REPORT ON INTEGRATED HEALTH AND NUTRITION
SURVEY
IN LARGER MERU NORTH COUNTY OF KENYA.
FINAL REPORT
(April, 2012)
Anastacia Maluki,
International Medical Corps
Monitoring and Evaluation officer
ACKNOWLEDGEMENTS
I take this opportunity to thank UNICEF for the financial support they provided to conduct this
survey.
Special thanks are expressed to: the Survey co-ordinators (DNO), Team leaders, team members,
data entry clerks, International Medical Corps staff members and drivers for their tireless efforts
to ensure that the survey was a success.
I am also indebted to the district administrators, local leaders and community members who
willingly participated in the survey and provided the information needed.
TABLE OF CONTENTS
LIST OF TABLES ................................................................................................................................................ 5
LIST OF FIGURES............................................................................................................................................... 5
LIST OF APPENDICES ........................................................................................................................................ 6
ACRONYMS AND ABBREVIATIONS................................................................................................................. 6
EXECUTIVE SUMMARY .................................................................................................................................... 8
1.0 BACKGROUND INTRODUCTION ............................................................................................................ 12
1.1 Rationale for conducting a survey ....................................................................................................... 13
1.2 Objectives: ............................................................................................................................................ 13
2 SURVEY METHODOLOGIES........................................................................................................................ 14
2.1 Sampling Methodology and Sample Size ............................................................................................. 14
2.2 Description of sampling frame (including source of population data) ............................................... 16
2.3 Description of sampling methods ........................................................................................................ 16
2.4 Data to be collected, and data collection methods and tools ............................................................... 17
2.5 Data collection Tools and Variables Measured .................................................................................... 17
2.6 Training and Supervision ..................................................................................................................... 18
2.7 Data Entry and Analysis ....................................................................................................................... 19
2.8 Nutritional Status Cut-off Points .......................................................................................................... 19
2.9 Survey data validation process ............................................................................................................. 21
2.10 Survey Limitations .............................................................................................................................. 21
2.11 Good Practice ..................................................................................................................................... 22
3. RESULTS ...................................................................................................................................................... 23
3.1 TARGET POPULATION DEMOGRAPHIC CHARACTERISTICS .............................................................. 23
3.2 ANTHROPOMETRIC RESULTS (BASED ON WHO STANDARDS 2006) ............................................... 24
3.3 ADULT NUTRITIONAL STATUS ........................................................................................................... 29
3.4 MATERNAL HEALTH CARE INFORMATION. ....................................................................................... 30
3.5 CHILD FEEDING, CARE AND HEALTH ................................................................................................. 31
3.6 SUPPLEMENTARY AND THERAPEUTIC FEEDING PROGRAMME COVERAGE .................................... 35
3.7 INSECTICIDE TREATED MOSQUITO NETS (ITN) HOLDING RATES AND UTILIZATION ................... 36
3.8 WATER, SANITATION AND HYGIENE PRACTICES .............................................................................. 36
3.9 HOUSEHOLD FOOD SECURITY ........................................................................................................... 38
3.10 MORTALITY RESULTS ........................................................................................................................ 43
4. CONCLUSION ............................................................................................................................................ 44
5 .RECOMMENDATIONS ............................................................................................................................... 45
6. APPENDICIES .............................................................................................................................................. 47
LIST OF TABLES
Table 1: Anthropometric and mortality sample size calculation
Table 2: Demographic information of target population
Table 3: Distribution of age and sex of 6-59 months.
Table 4: Prevalence of acute malnutrition based on weight-for-height z-scores
(and/or oedema) and by sex
Table 5: Prevalence of acute malnutrition by age, based on weight-for-height zscores and/or oedema
Table 6: Distribution of acute malnutrition and oedema based on weight-forheight z-scores
Table 7 Prevalence of acute malnutrition based on MUAC cut off's and/or oedema
Table 8: Prevalence of underweight based on weight-for-age z-scores by sex
Table 9: Prevalence of underweight by age, based on weight-for-age z-scores
Table 10: Prevalence of stunting based on height-for-age z-scores and by sex
Table 11: Prevalence of stunting by age based on height-for-age z-scores
Table 12: Mean z-scores, Design Effects and excluded subjects
Table 13: Vaccination coverage: OPV 1 & 3 for 6-59 months and measles at 9
months and deworming for 12-59 months
Table 14 Vitamin A coverage
Table 15: Symptom breakdown in the children in the two weeks prior to interview
(n=311)
Table 16: Main Sources of food consumed in 24 hr recall
Table 17: proportion of food crops shared sold and stored after harvesting.
Table 18: top ten coping strategies
Table 19: Mortality rates
Table 20: Causes of death among under/above 5 years
LIST OF FIGURES
Figure 1: Population age and sex pyramid
Figure 2: Prevalence of acute malnutrition by age, based on MUAC cut off's and/or
oedema
Figure 3. Nutrition Status of caregivers of < 5 year old children:
Figure 4:Lacteals given in the first three days of birth
Figure 5 food groups taken by children 6-23 months in the previous 24 hrs
Figure 6 :House hold water sources for general and domestic use
Figure 7 household water treatment methods.
Figure 8 Sources of Income
Figure 9 Frequency of meals taken in household
Figure 10 Ratio of foods groups consumed in 24-hour recall
LIST OF APPENDICES
Appendix 1: IYCN calculator
Appendix 2:Household Questionnaire
Appendix 3:Anthropometric Questionnaire
Appendix 4:IYCN Questionnaire
Appendix 5:Mortality Questionnaire
Appendix 6:Focu Group Discussion guide
Appendix 7: Plausibility checks.
Appendix 8: Assignment of Clusters
Appendix 9: Map
Appendix 10. Summary of findings
ACRONYMS AND ABBREVIATIONS
ACF
- Action Against Hunger
ARI
- Acute Respiratory Infection
AOP
BFHI
CED
CHNE
CI
CMAM
CMR
CSB
DDS
EMOP
ENA
EWAS
FAO
FANTA
FFA
FGD
GCM
GFD
GAM
GOK
GS
- Annual operation Plan
- Baby friendly Hospital Initiative
- Chronic Energy Deficiency
- Community-based Health/Nutrition Education
- Confidence Interval
- Community-based management of Acute Malnutrition
- Crude Mortality Rate
- Corn Soya Blend
- Dietary Diversity Score
- Emergency Operation Programme
- Emergency Nutrition Assessment
- Early warning System
- Food and Agriculture Organization
- Food and Nutrition Technical Assistance
- Food for Assets
- Focus Group Discussion
- Global Chronic Malnutrition
- General Food Distribution
- Global Acute Malnutrition
- Government of Kenya
- Growth Standards
HFA
- Height-for-Age
IMAM
- Integrated management of Acute Malnutrition
ICNP
IMC
IMCI
ITN
IYCF
KCO
KEPI
MMCG
MoMS
MoPHS
MUAC
NCHS
NGO
OJT
OPV
PPS
PR
PRRO
SAM
SCM
SD
SFP
SMART
SMP
SPSS
SSS
TBA
UFMR
UK
- Integrated Community Nutrition Programme
- International Medical Corps
- Integrated Management of Childhood Diseases
- Insecticide Treated Nets
- Infant and Young Child Feeding
- Kenya Country office
- Kenya Expanded Programme on Immunization
- Mother to Mother Care Groups
- Ministry of Medical Services
-Ministry of Public Health and Sanitation
- Mid-Upper Arm Circumference
- National Centre for Health Statistics
- Non-Governmental Organization
-On-the-Job Training
- Oral Polio Vaccine
- Probability Proportional to Population Size
- Protection Ration
- Protracted Relief and Recovery Operation
- Severe Acute Malnutrition
- Severe Chronic Malnutrition
- Standard Deviation
- Supplementary Feeding Programme
- Standardized Monitoring and Assessment of Relief and Transitions
- School Meals Programme
- Statistical Package for Social Scientists
- Small Scale Survey
- Traditional Birth Attendant
- Underfive Mortality Rate
- United Kingdom
UNICEF - United Nations Children’s Fund
USAID
- United States of America International Aid
WFH
- Weight-for-Height
WFA
WHO
- Weight-for-Age
- World Health Organization
EXECUTIVE SUMMARY
This survey covered the greater Meru North district (Igembe South, Igembe North, Tigania West
and Tigania East Districts), which is inhabited by people from Igembe and Tigania origins. The
population in Meru North District is relatively static and densely populated with an annual
growth rate of 2.8%. The district has an estimated 146,567 households with an average of 5
persons per house hold. It has an estimated population of 740,035 people (Igembe 471,836 and
Tigania 268,199) and 123,770 children below 5 years (Igembe 75,494 and Tigania
48,276).Giving an average proportion of 16.7% children under 5 years. The district comprises
of six livelihood zones namely; marginal mixed farming, mixed farming food crops, mixed
farming: Tea/dairy, rain fed cropping and rain fed tea/dairy. Majority of the population fall
under marginal mixed farming.
In view of the need to gauge the performance of the Essential Nutrition Action (ENA) package
and for informed future formulation and prioritization of appropriate interventions in the
district, International Medical Corps in collaboration with the MoPHS and MoMS carried out a
nutritional survey between 26th March and 6th April 2012.Training of enumerators took 4 days
(26th-29th March, 2012) and data collection took place as from 30th March, 2012– 6th, April,
2012. 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. The survey utilized the
Standardized Monitoring of Relief and Transitions (SMART) methodology and also 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.. IYCF multi survey
sampling calculator was used to calculate IYCF and Qualitative data was collected through: focus
group discussions (FGDs), key informant interviews and general observations.
Overall, the surveyed households had, on average, 5.7 (SD 2.3) members per household. The
findings showed a global acute malnutrition (GAM) rate of 7.8 % (5.2-11.6 CI), a severe acute
malnutrition (SAM) rate of 1.2 % (0.5-2.8 CI) by WHO-GS. The overall prevalence of GAM in
Meru North County reveals risky situation with aggravating factors in the community according
to WHO benchmarks. Notably was the measles break out in the district just before the survey and
high morbidity cases in coughing 50% and diarrhoea disease 11.3% which are considered as
aggravating factors. Tigania East division was most afflicted by acute malnutrition where the
prevalence of GAM stood at 11.7% (7.2-18.4 CI), this was followed by Igembe north 8.5%,
Igembe south 6.8% and finally Tigania west 4.3%. The findings though are not statistically valid
as the sample size are too small to represent a division. Both the crude mortality rate (CMR) of
0.24 (0.11-0.56 CI) deaths/10,000/day and the under-five mortality rate (UFMR) of 0.48 (0.141.59CI) deaths/10,000/day did not reach the threshold for ‘Alert’ status.
The MUAC measurements of 715 eligible primary childcare givers (15-49 years old) were taken
to assess their nutritional status. The survey findings showed that.2.2% (n=133) of caretakers had
MUAC <21cm meaning that they are at risk of malnutrition or have chronic energy deficiency
(CED). Overall, 87.7 % of mothers reported having attended MCH clinics and in spite of the
clinic visit only 55.3 % of the women delivered in the hospital.
The findings indicate that practically all children (98.1%) were reported to have breastfed but
only 53.3% were exclusively breastfed for 6 months. On average the mean food diversity was 2.8
(SD 1.8) given to children > 6 months. The findings showed that 64.2% of the children samples
consumed low dietary diversity of less than four groups, a threat to optimal child growth and
development while only 35.8% of the households had children >6 months who consumed 4 or
more of the food group. Survey revealed that majority of the used tap water as their main source
of water with 67% not treating water before drinking. 85.4% of the HH had access to toilet
facilities that they use.
The overall prevalence of GAM (7.8%) in Meru North County reveals poor nutritional status in
the community according to WHO benchmarks. The study identified aggravating factors that
had a negative bearing on optimal under-five nutritional status and their caregivers:

Poverty and issues of who controls family income have a heavy contribution to
household food security. Income sources are not diversified and therefore there’s over
reliance on farm produce both as an income source and family food. Poverty has also
made it difficult to access food from markets due to insufficient financial resources. Lack
of water supply in many parts of Meru North districts especially in Igembe North
division has led to infectious diseases spreading, causing childhood diarrhea, which leads
to major malnutrition and subsequent death due to diarrheal dehydration

Poor agricultural practices including cultivation of Miraa in most areas whose income
does not translate into food security. This is further compounded by poor soil fertility as
a result of poor farming practices and environmental degradation.

Lack of access to food.Most major food and nutrition crises do not occur because of a
lack of food, but rather because people are too poor to obtain enough food.

Poor child and adult dietary profiles. Over-consumption of certain food group like
cereals usually goes along with deficiencies in essential vitamins and minerals.

High child morbidity prevalence reported to have affected 44.6% of the under-fives
which was found to significantly affect child nutritional status;

Poor IYCF practices including early weaning, low maintenance of breast feeding and
poor feeding practices.

Poor access to medical facilities some are too far for household to access. On average
most health facilities are located 3.2 (SD 2.6) km away.

Poor water sanitation status in the community with minimal treatment of unsafe
drinking water at the household level increase vulnerability to infectious and waterborne diseases, which are direct causes of acute malnutrition.
Because malnutrition has many causes, only multiple and synergistic interventions embedded in
true multisectoral programs can be effective. A variety of actions both immediate and long term
solutions are needed:

Addressing the poor access to essential health and nutrition services by strengthening the
integrated outreach component- primarily focusing on regular medical outreach
camps/mobile clinic. This will help to intensify active case finding of malnourished
children and manage them accordingly.

Strengthen programmes and strategies currently addressing infant and young child
nutrition (IYCN) with a view to improving the protection, promotion, and support of
optimal IYCF. Viable action points include:

As the HINI program is rolled out there is need for continual monitoring of both facility
and community based interventions to track progress while also documenting the
process to assess the trends in the outcomes as well as impact indicators. Particular
attention should go to improved maternal nutrition, iron/folate supplementation during
the prenatal period and ensuring ORS/zinc support for diarrhoea.

Strengthening of hygiene practices to reduce the incidence of diarrhoeal disease
associated with contaminated water in the household including health education to
educate the community on domestic treatment of drinking water and effective hand
washing (soap/ash) after helping a child in the latrine, during food preparation and
before child feeding. This should be backed-up with provision of free water treatment
chemicals where feasible.

Continued water trucking to areas affected by water stress by Ministry of Water and
Irrigation and Kenya Red Cross especially in Igembe north District.


Provision of water purification chemicals for water treatment at Household level
Advocacy/public health campaigns on domestic water treatment such as boiling of
drinking water and use of purification chemical to minimize risks of water-borne
diseases, should be carried out.

The Ministries of Public Health and sanitation and Medical services in collaboration with
other stakeholders in the district to initiate and offer concrete support in the
implementation of strong awareness campaigns and community based health and
nutrition programs with special focus on infant and young child feeding practices,
dietary diversification, food preparation and preservation, consumption of energy dense
and micronutrient-rich foods and kitchen gardening. Women should be the prime
targets of these. Nutrition messages should address strategies/ways of improving access
to locally available and cheaper sources of fat, protein and micronutrients.

Focus on programmes by ministry of agriculture that improve and sustain dietary
diversity and consumption of micronutrient.-rich foods. And advising farmers on good
farming methods .By improving agricultural yields, farmers could reduce poverty by
increasing income as well as open up area for diversification of crops for household use.

To address the issues of limited access to safe water, there is a need to establish water
points in areas where water is inaccessible.

MOH should increase access to health facilities in the rural parts of kenya by adding
more health facilities or increasing CHW. These will improve hospital deliveries and
access to medical services for those who cannot access the health facilities
1.0 BACKGROUND INTRODUCTION
Meru County is located in the Eastern province and constitutes 7 constituencies: Igembe,
Ntonyiri, Tigania West, Tigania East, North Imenti, Central Imenti and South Imenti. The Larger
Meru North District is made up of four districts namely: Igembe South, Igembe North, Tigania
West and Tigania East Districts. Meru North covers an area of 4057 Km2 of which 833 Km2 is
Meru National Park .It has an estimated population of 740,035 people (Igembe 471,836 and
Tigania 268,199 )and 123,770 children below 5 years(Igembe 75,494and Tigania 48,276
).Giving an average proportion of 16.7% children under 5 years 1. The people of the district are
mainly of Igembe and Tigania origins. Borans, Somalis, and others are also residents of the
district.
The district lies within latitudes 0º 00’ and 0º 40’ North, and longitudes 37º 50’ East, with the
southern boundary lying along the equator .Altitude ranges from 2,145m above sea level in the
higher regions to 600m in the lower parts which cover the greatest land area (3/4 of total area).
These low lying areas were designated as the Northern Grazing Areas (NGA) and are
characterized by low and erratic rainfall. The soils are predominantly volcanic clay loams with
patches of rock and black cotton soils. Rainfall amounts range from 380mm p.a. in the lower
areas to 2500mm p.a. in the higher areas. Its spatial distribution is highly dependent on
elevation, with the high altitude areas receiving the most amounts compared to the low-lying
areas. Rainfall is bimodal with long rains expected from mid-March to May and the short rains
expected from mid-October to late November. Short rains are most reliable.
Agro-ecological zones in the district range from LH22 (tea and dairy) to L6 (lowland grazing
zones). LH2 zones cover a very small area while L6 covers the greatest area of the district. The
district comprises of six livelihood zones namely; marginal mixed farming, mixed farming food
crops, mixed farming: Tea/dairy, rain fed cropping and rain fed tea/dairy. Majority of the
population fall under marginal mixed farming .Miraa is a major cash crop being farmed and is
harvested throughout the whole year.
International Medical Corps with financial support from UNOCHA is supporting Ministry of
Public Health and Sanitation and Ministry of Medical Services in scaling up of High Impact
Interventions for improved maternal and child health in Meru North Districts. These
1
2
2010 Population projection, Ministry of Health
Simple agro-ecological zones were established by FAO in 1981. They are suited to make decisions in order to give
advice to farmers showing yield probabilities and risks: The zone groups are temperature belts defined according to
the maximum temperature limits within the main crops in Kenya can flourish; cashew and coconuts for the lowlands,
sugar cane and cotton for the lower midlands, Arabica coffee for the upper midlands, tea for the lower highlands,
pyrethrum for the upper highlands
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 and promotion of iron
enriched food 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.
1.1 Rationale for conducting a survey
In order to gauge the performance of the HINI package and inform future programming in the
district, International Medical Corps in collaboration with MOMS/MOPHS carried out a
nutritional survey in the greater Meru North district between 26th March and 6th April 2012, to
evaluate the extent and severity of malnutrition among children aged 6-59 months and analyze
the possible factors contributing to malnutrition and recommend appropriate interventions.
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.

To estimate the current prevalence of acute malnutrition in children aged 6-59 months
and to compare the overall nutritional changes with previous GAM and SAM

To estimate the retrospective crude and under five death rates and morbidity among
under five children and as well compare with previous CMR and U5MR.

To estimate Measles, BCG vaccination and Vitamin A supplementation for children 9-59
months and 6-59 months respectively

To assess the current food security situation of the surveyed population, prevalence of
some common diseases (Diarrhea, Fever, and Cough) and to identify factors likely to have
influenced malnutrition in young children

To assess child and infant care and feeding practices among caretakers with children 023 months

To establish the situation of water and sanitation, appropriate hygiene practices
including hand washing among caretakers
1.3 Timing of the survey (including seasonal calendar)
The survey was scheduled to take place as from 26th March and 6th April 2012.Training of
enumerators took 4 days (26th-29th March, 2012) and data collection took place as from 30th
March, 2012– 6th, April, 2012.
Seasonal Calendar
JAN
FEB
Dry season
SR
APRIL
MAY
JUN
E
LONG RAINS
Land
harvesting
MAR
preparation
Planting
weeding
JUL
Y
AUG
SEPT
Dry season
LR
harvesting
OCT
NOV
SHORT RAINS
Land
preparation
planting
weeding
Miraa harvesting
Key:
SR: short Rain
LR: Long Rain
2 SURVEY METHODOLOGIES
2.1 Sampling Methodology and Sample Size
Three different sampling methodologies were applied. IYCF multi survey sampling calculator
was used to calculate IYCF sample while Emergency Nutrition Assessment (ENA) for Standardised
Monitoring of Relief and Transition (SMART) was used to calculate anthropometric and mortality
data. This was guided both by the National Guidelines for Nutrition and Mortality assessments in
Kenya and the recommended UNICEF nutritional survey key indicators. Qualitative data was
collected through: focus group discussions (FGDs), key informant interviews and general
observations.
In calculating anthropometric sample size, a GAM prevalence of 7.2%3 (3.9-7.2 95% CI)4 ,
desired precision of 3%, a design effect of 1.5, an estimated household size of 5 persons, 17% < 5
years and non-response rate of 3% gave a sample size of 466 children (6-59 months) and a
household sample of 628 households. The second sampling stage comprises 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 was entered into the SMART
software, which generated the actual list of the villages to survey (including reserve clusters). At
the field level, the EPI method was employed to select the first household to be enumerated. This
was because it was not possible to get the list of households to use random sampling and the
villages were not arranged in a systematic manner to employ random sampling. A household was
3
4
DEC
Considered the upper limit of the GAM prevalence with a confidence Interval of 95%
Integrated Health and Nutrition survey ,Meru North District, Kenya, June 2008.MOH
SR
harvesting
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 below
20 households, following the methodology described above.
IYCF multi survey sampling calculator was used to obtain sample size for Infants and young
children (0-23 months). Indicators calculated were: Timely initiation of breastfeeding (children
0-23 months), Exclusive breastfeeding under 6 months, Timely complementary feeding, and
Continued breastfeeding at 1 year. Using information obtained from cluster survey5, the sample
size for children between 0-23 months was 730 (annex 1).The number of children aged 0-23
months to be reached per cluster was given by dividing 730 by 37 giving 20 children per cluster
.The number of households was given by dividing 146 by 1.5 (average number of children under
59 months in a household6) to give 98 households. Getting children below 6 months in a cluster
was quite a challenge and therefore purposive sampling was used where no children of that age
group were found in the cluster.
Sample size for mortality will be based on survey conducted in Meru north in ,2008 with a
crude death rate of 0.98 deaths/10,000/day a desired precision of 0.5, design effect of 1.5,
household size of 5 with a recall period of 90 days and non-response rate of 3%. This gives a
sample of 2732 people and 563 households.
Table1: Anthropometric and mortality sample size calculation
Data entered on ENA software
Anthropometric sample
7
Retrospective Mortality sample
Estimated prevalence
7.2
0.988
Desired precision
3
0.5
Design effect
1.5
1.5
Recall period
90 days
Average household size
59
Percent of under five children
1711
5
6
7
8
9
510
Multiple Indicator Cluster Survey, Meru North District, 2008.
Integrated Health and Nutrition survey ,Meru North District, Kenya, June 2008.MOH
Integrated Health and Nutrition survey ,Meru North District, Kenya, June 2008.MOH
Integrated Health and Nutrition survey ,Meru North District, Kenya, June 2008.MOH
Integrated Health and Nutrition survey ,Meru North District, Kenya, June 2008.MOH
10
11
Integrated Health and Nutrition survey ,Meru North District, Kenya, June 2008.MOH
2010 Population projection, Ministry of Health
Percent of non-respondent
3
3
Households to be included
628
563
Children to be included
466
Population to be included
2732
2.2 Description of sampling frame (including source of population data)
The survey covered all areas of the Larger Meru North District which is made up of four districts
namely: Igembe South, Igembe North, Tigania West and Tigania East Districts. Meru North
covers an area of 4057 Km2 of which 833 Km2 is Meru National Park .It has an estimated
population of 740,035 people (Igembe 471,836 and Tigania 268,199 )and 123,770 children
below 5 years(Igembe 75,494 and Tigania 48,276 ).Giving an average proportion of 16.7%
children under 5 years
12
. The people of the district are mainly of Igembe and Tigania origins.
Borans, Somalis, and others are also residents of the district.
2.3 Description of sampling methods
Number of households surveyed were 628 given by ENA software added to 98 households
calculated for IYCN (726) divided by number of Household reached per day (20) gave a total of
37 clusters that were surveyed. A total of 6 survey teams, each comprising of 1 team leader and 3
enumerators collected the data for 6 days. One team collected data for 7 days as they had an
extra cluster to survey.
Clusters were assigned randomly by the ENA FOR SMART SOFTWARE. Survey teams first
reported to the area chief, who assigned them a local guide. With the assistance of the local
guide, the teams 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 visited were randomly
selected by drawing a random number list between one and the number of households counted
when walking to the periphery. The subsequent households were selected by proximity always
selecting households to the right. In villages with more than one cluster, the village were
subdivided and the centre of each subdivision was determined and households were selected as
described above. In a cluster that was sparsely populated, all the households in the cluster were
visited. All children aged 6-59 in every household visited were included in the anthropometric
survey and 0-23 month category was included in IYCF.
12
2010 Population projection, Ministry of Health
2.4 Data to be collected, and data collection methods and tools
To estimate malnutrition prevalence, mortality rates and IYCF the following information was
collected:

Anthropometry (weight, height, oedema, MUAC, age, sex) for children aged 6-59
months and MUAC for caretakers












Vaccination information (measles, BCG, and Vitamin A supplementation)
Incidences of childhood illnesses in the last 2 weeks prior to the survey
Crude and Under 5 mortality rates over a recall period of the last 3 months
Other child care, food security and hygiene data at household level
For children aged below 23 months, IYCF data were equally be collected
HINI indicators were as well captured.
total number (of all ages) currently in the household
number who were in the household at the start of the recall period
number of deaths
number of births
number who left the household during the recall period
number who joined the household during the recall period
2.5 Data collection Tools and Variables Measured
A total of 6 survey teams, each comprising of 1 team leader and 3 enumerators collected the
data. 4 sets of questionnaires were used for data collection. These included 4 sets of structured
questionnaires Questionnaire A (household)- all HH members; Questionnaire B(anthropometry
and maternal)- 6-59 months, caregivers; Questionnaire C(IYCF)- 0-23months and
Questionnaire D(mortality)-all HH members as well as a focus group discussion (FGD) guide to
collect qualitative data.
2.5.1 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 (ITNs), livestock condition and household
socio-economic status indicators. (appendix 2)
2.5.2 Child (6-59 months old) questionnaire (Anthropometry)
Using this questionnaire, the following data were collected:
Child age: the age of the child was recorded based on a combination of information collected
from the child health cards, the mothers’/caretakers’ knowledge of the birth date and use of a
calendar of events for the district developed in collaboration with the survey team (Appendix 3).
Child sex : 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 with minimal light clothing on, using UNICEF
Salter Scales with a threshold of 25kgs .The teams were trained to use the Salter scale .The scales
were always first set at zero, with the weighing pants, before weighing the child.
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 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). Height rods with a marking at 85cm were used to assist in determining
measuring position.
Child MUAC: the MUAC of children were taken using child 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 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).
Feeding programme enrolment: it was established if children 6-59 months old were enrolled in
SFP or OTP and the duration in the feeding programme.
2.5.3 Under 6 months old child questionnaire
This was used to collect infant and young child feeding (IYCF) practices data in the households
visited. 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
2.5.4 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.
2.5.5 Focus group discussion (FGD) guide
A FGD guide was used to collect qualitative data to complement quantitative data . Each team implemented
2 FGDs, one for men and another for women in one of the assigned clusters. The FGD clusters were
selected from the targeted villages in a manner that ensured adequate representation of socio-economic,
ecological and livelihood differentials
2.6 Training and Supervision
The survey was coordinated and supervised by International Medical Corps staffs and Meru
north district Nutrition Officer (DNO) as the Survey Supervisor. For data collection, a total of 6
teams were recruited and trained for the survey. Each team comprised of a team leader and two
enumerators. The local events calendar was developed jointly with the survey team and the
questionnaires translated
The anthropometric standardization exercise13, as recommended by the SMART methodology,
was used as an assessment of the team members’ anthropometry techniques. Each team member
was given a score of competence based on performing measurements with accuracy and
precision. The results of the training exercise were analyzed by entering the data in the ENA
computer package and training report generated.
After the class room training, a Practical field experience was conducted on the last day of
training, in one of the unselected clusters to take anthropometric measurements of children and
caretakers, conduct interviews and fill questionnaires. The pre-testing exercise was performed
on 5 households.
Each team was supervised at least once a day throughout the data collection by either
International Medical Corps staffs or DNO. At the end of each day at base, there was a debriefing session and review of questionnaires. The survey, including the training, lasted for a
period of 11 days.
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 ,interview techniques ,duties and responsibilities
,research ethics ,community entry behaviour and survey logistics.
2.7 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 weight-for-height, height-for-age and weight-for-age Z scores to classify them into
various nutritional status categories using WHO9 standards and cut-off points and exported
back to SPSS for further analysis. IYCF and all the other quantitative data were entered and
analysed in the SPSS Statistics 15.
2.8 Nutritional Status Cut-off Points
The following nutritional indices and cut-off points were used in this survey:
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-for-height (WFH) z-scores, WFH percentage of median and MUAC indices. The results
13
9
SMART Regional Training Kit for Capacity-Building and Methodology (ACF Canada) 2010
WHO 2006
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)
Children whose WFH z-scores fell below -3 standard deviations from the median of the WHOGS or had bilateral oedema were classified as severely wasted (to reflect SAM)
A cut-off point of <12.5cm MUAC was used to denote GAM among the under-fives.
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.
Children whose WFH indices were <80% of the National Centre for Health Statistics (NCHS)
median or had bilateral oedema were classified as wasted (GAM)
Children whose WFH indices were <70% of the NCHS median or had bilateral oedema were
classified as severely wasted (SAM)
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 WHO-GS
were classified as stunted (to reflect Global Stunting)
Children whose HFA z-scores fell below -3 standard deviations from the median of the WHO-GS
were classified as severely stunted.
To determine the nutritional status the following variables were considered for analysis: sex, age,
weight, height or length and oedema. The cluster number was also included for segregation
purposes and to allow for smooth merging up of data with the other household variables in EPI
and the SPSS software. During the z-score calculations the following facts were taken into
consideration:
Table 2: Definition of boundaries for exclusion
1. If Sex is missing the observation is excluded from analysis.
2. If Weight is missing, no WHZ and WAZ are calculated, and the programme derives only HAZ.
3. If Height is missing, no WHZ and HAZ are calculated, and the programme derives only WAZ.
5. For any child records with missing age (age in months) only WHZ will be calculated.
6. If a child has oedema only his/her HAZ is calculated.
Additional analyses for frequencies, descriptive, correlations, cross–tabulations and regressions
were conducted using SPSS and excel. Indices were expressed both in terms of z scores that
represent the difference between observed weight and median weight of the reference
population expressed in standard deviation. The result of this survey was compared to WHO
standard cut-off points. The IYCF data was analysed to yield data for key indicators in SPSS and
excel.
2.9 Survey data validation process
Data quality was ensured through:
 approval of the methodology by Nutrition Working Group
 Thorough training of all team members for four daysthe majority of the enumerators and
team leaders had prior experience in carrying out nutrition surveys

standardization of interviewing procedures through verbal translation of questions by
survey team members into the local languages spoken in the district during training





standardization of anthropometric measurement procedures
practical sessions on interviewing and anthropometric measurements taking
daily supervision of the teams by IMC staff and Nutrition Coordinator
review of questionnaires on a daily basis for completeness and consistency
plausibility checks from SMART/ENA software specific to each team during daily data
entry

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 of quantitative data using qualitative information-KIIs, secondary data and
observation

Age of children verified by EPI health cards- in the absence of cards, use of height sticks
and the local calendar of events formulated was used to give estimates of the birth month
and year.
2.10 Survey Limitations
There were inherent difficulties in determining the exact age of some children (even with use of
the local calendar of events), as some health cards had erroneous information. This may have led
to inaccuracies when analysing chronic malnutrition. Although verification of age was done by
use of health cards, in some cases no exact date of birth was recorded on the card other than the
date a child first seen at the health facility or just the month of birth. Recall bias may link to
wrong age which then leads to wrong weight for age and height for age indices.
There was poor recording of vitamin A and de-worming in the health cards. Some of the
mothers indicated that their children had received Vitamin A and de-worming while it was not
recorded in the health cards.
2.11 Good Practice
Community mobilization which incorporated a significant part of administrative authority’s
interaction and prior identification of cluster guides by DNO would assist in enhancing
ownership of the outcome results of the survey.
Working closely with a cluster guide that was respected by community members, yielded better
quality data especially on sensitive topics e.g. infant mortality data.
Crosschecking the date of birth with both health card and calendar of local events enhanced the
age verification process
3. RESULTS
3.1 TARGET POPULATION DEMOGRAPHIC CHARACTERISTICS
Overall, the surveyed households had, on average, 5.7 (SD 2.3) members (with a range of 1-15
persons). The mean number of children below 6 months in the households was 0.2 (SD 0.4),
those aged 6-59 months 1.1 (SD 0.8). Polygamy was practised in 8.7% of the households and;
while 8.4% households were single parents the rest 82.9 % practised monogamy. Majority
(80.4%) of the households were being male-headed, 13.3% female-headed and 4.7% of the
respondents reporting that their parents were heading the household.
Table 2: Demographic information of target population
DEMOGRAPHY
Number
Number of HH surveyed
740
Number of children 6-59 months surveyed
709
Number of children 0-23 months surveyed for IYCN
731
Number of children 0-5 months surveyed for IYCN
152
Average number of persons per HH
5.7
S.D = 2.3
Average number of children (0-5 months ) per HH
0.2
S.D=0.4
Average number of children (6-59 months ) per HH
1.1
S.D = 0.8
Table 3: Distribution of age and sex of 6-59 months.
Boys
Girls
Total
Ratio
AGE (months)
no.
%
no.
%
no.
%
Boy:girl
6-17
131
54.1
111
45.9
242
34.1
1.2
18-29
112
49.1
116
50.9
228
32.2
1.0
30-41
47
47.5
52
52.5
99
14.0
0.9
42-53
43
49.4
44
50.6
87
12.3
1.0
54-59
27
50.9
26
49.1
53
7.5
1.0
Total
360
50.8
349
49.2
709
100.0
1.0
The distribution of index children (6-59 months old) by age group and sex was as shown in
Table 3 and figure 1, where both the age group and overall male: female ratios were within the
expected range of 0.8 – 1.214 which is demonstrative of an unbiased under five survey sample.
Of the children measured, 50.8% were boys and 49.2% were girls. Most of the children aged 629 months for IYCN were purposively sampled and this explains why they are many children
between these age groups.
14
Assessment and Treatment of Malnutrition in Emergency Situations, Claudine Prudhon, Action Contre la Faim (Action Against
Hunger), 2002.
Figure 1: Population age and sex pyramid
Child sex
m
60
60
50
50
40
40
30
30
20
20
10
10
0
Child age in months
Child age in months
f
0
40
30
20
10
0
10
20
30
40
Frequency
Numbers
3.2 ANTHROPOMETRIC RESULTS (BASED ON WHO STANDARDS 2006)
The use of the National Centre for Health Statistics (NCHS) references has been phased out and
replaced with the WHO growth standards (WHO-GS). The WHO-GS are structured as a
standard rather than a reference, and are therefore better in the assessment of the nutritional
status of under-fives regardless of child feeding differentials that characterize children in the
community.
3.2.1 Overall Prevalence of Global Acute Malnutrition by WFH Z-scores (WHO Standards)
The WFH index is the most appropriate index to quantify wasting in a population and reflects
the current nutrition/health status of the community. Other than having a true statistical
meaning, the use of z-scores (standard deviation scores) conveys malnutrition rates very
precisely and allows for inter-study comparisons. The WHO Global Database on Child Growth
and Malnutrition uses a Z-score cut-off point of <-2 SD to classify low weight-for-age, low
height-for-age and low weight-for-height as moderate and severe under nutrition, and <-3 SD
to define severe under nutrition. The cut-off point of >+2 SD classifies high weight-for-height as
overweight in children. The information presented below is based on the analyzable sample of
709 eligible children whose plausible anthropometric data were collected. 1.4% of the children
were flagged off the WFH analysis according to the WHO-GS flagging procedures due to
aberrant values
In the complete sample, the prevalence of global acute malnutrition i.e. GAM (z-scores <-2
standard deviations and/or oedema) by WHO-GS (Table 4) was 7.8% (5.2-11.6 CI) while the
prevalence of severe acute malnutrition (SAM) was 1.2% (0.5-2.8 CI). Although the prevalence
of both GAM and MAM was higher among boys than girls, the differences, however, were not
significant as indicated by the p.value of 0.208.
According to age distribution, SAM was highest 2.4 % among age group 42-53 months, while
MAM was highest among age group 54-59 months (table 5). The overall prevalence of GAM in
Meru North County reveals risky situation with aggravating factors in the community according
to WHO benchmarks11. Notably was the measles break out in the district just before the survey
and high morbidity cases in coughing 50% and diarrhoea disease 11.3% which are considered as
aggravating factors15. The major causes of malnutrition reported from FGD were: poverty, lack
of water supply for irrigation and no land to cultivate.
Table 4: Prevalence of acute malnutrition based on weight-for-height z-scores (and/or oedema)
and by sex
Boys
Girls
Total
Ratio
AGE (months)
no.
%
no.
%
no.
%
Boy:girl
6-17
131
54.1
111
45.9
242
34.1
1.2
18-29
112
49.1
116
50.9
228
32.2
1.0
30-41
47
47.5
52
52.5
99
14.0
0.9
42-53
43
49.4
44
50.6
87
12.3
1.0
54-59
27
50.9
26
49.1
53
7.5
1.0
Total
360
50.8
349
49.2
709
100.0
1.0
The prevalence of oedema is 0.3 %
Table 5: Prevalence of acute malnutrition by age, based on weight-for-height z-scores and/or
oedema
Severe wasting
(<-3 z-score)
Age
6-17
244
3
1.2
19
18-29
232
1
0.4
15
)
Oedema
z-score )
No.
no.
Normal
(>= -3 and <-2 (> = -2 z score)
Total
(months
%
Moderate wasting
No.
%
No.
%
No.
%
7.8
222
91.0
0
0.0
6.5
214
92.2
2
0.9
Table 6: Distribution of acute malnutrition and oedema based on weight-for-height z-scores
<-3 z-score
11
15
>=-3 z-score
ACUTE MALNUTRITION BENCHMARKING SYSTEM FOR GLOBAL HUMANITARIAN RESPONSE ,WHO (2000):
WHO (2002). The management of nutrition in major emergencies
Oedema present
Marasmic kwashiorkor
Kwashiorkor
Oedema absent
Marasmic
Not severely malnourished
No. 0 (0.0 %)
No. 6 (0.9 %)
No. 2 (0.3 %)
No. 684 (98.8 %)
This table shows that 6 children (0.9%) are severely wasted (marasmus) with no oedema. While
2 children 0.3% had kwashiorkor with oedema present.
3.2.2Prevalence of Acute Malnutrition by MUAC
Another measurement used to determine a child’s nutritional status is the mid-upper arm
circumference (MUAC) measurement. Because MUAC measurements require a simple, colourcoded measuring band rather than weighing scales and height boards, they are often used
during crisis situations and as a rapid screening tool for admission into nutrition intervention
programmes. Useful for children between six months and five years of age, a MUAC
measurement of less than 12.5 cm indicates that a child is suffering from moderate acute
malnutrition. If the MUAC measurement is under 11.0 cm, however, the under-five child’s life
may be in danger as he or she is suffering from severe acute malnutrition. Compared to WFH zscores, the mid-upper arm circumference (MUAC) is not a very sensitive indicator of acute
malnutrition and tends to overestimate acute malnutrition for children below one year of age.
However, used, Overall, MUAC usually tends to indicate lower GAM levels compared to WFH zscores. The findings (Table 7) indicate that overall, 9.9% suffered from GAM (MUAC <12.5cm),
9.6 % suffered from MAM (MUAC >=11.5 and <12.5cm ) and 3% (0.3-1.8 CI) suffered from
SAM (MUAC <11.5cm), with 27.3% of the under 5 years being at risk of malnutrition (MUAC
>=12.5 and <13.5cm ).Analysis by age group shows that a high number of children between the
age of 6-11 months are at risk of malnutrition.
Table 7 Prevalence of acute malnutrition based on MUAC cut off's and/or oedema
<-3 z-score
>=-3 z-score
Oedema present
Marasmic kwashiorkor
Kwashiorkor
Oedema absent
Marasmic
Not severely malnourished
No. 0 (0.0 %)
No. 6 (0.9 %)
No. 2 (0.3 %)
No. 684 (98.8 %)
Figure 2: Prevalence of acute malnutrition by age, based on MUAC cut off's and/or oedema
Acute Malnutrition expressed in MUAC in Age Groups
160
148
Number of cases
140
120
99
100
83
Severe Acute Malnutrition
70
80
Moderate Acute Malnutrition
60
40
20
35
29
18
12
34
At Risk of Malnutrition
712
6
04
12-23
months
24-35
months
01
8
16
Healthy
23
0
6-11
months
36-47
months
48-59
months
under 5 years age group
3.2.3 Prevalence of Underweight by Weight-for-age Z-scores (WHO-GS)
The weight-for-age (WFA) index provides a composite measure of wasting and stunting and is
commonly used to monitor the growth of individual children in EPI health cards since it enables
mothers to easily visualise the trend of their children’s increase in weight against age. A low
WFA is referred to as underweight. The prevalence of underweight among the children was
14.2% (11.5-17.4 CI) while 2.1% (1.3-3.6 CI) were severely underweight as shown in Table 8
More boys than girls suffered from global underweight as well as severe underweight. The
difference is extremely significant as indicated by p.Value of 0.004. AS shown in table 9, children
in age group 42-53 months were more affected as compared from the other age groups.
Table 8: Prevalence of underweight based on weight-for-age z-scores by sex
All
Boys
Girls
(100) 14.2 %
(65) 18.2 %
(35) 10.1 %
95% C.I.)
95% C.I.)
95% C.I.)
(85) 12.1 %
(54) 15.1 %
(31) 8.9 %
95% C.I.)
95% C.I.)
95% C.I.)
(15) 2.1 %
(11) 3.1 %
(4) 1.2 %
C.I.)
C.I.)
C.I.)
n = 705
Prevalence of underweight
(<-2 z-score)
Prevalence of moderate underweight
(<-2 z-score and >=-3 z-score)
Prevalence of severe underweight
(<-3 z-score)
n = 358
n = 347
(11.5 - 17.4 (13.9 - 23.4 (7.0 -
(9.7 -
14.9 (11.4 - 19.7 (5.8 -
14.4
13.5
(1.3 - 3.6 95% (1.5 - 6.1 95% (0.4 - 3.0 95%
Table 9: Prevalence of underweight by age, based on weight-for-age z-scores
Severe
Moderate
(<-3 z-score)
(>= -3 and <-2
underweight
Age
Total
No.
6-17
242
7
18-29
224
30-41
Oedema
(> = -2 z score)
z-score )
No.
%
No.
%
No.
2.9
32
13.2
203
83.9
0
0.0
3
1.3
20
8.9
201
89.7
0
0.0
99
1
1.0
6
6.1
92
92.9
0
0.0
42-53
87
3
3.4
17
19.5
67
77.0
0
0.0
54-59
53
1
1.9
10
18.9
42
79.2
0
0.0
Total
705
15
2.1
85
12.1
605
85.8
0
0.0
(months
)
no.
%
underweight
Normal
%
3.2.4 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 thus 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 (Table 10) indicated an overall global chronic malnutrition (GCM) rate of 29.5 %
(26.1-33.1 CI) and a severe chronic malnutrition (SCM) rate of 7.8 % (6.2-9.9 CI). The results
showed that the differences were significantly (p. value 0.009), more boys than girls suffered
from both GCM and SCM.
Table 10: Prevalence of stunting based on height-for-age z-scores and by sex
All
Boys
Girls
(207) 29.5 %
(120) 33.6 %
(87) 25.2 %
95% C.I.)
95% C.I.)
95% C.I.)
(152) 21.7 %
(82) 23.0 %
(70) 20.3 %
95% C.I.)
95% C.I.)
95% C.I.)
(55) 7.8 %
(38) 10.6 %
(17) 4.9 %
C.I.)
95% C.I.)
C.I.)
n = 702
Prevalence of stunting
(<-2 z-score)
Prevalence of moderate stunting
(<-2 z-score and >=-3 z-score)
Prevalence of severe stunting
(<-3 z-score)
n = 357
n = 345
(26.1 - 33.1 (28.3 - 39.4 (20.7 - 30.3
(19.0 - 24.6 (18.4 - 28.3 (16.7 - 24.4
(6.2 - 9.9 95% (7.9 -
14.2 (3.1 - 7.9 95%
Table 11: Prevalence of stunting by age based on height-for-age z-scores
Severe stunting
Moderate
(<-3 z-score)
Normal
stunting
(>= -3 and <-2
(> = -2 z score)
z-score )
Age
Total
No.
No.
%
No.
%
6-17
239
21
8.8
65
27.2
153
64.0
18-29
224
21
9.4
42
18.8
161
71.9
30-41
99
5
5.1
13
13.1
81
81.8
42-53
87
5
5.7
23
26.4
59
67.8
54-59
53
3
5.7
9
17.0
41
77.4
Total
702
55
7.8
152
21.7
495
70.5
(months
)
no.
%
Table 12: Mean z-scores, Design Effects and excluded subjects
Indicator
n
Weight-for-
Mean
z- Design Effect z-scores not z-scores out
(z-score < -2) available*
of range
690 -0.31±1.13
1.18
2
17
Weight-for-Age
705 -0.93±0.98
1.00
2
2
Height-for-Age
702 -1.38±1.14
1.00
0
7
Height
scores ± SD
* contains for WHZ and WAZ the children with edema.
The table above indicates the flagged values due to aberrant values for WFH, WFA and HFA.
3.3 ADULT NUTRITIONAL STATUS
The MUAC measurements of 697 eligible primary childcare givers (15-49 years old) were taken
to assess their nutritional status. The survey findings showed that of the 697 total, 4.3% were
pregnant, 63. % were lactating, and 32.7% were neither lactating nor pregnant .6.9% (n=48) of
caretakers had MUAC <21cm meaning that they are at risk of malnutrition/have chronic energy
deficiency (CED). Among the pregnant and lactating sub-group, 3.3% and 4.8% of subgroup
have MUAC<21.0 and therefore have severe chronic energy deficiency. 11.4% of women not
pregnant or lactating had CED (MUAC<21.0). The admission criteria into SFP in adult is
MUAC<21.0 for pregnant and lactating mothers of children <6 months old. The magnitude of
under-nutrition was high among non-pregnant women compared to those who were pregnant.
Pregnancy imposes a big nutrient-need load on mothers, which in the absence of adequate extra
nutrients leads to utilization of body nutrient reserves leading to malnutrition. Gestational
malnutrition leads to low birth weights and may ultimately culminate in poor child growth and
development, thus there is an urgent need to address high rates of malnutrition among pregnant
women. The figures above indicate that pregnant women and lactating mothers in the district
are relatively more vulnerable to malnutrition compared to their non-pregnant counterparts.
Poor adult nutritional status is a key indicator to household food insecurity. High figures of
malnourished pregnant and lactating mother carry a risk of growth retardation of the foetus and
consequently low birth weight.
Figure 3. Nutrition Status of caregivers of < 5 year old children:
Nutrition Status of caregivers of < 5 year old children:
11.4
Percentages of caregivers
12.0
10.0
8.0
6.9
6.0
4.0
4.8
3.3
% MUAC<21
2.0
0.0
Pregnant
Lactating
Not pregnant nor
lactating
Total
Maternal physiological status
3.4 MATERNAL HEALTH CARE INFORMATION.
Overall, 87.7 % of mothers reported having attended MCH clinics and received the necessary
care and advice including iron folate supplementation during their last pregnancy with a mean
frequency of 3.2 (SD 1.2) clinic visits. 6.8% never attended MCH clinics and the rest 5.6% never
delivered. Despite the high ANC uptake only 55.3 % of the women delivered in the hospital,
28.3% delivered at home with assistance from traditional birth attendants (TBAs), 8.0% delivered
at home without assistance, and 1.8% delivered at home with assistance from nurse. Some of the
Major reason as to why they did not attend ANC clinics were : they were not aware of the
importance of ANC (32.0%),TBA services are adequate (14%) ,cultural barriers (8%) ,health
facility was too far ( 6%) and unfriendly health worker (4%) .
The participation of TBAs in child deliveries is currently discouraged by WHO because the
services they offer fall short of the minimum care that delivering mothers should receive.
However, in many remote areas where there is limited access to conventional health care, they
might be the only practical care that delivering mothers have access to. It is, therefore,
recommended that children who are born outside a health facility setup should be taken to a
health facility within 2 weeks of birth to allow for optimal health check-up and administration
of the zero dose polio antigens. On the whole, only (36%) of the children delivered at home were
taken for medical attention within the recommended 2-week period.
Maternal vitamin A supplementation within 2 weeks after birth is crucial and recommended by
WHO as a means to boost its content in breast milk as well as promote maternal recovery
following delivery. 42 % of mothers reported having received vitamin A supplementation
following their last delivery. 34.7% and 34.6% of the mothers were given de-wormers and
iron/folate tablets respectively during their last pregnancy.
On average most health facilities are located 3.2 (SD 2.6) km away . The amount of time spent
outside the home by mothers has a direct influence on both the quality and quantity of care that
mothers are able to give to their children, which influences child health, growth and
development. It also influences willingness and ability to access and utilize medical care services.
3.5 CHILD FEEDING, CARE AND HEALTH
3.5.1 Infant and Young Child Feeding Practices
The findings indicate that practically all children (98.1%) were reported to have breastfed. The
main reason for children who were not breastfed was that there was no milk from the mothers
breast. Benefits of timely initiation of breastfeeding and therefore provision of colostrum include
stimulation of the onset and maintenance of lactation as well as provision of necessary maternal
antigens to the infant through colostrum. The proportion of infants reportedly put on the breast
within the first hour of birth was 86.3%, with 66.4% of them reported having received colostrum
during the first 3 days of birth. 14.4% of the infants were reportedly given pre-lacteals. Giving
pre-lacteals interferes with optimal establishment of breastfeeding and may also give rise to
infections such as diarrhoea in infants. Among infants given pre-lacteals, the most frequently
given item (Figure 4) was plain water (88 %), followed by infant formula 5%, sugar/glucose
water or honey 3%, Gripe water 3% and finally by animal milk and its products (1%) and
Hospital delivery would help in curbing the practice of giving pre-lacteals to infants.
Figure 4:Pre-Lacteals given in the first three days of birth
lacteals given in the first three days
4%
3% 3%
2%
Plain water
Infant formula
Sugar/glucose water
Gripe water
Animal products
88%
Practically all (99.3%) of the children less than 6 months were reported to have been
breastfeeding during the survey. However, the frequency of breastfeeding fell short of the ‘on-
demand’ rule only 13.2% were breastfed more than 12 times during the preceding day. The
WHO recommends that infants should be breastfed at least twice every 2 hours, which translates
to 12 times a day. Exclusive breastfeeding was computed among infants who had not received
pre-lacteals and were not on other foods. The findings revealed that 53% were exclusively
breastfed compared to a national average of 31.9%16 according to the Kenya Demographic and
Health Survey (KDHS) report. Out of those who were not exclusively breastfed, the average age
when the weaning started was 99day (SD 58 days) with only 16.9% weaned at the WHO
recommendation of 6 months. The findings of the FGDs revealed that the main reason cited for
early weaning was to ‘prevent child from crying as the mothers seek casual labour, this is
because children are left at home without breast milk’ .It was also revealed that the main type of
food babies are introduces to is porridge because it is cheap and easy to swallow. Early weaning
increases the risk of infections in young children, with the foods given being nutritionally
inferior to breast milk, which ultimately aggravates malnutrition.
After 6 months children should receive other foods in addition to breast milk since the nutrients
from breast milk alone cannot meet all the needs for accelerated growth and development. The
findings indicated that 10.6% of the children aged 6-24 months had stopped breastfeeding,
indicating that maintenance of breast feeding up to 2 years was maintained only for 89.7% of the
children. The foodstuffs given to children between the ages of 6-24 months are referred to as
complementary foods. Assessment of complementary feeding was therefore computed for
children above 6 months. Dietary diversity is a qualitative measure of food consumption that
reflects household access to a wide variety of foods, and is also a proxy of the nutrient intake
adequacy of the diet for individuals. Dietary diversity scores (DDS), were created by summing up
16
Kenya National Bureau of Statistics (June 2010): Kenya Demographic and Health Survey.
the number of food groups consumed the previous day to aid in understanding if and how the
diets are diversified. According to the Food and Agricultural Organization (FAO), dietary
diversity scores are meant to reflect, in a snap shot, the economic ability of a household to
consume a variety of foods17. A score of 1 was allocated to each of the 8 food groups that were
consumed by the child and a score of 0 for each of the food groups not consumed and thus the
highest possible score was 8. Children who had consumed less than four food groups were
classified as the low dietary diversity group and those with a score of 4 or more as high dietary
diversity group. The dietary diversity questionnaire tool was based on the 24-hour food intake
recall.
On average the mean food diversity was 3.2 (SD 1.6) given to children > 6 months. The findings
showed that 64.2% of the children samples consumed low dietary diversity of less than four
groups, a threat to optimal child growth and development while only 35.8% of the households
had children >6 months who consumed 4 or more of the food group. 63.7% of children > 6
month who were still breastfeeding at the time of the survey consumed 3 or more food groups
while 31.9% of non-breastfeeding children consumed 4 or more food groups. The mean
frequency of feeding children between age 6-8 months was 3.2 (SD 1.2) and between age 9-23
months was also 3.2 (SD 0.9). An analysis of the food groups taken by children (Figure 5)
indicates that relatively low proportions took eggs (4%). and meat products (5%). The food group
taken by the highest proportion of children was carbohydrates (30%), Vitamin A rich foods
(18%), Dairy products (16 %%), legumes (14%), and fruits and vegetables (13%).The reason
given from FGD for low intake of dairy and meat products was that there were no enough dairy
animals in the area and most of the households lacked enough money to buy milk and meat.
Figure 5 food groups taken by children 6-23 months in the previous 24 hrs
17
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
Food groups taken by children in the previous 24
hours
f
o
o
d
Eggs
4
Meat, poultry, fish, sea food
5
Fruits/ vegetables
13
g Pulses / Legumes/ Nuts and Seeds
r
Dairy products
o
Vitamin-A rich
u
Grains, roots or tubers
p
0
s
14
16
18
30
5
10
15
20
25
30
35
percentage of food groups
3.5.2 Child Immunization, Vitamin A Supplementation and Deworming
Child immunization is crucial as it prevents and/or reduces the severity of certain diseases in
young children. The immunization coverage rates for polio 1 was (97.8%), polio 3 (95.8%) and
measles (85.1 %) were commendably high and above the Kenya Expanded Programme on
Immunization (KEPI) recommendation of 80%. Vitamin A supplementation is carried out as part
of routine disease treatment in health facilities in Kenya. From the survey, an overall 65.7% of the
under 5 years were reported to have received vitamin A supplementation. 58.5 % of those who
received Vitamin A were aged 6-11 months while 66.7 % where in the age group 12-59 months.
Deworming is crucial in warding off the debilitating effects that helminthic infections cause
among growing children.53.1 % of children reported to have been dewormed. The high measles
coverage can also be explained as a fact that there was an on –going measles campaign in Meru
north district at the time of the survey and therefore most of the children had been immunized at
the time.
Table 13: Vaccination coverage: OPV 1 & 3 for 6-59 months and measles at 9 months and
deworming for 12-59 months
Measles
OPV 1
n=651
OPV 3
n=697
Deworming
n=697
(12-59
Months)
N=603
YES
with
With
with
With
with
With
with
With
n=279
from
n=360
from
n=347
from
n=91
from
card
Recall
mother
card
n=275
%
42.9
42.2
Recall
mother
card
n=322
51.6
46.2
Recall
mother
card
n=321
49.8
46.1
Recall
mother
n=229
15.1
28
Table 14 Vitamin A coverage
Vitamin A
Vitamin A
Vitamin A
N=697
N=94
received twice in the
6-59 months
6-11 months
12-59
months
(
last 1 year)
N=603
65.6%
58.5%
66.7 %
3.5.3 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. A good proportion (44.6%) of the underfives was reported to have been sick. The most prevalent illness affecting the under-fives were
cough 50% , followed by malaria (21.9% )then diarrhoea (11.3%) and finally by measles (2.3%).
The health seeking behaviour by mothers of sick children was assessed by asking the respondents
what they did the last time their under-five child was sick. During the last episode of illness, the
majority (56.9%) of mothers reportedly took the children to public health facilities, 25.4% sought
assistance from private clinics or pharmacies, 13.4% did not get any assistance, and 2.9 % bought
medicine from shops/kiosks while the rest 0.3% each sorts assistance through CHW and mobile
outreaches.
Of the children who had diarrhoea 30.8% were given Oralite, 15.4 % zinc, 5.1% both zinc and
ORS,12.8% home- made salt/sugar and 35.9% did nothing to the child .
Table 15: Symptom breakdown in the children in the two weeks prior to interview (n=309)
Symptoms
6-59 months
Cough
50.0 %
Malaria
21.9%
Diarrhoea
11.3 %
Measles
2.3 %
Other
14.5 %
3.6 SUPPLEMENTARY AND THERAPEUTIC FEEDING PROGRAMME COVERAGE
The point coverage for both SFP and OTP was estimated using WFH z-scores, which are
currently recommended for screening and admitting children into the programmes. In the
survey sample and according to the WFH z-scores index, out of the 46 children who were
moderately malnourished, 39 of them were reported to have been enrolled in the SFP
programme. The point coverage for the SFP (estimated as the number of moderately
malnourished children (39) in the programme) divided by the total number of moderately
malnourished children found during the survey (46) is therefore 84.8 % with a mean duration of
23 days (SD 13) Likewise, the point coverage for OTP is estimated as the total number of children
suffering from SAM (8 ) found during the survey divided by number of children suffering from
SAM enrolled into the programme (4), which translates to 50% coverage with mean duration of
10.1 days (SD 18.5). SPHERE18 recommends a minimum 60% coverage for community nutrition
intervention programmes.
SFP coverage = Children registered in SFP
x 100
Children registered in SFP+ children with WHZ<-2 z-score and >=-3z-score that are not
enrolled
OTP coverage = Children registered in OTP
x 100
Children registered in OTP + children with WHM=<-3 z-score that are not enrolled
3.7 INSECTICIDE TREATED MOSQUITO NETS (ITN) HOLDING RATES AND UTILIZATION
The MoMS provides free insecticide treated mosquito nets (ITNs) to expectant mothers attending
MCH clinics. 58.8 % of the households reported having mosquito nets, most (89.6%) of which
had been sourced from the MoMS or Mission hospitals, while 7.8 % and 0.9 % had obtained the
nets from shops and non-governmental organizations (NGOs), respectively. The nets obtained
from hospitals and NGOs are treated with long-term insect-repelling chemicals while the ones
obtained from shops or vendors may not be treated, which makes it necessary to wash them in
the chemicals to repel mosquitoes and other insects. The proportion of households that reported
treating nets they had obtained from shops was 38.9%. The reported utilization of the nets
during the night preceding the survey was highest (84.6%) among the under-fives followed by
fathers of children (73.7%), mothers (72.8%), children above five years (46.8%) and pregnant
women (6.7%).
3.8 WATER, SANITATION AND HYGIENE PRACTICES
There were several sources of water for household use reported by the survey respondents.
33.2% and 31.7% of the households got water from tap for general use and drinking
18
The SPHERE Project Handbook (2004). Humanitarian Charter and Minimum Standards in Disaster Response.
respectively. Other sources of water reported for general use and drinking were; Rivers,
unprotected well, boreholes. Only 0.3 % used rain water for drinking purposes. The findings
show very minimal treatment of drinking water at the household level with 67% did not treat
water before drinking, 30 % boiled drinking water while 3% used chemicals to treat their water.
Clearly the role of untreated water as the main cause of childhood diarrhoea and subsequent
levels of acute malnutrition cannot be underestimated.On average, it takes a caregiver about
41.75 minutes (SD 45) to access their main source of water and use 97.8 (SD 55.5) litres of
water per day (which translates to about five 20-litre jerricans). Households buying water in
jerricans paid on average Kshs 7.49 (SD 14.2) per 20-litre jerrican. Communities should be
encouraged to boil their drinking water at the household level, being the most viable and cheap
method.
85.4% of the HH had access to toilet facilities. Of those households with toilet facilities, majority
74.1% used traditional pit latrines, 10% used ventilated improved latrines, and 0.9% used
buckets while 1.1% used other types of toilets. For the households with no toilet facility, bush
50% and open field 17%) were the major alternative methods used while 3% went behind their
houses. It was also confirmed through observation that a significant proportion of children’s
feaces are also disposed of hygienically (65.7%), and 63.1% of the compounds were clean. 64.9%
of the mothers reported washing their hands with soap, 29.0% said they wash hands but without
soap while the rest 6.1% don’t wash hands. Of those who wash hands; majority 38.2% washed
hands before eating, 35.9% after visiting the toilet, 20.7% before food preparation while the rest
5.2 % after changing baby’s diapers. This makes it necessary to educate the community on the
health implications of unhygienic faecal disposal. Washing of hands before handling food should
also be given greater attention for example through health education messages since 20.7% of
the mothers reported not washing hands before handling food.
Figure 6: House hold water sources for general and domestic use
Household water uses
percentage Usage
35.0
33.2
31.732.0 31.6
30.0
25.0
20.0
14.6
14.0
15.0
10.0
8.5 9.6
6.5 6.2
5.0
3.7 3.4
0.8
0.7
1.8
0.3
0.3
0.3
0.3
0.0
0.3
0.2
0.0
Water Sources
General use
Drinking
Figure 7 household water treatment methods.
Methods of Water treatment
3%
30%
Nothing
Boiling
67%
Add chemicals
3.9 HOUSEHOLD FOOD SECURITY
3.9.1 Sources of Income
Overall, the three main source of income during the previous 3 months preceding the survey in
Meru North were: wage labour 48%, sale of own crop 17% and petty trade 11%. Majority of
inhabitants in Meru north plant miraa as a cash crop which is harvested throughout the year.
Other sources of income included: Salaried employment, sale of charcoal/firewood, Sale of
livestock, Sale of livestock products, Brewing, Remittances and Weaving/basketry which
accounted for 10.8%.The mix of income sources is reflective of the varied livelihood activities in
the larger district including crop farming and pastoralist activities. The survey also showed on
average each household has one person (SD 0.7) who earned money that directly benefited the
household. Within the wealth ranking system, the bigger majority is ranked as medium 49.3%
and poor 46.9%. The findings from FGD showed that the ranking criteria were based on if the
household has cattle, tea estate or assets in terms of rental houses. FGD findings also revealed
Majority 75% of the community was poor with only 25% categorized as rich.
Majority 58.3% of the inhabitants owned livestock. Of those who reported they had livestock
40% reported that the number of livestock had not changed, 30% had reduced and 27.5% had
increased. The main reason given as to why the number of livestock had reduced and increased
were: the livestock were sold and animals gave birth respectively. Findings from FGD revealed
that most of the livestock were thin and emaciated due to lack pasture. The lack of pasture was
due lack of enough rain and no land to cultivate pasture
Figure 8 Sources of Income
Source of income
Wage labour
Sale of own crop
Petty trade
Business
Other
Salaried employment
Sale of charcoal/firewood
Sale of livestock
Sale of food ration
Sale of livestock products
Brewing
3.9.2 Household Dietary Diversity and Food Sources, food Aid
The mean of meal frequency usually taken by household was 2.7 (SD of 0.6) times while the one
reported for the previous day prior to survey was 2.6 (SD 0.7).71.4 % of the household usually
have meal frequency of >3 meals a day while 66.1% households reported having had >3 meals a
day the previous day of the survey. From the survey 99.2 % of the household use iodized salts.
Figure 9 Frequency of meals taken in household
Frequency of meals intake in households.
80.0
70.7
65.7
Percentage of household
70.0
60.0
50.0
40.0
usual meal frequency
24.125.1
30.0
Day preceeding survey
20.0
10.0
4.4
8.8
0.7 0.3
0.0 0.1
4
5
0.0
1
2
3
Frequency of meals intake
At the household level, the dietary diversity score (DDS) is indicative of the ability to acquire a
variety of foods, including foods that may not have high nutrient value such as beverages and
condiments. The previous 24-hours’ food intake by mothers was used as a proxy to assess
household dietary diversity in this survey. Food intake by caretakers is a good estimation of the
variety of what other members of the households took (excluding the U5s). The 12 major food
groups inquired about are cereals, fish and sea food, roots and tubers, vegetables, fruits, meat
and poultry , eggs, legumes, milk and milk products, fats and oils, sugar and sweets, condiments
and miscellaneous(spices, sweets, unsweetened beverages). A diverse diet was indicated by
consumption of four or more food groups
On average the mean Individual Diet Diversity Score was 4.1 (SD 1.5) for the number of food
groups consumed. Overall, majority (66.1%) of the caregivers consumed at least four food
groups in the previous 24 hours (above the threshold for a diverse diet). However, 33.9% HH had
a low diet diversity score of <=3, which highlights serious food insecurity.
A high proportion (78.0%) of households reported that all members took the meals prepared the
previous day, with the main reason given for those who did not take meals at home being that
they had taken their meals elsewhere (69.7%), lack of adequate food in the household (18.3%)
and lastly 11.3% said food was not suitable. Figure 9 shows that the most common foods
consumed by the households were Cereals and cereal products, Pulses / legumes / nuts and seeds
and Fats and oils. The least consumed foods groups were fruits, meat and poultry, eggs and fish
which each contributed to 1%. The uncharacteristic low consumption of meat, Vegetables and
fruits was explained in FGDs by that fact that they were inaccessible because of increased prices.
In addition, lack of sufficient nutritional knowledge on the importance of the consumption of
food groups such as vegetables, fruits, eggs and pulses due to cultural reasons that shape food
selection habits, also attributed to the low consumption of these food groups.
Figure 10 Ratio of foods groups consumed in 24-hour recall
1% 1% 1%
1% 1%
Ratio of food consumed
7%
Cereals and cereal products
24%
Pulses / legumes / nuts and
seeds
Fats and oils
10%
Milk and milk products
Vegetables
11%
15%
13%
Sugars / Honey and
commercial juices
Roots and tubers
Fruits
15%
Table 16 shows that 70.3% of the households purchase food and 28.35 got it from their own
production while only 0.4% borrowed food. This shows that sharing between households is not
such a common occurrence. Within the last three months only 7% of the households received
general food aids which lasted them a mean of 2.4 (SD 3.4) days. Of those who had received food
aids , the biggest amount of foodstuff received was maize 65.4 %, with households reporting
receiving, on average, 2.8 (SD 4.8) kgs, followed by beans 44.2% receiving an average of 0.7( SD
0.95) Kgs, rice 34.6% receiving an average of 0.63 (SD 0.98) kgs, and finally received vegetable
oil on average 0.17 (SD 0.3 litres).
Table 16: Main Sources of food consumed in 24 hr recall
Food source
percentage
Purchase
70.3
Own production
28.3
Gift from relatives
0.9
Borrowed/credit
0.4
Totals
100
81% of responded reported that they cultivated land, on average 0.9 (SD 1.2) acres was
cultivated. Of those who reported having cultivated land the major food crop harvested was
maize 88.7%, followed by Beans 68.4%, cowpeas 5.8 and finally green grams 4.3% .The table
below shows the percentage of food crop shared, sold and available in the stores. According to
the responses given during FGD, food availability was scarce due to the drought, lack of water
for irrigation the scarcity of land to be cultivated. Food was available in the market but the prices
were high and therefore hindering them to purchase.
Table 17:proportion of food crops shared sold and stored after harvesting.
Food crop
%shared
%sold
%Available
Maize
39
19.7
50
Beans
25.4
12.9
25.4
Cow peas
1.7
0.7
1.3
Green grams
2.8
1.3
2.5
store
in
During the previous 2-month period, close to half (45.8%) of the sampled households reported
having experienced a food shortage. The sample population reported having various coping
strategies. The table belows shows top 10 coping strategies reported by the respondent. It was
reported from FGD that sell of livestock as a coping strategy was mainly done when there was
severe food shortage.
Table 18: top ten coping strategies
Coping Strategies
Coping Strategies
%
Reduction in size of meals
14.8
Reduction in the number of meals per day
13.3
Borrow food from friends/beg
8.8
Skip food consumption for an entire day
8.6
Purchase food on credit
6.8
Sale of charcoal
2.4
Restrict consumption of adults to allow more 1.8
for children
Swapped consumption to less foods/preferred
1.5
Individual migration out of the area
0.6
Consume wild foods
0.3
3.10 MORTALITY RESULTS
The recall period for questions relating to the mortality questionnaire was 90 days (3 months)
from the start date of the survey. Both the crude mortality rate (CMR) of 0.24 deaths/10,000/day
and the under-five mortality rate (UFMR) of 0.48 deaths/10,000/day were within the acceptable
levels for emergency situations16; (table 19).The major cause of death among the under 5 years
was not known the second major been ARI (25%).The major cause of death above the 5 years of
age was accident/ the person was killed (25%).
Table 19: Mortality rates
CMR (total deaths/10,000 people / day
0.24 (0.11-0.56) (95% CI)
U5MR (deaths in children under five/10,000
0.48 (0.14-1.59) (95% CI)
children under five / day
Table 20: Causes of death among under/above 5 years
Causes of Death
>5 years
<5 years
diarrhoea
12.50%
0.00%
ARI
12.50%
25.00%
Malaria
12.50%
0.00%
Killed/accident
25.00%
0.00%
Not known
12.50%
75.00%
Old age
12.50%
0.00%
Others
12.50%
0.00%
Totals
100.00%
100.00%
Waterly
16
The Sphere Standards, 2004. Under Five Mortality Rate (U5MR): emergency threshold is 2.3/10,000/day, Alert 1.0/10000/day
4. CONCLUSION
Malnutrition is a major health problem, especially in developing countries. Water supply,
sanitation and hygiene, given their direct impact on infectious disease, especially diarrhoea, are
important for preventing malnutrition. Both malnutrition and inadequate water supply and
sanitation are linked to poverty. Other underlying factors causing malnutrition are morbidity,
inadequate health and nutrition programme coverage and poor IYCF practices (breastfeeding,
food frequency and dietary diversity).
The study identified aggravating factors that had a negative bearing on optimal under-five
nutritional status and their caregivers:

Poverty and issues of who controls family income have a heavy contribution to
household food security. Income sources are not diversified and therefore there’s over
reliance on farm produce both as an income source and family food. Poverty has also
made it difficult to access food from markets due to insufficient financial resources. Lack
of water supply in many parts of Meru North districts especially in Igembe North
division has led to infectious diseases spreading, causing childhood diarrhea, which leads
to major malnutrition and subsequent death due to diarrheal dehydration

Poor agricultural practices including cultivation of Miraa in most areas whose income
does not translate into food security. This is further compounded by poor soil fertility as
a result of poor farming practices and environmental degradation.

Lack of access to food.Most major food and nutrition crises do not occur because of a
lack of food, but rather because people are too poor to obtain enough food.

Poor child and adult dietary profiles. Over-consumption of certain food group like
cereals usually goes along with deficiencies in essential vitamins and minerals.

High child morbidity prevalence reported to have affected 44.6% of the under-fives
which was found to significantly affect child nutritional status;

Poor IYCF practices including early weaning, low maintenance of breast feeding and
poor feeding practices.

Poor access to medical facilities some are too far for household to access. On average
most health facilities are located 3.2 (SD 2.6) km away.

Poor water sanitation status in the community with minimal treatment of unsafe
drinking water at the household level increase vulnerability to infectious and waterborne diseases, which are direct causes of acute malnutrition.
5 .RECOMMENDATIONS
Because malnutrition has many causes, only multiple and synergistic interventions embedded in
true multi-sectoral programs can be effective. A variety of actions both immediate and long term
solutions are needed:
Immediate Interventions

Addressing the poor access to essential health and nutrition services by strengthening the
integrated outreach component- primarily focusing on regular medical outreach
camps/mobile clinic. This will help to intensify active case finding of malnourished
children and manage them accordingly.

Strengthen programmes and strategies currently addressing infant and young child
nutrition (IYCN) with a view to improving the protection, promotion, and support of
optimal IYCF. Viable action points include:

As the HINI program is rolled out there is need for continual monitoring of both facility
and community based interventions to track progress while also documenting the
process to assess the trends in the outcomes as well as impact indicators. Particular
attention should go to improved maternal nutrition, iron/folate supplementation during
the prenatal period and ensuring ORS/zinc support for diarrhoea.

Strengthening of hygiene practices to reduce the incidence of diarrhoeal disease
associated with contaminated water in the household including health education to
educate the community on domestic treatment of drinking water and effective hand
washing (soap/ash) after helping a child in the latrine, during food preparation and
before child feeding. This should be backed-up with provision of free water treatment
chemicals where feasible.

Continued water trucking to areas affected by water stress by Ministry of Water and
Irrigation and Kenya Red Cross especially in Igembe north District.


Provision of water purification chemicals for water treatment at Household level
Advocacy/public health campaigns on domestic water treatment such as boiling of
drinking water and use of purification chemical to minimise risks of water-borne
diseases, should be carried out.

The Ministries of Public Health and sanitation and Medical services in collaboration with
other stakeholders in the district to initiate and offer concrete support in the
implementation of strong awareness campaigns and community based health and
nutrition programs with special focus on infant and young child feeding practices,
dietary diversification, food preparation and preservation, consumption of energy dense
and micronutrient-rich foods and kitchen gardening. Women should be the prime
targets of these. Nutrition messages should address strategies/ways of improving access
to locally available and cheaper sources of fat, protein and micronutrients.
Long-Term Interventions

Focus on programmes by ministry of agriculture that improve and sustain dietary
diversity and consumption of micronutrient.-rich foods. And advising farmers on good
farming methods .By improving agricultural yields, farmers could reduce poverty by
increasing income as well as open up area for diversification of crops for household use.

To address the issues of limited access to safe water, there is a need to establish water
points in areas where water is inaccessible.

MOH should increase access to health facilities in the rural parts of kenya by adding
more health facilities or increasing CHW. These will improve hospital deliveries and
access to medical services for those who cannot access the health facilities
6. APPENDICIES
Appendix 1: IYCN calculator
Sample Size IYCF
calculator Meru North.xls
Appendix 2: Household Questionnaire
Final Household
Questionnaire.doc
Appendix 3: Anthropometric Questionnaire
Final 6-59 months
Questionnaire.doc
Appendix 4: IYCN Questionnaire
Final IYCF
Questionnaire.doc
Appendix 5: Mortality Questionnaire
Final Mortality
Questionnaire.doc
Appendix 6: Focus Group Discussion guide
Final FGD
Questionnaire.doc
Appendix 7: Plausibility checks..........
meru north
plausibility check.rtf
Appendix 8: Assignment of Clusters
selected clusters
Meru North District.xlsx
Appendix 9: Map
Appendix 10. Summary of findings
Characteristic
% ( 95% CI)
Overall GAM (WFH <-2 Z score or presence of oedema) - WHO 2006
7.8% [5.2 – 11.6]
Overall SAM (WFH <-3 Z score or presence of oedema) - WHO 2006
1.2% [0.5 – 2.8]
Overall underweight (WFA <-2 Z score or presence of oedema) - WHO
14.2% [11.5 – 17.4]
Overall Severe underweight (WFA <-3 Z score or presence of oedema)-WHO
2.1% [1.3 – 3.6]
Overall stunting (HFA <-2 Z score)- WHO
29.5% [26.1 - 33.1]
Overall Severe stunting (Height for age <-3 Z score) -WHO
7.8% [6.2 – 9.9]
Prevalence of GAM by MUAC (<12.5cm)
12.6%
SFP Programme Coverage (Period Prevalence Estimate)
84.8%
OTP Programme Coverage (Period Prevalence Estimate)
50%
Proportion of children sick two weeks prior to survey
44.6%
Measles* immunization (card and confirmation)
85.1%
OPV1 immunization (card and confirmation)
97.8%
OPV3 immunization (card and confirmation)
95.8%
Vitamin A supplementation coverage
65.6%
Proportion of children dewormed
52.6
Proportion of malnourished women (MUAC<21.0cm)
2.2%
Proportion of malnourished pregnant and Lactating women (MUAC <21.0cm)
7.3%
Hospital Delivery
55.3%
Timely initiation of breastfeeding (children 0-23 months)
86.3
Exclusive breastfeeding under 6 months
53.3
Continued breastfeeding at 1 year
89.4
Minimum dietary diversity
2.8
Minimum meal frequency
3.2
Toilet coverage
85.4
Household that treat water before drinking
33%
% of caregivers wash hands with soap
64.9%
Under-five mortality rate (deaths/10000/day)
0.24[0.11-0.56]
Crude mortality rate (deaths/10000/day)
0.48 [0.14-0.59]