
CED
CI
CMR
CSB
ENA
FAO
FGD
GCM
GFD
GAM
GOK
GS
HFA
IMAM
IMC
ITN
KEPI
MOH
MoMS
MoPHS
MUAC
NCHS
OPV
PPS
SAM
SD
SFP
SMART
SPSS
TBA
UFMR
UNICEF
WFA
WFH
WFP
WHO
- Acute Respiratory Infection
- Chronic Energy Deficiency
- Confidence Interval
- Crude Mortality Rate
- Corn Soya Blend
- Emergency Nutrition Assessment
- Food and Agriculture Organization
- Focus Group Discussion
- Global Chronic Malnutrition
- General Food Distribution
- Global Acute Malnutrition
- Government of Kenya
- Growth Standards
- Height-for-Age
- Integrated Management of Acute Malnutrition
- International Medical Corps
- Insecticide Treated Nets
- Kenya Expanded Programme on Immunization
- Ministry of Health
- Ministry of Public Health Services
- Ministry of Public Health Services
- Mid-Upper Arm Circumference
- National Centre for Health Statistics
- Oral Polio Vaccine
- Probability Proportional to Population Size
- Severe Acute Malnutrition
- Standard Deviation
- Supplementary Feeding Programme
- Standardized Monitoring and Assessment of Relief and Transitions
- Statistical Package for Social Scientists
- Traditional Birth Attendant
- Underfive Mortality Rate
- United Nations Children’s Fund
- Weight-for-Age
- Weight-for-Height
- World Food Programme
- World Health Organization
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EXECUTIVE SUMMARY
Tana River County comprises of 3 districts (Tana North, Tana River and Tana Delta) covering an area
of 38,782 km² with an estimated population of 245,204 persons1. It borders Kitui District to the West,
Mwingi to the North West, Garissa to the East, Tharaka-Nithi and Isiolo to the North, Lamu to the South
East, Kilifi and the Indian Ocean to the South East. Its only permanent source of water (Tana River)
traverses the northern border of the county, which makes the inhabitant community heavily reliant on
seasonal rivers during the wet season and their river beds (laga) for water during the dry season. There
are three main livelihood zones in the county namely, Marginal Mixed Farming (which accommodates
49% of the population), Pastoral (14%) and Mixed Farming (37%). Many parts of the county receive
erratic and poorly distributed rains. It is estimated that 72% of the population live below the poverty line,
therefore, do not have access to adequate food and consequently heavily rely on relief food aid and
charitable donations2. With the on-going rehabilitation of irrigation schemes, many people are shifting
from the former heavy reliance on pastoral activities to agricultural activities. The food security situation
in the county was at ‘Stressed Phase’ with the status rated at ‘Alert and Deteriorating’ (ALRMP
Drought Early Warning Bulletin - January 2012)3.
The International Medical Corps, with financial support from UNICEF is supporting Ministry of Public
Health and Sanitation and Ministry of Medical Services (MoPHS) in the scaling up of High Impact
Interventions (HINI) for improved maternal and child health in Tana River Districts. These interventions
are in line with the priorities outlined in the nutrition sector partnership framework, which supports
scaling up of HINI as well as supporting the Ministry of Health to deliver essential nutrition/health
services.The overall strategy for International Medical Corps is to improve the technical and logistical
capacity of the Ministry of Medical Services (MoMS) and MoPHS to deliver high-impact nutrition
interventions through an integrated package that includes: promotion of exclusive breastfeeding for the
first six months of life; promotion of optimal complementary feeding for infants after the age of six
months; Vitamin A supplementation (2 doses per year for children aged 6-59 months); zinc
supplementation in diarrheal disease management; multiple micronutrients for children under five
years; deworming for children (2 doses per year for children aged 12-59 months); iron/folic acid
supplementation for pregnant mothers; prevention and treatment of SAM and MAM; promotion of
improved hygiene practices including hand washing and promotion of the utilization of iodized salt. This
survey therefore served to assess the nutritional situation in the county to gauge the performance of
HINI and inform future programming.
The survey utilized the Standardized Monitoring and Assessment of Relief and Transitions (SMART)
methodology in accordance with both the National Guidelines for Nutrition and Mortality assessments in
Kenya and the UNICEF-recommended nutritional survey key indicators. Both anthropometric and
mortality data were collected simultaneously during the survey. A two-stage cluster sampling with
probability proportional to size (PPS) design was employed for the integrated nutrition survey. Sample
size was determined on the basis of estimated prevalence rates of malnutrition (GAM), desired
precision and design effect) using the ENA for SMART software.
The 779 households assessed in this survey had, an average membership of 6.1 (SD 2.5) persons and
yielded a total of 4746 persons, out of which 1020 (21.5%) were children below five years, whose mean
number was 1.3 (SD 0.8) per household. The prevalence of global acute malnutrition i.e. GAM (WFH zscores < -2 standard deviations from the median of the WHO-GS or having oedema) of 13.5% (11.315.9 CI) was beyond acceptable limits according to WHO4 benchmarks. The prevalence of severe
Tana River District Development Plan (2002-2008).
Tana River Development Plan
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Drought Early Warning Bulletin (January, 2012)
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WHO (1995): Management of Nutrition in Major Emergencies.
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acute malnutriton (SAM) i.e. z-scores < -3 or oedema was likewise relatively high at 3.1% (2.3-4.2 CI).
The current levels of GAM and SAM are higher (though not significantly) than those (10.6% 8.4-13.3 CI
and 2.1% 1.2-3.7 CI, respectively) revealed by the last SMART survey in the county of December 2010.
MUAC findings indicated an overall GAM prevalence of 5.6% (4.2-7.3 CI). The prevalence of
underweight among the children (27.2% 23.3-31.5 CI) was both below the average for Coast province
(39.0%) as well as the National average of 35.5%. The prevalence of severe underweight among the
children was 7.0% (4.8-10.1 CI). The findings indicated a global chronic malnutrition (GCM) rate in the
county of 33.4% (24.8-43.2 CI), which was also below both the average for Coast province (39.0%) as
well as the National average of 35.3%5. Severe chronic stunting level stood at 10.5% (6.4-16.7 CI).
Significantly more pregnant women (34.7% 24.7-46.2 CI) than the non-pregnant (4.9% 3.3-7.0 CI)
suffered from chronic energy deficiency (P<0.01).
After birth, 98.3% of the IYCFP sample of 409 children was reported to have breastfed at some point in
their lives. The proportion of infants put on the breast within the first hour of birth was two thirds
(66.4%), though with 30.4% of the children given pre-lacteals in the first three days. More than four
fifths (87.4%) of the children had received colostrum, which is important in boosting immunity among
newly born infants. The level of exclusive breastfeeding was slightly more than two thirds (67.1%)
compared to the national average of only 31.9%. The mean frequency of breast feeding among the
exclusively breastfed infants was relatively high at 9.33 (SD 3.9) times relative to the WHO
recommendation of at least 12 times daily. Maintenance of breastfeeding though dropped by more than
half from 92.9% at one year to 42.9% at two years. Although complementary feeding rate was high at
95.7%, a qualitative analysis of the diet taken by the children was reflective of poorly nutrient-profiled
diets, since less than half (43.6%) of the children took meals meeting the minimum optimal dietary
diversification on the basis of their breastfeeding status6, with findings suggestive of inadequate dietary
micronutrient (vitamins and minerals) intake by the children.
The immunization coverage rates for polio (91.7%) and measles (89.5%) were commendably high and
above the Kenya Expanded Programme on Immunization (KEPI) and WHO recommendation of 80%
coverage. However, vitamin A supplementation (77.8%) and deworming coverage (51.5%) fell below
the KEPI and WHO recommendation. A 2-week recall indicated a high morbidity load among the
children as more than two thirds (67.4%) of the children were reported to have been sick, with the most
prevalent illness affecting the underfives being ARI (39.9%) followed by malaria (12.9%) and diarrhoea
(7.9%). Zinc supplementation, which is important in the control of diarrhoeal diseases, was very low at
only 1.5%, which was attributed to non-availability of zinc tablets at health facilities. When sick, the
majority (70.9%) of childcare givers sought assistance from public facilities.
Although ANC attendance by mothers was high (87.5%), only 23.4% reported giving birth under
qualified medical supervision, eroding many possible benefits that might have accrued from their ANC
attendance. Likewise, though a relatively high proportion of mothers (61.7%) reported having received
iron folate supplementation during their previous pregnancy, a mere 2.4% took the tablets for the
recommended 90 or more days. Less than half (45.1%) of the mothers reported having received
vitamin A supplementation after delivery. The risk of iodine deficiency in the county was, however,
minimal as 98.8% of the households reported using iodized table salt.
GOK 2009: Kenya Demographic and Health Survey Report
Guidelines for measuring household and individual dietary diversity. Version 2, June 2007. Prepared by FAO Nutrition and Consumer
Protection Division with the support from EC/FAO Food Security Information for Action Programme and the Food and Nutrition Technical
Assistance (FANTA) Project. Rome, Italy
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The findings of the survey indicate that up to two thirds (65.9%) of the households owned mosquito
nets, with more than three quarters (75.5%) having been obtained from the MOH. Among those
received from shops or kiosks, 32.5% were treated with chemicals. Utilization of the nets during the
night preceding the survey reveals that a majority (87.4%) of underfive children had slept under the
nets, followed by non-pregnant women (83.1%), pregnant women (74.5%) and children above 5 years
(66.1%), a generally high ITN utilization rate considering that the county is a malarial endemic zone.
The proportion of households obtaining water within the SPHERE recommended time of 30 minutes
was only slightly more than half (56.8%). The households mainly reported sourcing their water for
household use as well as for drinking from protected wells (28.1% and 25.7%, respectively) rivers
(mainly Tana River) for 20.5% for general use and 23.6%) for drinking. Boreholes were the third main
source accounting for 11.8% households obtaining water for general use and 0.7% for drinking. There
is need to sensitize the Tana River County on treatment of drinking water through boiling, being a very
easy, feasible and cheap method, as more than four fifths (82.1%) of the households did not
appropriately treat their unsafe drinking water. The reported latrine access in the county stood at only
one third (32.5%), with the majority (95.5%) of those without reportedly using bush, a practice daunted
with risks of drinking water contamination. Overall, less than one tenth (8.1%) of the respondents
washed their hands appropriately, which calls for hygiene education to improve on appropriate
handwashing
Overall, the inhabitants of Tana River County depended on four main sources of income: wage labour
(32.2%), sale of livestock/products (20.7%), sale of charcoal/firewood (17.1%) and sale of crops
(11.1%), a finding indicative of a community shifting from over-reliance on pastoral activities and
diversifying economic activities, which in the long run would lead to an improvement of the nutritional
situation. Slightly more than half (51.6%) of the households reporting receiving general food aid (GFA)
in the previous 3 months, which on average, lasted 18.2 (SD 13.8) days. More than half (56.5%) of the
households had cultivated their land during the previous planting season, where the food crop grown by
the highest proportion of households was maize (29.4%) followed by green grams (13.3%) and
cowpeas (10.9%). Unlike the case for the underfives where relatively low proportions (43.6%) had taken
highly diversified diets, more than half (51.7%) of the mothers had taken highly diversified diets. On the
whole, analysis of variance showed that the reported usual/normal frequency of taking meals (2.7 SD
0.5) by households was significantly higher than the 2.52 (SD 0.7) times reported for the day prior to
the survey (P<0.01), indicating a relative food stress situation. This was further amplified by the low
proportion of households (19.5%) relying on own food production relative to the high proportion (60.9%)
relying on food purchases, the fact that 15.9% relied on food aid, the reported high market food prices
(FGDs) and use of coping strategies reflective of mild to severe food stress. The findings showed that
children from households with more than 6 members, those without toilets, and where childcare givers
age was above 30 years were significantly more wasted than their opposite counterparts (P<0.05). Both
the crude mortality rate (CMR) of 0.75 deaths/10,000/day and the underfive mortality rate (UFMR) of
1.23 deaths/10,000/day did not reach the threshold for ‘Alert’ status.
In conclusion, this survey was conducted during the hunger-gap period that precedes the onset of long
rains expected during the month of March. Though both the underfive mortality rate (UFMR) and crude
mortality rate (CMR) were below the ‘Alert’ status, the prevalence of GAM of 13.5% (11.3-15.9 95% CI)
is beyond acceptable limits according to WHO benchmarks and rated ‘Risky’. Underfive children in TRD
county were faced with a high burden of morbidity mainly due to ARI and malaria. Zinc and vitamin A
supplementation and deworming coverage were below WHO recommendation of 80%. WASH practices
are still poor in the county as reflected by the facts that less than one third of the households had
access to toilets, less than one fifth of the households treated unsafe drinking water and appropriate
hand washing was practised by only about one tenth of the child caregivers. Though some indicators of
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optimal infant and young child feeding (IYCF) practices were good (such as timely initiation of
breastfeeding, exclusive breastfeeding and maintenance of breastfeeding at 1 year), maintenance of
breastfeeding at 2 years was low at less than half of the sampled children, with FGDs indicating sociocultural and ignorance factors mainly culpable for non-compliance. Although complementary feeding
practices (frequency of meals) were optimal for up to one third of the children, qualitative analysis of the
diet indicated poor dietary profiles for eligible children (6-23 months), with more than half subsisting on
poorly diversified diets. The food security situation in the county was generally poor. Household food
consumption during the survey’s conduct indicated a significant reduction in daily meal frequency
relative to the usual frequency of taking meals, with only about half of the households taking highly
diversified diets. Sixty percent of the households relied on food purchase as their main food source in
the face of reported high market food prices and a number of main food stress coping strategies
practised applied to mild to serious food deficit periods. Focussed group discussions as well as
observations revealed a community readily embracing farming activities in the on-going irrigation
scheme rehabilitation. The following recommendations are made:
1. There is need to improve on the following HINI components:
 Zinc supplementation during diarrhea;
 Vitamin A supplementation;
 Toilet access and use;
 Treatment of drinking water through boiling;
 Training of the community on appropriate hand washing;
 Medical supervision of mothers during child birth;
 Continued breastfeeding after 1 year;
 Constitution of balanced diets using locally available foodstuffs (with continued agricultural
diversification); and
 General primary health-promotive strategies e.g. use of ITNs
2. Stepping up of stop-gap measures (GFD and FFA) to cushion the community against current fooddeficit situation before onset of long rains, planting and harvest
3. Sustained rehabilitation of irrigation schemes with agricultural diversification, protection of scheme
areas against crop destruction by wild animals and improved marketing of food products to further
improve production in the County
4. Initiation of small-scale home-based irrigation projects (mainly kitchen gardens) in areas outside
main scheme e.g. through drip irrigation during dry seasons to help diversify diets to promote
optimal nutritional status in the community
5. Infrastructural improvement to improve access to markets and facilitate general development in all
areas of the County.
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1.0 INTRODUCTION
1.1 Background to the Survey and Rationale
Tana River County is located in the Coast province and comprises of 3 districts (Tana North, Tana
River and Tana Delta) covering an area of 38,782 km² with an estimated population of 245,204
persons7. It borders Kitui District to the West, Mwingi to the North West, Garissa to the East, TharakaNithi and Isiolo to the North, Lamu to the South East, Kilifi and the Indian Ocean to the South East. Its
only permanent source of water (Tana River) traverses the northern border of the county, which makes
the inhabitant community heavily reliant on seasonal rivers during the wet season and their river beds
(laga) for water during the dry season. There are three main livelihood zones in the county namely,
Marginal Mixed Farming (which accommodates 49% of the population), Pastoral (14%) and Mixed
Farming (37%). The Marginal mixed farming zone occupies the river line of Tana River in Wenje,
Madogo, and parts of Bura, Galole and Bangale divisions. Mixed farming livelihood zone occupies the
Southern part which includes Garsen, Tarasaa and Kipini divisions while the pastoral zone covers
Bangale, Bura, Galole and parts of Garsen divisions. The county experiences a bimodal rainfall pattern,
with the long rains falling between April and June and the short rains falling between October and
December. The mixed farming livelihood zone is mainly short rains-dependent while the marginal mixed
farming and pastoral livelihood zones are long rains-dependent. The mean annual rainfall ranges
between 220mm to 500mm, with the exception of the mixed farming livelihood zone, where rainfall
ranges between 750mm to 1250mm. Many parts of the county receive erratic and poorly distributed
rains. It is estimated that 72% of the population live below the poverty line, therefore, do not have
access to adequate food and consequently heavily rely on relief food aid and charitable donations 8.
With the on-going rehabilitation of irrigation schemes, many people are shifting from the former heavy
reliance on pastoral activities to agricultural activities. The County is inhabited by people from the
Pokomo, Orma, Wardei, Somali, Malakote, Bajuni, Mijikenda and Munyoyaya ethnic groups. Prior to
this survey, the food security situation in the county was at ‘Stressed Phase’ with the status rated at
‘Alert and Deteriorating’ ALRMP9.
The International Medical Corps Kenya with financial support from UNICEF is supporting Ministry of
Public Health and Sanitation (MoPHS) and Ministry of Medical Services (MoMS) in scaling up of High
Impact Interventions for improved maternal and child health in the Tana County. These interventions
are in line with the priorities outlined in the nutrition sector partnership framework which supports
scaling up of high impact interventions as well as supporting the Ministry of Health to deliver essential
nutrition services.The overall strategy for International Medical Corps is to improve the technical and
logistical capacity of the MoMS / MoPHS to deliver high-impact nutrition interventions through an
integrated package that includes: Promotion of exclusive breastfeeding for the first six months of life;
promotion of optimal complementary feeding for infants after the age of six months; Vitamin A
Supplementation (2 doses per year for children aged 6-59 months); Zinc supplementation for diarrhea
management; multiple micronutrients for children under five years; deworming for children (2 doses per
year for children aged 12-59 months); iron-folic acid supplementation for pregnant mothers; prevention
or treatment of SAM and MAM; promotion of improved hygiene practices including hand washing and
promotion of the utilization of iodized salt. In order to gauge the performance of the HINI package and
inform future programming in the County, International Medical Corps in collaboration with
MOMS/MOPHS and UNICEF carried this nutritional survey between 6th February and 18th February
2012, to evaluate the extent and severity of malnutrition among children aged 6-59 months, analyze the
possible factors contributing to malnutrition and recommend appropriate interventions.
Tana River District Development Plan (2002-2008).
Tana River Development Plan
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Drought Early Warning Bulletin (January, 2012)
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1.2 Objectives
The main objective of this survey was to establish the extent and severity of malnutrition and to provide
data for use in monitoring the progression of the situation.
1. To evaluate the nutritional status of children aged 6 to 59 months
2. To assess the nutritional status of pregnant and lactating mothers aged 15-49 years
3. To estimate the measles and polio immunization coverage for children aged 9 to 59 months
4. To estimate the crude and under-five mortality rates
5. To estimate the systematic treatment (vitamin A supplementation and de-worming coverage)
6. To identify factors likely to have influenced the nutritional status of young children
7. To estimate the prevalence of some common illnesses (e.g. measles, diarrhea, malaria, and
ARI)
8. To establish the current household food security situation
9. To establish the situation of water, sanitation and hygiene
10. To assess the percentage of mothers accessing MCH facilities and the level of exclusive
breastfeeding of children under six months
11. To estimate the iron /folate coverage among mothers
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2.0 METHODOLOGY
2.1 Geographic Target Area and Population Group
This survey covered the three districts that comprise the Tana River County (Tana North, Tana River
and Tana Delta) with the target population comprising of children 6-59 months old for anthropometric
measurements and their mothers/primary caregivers as the primary respondents to the household and
child questionnaires. The nutritional status of mothers or primary child caregivers aged 15-49 years was
also assessed.
2.2 Type of Survey
This Anthropometric and Retrospective Mortality survey utilized the Standardized Monitoring and
Assessment of Relief and Transitions (SMART) methodology and was also in accordance with both the
National Guidelines for Nutrition and Mortality assessments in Kenya and the recommended UNICEF
key nutritional survey indicators. Both anthropometric and mortality data were collected simultaneously
in all households visited during the survey (where applicable, data was also collected for IYCF practices
information for eligible children aged below 24 months). Qualitative data (focus group discussions
(FGDs), key informant interviews and general observations) were also collected to complement the
quantitative findings.
2.3 Sampling Methodology and Sample Size
A two-stage cluster sampling methodology with probability proportional to size (PPS) design was
employed for this integrated nutritional survey. Three different sampling methodologies were employed.
The Emergency Nutrition Assessment (ENA) for Standardised Monitoring and assessment of Relief and
Transition (SMART) was used to calculate both the anthropometric and mortality samples while the
IYCF Multi Survey Sampling Calculator was used to calculate the IYCF sample.
In the first sampling stage of determining sample size, a GAM prevalence of 13.3% based of upper CI
of the last SMARt survey (8.4-13.3 CI)10, desired precision of 4%, a design effect of 2, estimated
household size of 6 persons and non-response rate of 3% gave a sample size of 603 children (6-59
months) and a household sample of 719 households for the anthropometric survey. The sample size for
mortality survey was based on most recent SMART survey conducted in Tana River with 0.36
deaths/10,000/day (0.22-0.58 CI), a desired precision of 0.3, design effect of 2, household size of 6 with
a recall period of 90 days and non-response rate of 5% which resulted in a total poulation of 3717
people and 652 households. The IYCF multi survey sampling calculator was used to obtain sample size
for Infants and young children (0-23 months) using timely initiation of breastfeeding (children 0-23
months), exclusive breastfeeding for children below 6 months, timely complementary feeding and
minimum dietary diversity. Using information obtained from the survey conducted in Tana River in
December 2010, the sample size for children between 0-23 months was 406. To obtain the sample size
to be used for children aged 0-6 months, 20% of 406 was calculated which gave a figure of 81. The
number of households to cover during the IYCF survey was given by dividing 81 by 1.5 (average
number of children under 59 months in a household) which gave 54 households. The grand total
number of households surveyed were therefore the 719 given by ENA software plus the extra 54
calculated for IYCN sample totalling to 773. The anthropometric sample being higher than the mortality
sample, therefore, was also in the mortality survey. The total number of households to be reached per
day (19) gave a total of 41 clusters to be surveyed. A total of 6 survey teams, each comprising of 1
team leader and 3 enumerators collected data for 7 days, with one extra day set for contigencies.
The second sampling stage comprised of village and household selection. In order to select survey
clusters, the names of villages/sub-locations, their respective population sizes and the required number
of clusters were entered into the SMART software, which generated the actual list of the villages to
10
International Medical Corps (December 2010): Tana River SMART Nutrition Survey
11
survey (including reserve clusters). At the field level, improved EPI method was employed to select the
first household to be enumerated. The survey teams first reported to the area chief, assistant chief or a
village elder who assigned them a local guide. With the assistance of the local guide, the teams then
went to the approximate centre of the village and span a pen to select a random direction to walk to the
boundary of the village. While at the boundary of the village, the teams span the pen again to select a
second direction. The first household to be visited was randomly selected by drawing a random number
list between one and the number of households counted when walking to the periphery of the village.
The subsequent households were selected by proximity, always selecting households to the right. In
villages with more than one cluster, the village was subdivided and the centre of each subdivision
determined and households selected as described above. All children aged 6-59 in every household
visited were included in the anthropometric survey and any 0-23 month child enumerated for IYCF
practices according to SMART Survey Guidelines11. A household was defined as a group of people
who lived together and shared a common cooking pot. In polygamous families with several structures
within the same compound but with different wives having their own cooking pots, the structures were
considered as separate households and assessed separately. In cases where there was no eligible
child, a household was still considered part of the sample, where only household and mortality data
were collected. If a respondent was absent during the time of household visit, the teams left a message
and re-visited later to collect data for the missing person, with no substitution of households allowed.
The teams visited the nearest adjacent village (not among those sampled) to make up for the required
number of households if the selected village yielded a number less than 19 households, following the
methodology described above.
2.4 Data collection Tools and Variables Measured
A total of 6 survey teams, each comprising of 1 team leader and 3 enumerators collected the data. Five
sets of questionnaires were used for data collection. These included four sets of structured
questionnaires (household, 6-59 months old child and maternal/primary child caregiver, 0-<6 months
child and mortality questionnaires) and a focus group discussion (FGD) guide to collect qualitative data.
2.4.1 The household questionnaire
This was used to elicit general household information (demographic data, household water sources and
consumption, household food consumption, maternal health care information, maternal dietary
diversity, sanitation, food aid, food insecurity mitigation strategies, possession and utilization of
insecticide-treated mosquito nets, livestock condition and household socio-economic status indicators.
2.4.2 Child (6-59 months old) and maternal questionnaire
Using this questionnaire, the following data were collected:
Child age: the age of the child was recorded based on a combination of child health cards, baptism
cards, the mothers’/caretakers’ knowledge of the birth date and use of a calendar of events for the
County developed in collaboration with the survey team.
Child Sex: it was recorded whether a child was male or female.
Bilateral oedema: normal thumb pressure was applied on the top part of both feet for 3 seconds. If
pitting occurred on both feet upon release of the fingers, nutritional oedema was indicated.
Child weight: the weights of children were taken in the nude (or with minimal light clothing on) using
UNICEF Salter Scales with a threshold of 25kgs and recorded to the nearest 0.1kg.
Child length/height: children were measured bareheaded and barefooted using wooden UNICEF
height boards with a precision of 0.1cm. Children under the age of two years were measured while lying
down (length) and those over two years while standing upright (height). If child age could not be
11
SMART (2006): Measuring Mortality, Nutritional Status and Food Security in Crises Situations: SMART METHODOLOGY
12
accurately determined, proxy heights were used to determine cases where height would be taken in a
supine position (between 65cm-<85cm) or in an upright position (heights greater ≥85cm).
Child and maternal MUAC: the MUAC of children and child caregivers were taken using child and
adult tapes, respectively, and recorded to the nearest 0.1cm.
Morbidity: a 2-week morbidity recall was conducted for all index children (6-59 months) to assess the
prevalence of common diseases (e.g. malaria, acute respiratory infections (ARI), diarrhoea, measles,
stomach-ache, eye and skin infections).
Child feeding: information on breastfeeding, weaning and child feeding were collected. Dietary
diversity information based on a 24-hour food intake recall was collected for the children to assess the
number of food groups taken the previous day.
Child immunization and Vitamin A supplementation: data on vitamin A supplementation,
deworming, and immunization for polio and measles were collected to estimate their coverage. The
coverage for measles immunization was only done for eligible children (≥ 9 months).
2.4.3 Under 6 months old child questionnaire This was used to collect infant and young child feeding
(IYCF) practices data in the households visited.
2.4.4 Mortality questionnaire
This elicited 3-month (90-day) retrospective recall information on whether there had been any deaths in
households and the probable causes of death through verbal autopsy.
2.4.5 IYCF questionnaire
This elicited information on infant and young child feeding practices.
2.4.6 Focus group discussion (FGD) guide
A FGD guide was used to collect qualitative data to complement quantitative data. A total of 12 FGDs
were implemented (seperately for women and men). The FGD clusters were selected from the targeted
villages in a manner that ensured adequate representation of socio-economic, ecological and livelihood
differentials among the clusters in Tana River County.
2.5 Training and Supervision
A consultant nutritionist recruited by International Medical Corps trained the survey team for five days
(13th to 17 February 2012) at the Laza leisure Lodge. The team had been selected by IMC in
collaboration with MoPHS on the basis of previous survey experience, education and knowledge of
local languages of the communities surveyed. Training included survey team standardization and a pretest of the survey tools and procedures which was conducted in Kibuyu village on 17th February after
which the entire team met to review and share experiences before teams were dispatched to their
respective clusters to embark on the definitive survey, which took place from 18th to 24th February 2012.
During data collection and entry, the teams were supervised by the consultant, International Medical
Corps nutritionists and Tana River County districts’ nutritionists. The following topics were covered
during training:
 survey objectives, types and causes of malnutrition
 SMART survey and sampling methodologies
 verbal interpretation of the questions into the local languages during training for uniform
contextual understanding by all the teams
 household, child and mortality questionnaire interviewing techniques
 anthropometric measurement procedures
 practical on conducting interviews and anthropometric measurements
 conduction of mock (simulated) interviews
 duties and responsibilities
 survey ethics
 community entry behaviour
 survey logistics
13
2.6 Data Entry and Analysis
Anthropometric and mortality data entry and processing was done using the SMART/ENA software
where the World Health Organization Growth Standards (WHO-GS) data cleaning and flagging
procedures were used to identify outliers which enabled data cleaning as well as exclusion of
discordant measurements from anthropometric analysis. The SMART/ENA software generated weightfor-height, height-for-age and weight-for-age Z scores to classify the underfives into various nutritional
status categories using WHO12 standards and cut-off points and exported back to SPSS for further
analysis. All the other quantitative data were entered and analysed in the SPSS (Version 17.0)
computer package.
2.7 Nutritional Status Cut-off Points
The following nutritional indices and cut-off points were used in this survey:
2.7.1 Weight-for-height (WFH) and MUAC – Wasting among Children
The prevalence of wasting (a reflection of the current health/nutritional status of an individual) are
presented as global acute malnutrition (GAM) and severe acute malnutrition (SAM) using weight-forheight (WFH) z-scores, WFH percentage of median and MUAC indices. The results on wasting are
presented as global acute malnutrition (GAM) and severe acute malnutrition (SAM):
 Children whose WFH z-scores fell below -2 standard deviations from the median of the WHO
standards (WHO-GS) or had bilateral oedema were classified as wasted (to reflect GAM)
 A cut-off point of <12.5cm MUAC was used to denote GAM among the underfives.
2.7.2 Weight-for-age (WFA) – Underweight
The measure of underweight gives a mixed reflection of both the current and past nutritional experience
by a population and is a very useful tool in growth monitoring.
 Children whose WFA z-scores fell below -2 standard deviations from the median of the WHOGS or had bilateral oedema were classified as underweight
 Children whose WFA z-scores fell below -3 standard deviations from the median of the WHOGS or had bilateral oedema were classified as severely underweight.
2.7.3 Height-for-age (HFA) – Stunting
Height-for-age is a measure of linear growth and therefore an unequivocal reflection of the cumulative
effects of past nutritional inadequacy and/or illness episodes.
 Children whose HFA z-scores fell below -2 standard deviations from the median of the WHOGS were classified as stunted (to reflect Global Stunting)
 Children whose HFA z-scores fell below -3 standard deviations from the median of the WHOGS were classified as severely stunted.
2.7.4 Maternal MUAC
The following cut-off points for MUAC (Table2) were used to classify pregnant and non-pregnant
mothers into various nutritional status categories according to SPHERE standards13.
Table 1: Maternal MUAC cut-off points
Nutritional status
Normal
GAM
Severe wasting
Pregnant
≥ 23.0cm
< 23.0cm
< 20.7cm
Non-pregnant
≥ 21.0cm
< 21.0cm
< 18.5cm
2.8 Data Quality control
Data quality was ensured through:
 thorough training of team members for four days
 the majority of the enumerators and team leaders had prior experience in carrying out nutrition
surveys
12
13
WHO (2005): Anthro 2005 Version 2.02 Standards
The SPHERE Project Handbook (2004). Humanitarian Charter and Minimum Standards in Disaster Response.
14











standardization of interviewing procedures through verbal translation of questions by survey
team members into the local languages spoken in the County during training
standardization of anthropometric measurement procedures
practical sessions on interviewing and anthropometric measurements taking during survey team
standardization
daily supervision of the teams by their team leaders, the consultant, IMC nutritionists and Tana
River County districts’ nutritionists
review of questionnaires on a daily basis for completeness and consistency
on-the-spot correction/feedback of any mistakes noted during data collection to avoid mistake
carry-overs
review of questionnaires by teams before leaving the household to ensure questionnaire
completeness and consistency
frequencies for all variables were first run and the data cleaned by cross-checking any aberrant
values observed on the respective questionnaire before analysis
triangulation and validation of quantitative data using qualitative information
entry of anthropometric data in the SMART/ENA software which enabled on-the-spot
identification, cross-checking and correction of any aberrant values
use of ENA for SMART random table software to generate the actual list of villages (clusters) to
cover after selection of sub-locations.
15
3.0 RESULTS AND DISCUSSIONS
3.1 General Characteristics of Study Population and Households
The 779 households assessed in this survey yielded a total of 4746 persons out of which 1020 (21.5%)
were children below five years, whose mean number was 1.3 (SD 0.8) per household. The mean
household size was 6.1 (SD 2.5) persons. As expected a majority (89.3%) of the households in Tana
River County were male-headed with only 6.9% being female headed. One quarter (25.4%) of the
households comprised of polygamous families, out of which there were 2 wives in 81.3%, 3 wives in
15% and 4 wives in 3.6% of the households. The anthropometric survey sample comprised of 863
children (6-59 months) comprising of 449 (52.0%) males and 414 (48.0%) females with an overall sex
ratio of 1.1, which demonstrates an unbiased survey sample (Table 2).
Table 2: Age and sex distribution of sample children
Males
Age in months
n
%
Females
Total
n
%
n
Sex
ratio
M/F
%
6-17
99
50.5
97
49.5
196
22.7
1.0
18-29
119
52.0
110
48.0
229
26.5
1.1
30-41
110
53.7
95
46.3
205
23.8
1.2
42-53
91
52.6
82
47.4
173
20.0
1.1
54-59
30
50.0
30
50.0
60
7.0
1.0
Total
449
52.0
414
48.0
863
100.0
1.1
3.2 Nutritional Status of Children 6-59 Months
The World Health Organization’s Growth Standards (WHO-GS) z-scores are used in nutritional status
assessment14 using the Emergency Nutrition Assessment (ENA) for Standardized Monitoring and
Assessment of Relief and Transitions (SMART) software in this report. Acute malnutrition is also
reported using the Mid-upper Arm Circumference (MUAC) index, which is usually used as a rapid
estimation of acute malnutrition in emergencies. The national Centre for Health Statistics (NCHS)
references are used to report prevalence of acute malnutrition by percentage of the median (which the
SMART software does not generate).
Prevalence of Global Acute Malnutrition (GAM) by WFH Z-scores (WHO-GS)
The weight-for-height (WFH) index reflects the current nutritional status of the community, therefore, is
an indicator of acute malnutrition. According to WHO-GS flagging procedures, 9 (1.0%) of the children
were excluded from analysis due to aberrant values. The prevalence of global acute malnutrition i.e.
GAM (WFH z-scores < -2 standard deviations from the median of the WHO-GS reference population or
having oedema) of 13.5% (11.3-15.9 CI) was beyond acceptable limits according to WHO15
benchmarks. The level of severe acute malnutriton (SAM) i.e. z-scores < -3 or oedema was likewise
relatively high at 3.1% (2.3-4.2 CI). The current levels of GAM and SAM are higher (though not
significantly) than those (10.6% 8.4-13.3 CI and 2.1% 1.2-3.7 CI, respectively) shown by the last
SMART survey in the county of December 2010. Although the prevalences of both GAM and SAM were
higher among boys than girls, the differences were, however, not statistically significant as indicated by
overlapping confidence intervals (Table 3). An analysis of acute malnutrition by oedema reveals 24
(2.8%) cases of marasmus and 3 (0.3%) of kwashiorkor in the sample, which suggests inadequacy of
all nutrients was largely culpable for child malnutrition in the county.
3.2.1
WHO Muliticentre Growth Reference Study Group. WHO Child Growth Standards based on length/height, weight and age. Acta Paediat
2006; (Suppl 450): 76-85.
15
WHO (1995): Management of Nutrition in Major Emergencies.
14
16
Table 3: Prevalence of acute malnutrition by weight-for-height z-scores (WHO-GS)
Global acute malnutrition (GAM)
Males (n=449)
Females (n= 413)
Total (N= 862)
n
95% CI
n
95% CI
n
95% CI
71
15.8
45
10.9
116
13.5
W/H <-2 Z scores or oedema
Severe acute malnutrition (SAM)
[12.7-19.5]
17
W/H <-3 Z scores or oedema
3.8
[8.6-13.7]
10
[2.6-5.5]
2.4
[11.3-15.9]
27
[1.2-4.9]
3.1
[2.3-4.2]
Overall, the prevalence of GAM by child age (Figure 1) indicates a general increase with child age, with
the highest prevalence being among children of age group 54-59 months (25.0%). This may partly be
attributable to cessation of breastfeeding and expected consequent decline in the quality of child
feeding and care practices among relatively older children.
Figure 1: Overall prevalence of GAM by child age
25
25
20
15.6
15
13.5
11.3
12.2
11.7
10
5
0
6-17
18-29
30-41
42-53
(N=195) (N=229) (N=205) (N=173)
54-59
(N=60)
Total
(N=862)
Both the male and female sample children’s weight-for-height distribution curves shift to the left of the
WHO-GS reference, with a mean Z-score of -0.8 (SD1.2), implying an overall worse-off nutritional
situation for the sampled underfives (Figure 2).
Figure 2: Distribution of W/H Z-scores for sampled children
Analysis of the findings by district shows that the prevalence of GAM was highest in Tana North district
(16.3% 12.6-20.8 CI) followed by Tana Delta (10.1% 7.1-14.1 CI) and lowest in Tana River (8.8% 5.513.8 CI). The prevalence of GAM in Tana North district was significantly (P<0.05) higher than in the
17
other two districts of the county. Tana North district is a predominantly pastoral-livelihood zone and
relatively drier and more food insecure compared to Tana and Delta districts.
Prevalence of Acute Malnutrition by MUAC
MUAC findings (Table 4) indicate a lower overall GAM prevalence (5.6% 4.2-7.3 CI) compared to
13.5% by WFH z-scores. Though still useful for both SFP and OTP field case-finding, MUAC is not a
very sensitive indicator of acute malnutrition. The findings further indicate that close to one fifth (19.8%
17.3-22.6 CI) of the children were at risk of malnutrition.
3.2.2
Table 4: Child nutritional status based on MUAC
Criteria
Interpretation
n
% and CIs
MUAC < 11.5cm
SAM
12
1.4 [0.0-2.4]
11.5- <12.5cm
Moderate malnutrition
36
4.2 [3.0-5.7]
Total malnourished (<12.5cm)
GAM
48
5.6 [4.2-7.3]
12.5- <13.5cm
At risk of malnutrition
171
19.8 [17.3-22.6]
>13.5cm
Normal
644
74.6 [71.6-77.4]
Total
863
The prevalence of GAM by MUAC and child age (Figure 3) indicates that the highest prevalence of
GAM was among children in the 6-17 months age group (13.2% (9.2-18.7 CI). This is because MUAC
tends to overestimate GAM among young children, particularly those below one year.
Figure 3: Wasting by MUAC and child age
14
12
10
8
6
4
2
0
13.2
5.6
5
2.9
1.7
0
6-17
18-29
30-41
42-53
54-59
Total
(N=196) (N=229) (N=205) (N=173) (N=60) (N=863)
Prevalence of Underweight by Weight-for-age Z-scores (WHO-GS)
The weight-for-age (WFA) index is a composite measure of wasting and stunting since it reflects deficits
in both skeletal and soft body tissue masses. It is commonly used to monitor the growth of individual
children in the community since it enables mothers to easily visualise the trend of their children’s
increase in weight against age along the ‘Road to Health’ growth curves. This enables them to make
and take requisite actions even with minimal advice from healthcare providers. A low WFA is referred to
as underweight while a high WFA refers to overweight. The prevalence of underweight among the
children was 27.2% (23.3-31.5 CI) while 7.0% (4.8-10.1 CI) of the children were severely underweight.
There was no significant difference in the prevalence of underweight among boys and girls as shown by
overlapping confidence intervals. The prevalence of global underweight is above both the average for
Coast province (23.5%) national average of 16.1% according to KDHS of 2008-09.
3.2.3
18
Table 5: Prevalence of underweight by weight-for-age z-scores (WHO-GS)
Global acute malnutrition (GAM)
Males (n= 448)
Females (n= 411)
Total (N= 859)
n
95% CI
n
95% CI
n
95% CI
132
29.5
102
24.8
234
27.2
W/A <-2 Z scores or oedema
Severe acute malnutrition (SAM)
[25.4-33.8]
33
W/A <-3 Z scores or oedema
7.4
[19.2-31.4]
27
6.6
[4.4-12.2]
[23.3-31.5]
60
[4.5-9.5]
7.0
[4.8-10.1]
Prevalence of Stunting by Height-for-Age (HFA) Z-scores (WHO-GS)
The height-for-age (HFA) index is a measure of long-standing (chronic) malnutrition. It measures linear
growth and is therefore reflective of the cumulative effects of long-standing nutritional inadequacy
and/or recurrent chronic illness episodes. Unlike wasting, it is not affected by seasonality but is rather
related to the long-term effects of socio-economic development and long-standing food insecurity
situation. A low height-for-age reflects deficits in linear growth and is referred to as stunting. The
findings indicate that the global chronic malnutrition (GCM) rate in the county of 33.4% (24.8-43.2 CI)
was below both the average for Coast province (39.0%) as well as the national average of 35.3%16.
Severe chronic stunting level stood at 10.5% (6.4-16.7 CI).
3.2.4
Table 6: Prevalence of stunting by height-for-age z-scores (WHO-GS)
Global acute malnutrition (GCM)
Males (n=448)
Females (n=412)
Total (N= 860)
n
% CI
n
% CI
n
% CI
153
34.2
134
32.5
287
33.4
W/H <-2 Z scores or oedema
Severe acute malnutrition (SCM)
[25.6-43.8]
44
W/H <-3 Z scores or oedema
9.8
[5.7-16.4]
[23.2-43.5]
46
11.2
[6.7-18.0]
[24.8-43.2]
90
10.5
[6.4-16.7]
3.3 Adult Nutritional Status by MUAC
The nutritional status of pregnant mothers in many areas of Kenya (including Tana River) has
consistently been significantly worse than that of their non-pregnant counterparts. Pregnancy imposes
a big nutrient-need load on mothers, which in the absence of adequate extra nutrients leads to
utilization of body nutrient reserves giving rise to gestational malnutrition, which affects both the mother
and her foetus and ultimately impacts negatively on the health of the mother and that of the child even
later in life. The MUAC measurements of 606 eligible women (15-49 years) were taken to assess their
nutritional status. As shown in Table 7, significantly more pregnant women than the non-pregnant
suffered from chronic energy deficiency (P<0.01). Among the pregnant, the prevalence of CED was
34.7% (24.7-46.2 CI) while 4.9% (3.3-7.0 CI) non-pregnant women suffered from CED. The prevalence
of severe CED among pregnant women was 6.9% (3.0-15.2 CI) and that among non-pregnant women
stood at 0.4% 0.0-1.3 CI. Overall, 8.4% (6.4-10.9 CI) of the women were malnourished.
16
GOK 2009: Kenya Demographic and Health Survey Report
19
Table 7: Adult nutritional status by MUAC
Wasting by MUAC
Severe
<20.7cm pregnant
<18.5cm non-pregnant
Moderate
<23.0cm pregnant
<21.0cm non-pregnant
Total wasted
n
5
Physiological status
Pregnant
Non-pregnant
(n=72)
(n=534)
95% CI
n
95% CI
6.9*
2
0.4
[3.0-15.2]
[0.0-1.3]
Total (N=606)
n
95% CI
7
1.2
[0.0-2.3]
20
27.8
[18.7-39.0]
24
4.5
[3.0-6.6]
44
7.2
[5.4-9.6]
25
34.7*
[24.7-46.2]
*P<0.01
26
4.9
[3.3-7.0]
51
8.4
[6.4-10.9]
3.4 Child Feeding, Care and Health
The 24-hour approach is widely used and is appropriate in surveys of dietary intake when the objective
is to describe infant feeding practices and care in populations17. Infant and young child feeding (IYCF)
practices was assessed for children below 24 months. The IYCFP sample of 409 children was obtained
using the IYCF multi survey sampling calculator and comprised of 222 (54.3%) males and 187 (45.7%)
females.
Infant and Young Child Feeding Practices
After birth, 98.3% of the children were reported to have been breastfed at some point in their lives.
Infants should be breastfed within 1 hour after birth according to World Health Organization (WHO).
Among other benefits, it stimulates the onset and maintenance of lactation as well as provision of
necessary maternal antigens to the infant. As shown in Figure 4, the proportion of infants put on the
breast within the first hour of birth was two thirds (66.4%), with 30.4% children having been given prelacteals consisting of mainly sugar/glucose water for 15.6%, animal products for 9.2% and plain water
for 5.5% of the children in the first 3 days of birth. More than four fifths (87.4%) of the children were
given colostrum, which offers maternal immunity to infants after birth. Information from FGDs reveals
that the practice of giving prelacteals is mainly hinged on the belief that it is necessary to ‘cleanse the
digestive system of the child so that the child can excrete initial green stool in order to be able to feed
properly’ and also ‘lack of enough breast milk especially in the first few days’. This calls for more
concerted efforts to improve maternal knowledge on optimal infant feeding and care practices.
Exclusive breastfeeding among eligible children (below 6 months) regardless of whether they had
received prelacteals or not was slightly more than two thirds (67.1%) compared to the national average
of only 31.9%. Among the non-exclusively breastfed children, more than half (52.0%) of them had been
weaned by their second month of birth. Early weaning increases the risk of infections among young
infants and the feeds given are nutritionally inferior to breast milk, which ultimately results in
malnutrition. Breast feeding alone, at the right frequency, is adequate for infants below 6 months in
addition to being protective against infections, which may occur as a result of unhygienic practices
during food preparation, infant feeding and feed storage. The mean frequency of breast feeding among
the exclusively breastfed infants was 9.33 (SD 3.9) times compared to WHO recommendation of at
least 12 times daily. Results show that only one fifth (20.0%) of the infants were breastfed 12 or more
times according to the findings of a 24-hour breastfeeding recall. Maintenance of breastfeeding
dropped by more than half from 92.9% at one year to 42.9% at two years.
3.4.1
Engebresten SMI, Wamani H, Karamangi C, Semiyanga N, Tumwine J, Tylleskar T (2007): Low Adherence to Exclusive Breastfeeding
in Eastern Uganda: A Community-based Cross-sectional Study Comparing Dietary Recall since Birth with 24-hour Recall. BMC
Paediatrics 2007; 7 (10): 1-12.
17
20
100
Figure 4: Breastfeeding practices
98.3
92.9
66.4
67.1
80
42.9
60
40
20
0
After 6 months, children should be put on other foods to give additional nutrients that breast milk alone
cannot provide. These foods are refered to as complementary foods, with the process of giving them in
addition to breast milk known as weaning. Complementary feeding rate stood at 95.7% implying that
late weaning was practised for 4.3% of the children. Overall, results show that only about two thirds
(65.7%) of the eligible children (6-23 months old) received minimum optimal complementary feeding as
reflected by the previous day’s feeding frequency. A qualitative analysis of the diet taken by the children
was carried out to establish dietary diversity. The findings are reflective of poorly profiled diets since
only 43.6% of the children took meals meeting the minimum optimal dietary diversification on the basis
of their breastfeeding status18.
An analysis of the actual food groups taken by the children (Figure 5) indicates that less one-fifths
(43.6%) of the children took meats and poultry, vitamin A-rich plant foods, other fruits and vegetables
and eggs (despite the fact that many chicken are reared in the county). Overall, the findings are
suggestive of inadequate dietary micronutrient intake by the children.
Figure 5: Food groups taken by children in the previous 24 hours
Eggs
2.8
Other fruits & vegetables
11.1
Vit A rich plant foods
12.6
17.2
Meats & poultry
25.5
Legumes
36.9
Fats and oils
67.4
Dairy products
0
20
40
60
80
Child Immunization, Vitamin A Supplementation and Deworming
Child immunization prevents and/or reduces the severity of certain diseases in young children. The
immunization coverage rates (Figure 5) for polio (91.7%) and measles (89.5%) were commendably high
and above the Kenya Expanded Programme on Immunization (KEPI) and WHO recommendation of
3.4.2
Guidelines for measuring household and individual dietary diversity. Version 2, June 2007. Prepared by FAO Nutrition and Consumer
Protection Division with the support from EC/FAO Food Security Information for Action Programme and the Food and Nutrition Technical
Assistance (FANTA) Project. Rome, Italy
18
21
80% coverage. The polio immunization indicated a 4.6% dropout rate. Vitamin A supplementation is
carried out routinely in the county and is also part of routine systemic disease treatment in all health
facilities in Kenya for underfives. In the previous one year period prior to this survey, more than three
quarters (77.8%) of the underfives were reported to have received vitamin A supplementation at least
once. A 6-month recall for deworming among the children indicated a coverage rate of 51.5%, which fell
below the KEPI and WHO recommendation. Deworming prevents the debilitating effect of helminthic
infections among growing children.
Figure 6: Immunization, vitamin A supplementation and deworming coverage
96.3
100
91.7
89.5
77.8
80
51.5
60
40
20
0
OPV1
(N=863)
OPV3
(N=863)
Measles
(N=820)
Vit A
(N=861)
Deworm
(N=536)
Child Morbidity
A 2-week child morbidity recall (inclusive of the day of survey) was assessed to establish the
prevalence of common illnesses among the children. The findings indicate a heavy morbidity load
among the children where more than two thirds (67.4%) were reported to have been sick in the
previous 2-week period. As shown in Figure 7, the most prevalent illness affecting the underfives was
acute respiratory infections suffered by 39.9% of the children followed by malaria (12.9%) and
diarrhoea (7.9%). Information obtained from the MOH (Tana River district hospital’s) Health Information
Systems, also confirmed these as the leading causes of child morbidity in the county. Morbidity
imposes high nutrient demand, increases nutrient wastage and lowers nutrient utilization, which
together with inadequate nutrient intake results in deteriorative synergy that leads to malnutrition.
3.4.3
Figure 7: Child morbidity
1.6
Stomachache (n=14)
2.1
Skiin infections (n=18)
7.9
Diarrhoea (n=68)
12.9
Malaria (n=111)
39.9
ARI (n=344)
0
10
20
30
40
The health-seeking behaviour by mothers of sick children was assessed by asking the respondents
what they did the last time their underfive child was sick. This was in order to gauge access to as well
as utilization of available health facilities and services in the county. The findings indicate that a majority
(70.9%) of childcare givers took their sick children to public facilities. Overall, 24.3% respondents
sought non-qualified assistance when their children fell sick, with the rest (75.7%) seeking qualified
22
assistance. Zinc supplememtation during diarrhoea is crucial and a component of the accelerated high
impact nutrition intervention (HINI) program in the county. A very low proportion (1.5%) of the children
who had diarrhoea in the 2-week period prior to the survey was reportedly given zinc tablets, which
according to verbatim information, was attributed to non-availability of zinc tablets in the health facilities
in the county. As shown in Figure 8, 36.8% of the children were given oralite/ORS while 26.5% received
home-made soups/porridge during the last diarrhoeal episode.
Figure 8: Management of diarrhoea
Oralite/
ORS
36.8
Home
soup/po
rridge
26.5
Others
22.1
Zinc +
Salt/sug
ORS
ar
8.8
Zinc solution
s
tablets
4.4
1.5
3.5 Access to Health Facilities and Maternal Health Care
According to SPHERE19 and WHO recommendations, health facilities should be within a 30-minute
travelling distance to households regardless of the means used. The amount of time spent outside the
home by mothers has a direct influence on both the quality and quantity of care that they are able to
give to their children, which influences child health, growth and development. It also influences
willingness and ability to access and utilize health-care services. On average, overall, it took the
inhabitants of Tana River County 1.6 (SD 2.1) hours to access their nearest health facility. Further
analysis of the findings on access to health facilities (Figure 9) shows that overall, only slightly more
than one quarter (26.9%) of the population in the county were within the recommended 30-minutes
distance to health facilities, 14.3% took 30 minutes-1 hour’s time while the rest (58.8%) took more than
1 hour to access the facilities.
Figure 9: Time taken to access health facilities
>1 hour
58.80%
<30 mins
26.9%
30mins 1hr
14.3%
Although more than four fifths (87.5%) of the mothers reported having attended ANC clinics during their
previous pregnancy, a paltry 23.4% reported giving birth under qualified medical supervision, eroding
many possible benefits that might have accrued from their ANC attendance. Supplementation with iron
during pregnancy is routinely carried out as a strategy of reducing the risk of anaemia, which is
common among pregnant women, particularly in food-insecure areas. Although a relatively high
proprtion (61.7%) of the mothers reported having received iron folate supplementation during their
19
The SPHERE Project Handbook (2004). Humanitarian Charter and Minimum Standards in Disaster Response
23
previous pregnancy, only 2.4% took the tablets for the recommended 90 or more days, subjecting a
high proportion of them to the risk of anaemia. Likewise, less than half (45.1%) of the mothers reported
having received vitamin A supplementation after delivery, which boosts body reserves depleted during
pregnancy and also improves its content in breast milk. The risk of iodine deficiency in the county was,
however, minimal as 98.8% of the households reported using iodized table salt.
3.6 Insecticide Treated Mosquito Nets (ITN) Holding Rates and Utilization
Insecticide treated mosquito nets (ITNs) are provided free of charge by the Ministry of Public Health
Services (MoPHS) to expectant mothers attending MCH clinics. The findings of this survey indicate that
up to two thirds (65.9%) of the households owned mosquito nets, with more than three quarters
(75.5%) of having obtained them from the MOH while others (16.5%) had obtained them from shops or
kiosks and the rest (8.0%) from NGOs (Figure 10). Use of mosquito nets is a cheap and easy-toimplement primary disease prevention strategy, considering the potential economic and health losses
that would accrue from an actual malarial attack, thus the need to furtehr sensitize community members
on the importance of ITN utilization in order to achieve universal holding and utilization rates in the
county.
Figure 10: Sources of ITNs
Shops/k
iosks
16.5%
NGOs
8.0%
MoPHS
75.5%
The nets obtained from hospitals and NGOs are treated with long-term insect-repelling chemicals while
the ones from shops or vendors may not be treated, which makes it necessary to wash them in
chemicals to repel mosquitoes and other insects. Among those having received from shops or kiosks,
32.5% had treated them with chemicals with equal proportions (20.0%) having done so within the
previous month’s period and more than 6 months previously while 28.0% had treated theirs within the
previous 1-6 months period. Close to one third (32.0%) could not remember when they had last treated
their nets. Data on utilization of the nets during the night preceding the survey reveals that a majority
(87.4%) of underfive children had slept under the nets, followed by non-pregnant women (83.1%),
pregnant women (74.5%) and children above 5 years (66.1%). This finding generally reflects a
commendably high ITN utilization rate; though there is need to improve for children above 5 years,
considering that the county is a malarial endemic area.
Figure 11: ITN utilization by among household members
Fathers
73.5%
Pregnan
t
women
74.5%
Children
> 5 yrs
66.1%
Underfiv
es
87.4%
Nonpregnan
t
mothers
83.1%
24
3.7 Water, Sanitation and Hygiene (WASH) Practices
This survey was conducted during the dry spell in February before the onset of long rains expected in
the month of March in the county. With no seasonal rivers flowing, the highest proportion of households
reported mainly sourcing their water for household use as well as for drinking from protected wells
(28.1% and 25.7%, respectively). Rivers (mainly Tana River) were the next main reported source of
water with 20.5% of the households sourcing water for general use and 23.6%) for drinking. This was
followed by boreholes accounting for 11.8% households obtaining water for general use and 0.7% for
drinking. About one-tenth of the households sourced their water for general household use and drinking
from taps and public pans (Table 8). There is need to sensitize the Tana River County on treatment of
drinking water through boiling, being a very easy, feasible and cheap method, as more than four fifths
(82.1%) of the households did not treat their unsafe drinking water as shown in Table 8.
Table 8: Sources of water and treatment of drinking water
For HHD use
For Drinking
(N=779)
(N=779)
Source of water
(%)
(%)
Protected well
28.1
25.7
River
20.5
23.6
Borehole
11.8
10.7
Tap
11.6
13.0
Public pan
10.7
11.8
Canal
5.1
4.6
Unprotected well
4.9
4.6
Digging along laga
3.0
2.7
Bowser
2.7
2.4
Others
1.6
0.9
Treatment of drinking water (N=779)
Doing nothing 81.1
Use of chemicals 16.4
Boiling 1.5
Others 1.0
On average, households took 33.8 (SD 53.2) minutes to access their main source of water and used
80.2 (SD 39.5) litres of water daily (which translates to approximately four 20-litre jerricans). The
proportion of households obtaining water within the SPHERE recommended time of 30 minutes was
only slightly more than half (56.8%).During the period of the survey, households bought water at an
average of Kshs 3.6 (SD 15.4) per 20-litre jerrican. The reported latrine access in the County stood at
one third (32.5%) out of which the main type was traditional pit latrines (80.8) followed by VIP (11.7%)
and flush type for 4.6% of the households sampled. A majority (95.5%) of those without toilets
reportedly used the bush to relieve themselves, a practice which is daunted with possibilities of drinking
water contaminition in light of the fact that a big majority of households reported not treating their
drinking water in any way despite obtaining it from unsafe sources prone to rain run-off contamination
with faecal matter. From observations made to assess if the compounds immediate to dwelling areas
were clean, evidence of child faecal matter was found in 14.8% around the immediate dwelling of the
houses, with close to three quarters (76.3%) of the general area around compounds, however, found
unclean. This makes it necessary to educate the community on the health implications of unhygienic
child faecal disposal.
Appropriate water, sanitation and hygiene (WASH) practices reduces the burden of diarrhoeal diseases
and thus improves nutritional status. Handwashing, though a simple procedure, is crucial in the
prevention of diarrhoeal diseases in the community. Handwashing practices were assessed by asking
respondents whether they wash their hands and on what occassions. The findings (Figure 12) show
that only one quarter (25.8%) of the respondents reported washing their hands with soap. The findings
show that the two occassions when the majority washed hands were before eating (89.2%) and after
25
visiting toilets (86.5%), with less than half (46.1%) doing so before food preparation and only about one
third (12.9%) after changing the baby. Handwashing was scored for the four occassions, which shows
that less than one tenth (8.1%) of the respondents washed their hands appropriately (during the 4
occassions). This calls for hygiene education to improve on handwashing before food preparartion and
after changing the baby, which is apparently not considered important by mothers in the Tana County.
100
80
60
40
20
0
Figure 12: Handwashing
89.2 86.5
47.3
46.1
25.8
12.9
8.1
3.8 Household Food Security Indicators
3.8.1 Sources of Income
Overall, the inhabitants of Tana River county (Figure 13) depended on four main sources of income
during the previous 3 months with wage labour reported by the highest proportion (32.2%) followed by
sale of livestock/products (20.7%), sale of charcoal/firewood (17.1%) and sale of crops (11.1%).
Increased dependance on wage labour is attributable to the on-going rehabilitation of irrigation
schemes and consequent increase in the volume of emerging developmental economic activities in the
county. The finding on income sources is also indicative of a community shifting from over-reliance on
pastoral activities and diversification of economic activities, which in the long run would lead to an
improvement of the nutritional situation in the county. However, charcoal burning/sale of firewood
without replanting of trees in many areas of the county has led to depletion of vegetation cover which in
the long term could lead to loss of livelihood in addition to the more serious problem of environmental
degradation.
Figure 13: Main sources of household income
4.2
1.9
2.6
4.9
5.3
Others
Business
Salaried employment
11.1
17.1
20.7
Sale of charcoal/firewood
32.2
Wage labour
0
10
20
30
40
Overall, the number of household persons who earned some income that directly benefited the
households was 1.2(SD 0.6) members per household. The household wealth indicators varied
depending on the means of livelihood each community depended on. Using local indicators obtained
from FGDs conducted in each livelihood zone, 47.2% of the households were classified poor, 49.1%
middle and only 3.7% as rich.
26
Food Aid
Slightly more than half (51.6%) of the households reporting having received general food aid (GFA) in
the previous 3 months, where two thirds (66.2%) of the recipient households had got it within the
previous month, 31.6% between 1-2 months and 2.3% more than 2 months previously. On average, as
shown in Table 9, the food item received in the largest quantity was bulgar wheat (21.3 (SD 27.4) kgs
followed by maize (17.0 SD 27.9) kgs, peas (4.4 SD 5.1) kgs. The food aid received lasted the recipient
households an average of 18.2 (SD 13.8) days.
3.8.2
Table 9: Quantities of food aid received by households
Type of food
Burgar wheat
Maize
Peas
CSB
Wheat
Vegetable oil
Quantity
received (kgs)
21.3
17.0
4.4
3.8
2.6
1.8
SD
27.4
27.9
5.1
4.4
9.0
1.6
More than half (56.5%) of the households interviewed had cultivated their land during the previous
planting season. The mean size of land cultivated was 1.4 (SD 1.3) acres where the main types of
staple food crops grown were maize, green grams and cowpeas. The findings show that the food crop
grown in the highest proportion of households in the county was maize (29.4%) followed by green
grams (13.3%) and cowpeas (10.9%). Observations made on food stores showed that maize was
stored by 21.1% households, green grams (6.9%) and 4.4% had some cowpeas in their food granaries
from the previous food harvest.
Household Dietary Diversity and Food Sources
A qualitative 24-hour food intake recall was conducted on primary childcare givers and used as a proxy
to household dietary diversity, since food intake by mothers is a good estimation of the variety of what
other members of the households took (excluding the underfives). The dietary diversity of mothers was
based on 12 food groups according to the UN’s FAO recommendation20. Unlike the case for underfives
where relatively low proportions had taken highly diversified diets, more than half (51.7%) of the
mothers had taken highly diversified diets (4 or more food groups). On the whole, analysis of variance
showed that the reported usual/normal frequency of taking meals (2.7 SD 0.5) by households was
significantly higher than the 2.52 (SD 0.7) times reported for the day prior to the survey (P<0.01),
indicating a relative food stress situation during the conduct of the survey.
3.8.3
An analysis of the food groups taken by mothers (Figure 14), however, indicates that most took foods
predominantly consisting of carbohydrates i.e. cereals (97.9%), sugars/commercial juices (66.0%),
pulses/legumes and milk and its products (56.8% each) and fats and oils (46.6%). Less than one fifth of
the respondents had taken fish/sea foods, vegetables, meats, roots/tubers, eggs and fruits. Overall, as
was the case for the underfives, the micronutrient profile of the foodstuffs taken by mothers was
generally poor with regard to provision of micronutrients (vitamins and minerals).
Guidelines for measuring household and individual dietary diversity. Version 2, June 2007. Prepared by FAO Nutrition and Consumer
Protection Division with the support from EC/FAO Food Security Information for Action Programme and the Food and Nutrition Technical
Assistance (FANTA) Project. Rome, Italy
20
27
Figure 14: Food groups taken by mothers
2.2
2.4
4.6
5.3
Eggs
Meats/poultry
13.9
17.6
17.8
Vegetables
46.6
Fats&oils
56.8
56.8
Pulses/legumes
66
97.9
Cereals
0
20
40
60
80
100
Food-secure rural households usually depend on a balanced mix of own food production with minimal
food purchases. As shown in Figure 15, the proportion of households relying food purchase as their
main source of food were more than thrice those relying on own production (19.5%) while 15.9% relied
on food aid. This together with high food prices in the market reported during FGDs indicates relative
food insecure situation in the county during the survey.
Figure 15: Main household food sources (24-hour recall)
Purchase
60.8
Others
1.8
Borrowed/
credit
2
Food Aid
15.9
Own
production
19.5
All household members reportedly took the meals prepared the previous day in more than four fifths
(88.4%) of the households, with the main reason given for eligible members who did not take all meals
at home being that they took meals elsewhere in 39.2% of the households, unsuitability of food
prepared in 34.2% and food prepared being not enough (26.3%).
Coping Strategies
An analysis of food stress coping strategies is a good proxy indicator of the severity of food insecurity in
the community. When asked if their households had experienced a food shortage in the previous 2
months, more than two thirds (67.1%) of the respondents replied in the affirmative. Focus group
discussants were asked about the food shortage coping strategies their communities had employed in
the previous 2 months and requested to classify them according to severity of food shortage when they
are usually practised in the community. As shown in Figure 16, begging for food practised by 42.6% of
the households that had experienced food shortage and sale of milking livestock (10.7%) were
classified as severe food-deficit strategies. Reduction of the number of times households took meals
practised by 48.0% of the households and reduction of meal size were rated mild food-stress coping
strategies, with the former also reflected by the reported significant reduction in the frequency of taking
meals by households. On the whole, therefore, the coping strategies are reflective of mild to severe
food stress experience during the preceding 2-month period in the county.
3.8.4
28
Figure 16: Household food stress coping mechanisms
10.7
19.1
20.8
25.6
28.7
33.5
42.6
48
Borrow food*
Buy food on credit*
Reduce meal size.**
Reduce no. of meals**
0
10
20
30
40
50
*Coping strategy practised under normal circumstances
**Coping Strategies practised during mild food shortage
***Coping strategies practised during severe food shortage
3.9 Mortality
Both the crude mortality rate (CMR) of 0.75 deaths/10,000/day and the underfive mortality rate (UFMR)
of 1.23 deaths/10,000/day did not reach the threshold for ‘Alert’ status (Table 10).
Table 10: Underfive and crude mortality rates
Mortality rate
(95% CI)
UFMR
1.23 deaths/10,000/day
(0.62-2.20) 95% CI
CMR
0.75 deaths/10,000/day
(0.53-1.06) 95% CI
3.10 Association between GAM and Important Public Heath Variables
The relationship between GAM rates among the underfives and selected important public health
variables was investigated to establish factors which posed significant risk to the underfive nutritional
status. The findings show that children from households with more than 6 members, without toilets, and
childcare givers above 30 years were significantly more wasted than their opposite counterparts
(P<0.05). Overall, though no significant relationships were established among other variables,the
findings generally show that children enjoyed relatively better nutritional status when most of the public
health indicators were favourable as shown in Table 11.
29
Table 11: Association between GAM and other variables
%
GAM
Variable
Do you wash your
hands?
Appropriate
handwash?
Dietary
diversity
Household
size
Caretaker
nutritional status
Toilet
availability
Household
Herd size
Mosquito net
Availabile?
Vitamin A
supplementation
Child
dewormed?
Caregiver
age
Food aid
received?
Child
Sick?
Livestock owned?
Cultivated
Land?
Mother
pregnant?
Status
Yes
No
yes
No
Low
High
<6 members
>6 members
Wasted
Not wasted
Yes
No
Increased
Decreased
Yes
No
Yes
No
Yes
No
<30 years
>30 years
Yes
No
Yes
No
Yes
No
Yes
No
Yes
No
11.3
15.0
10.3
12.4
13.5
10.6
9.6
13.8
19.5
11.7
9.1
13.8
12.7
13.6
11.2
13.9
12.7
10.6
12.7
11.8
9.9
15.9
11.8
12.8
13.7
9.3
12.5
11.8
10.4
14.6
10.1
12.4
Odds ratio
(OR)*
0.720
Correlation
Coefficient
(R)**
0.036
P value
(P)***
0.146
1.243
0.032
0.576
1.320
0.340
0.190
0.659
0.033
0.047***
1.838
0.042
0.132
0.624
0.032
0.034***
0.920
0.045
0.776
0.786
0.035
0.269
1.221
0.033
0.449
1.090
0.014
0.682
0.583
0.035
0.010***
0.907
0.034
0.641
1.552
0.032
0.065
1.069
0.034
0.759
0.679
0.035
0.044
0.798
0.032
0.540
* Odds ratio (OR) shows the risk that a child stands to be malnourished if GAM is present together with respective characteristic.
** R (correlation) shows positive or negative direction of association.
*** P value < 0.05 indicates a positive significant relationship
30
4.0 CONCLUSION AND RECOMMENDATIONS
4.1 Conclusions
This survey was conducted during the hunger-gap period that precedes the onset of long rains
expected during the month of March. Though both the underfive mortality rate (UFMR) and crude
mortality rate (CMR) were below the ‘Alert’ status, the prevalence of GAM of 13.5% (11.3-15.9 95% CI)
is beyond acceptable limits according to WHO benchmarks and rated ‘Risky’. Underfive children in TRD
county were faced with a high burden of morbidity mainly due to ARI and malaria. Zinc and vitamin A
supplementation and deworming coverage were below WHO recommendation of 80%. WASH practices
are still poor in the county as reflected by the facts that less than one third of the households had
access to toilets, less than one fifth of the households treated unsafe drinking water and appropriate
hand washing was practised by only about one tenth of the child caregivers. Though some indicators of
optimal infant and young child feeding (IYCF) practices were good (such as timely initiation of
breastfeeding, exclusive breastfeeding and maintenance of breastfeeding at 1 year), maintenance of
breastfeeding at 2 years was low at less than half of the sampled children, with FGDs indicating sociocultural and ignorance factors mainly culpable for non-compliance. Although complementary feeding
practices (frequency of meals) were optimal for up to one third of the children, qualitative analysis of the
diet indicated poor dietary profiles for eligible children (6-23 months), with more than half subsisting on
poorly diversified diets. The food security situation in the county was generally poor. Household food
consumption during the survey’s conduct indicated a significant reduction in daily meal frequency
relative to the usual frequency of taking meals, with only about half of the households taking highly
diversified diets. Sixty percent of the households relied on food purchase as their main food source in
the face of reported high market food prices and a number of main food stress coping strategies
practised applied to mild to serious food deficit periods. Focussed group discussions as well as
observations revealed a community readily embracing farming activities in the on-going irrigation
scheme rehabilitation.
4.2 Recommendations
The following recommendations are made:
1. There is need to improve on the following HINI components:
 Zinc supplementation during diarrhea;
 Vitamin A supplementation;
 Toilet access and use;
 Treatment of drinking water through boiling;
 Training of the community on appropriate hand washing;
 Medical supervision of mothers during child birth;
 Continued breastfeeding after 1 year;
 Constitution of balanced diets using locally available foodstuffs (with continued agricultural
diversification); and
 General primary health-promotive strategies e.g. use of ITNs
2. Stepping up of stop-gap measures (GFD and FFA) to cushion the community against current fooddeficit situation before onset of long rains, planting and harvest
3. Sustained rehabilitation of irrigation schemes with agricultural diversification, protection of scheme
areas against crop destruction by wild animals and improved marketing of food products to further
improve production in the County
4. Initiation of small-scale home-based irrigation projects (mainly kitchen gardens) in areas outside
main scheme e.g. through drip irrigation during dry seasons to help diversify diets to promote
optimal nutritional status in the community
5. Infrastructural improvement to improve access to markets and facilitate general development in all
areas of the County
31
Appendix 1: Calendar of
Events for County
Dry Spell
January
2011
2007
-New year
-Opening of schools
-Drought/migration of livestock to the
Delta Region
-Rift Valley Fever
-Floods
-Tribal clashes in Bura
Age
2008
Age
2009
Age
2010
Age
Age
-Very heavy downpour
-New year
-Postelection violence
- Opening of schools
- Opening of schools
-Drought/migration of
livestock to the Delta Region
49
-New year
-Opening of schools
- Opening of schools
-Drought/migration of livestock
to the Delta Region
37
-New year
-Opening of schools
- Opening of schools
-Drought/migration of livestock to the
Delta Region
25
13
-Orma and Wardei tensions
February
-Rift Valley Fever
Eligible child for 6-59 Qnn MUST have been
born AFTER 18th March 2007
59
48
36
24
47
35
-Minor solar eclipse
-Voter registration
34
-Easter
-Formation of Tana North district
23
April
Long rains
-Revival of Hola Scheme
March
-Easter
58
-Easter
46
-Easter
22
12
-3rd March clashes between Orma
and Wardei
-Population migrations due to
tension
-Govt deployment RDU to deal with
tensions
-Severe drought starts
11
10
-Severe drought persists
May
-Opening of schools
57
-Opening of schools
56
-Cold season
-Madaraka Day
June
44
-Cold season
- Madaraka Day
Eligible child for 6-59 Qnn MUST have been
born BEFORE 18th August 2011
August
Dry / Cold Spell
55
July
September
December
Short rains
October
November
-Cold season
-Cold season
-Madaraka Day
-Drying of Tana river in T.Delta
-Circumcisions in South
-School Holiday
-Opening of schools
-Iddul Fitr
-Opening of schools
42
41
33
32
31
-Cold season
-Census
-Ramadhan
-Hola Bus accident
-Circumcisions in South
-School Holiday
54
53
-Opening of schools
43
-Cold season
-Circumcisions in South
-School Holiday
-Opening of schools
45
30
29
-Kenyatta Day
52
-Kenyatta Day
40
-Kenyatta Day
28
-Formation Tana Delta Distr
51
-Obama elections
39
-Idul Hajj
-Flooding in Tana Delta
27
50
-Peace meeting in Bura –
Christmas
38
-Elections
-Electricity supply in Hola
-Christmas
-SA World Cup
-Opening of schools
-Drought in Tana North
-Cold season
-Madaraka Day
-Arrest of Somali Refugees at
Abakik
-Cold season
-Somali/Kamba Peace pact
-Kora KWS security operation
-Katiba Yes/No election
-Ramadhan
-Circumcisions in South
-Red mobile call scare
-School Holiday
-Iddul Fitr
-Man shot with 50 bullets in Mitiboma
-Opening of schools
-Mashujaa Day
-Idul Hajj
-Short rains
26
-Christmas
20
19
-Madaraka day
-Water trucking by Gvt following
widespread water shortage
-Many livestock deaths
8
-Cold season
-Water trucking by Gvt following
widespread water shortage
7
-Ramadhan
-Water trucking
-Circumcisions in South
6
18
-Desiltation of water pans
-Idul Fitr
5
17
16
-Rains start in mid-October
-Oral polio vaccine campaign
-Mashujaa Day
4
-Rains continue
15
14
-Christmas
9
21
3
-Water pans filled to capacity
-2nd round oral polio campaigns (midDecember
-Christmas
2
Appendix 2: Survey Tools
Qnn A: Household Questionnaire Nutrition and Food Security Survey for Tana River County
Name of
District
Name of
Division
Division
No
Name of Village/
Sub-location
Cluster/Vill
No
Househo
ld No
Date of Interview
(dd/mm/yy)
Name of
Interviewer
Name of
Team Leader
Team
No
______/______/______
Note: This Questionnaire should be addressed to the Primary Childcare giver and must be filled in ALL the 19 households visited per cluster regardless of whether
they have children 6-59 months or not.
Household Demographic Information:
1. How many people live in this household together and share meals? (Household size) [ _____]
1b) How many of them are: Below 5 years [_____] Below 6 months [_____]
2. Who is the head of this household? [_____] (Codes: 1=Husband 2=Self (Mother) 3=My parent 4=Other (specify) ________________
3. Is your family monogamous or polygamous? [____] (Codes: 1=Monogamous 2=Polygamous 3=Single parent)
[If Monogamous SKIP to Q5]
4. If polygamous (i.e. Q3 =2), how many wives does your husband have? [_____]
5. Household Water Sources and Consumption
5.1 What is your current MAIN source of water
for general household use?
Codes:
1=River
2=Lake
3=Tap water
4=Borehole
5=protected well
6=Unprotected well
7=Public pan
8=Water bowser/tanker
9=Dam
10=Digging along the Laga
11=Rain water
12=Canal
13= Other(specify) _______
Main source
5.2 How long does it take
to go to the MAIN source
of water, fetch it and
come back (including
waiting time at the water
point) in minutes?
Minutes
5.3 On average,
how many
jerricans of water
does the
household use per
day?
5.4 How much
do you pay for
a 20 litre
jerrican of
water
currently?
[Enter in litres]
(enter zero if
water is free)
Litres
5.5 What is your Current main source of
DRINKING water?
5.6 Do you do anything
to the water before
drinking it?
Codes:
1=River
2=Lake
3=Tap water
4=Borehole
5=Protected well
6=Unprotected well
7=Public pan
8=Water
bowser
9=Dam
10= Laga
11=Rain water
12=Canal
13= Other
Specify______
Codes:
1=Nothing
2=Boiling
3= Add chemicals
4= Use traditional herbs
5=Filters/Sieves
6=Decant
Kshs
Household Food Consumption
7.
8.
9.
10.
Usually, how many times does your household take meals in a day? [_____]
How many times did the household take meals YESTERDAY? [_____]
Did all eligible members of your household (excluding those who are away from home or very young children) take all the meals prepared YESTERDAY? [_____] (Codes: 1=Yes 2=No)
(If NO), for what reason did some members who were present not take ALL meals? [_____] Codes: 1=Not enough food 2=Took meals elsewhere 3=Food prepared not suitable for them
10b. what btype of salt do you use? [_____] Codes: 1= Fine crystals 2= Coarse crystals
Maternal Health Care Information
11. During your last pregnancy, did you attend Ante-Natal Clinic (ANC)? [_____] Codes: 1=Yes 2= No 3= Mother never delivered [If Never delivered SKIP to Q 16d]
12. [IF YES], how many times did you attend the clinic? [_____] times
13. [IF NO], why did you not attend? [_____] Codes: 1=Not aware of existence/importance of ANC 2=Health facility too far 3=Unfriendly health workers 4=TBA services adequate
5= Cultural barriers e.g. staff too young, male staff etc 6=Other (Specify)_______________________________
14. Where did your last delivery take place? [_____] Codes: 1=At home by TBA 2=At home by Nurse 3=At home without assistance 4=Hospital 5=Other (specify) ______________________
15. [If at HOME], how long did it take before you took child to a clinic for the first time? [_____] Codes: 1=Within first 2 weeks 2= Between 2 weeks and 1 month 3=After 1 month
4= Child not taken/does not intend to take child to clinic
16. After your last delivery, did you receive vitamin A supplementation wthin the first 2 weeks? (Show mother Vitamin A Capsule) [_____] 1= Yes 2= No
16a) During your last pregnancy, did you receive dewormers (Mebedazole) [_____]1= Yes 2= No
16(b) During your last pregnancy, did you recieve iron/folate supplementation? [Show tablet samples] [_____] 1= Yes 2= No 3= DNK
16(c) [IF YES to Q16b], for how long did you take the iron/folate? [_____] (Convert and record in weeks)
Q16(d) How long does it take you to access the nearest health facility? [_____] minutes
17. Food consumption for mother or primary child giver: Since you (mother) woke up yesterday morning to the time you slept in the evening, what types of food and drinks did you take? First tick all the
food groups reported as having been consumed. Enter 1 for food groups reported as having been consumed and 0 for those not consumed. If a food group was consumed more than once, entre 1 only
once. [Do not read the list to the respondent]. [This question applies only to the caretaker and not any other household member]
Food group
17.1
17.2
17.3
17.4
17.5
17.6
17.7
17.8
17.9
17.10
17.11
17.12
Cereals and Cereal Products/starches
Fish and Sea Foods
Roots and Tubers
Vegetables
Fruits
Meats and Poultry
Eggs
Pulses / Legumes / Nuts and Seeds
Milk and Milk Products
Fats and Oils
Sugars / Honey and Commercial Juices
Miscellaneous/condiments
Examples
Maize, rice, pasta, ugali, porridge, bread, biscuits, millet, sorghum, wheat, green bananas [and any other locally available grains]
fresh or dried fish or shellfish
Irish potatoes, sweet potatoes, yams, cassava, or foods made from roots or wild roots and tubers
Sukuma wiki, cabbages, carrots, spinach, and any other locally available vegetables including wild vegetables
Oranges, ripe bananas, mangoes, avocados,
Camel, beef, lamb, goat, rabbit, wild game, chicken or other birds, liver, kidney, heart , matumbo, meat soup or blood-based foods
Chicken, bird eggs, crcodile eggs
Beans, peas, lentils, nuts, seeds or foods made from these, pojo, soya tea
Fresh/fermented milk, cheese, yogurt, or other milk products
Oil, fats, ghee, margarine or butter added to food or used for cooking, animal fat
Sugar in tea, honey, sweetened soda or sugary foods such as commercial juices, chocolates, sweets or candies
Spices, sweets, unsweetened beverages, black tea, black coffee
1=Yes
0=No
17.1
17.2
17.3
17.4
17.5
17.6
17.7
17.8
17.9
17.10
17.11
17.12
17b) What was the main source of food consumed in HHD yesterday? [_____] Codes: 1= Own production 2= Purchase 3= Gift from relatives 4= Food aid 5= Bartered 6= Borrowed/credit 7= Wild food 8= Other (Specify
18. Sanitation – Toilet facility
18.1. Does your
household have
access to a
toilet facility
that you use?
[If NO, Skip to 18.3]
1=Yes
2=No
18.2. (If yes), what type of
toilet facility do you have?
1=Bucket
2=Traditional pit latrines
3=Ventilated improved pit latrine
4=Flush toilet
5=Other Specify ____________
18.3. (If No), where do
you go/use? (probe
further)
1= Bush
2=Open field
3.=Near a water source
4.=Behind the house
5.=Other ( specify)_______
18.4 [OBSERVE] how
children’s faeces is
disposed
1= disposed of immediately
and hygienically
2= Not disposed
(scattered in the compound)
18.5 [OBSERVE]
Is the compound
clean?
1 = Yes
2 = No
18.6 Do you wash
your hands (probe
if saop is used)
18.7 [If Yes] on what occassions do you wash your hands?
(Multiple responses possible)
1 = Yes (with soap)
2= yes (without soap)
3 = No
18.71 After visiting toilet
[If No Skip to Q19]
18.73 After changing baby’s diapers/napies
Occassions
1= Yes
0 = No
18.72 Before preparing/handling food
18.74 Before eating
19. Food Security
19.1Have you received General Food Aid within the last three (3) months i.e. Since Mid-November last year? [______] Codes: 1= Yes 2= No [If NO skip to Q19.9b]
19.2 If Yes when? [_____] codes: 1= Less than 1 month ago 2= between 1 and 2 months 3= Over 2 months ago
19.3 [If YES] Please indicate the food commodities received in the last distribution and the quantities received.
FOOD AID COMMODITY
Quantity received Kgs
19.4 Maize
19.5 Vegetable oil (litres)
Litres
19.6 Peas
19.7 CSB (Corn soya blend)
19.8 Burger wheat
19.9 Wheat
19.9a) [If YES], How many days did the food aid received last the household? [______] Days
Q19.9b) During the last season, did you cultivate any land? [______] Codes: 1 = Yes 2 = No
Q19.9c) [If YES] what size of land did you cultivate?
[If NO skip to Q 20]
[_____] Acres
19.9d) Which food commodities did you cultivate (tick those mentioned). Has the food commodity been harvested and if so how has it been used? Do you have any of the mentioned foodstuff in
your food store currently? Fill the table below from respondent’s answers. (Indicate N/A for foodstuffs not grown)
Has the food
[If YES] has any been [If YES] has any
Is food commodity available in
commodity been
shared?
been sold?
the store currently?
Foodstuff
harvested?
1 = Yes
1 = Yes
1 = Yes
1 = Yes
2 = No
2 = No
2 = No
2 = No
Maize
1.
Green grams
2.
Cassava
3.
Beans
4.
Cowpeas
5.
20 COPING STRATEGIES
20.1 In the previous TWO months, (i.e. Since Mid-December) did your
household experience a food shortage? [_____] 1=Yes 2=No [If NO Skip to
Q21]
[If Yes] what did you do to mitigate/solve the food shortage? First tick all the
coping strategies mentioned. Do not read the list to the respondent
21.0 [IF YES], How
many times in a WEEK
(Frequency) did HHD
engage in the coping
strategies mentioned?
Enter Number of times
COPING STRATEGIES
21.
20.2
Reduction in the number of meals per day
20.3
Skip food consumption for an entire day
20.4
Reduction in size of meals
20.5
Restrict consumption of adults to allow more for children
20.6
Feed working members at expense of non-working
20.7
Swapped consumption to less preferred or cheaper foods
20.8
Borrow food from a friend or relative
20.9
Purchase food on credit
20.10 Consume wild foods (normal wild food) e.g Makoma
20.11 Consume toxic/taboo foods (acacia pod/bitter fruit) e.g. Mayonda
2012 Consume immature crop
20.13 Consumption of seed stock
20.14 Send children to eat elsewhere eg neighbours, school, religious centres
20.15 Withdraw child(ren) from school
20.16 Begging or engaging in degrading jobs or means
20.17 Individual migration out of the area
20.18 Household migration out of the area
20.19 Sale of farm implements
20.20 Sale of milking livestock
20.21 Sale of household goods
20.22 Disintegration of families
20.23 Abandonment of children or elderly
20.24 Sale of charcoal and/or fire wood
20.25 Part of family migrating with animals to look for grazing
20.26 Ask for food assistance from religious organizations
36
20.2
20.3
20.4
20.5
20.6
20.7
20.8
20.9
20.10
20.11
2012
20.13
20.14
20.15
20.16
20.17
20.18
20.19
20.20
20.21
20.22
20.23
20.24
20.25
20.26
21. Possession and Utilization of ITNs
21.1
21.2
Does this household
have a mosquito net or
nets?
[If YES], Where did you get it from?
Codes:
1 = A shop/vendors
2 = An agency/NGO
3 = MOH/Mission hospital
Codes:
1 = Yes
2 = No
[IF NO, GO TO Q 22] [If 2 or 3 Skip to Q 21.5]
21.3
21.4
[If from the shop] Have
you ever treated your
net (soaked or dipped
it in dawa or chemical
to repel mosquito or
insects)?
1 = Yes
2 = No
[If YES], When did you last treat it?
21.5
Who slept under the mosquito net last night? (Probe enter all responses mentioned)
1) Children less than 5 years
Enter code
1)
2)
3)
4)
[If NO, Skip to 21.5]
Less than one month ago
Between one and six months ago
More than six months ago
Cannot remember
2) Children over 5 years
3) Pregnant woman
4) Non-pregnant woman
5) Father
22. Livestock Situation
Livestock Size
22.0
22.1
22.2
Do you own any livestock?
Codes 1= Yes 2=No
Has the number of your livestock changed in the last three months (Since Mid-November last year)? Codes: 1=Increased
2=Reduced
3=Remained the same
If increased what was the MAIN reason? Codes:1= Animals gave birth 2= Bought 3= Given 4= Other (specify)---------------If decreased what was the MAIN reason? 1= Death because of drought 2= Death because diseases 3= Sold 4= Raid 5= Bride price 6= Slaughtered
23. Sources of Income
Main Source of Income
In the last three months [i.e. Since mid-November last year] what was the MAIN source of income for your household?
Codes:
1= Sale of livestock 2= Sale of livestock products 3= Sale of food ration 4= Sale of own crop 5= Wage labor 6= Salaried employment 7= Petty trade 8= Remittances
9= Sale of charcoal/firewood 10= Weaving/basketry 11= Business 12= Quarrying 13= Brewing 14= Tapping 15= Fishing 16=Other (Specify) ________________
24. Household Wealth Ranking
Household Wealth Ranking
24.1
According to your community’s wealth ranking system, how do other people classify your household? 1= Rich 2= Middle
3= Poor
24.2
How many people in your household earn some income that directly benefits the household? (Record number of
persons)
Increase
Reason:
Decrease
Reason:
Codes:
1=Yes
2= No
Qnn B: Tana River County Survey - Child Immunization, Anthropometric and Breast Feeding Data Form (Only for Children 6-59 months Old)
Name of District __________Name of division____________Division No_____Name of Sub-Location______________Sub-loc No_____Name of Village/Cluster___________ Cluster No______ Date of Interview____/____/_____ TL Name __________TeamNo___
Q1
Q2
HHD
No.
(Copy
from
main
HHD
Qnn for
ALL
children)
Child
serial
No
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
Q3
Child’s IntraHousehold ID
number and Name
Give youngest child in
the household ID no 1.
If more than one child,
record them
sequentially by age)
Child
IntraHHD**
ID No.
Child’s
Name
Q4a
Child’s Date
of Birth
(Use Clinic
Cards and
Calendar
of EVENTS)
Q4b
Enter
the
Age of
child in
months
(Use
Clinic
Cards
and
Calendar
of
EVENTS)
Q5
Q6
Child
age
Verification
1= Vaccination
card
2= Birth
certificate
3= Baptism
card
4= Recall
Child
Sex
1= M
2= F
Q7
Q8
Q9
Q10
How many
times has
(Name)
received vit
A capsules
in the last
1 Year?
(Show the
mother the
Red or Blue,
capsules)
If none, enter
ZERO
Has (Name)
been
Has
(Name)
Has
(Name)
Immunized
received
received
against
OPV1?
OPV3?
measles?*
Codes:
1=Yes
by Card
2=Yes
by Recall
3=No
4=DNK
Codes:
1=Yes
by Card
2=Yes
by recall
3=No
4=DNK
Codes:
1=Yes
by Card
2=Yes
byrecall
3=No
4=DNK
Q11
Has (Name)
taken any
deworrming
drug in the
last 6
months?
Codes:
1=Yes by
Card
2=Yes by
recall
3=No
4=DNK
Q12
Q13
Height
In cm
(Nearest
0.1cm)
Oedema
present?
Q14
Weight
In KGs
Write down the
decimal and do
not round up
1=Yes
2=No
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
(Nearest
0.1kg)
Write down
the decimal
and do not
round up
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
Q15
MUAC
In cm
(Nearest
0.1cm)
Write down the
decimal and do
not round up
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
Tana River County Survey - Child Immunization, Anthropometric and Breast Feeding Data Form (Only for Children 6-59 months Old)
Name of District __________Name of division____________Division No_____Name of Sub-Location______________Sub-loc No_____Name of Village/Cluster___________ Cluster No______ Date of Interview____/____/_____ TL Name __________TeamNo___
Q1
Q2
HHD
No.
(Copy
from
main
HHD
Qnn for
ALL
children)
Child
Serial
No
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
36.
37.
38.
Q3
Child’s IntraHousehold ID
number and Name
Give youngest child in
the household ID no 1.
If more than one child,
record them
sequentially by age)
Child
IntraHHD**
ID No.
Child’s
Name
Q4a
Child’s Date
of Birth
Q4b
Enter
the
Age of
child in
months
(Use Clinic
Cards and
Calendar
of EVENTS
(Use
Clinic
Cards
and
Calendar
of
EVENTS
Q5
Q6
Child
age
Verification
1= Vaccination
card
2= Birth
certificate
3= Baptism
card
4= Recall
Child
Sex
1= M
2= F
Q7
Q8
Q9
Q10
How many
times has
(Name)
received vit
A capsules
in the last
1 Year?
(Show the
mother the
Red or Blue,
capsules)
If none, enter
ZERO
Has (Name)
been
Has
(Name)
Has
(Name)
Immunized
received
received
against
OPV1?
OPV3?
measles?*
Codes:
1=Yes
by Card
2=Yes
by Recall
3=No
4=DNK
Codes:
1=Yes
by Card
2=Yes
by recall
3=No
4=DNK
Codes:
1=Yes
by Card
2=Yes
byrecall
3=No
4=DNK
Q11
Has (Name)
taken any
deworrming
drug in the
last 6
months?
Codes:
1=Yes by
Card
2=Yes by
recall
3=No
4=DNK
Q12
Q13
Height
In cm
(Nearest
0.1cm)
Oedema
present?
Q14
Weight
In KGs
Write down the
decimal and do
not round up
1=Yes
2=No
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
(Nearest
0.1kg)
Write down
the decimal
and do not
round up
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
Q15
MUAC
In cm
(Nearest
0.1cm)
Write down the
decimal and do
not round up
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
Q1
HHOLD
No.
Copy
HHD Numbers
in exactly
the same order in
which they appear
on page 1
Tana River County Survey – Child Morbidity and Child Feeding Data Form (Only for Children 6-59 months Old)
Q3
Q16
Q17
Q18
Q19
Q2
Child
Serial
Child’s Intra- HHD ID
number and Name
Copy child intrahousehold ID
Numbers and Names
in exactly the same
order in which they
appear on page 1
No.
Child
IntraHHD**
ID No.
Has (Name)
been
sick in the last
2 WEEKS?
1=Yes 2= No
[If yes], enter
type of illness
1= Cough/ARI
2= Measles
3= Eye infect
4= WatDiarrea
5=Bloo diarrho
6= Malaria
7= Stomache
8= Skin infect
9= N/A
10=Others
specify
Child Name
Sick?
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
Illness
If DIARRHOEA was
YES i.e. = 4 or 5, what
was e/she given while
he/she was having
diarrhoea?
Codes:
1= Oralite/ORS
2=Zinc(Show sample)
3=Both Zinc &ORS
4=Any other homemade liquid such as
porridge, soup, yoghut,
fruit drink, tea, milk,
rice water
5= Nothing
6= Other (specify)
When (Name) was
sick the LAST time,
did you seek
assistance?
IF YES, where?
1=No Assistance
2= Public
Clinic/Hospital
3= CHW
4= Mobile/outreach
Clinic
5= Private
Clinic/Pharmcy
6= Shop/Kiosk
7= Relative/Friend
8= Traditional
Healer
9= Other (specify)---
[Continue from Page 1]
Q20
Q21
Is (Name) currently enrolled in the
hospital Feeding Programme?
1=Yes 2=No
[If YES, for how long? [convert time
and indicate how long in DAYS
Physiological
status of
mother/child care
taker
[If YES], indicate which type of
programme]
1=Supplment Feed Prog
2=Theraptic Prog (OTP)
In
Program?
Duraion
In program
Type of
programme
Q22
Maternal MUAC
Age of Mother/
Primary
Childcare Taker
in years
1=Pregnant
2=Lactating
3=Preg &lact
4=Not preg/ not
lactating
Mother MUST be
between 15-49
years For MUAC to
be taken
Record maternal
MUAC to the
nearest 0.1cm
Tana River County Survey – Child Morbidity and Child Feeding Data Form (Only for Children 6-59 months Old)
[Continue from Page 2]
Name of District __________Name of division____________Division No_____Name of Sub-Location______________Sub-loc No_____Name of Village/Cluster___________ Cluster No______ Date of Interview____/____/_____ TL Name __________TeamNo___
Q1
Q2
HHOLD
No.
Copy
HHD
Numbers
in exactly
the same
order in
which
they
appear
on
page 1
Child
Serial
No.
Q3
Child’s Intra- HHD ID
number and Name
Copy child intrahousehold ID
Numbers and Names
in exactly the same
order in which they
appear on page 1
Child
IntraHHD**
ID No.
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
36.
37.
38.
Child Name
Q16
Q17
Q18
Q19
Has (Name)
been sick in
the last 2
WEEKS?
1=Yes 2= No
[If yes], enter
type of illness
1= Cough/ARI
2= Measles
3= Eye infect
4=WatDiarrhea
5=Bloo Diarrh
6= Malaria
7= Stomache
8= Skin infect
9= N/A
10=Others
specify--------Sick? Illness
If DIARRHOEA was
YES I.E. 4 or 5, what
was he/she given while
having diarrhoea?
When (Name) was
sick the LAST time,
did you seek
assistance?
IF YES, where?
1=No Assistance
sought
2= Public
Clinic/Hospital
3= CHW
4= Mobile/outreach
Clinic
5= Private
Clinic/Pharmcy
6= Shop/Kiosk
7= Relative/Friend
8= Traditional
Healer
9= Other (specify)---
Is (Name) currently enrolled in the
hospital Feeding Programme?
1=Yes 2=No
[If YES, for how long? [convert
time and indicate how long in
DAYS
Codes:
1= Oralite/ORS
2=Zinc(Show sample)
3=Both Zinc &ORS
4=Any other homemade liquid such as
porridge, soup, yoghut,
fruit drink, tea, milk,
rice water
5= Nothing
6= Other (specify)
[If YES], indicate which type of
programme]
1=Supplment Feed Prog
2=Theraptic Prog (OTP)
In
Program?
Duraion Type of
In program programme
Q20
Q21
Q22
Maternal MUAC
Age of Mother/
Primary Childcare
Taker
in years
Physiological
status of
mother/child
care taker
1=Pregnant
2=Lactating
3=Preg &lact
4=Not preg/ not
lactating
Mother MUST be
between 15-49
years For MUAC
to
be taken
Record maternal
MUAC to the
nearest 0.1cm
Tana River County Nutrition Survey
Qnn No C: 0-23 MONTH-OLD CHILD QUESTIONNAIRE - ONLY to be filled for Children 0 to 23 Months (i.e. <24 Months)
Name of district
Name of Division
Division
No
Name of
Sub-Location
Sub-Loc
No.
Village/
Cluster Name
Cluster
No
Date of Interview
Name of
Team Leader
Team
No
______/______/______
Important NOTE:



Q1
Q2
Q3
Make every effort to speak with the mother. If she is not available, speak with the primary caregiver responsible for feeding of the child.
Fill in the identification information in the table above from the Main Household Questionnaire.
Fill Questionnaire to cover 2 children aged 0-<6 months and 8 children aged 6-23 months.
Information for children < 6 months should appear only at serial numbers 9 and 10
Q4
Q4(b)
Q5
Q6
Q7
Child Date
of Birth
Child serial
No.
1.
2.
3.
4.
5.
6.
7.
8.
9. <6 Months
10. <6 Months
Child’s
Name
Child Age
in DAYS
(Convert
months to
DAYS)
(Copy from
Clinic Card
or use
Calendar of
Events)
(dd/mm/yy)
Child age
verification
1=Vaccination
card
2=Birth
certificate
3=Baptism
card
4=Recall
Child
Sex
Did (Name)
ever
breastfeed?
1= M
2= F
1= Yes
2= No
[If NO, skip
to Q8(b)
Q8(a)
[If yes to
Q7],
How long
did it take
you before
breastfeedi
ng (Name)
for the first
time after
birth?
(PROBE)
Codes:
1= Within
ONE Hour
2= More
than ONE
hour but
less than 1
day
3= After first
day
Q8(b)
[If No to Q7],
Why did
(Name) not
breastfeed?
Codes:
1= No milk from
breasts
2= Child refused
to breastfeed
3= Traditional
beliefs
4= Child
deformity
5=Mother not
available e.g.
dead
6=Mother had
health problems
Q9
Q10
Q11
[If Yes to
Q7],
During the
first 3 days
after
delivery, did
you give
(Name) the
fluid/liquid
that came
from your
breasts i.e.
colostrum?
[If YES to Q7],
[If YES to
Q7],
Codes
1= Yes
2= No
In the first 3
days after
delivery, was
(Name) given
anything else
other than
breast milk?
(PROBE)
(Laxatives)
Codes:
1= No
2=Plain water
3=Sugar/glucos
e water/honey
4=Animal
milk/products
5=Infant
formula
6=Fruit juice
7=GripeWater
Q12
Is (Name)
Currently
still
breastFeeding?
[If YES to
Q11]
How many
times did
(Name)
breastfeed
Yesterday?
Codes:
1= Yes
2= No
Record
number of
times
Q13(a)
Is (Name)
currently
taking
other
foods or
drinks
other than
breast
milk?
(Note:
other
drinks
include
water)
Codes:
1=Yes
2=No
Q13 (b)
Q13(c)
[If Yes to
Q13a],
[If Yes to
Q13a],
How many
times was
(Name)
given these
other foods
and drinks
from the time
he/she woke
up to the
time of
sleeping at
night
At what
age did
you start
giving
(Name)
other
foods and
drinks
which
were not
breast
milk?
(Convert
if months
and
record in
DAYS)
YESTERDAY?
Enter the no.
of times
mentioned
Name of district
Name of Division
Division
No
Name of
Sub-Location
Sub-Loc
No.
Village/
Cluster Name
Cluster
No
Date of Interview
Name of
Team Leader
______/______/______


Q1
Q2
Make every effort to speak with the mother. If she is not available, speak with the primary caregiver responsible for feeding of the child.
Ask questions on this page only for children between 6-23 months
Q3
HHD No.
(Copy from
MAIN
household
Questionnaire)
If done outside
sample
households
indicate N/A in
this column)
Child
serial
No.
Child’s
Name and Age in
months
(Copy from previous
page).
Name
Age in months
Q14 Questions 14.1 – 14.7 I would like to ask you about the type of foods and drinks the child(ren) aged 6-23
months ate or drank yesterday from the time they woke up in the morning to the time they slept at night. [Enter
1 against a food group that is reported as having been consumed by each child 6-23 months assessed in this
questionnaire and 0 for foodstuffs NOT consumed]. This question does NOT apply to children below 6 months
of age. Do not read the list of foodstuffs in the table below to the respondent.
Q14.1
Grains,
Cereal
Roots or
Tubers
Eg Maize,
Bread,
Sorghum,
Wheat, Rice,
Pastas, Irish
and Sweet
Potatoes,
Porridge,
matoke
1.
2.
3.
4.
5.
6.
7.
8.
Number of Children 6-23 months = ___________ (Must be 8)
Q14.2
Vitamin-A
rich Plant
Foods
E.g. Dark
green leafy
vegetables
(e.g. Sukuma
wiki,
Spinach) and
Bright-colored
vegetables e.g.
Carrots,
Pawpaw,
Pumpkins,
kunde, mrenda,
mchicha,
pumpkin leaves
Q14.3
Other
Fruits and
Vegetables
Any other
vegetables or
fruits eg
Oranges,
Mangoes,
Avocado, Ripe
bananas,
Cabbages
Note: 1=Yes 0=No
Q14.4
Q14.5
Meat,
Poultry,
Fish,
Eggs
Organ
E.g.
meat,
Chicken
Seafood
E.g. Beef,
Poultry, Fish
Shellfish,
Organ meats
e.g.
Matumbo,
Liver, Kidney
Bird eggs
Q14.6
Q14.7
Q14.8
Pulses
Legumes
Nuts and
Seeds
E.g.
Beans,
Peas, Nuts,
Seeds,
Ground
Nut
Dairy
products
E.g.
Milk, Cheese
Tea with milk
Fats and
Oils
Team
No
Qnn D: Mortality Data Form
Name of district
Name of
Division
Div
No
Name of SubLocation
Sub
-Loc
No.
Name of Village/
Sub-location
Village
/Cluster
No
Date of Interview
(dd/mm/yy)
Name of
Team Leader
Team
No
______/______/______
NOTE: Mortality Questionnaire MUST be administered in ALL the 19 Households visited for HOUSEHOLD Survey.
Q1
HH
no.
Q2
Total
number
of people
in
HHD
(Hdsize)
currently
Q3
Total
Number
<5
years
in HHD
currently
Q4
Total
people
join HH in
the last
3months
(Excluding
birth)
(i.e. Since
November
last year
After the 1st
Round of
Oral Polio
Campaign )
Q5
Number of
underfives
join HH last
3 months
(Excluding
birth)
(i.e. Since
November
last year
After the 1st
Round of
Oral Polio
Campaign )
Q6
Total
people
left HHD
in the last
3 months
(i.e. Since
November
last year
After the 1st
Round of
Oral Polio
Campaign )
Q7
Number
underfives
left
household
in the last
3 months
(i.e. Since
November
last year
After the 1st
Round of
Oral Polio
Campaign )
Q8
No of
Births in
the HHD
in the last
3 months
(i.e. Since
November
last year
After the 1st
Round of
Oral Polio
Campaign ))
Q9
** Total
number
of deaths
in the
HHD
(i.e. Since
November
last year
After the 1st
Round of
Oral Polio
Campaign ))
Q10
Number
deaths
of people
< 5 yrs
old in the
last
3 months
(i.e. Since
November
last year
After the 1st
Round of
Oral Polio
Campaign )
Q11
Number
deaths
of people
> 5 yrs
Old
In the last 3
months
(i.e. Since
November last
year After the
1st Round of
Oral Polio
Campaign )
Q12
Causes
of
death
for
people
<5
years
Old
(Use
codes
below)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
** Q9: First ask (CAUTIOUSLY and CAREFULLY) if there has been any death in the household in the last 3 months and Specify the
Recall Period (i.e. Since November last year After the 1st Round of Oral Polio Campaign)
Causes of death Codes:
ENTER N/A in Q12 and Q13 if no deaths reported in Q10 and Q11
1= Watery Diarrhoea
2= Bloody Diarrhoea
3= ARI (Cough + difficulty breathing (pneumonia)
4= Malaria (Fever with malaria-like chills
5=Neonatal death
6= Measles (persistent fever, oesophagus infection, skin rash, red eyes)
Name of Team Leader ______________________ Signature ____________________
7= Malnutrition (bilateral oedema and or wasting)
8= Killed/Accidents
9= Not known
10=Old age
11=During delivery
12=Others (specify) ___________________
Date ___________________
Q13
Causes
of
Death
for
people
>5
Years
Old
(Use
codes
below)
FOCUS GROUP DISCUSSION CHECKLIST
Name of
district
Name of
Division
Division
No
Name of Village/
Sub-location
Cluster
No
Date of Interview
(dd/mm/yy)
Name of
Team Leader
Team
No
______/______/______
There should be 8-10 people in each FGD. Representation should be sought from a wide cross-section of
community members including local leaders, women leaders, TBAs, and community members of different socioeconomic status (rich, medium and poor). Separate FGDs should be held for men and women.
[Note: Probe ALL responses given]
1. What is the current livestock situation in this community in terms of:
a) Body condition
b) Pasture availability and condition
c) Access to animal products by children and women e.g. milk and meat
d) Any recent serious disease outbreaks
e) Who makes important decisions e.g. selling and slaughter on livestock (Camels, cattle, shoats and chicken)
2. a) Into how many groups are the various socio-economic groups categorized in this community e.g. rich, middle,
poor etc? What are the 3 main criteria used to classify people into the socio-economic status groups?
b) In case of drought or food shortage, which of these groups above is most adversely affected? Give reasons why
c) What proportion of households fall under each of the categories mentioned in this area (cluster) currently? (Use
proportional piling if necessary).
3. What is the current food availability situation in this community in terms of:
a. Household food production
b. Availability of food in the market
c. Prices of food in the market
4. a) Has the community been faced with a food shortage in the last 2 months? IF YES, what are the 3 main coping
strategies that this community has used to deal with food shortage in the last two months? List those stated.
b) For each coping strategies listed in Q4, ask when it is usually practiced: is it when the food shortage situation is
severe or mild?
5. a) At what age are babies given foods other than breast milk for the first time in this community? (food is any
solid or liquid such as animal milk, water, juice, glucose, porridge etc which is not breast milk)
b) What type of food is mainly given to babies for the first time after birth and what are the reasons for giving the
mentioned food?
6. a) What are the main causes of maternal and underfive malnutrition in this community?
b) What do you think should be done at the community level to address this problem among mothers and the
children?
7. How long on average does it take members of this community to access the nearest health facility in minutes?
8. What is the general major problem facing this community currently?
9. What do you think your Community can do to recover from the problem listed in Q11?
10. What external assistance do you think the community would need to recover from the problem listed in Q11?
Name of Team Leader ______________________ Signature ____________________
Date ___________________