NUTRITIONAL ANTHROPOMETRIC AND MORTALITY SURVEY CHILDREN UNDER FIVE YEARS OF AGE FINAL REPORT MATHARE AND PART OF KASARANI DIVISIONS NAIROBI

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1 NUTRITIONAL ANTHROPOMETRIC AND MORTALITY SURVEY CHILDREN UNDER FIVE YEARS OF AGE FINAL REPORT MATHARE AND PART OF KASARANI DIVISIONS NAIROBI 17 TH NOVEMBER 25 TH NOVEMBER 2008 Funded by 1

2 ACKNOWLEDGMENTS On behalf of Action Against Hunger USA (ACF-USA), the authors would like to express their deep gratitude to the Ministries of Public Health and Sanitation; Medicals Services and the Kenya National Bureau of Statistics for releasing 9 of their staff from Nyando, Kajiado, Eldoret, Muranga, Maragua, Kilifi, Nairobi North, Nyeri and Nairobi Districts to participate in the Mathare survey, We would like to thank ACF-USA staff, particularly the management team at the Nairobi office for the preparation of the survey, logistics, personnel and administrative issues and fieldwork without which this survey would not have been possible. Furthermore, we would like to thank the local logistician for Mathare for all the ground work he did to enable our movement and safety within the Mathare slums; all team members (measures, data recorders and team leaders) who were involved in ensuring the survey obtained good quality data. Thanks also to all the drivers who ensured timely movement of field staff. Special thanks go to the chiefs of all the divisions in Mathare and the elders of all the villages surveyed in Mathare slums for allowing us to carry out the survey. We also thank the villagers in Mathare for welcoming us in their villages and supporting us during the survey. We finally like to say many thanks to the mothers and the fathers who pleasantly allowed the teams to measure their children and patiently sat through the interviews and shared with the team valuable information. For the funding of the surveys Action Against Hunger USA thanks the United Nations Children and Educational Fund (UNICEF) 2

3 TABLE OF CONTENTS.I. EXECUTIVE SUMMARY... 5.II. INTRODUCTION... 9.III. METHODOLOGY III.1 Type of survey and sample size Data collection IV. RESULTS OF THE ANTHROPOMETRIC SURVEY IV.1 Anthropometric results IV.2 Distribution by age and sex IV.4 Immunization coverage IV.5 Composition of the households V. RESULTS OF THE RETROSPECTIVE MORTALITY SURVEY VI. DISCUSSION AND CONCLUSION VII. RECOMMENDATIONS VIII. APPENDIX A: Sample size and cluster determination for mathare slum B: Anthropometric survey data form, nutrition survey mathare slum, november C: Household Mortality D: Questionnaire for mortality rate calculation (one sheet/cluster) E: Local events calendar mathare survey nov F: Plausibility check mathare nutrition survey NCHS

4 LIST OF ABBREVIATIONS ACF AIDS CHW CMR EPI GAM GoK HH HIV MS MoH MUAC NCHS OTP SAM SD SFP SMART SPSS TFC U5MR UNICEF WFH WFP WHO NGOs FBOs CBOs Action Contre la Faim, Action Against Hunger Acquired Immune Deficiency Syndrome Community Health Worker Crude mortality rate, Crude death rate Expanded Programme on Immunisation Global acute malnutrition Government of Kenya Household Human Immunodeficiency Virus Microsoft Ministry of Health Mid-upper arm circumference National Centre for Health Statistic Outpatient Treatment Programme Severe acute malnutrition Standard deviation Supplementary Feeding Programme Standardized Monitoring and Assessment of Relief and Transition Statistical Package for Social Science Therapeutic Feeding Centre Under-five mortality rate, Under-five death rate United Nations Children and Educational Fund Weight-for-Height World Food Programme of the United Nations World Health Organisation Non Governmental Organizations Faith Based Organizations Community Based Organizations 4

5 .I. EXECUTIVE SUMMARY Mathare slum is the second largest slum in Kenya located in Nairobi. It is part of Nairobi North District. Mathare is located in East Nairobi, and is home to about a half a million people (MSF France, 2008). Mathare is part of the Starehe constituency in East Nairobi. The constituency is located in the triangle delimited by 3 roads going to East Nairobi and suburbs; Jogoo road in the East, Juja road linking Pangani to Kariobangi in the South and Thika road in the North. There are several slums in the area; the main one is Mathare Valley. This is bordered by other estates; Pangani (West), Eastleigh (South), Mathare North and Huruma (east). The population of the greater Mathare area is estimated to be around 500,000; the Mathare valley slum dwellers were estimated to be about 250,000 (Habitat, 2003). Mathare slum is divided into 10 units or villages spreading on both sides of the Getathuru river (1, 2, 3, 4A, 4B, 10). The whole slum is 2 kilometers by 300 meters (1.2 miles by 0.2 miles). Mathare Valley can be divided into four levels: 1). The better off part has their houses built in stone near the main road; they look much more costly than the shanty huts. They have rooms for small businesses and for living quarters. 2) The middle class is a combination of stone structures and shanty mud huts or iron sheets. 3) The poor are living in iron sheets structures built by individuals and tiny mud shanties. 4) The very poor in the bottom of the valley. Along the river are tightly squeezed together and usually overblown or destroyed during the rainy season and entire families swept away by the river. Waste from the upper levels buildings rushes down into the valley, adding to the already accumulated filth and human excrement. Source: MSF-France 5

6 The predominant ethnic group is Kikuyu (22%), followed by Luo (17%), Luhya (16%), and Kamba (13%) and Uganda (8%) in smaller proportion. There is a strong ethnic discrepancy as most of the Kikuyus are in village 2 and Kosovo, and the majority of Luo and Luhya in villages 4A, 4B, Mabatini, Gitahuru and Mathare 10. Only villages 3A, 3B and 3C are really mixed. Source of income for the residents varies. Majority of the residents are self employed in the informal sector, or are casual laborers and traders in household consumables feature prominently amongst the male and female residents respectively with incomes average of Kshs 90 per day (according to Habitat report, 2003). A traditional illicit brew, chang aa is brewed and sold to local here, and has become a common source of livelihood to many residents of Mathare. The area falls under the Nairobi North District, and gets its services from the Nairobi City Council. There are two health facilities in the area falling under the Ministries of Medical Services; and Public Health and Sanitation. There are also several Non Governmental Organizations (NGOs), Faith Based Organizations (FBOs), Community Based Organizations (CBOs) and other institutions that are operating on the ground to improve the livelihood of the residents of Mathare. Table 1 below shows some of these organizations. Table 1: UN agencies, International NGOs and GoK ministries operating in the area MSF-France Nairobi City Council Ministry of Local Ministry of Health Runs HIV program and youth group counselling. Run health facilities and nutrition centres. Runs Administrative activities in Mathare Runs health services through Mathare North Health Centre Due to the recent food crisis and the vulnerability of the slum dwellers to the raising high cost of living UNICEF in collaboration with the Ministry of Health in the frame of a capacity building exercise on nutrition assessment choose Mathare as part of a practical exercise as well as to assess the potential impact of the food price rise on the most vulnerable population in urban setting. No other nutrition survey was done in the slum hence the survey also acted as a baseline for nutrition information. The survey was conducted from 17 th to 25 th November The SMART methodology was used in the planning, training, field data collection and analysis of the anthropometric and mortality data during the survey. OBJECTIVES OF THE SURVEY The objectives of the surveys were: To assess the prevalence of acute malnutrition in children aged 6-59 months To estimate the crude and under five mortality rate To estimate the coverage of measles among targeted children To estimate the coverage rate of vitamin A capsules distributions To identify the underlying causes and factors of malnutrition METHODOLOGY USED FOR THE SURVEY Standardized Monitoring and Assessment of Relief and Transitions (SMART) methodology was utilized in the implementation of the nutritional anthropometric survey. Children aged 6-59 months formed the target group. During the planning phase accessible population figures of all 6

7 villages in Mathare Valley slums were employed to derive sample size as tabulated below. A total of 36 clusters were sampled from the 26 villages comprising the Mathare Valley area. At least 18 children were measured in each cluster and 35 households enumerated for mortality. In total, 786 children were covered. For the mortality survey, a total of 1455 households were visited covering 6159 residents. Table 2: Population Figures, Prevalence, Precision and Sample Sizes, Mathare Slums Anthropometric Mortality survey Population Estimated prevalence ± desired precision % Design effects 2 2 Sample sizes The anthropometric sample size was increased by 10% to cater for unforeseen contingencies. The final sample size of 786 children was divided by 205 to obtain 36 clusters. In each selected cluster, teams moved to the center of the village and spun a pen. This determined the starting direction upon which teams walked to the edge. At the periphery of the village, the pen was re-spun. This time round; households at an arm s length along the pointed direction were counted till the end. Simple balloting was used in determining the starting point (household). In every selected household, both the anthropometric and mortality questionnaires were administered accordingly. The subsequent households were determined through proximity. All eligible children were assessed till a target of 18 was obtained. Ages of the children were estimated through use of birth cards and also by use of calendar of events. 1 20% of the total accessible population. 2 Total accessible population in Mathare 3 Total present now to be included in retrospective mortality survey 4 Minimum number of children aged 6-59 months measured per cluster. 7

8 SUMMARY OF FINDINGS Nutrition and Mortality Survey Results The final analysis included 761 children after exclusion of 27 children due to incoherency according NCHS 1977 reference table. Analysis in reference to WHO 2005 reference included 751 children (37 exclusions). Table 3: Results Summary INDEX INDICATOR RESULTS6 NCHS(1977) WHO(2005) MUAC Z- scores % Median Z-scores % Median Height >=65 cm Global Acute Malnutrition W/H< -2 z and/or oedema Severe Acute Malnutrition W/H < -3 z and/or oedema Global Acute Malnutrition W/H < 80% and/or oedema Severe Acute Malnutrition W/H < 70% and/or oedema Global Acute Malnutrition W/H< -2 z and/or oedema Severe Acute Malnutrition W/H < -3 z and/or oedema Global Acute Malnutrition W/H < 80% and/or oedema Severe Acute Malnutrition W/H < 70% and/or oedema Global Acute Malnutrition (<120mm) Severe Acute Malnutrition (<110mm) Total crude retrospective mortality (last 3 months) /10,000/day Under five crude retrospective mortality /10,000/day Measles immunization coverage (N= 730 children 9months old) By card According to caretaker 7 Not immunized 4.1% [2.7% -5.5%] 0.7% [0.0% - 1.4%] 2.1% [0.9% - 3.3%] 0.5% [ %] 3.9% [2.5% - 5.2%] 0.5% [0.0% - 1.2%] 0.8% [0.0% - 1.6%] 0.5% [0.0% - 1.2%] 1.6% [0.6% - 2.3%] 0.3% [0.0% - 0.6%] 0.31 [ ] 0.61 [ ] 47.3% [43.6% %] 43.2% [39.6% %] 9.6% [7.5% %] 6 Results in bracket are at 95% confidence intervals. 7 When no EPI card was available for the child at the household, measles vaccination information was collected according to the caretaker/ mother of child 8

9 .II. INTRODUCTION Mathare is part of the Starehe constituency in East Nairobi. The constituency is located in the triangle delimited by 3 roads going to East Nairobi and suburbs; Jogoo road in the East, Juja road linking Pangani to Kariobangi in the South and Thika road in the North. There are several slums in the area; the main one is Mathare Valley. This is bordered by other estates; Pangani (West), Eastleigh (South), Mathare North and Huruma (east). The population of the greater Mathare area is estimated to be around 500,000; the Mathare valley slum dwellers were estimated to be about 250,000 (Habitat, 2003). The origin of Mathare slum are attributed to the following factors: 1) migration during the struggle for independence; 2) rural-urban migration; 3) urban population growth without housing provision; 4) resettlement due to new developments; 5) upgrading or relocation in suitable sites; and 6) extension of city boundaries. The population size according to focus groups and individual interview with the village elders is 443,000 people in 139,000 households whereby a household is defined as a group of persons sharing the same income sources and eating together. The average families size is 3.9 for the whole slum area. Mathare Valley can be divided into four levels: 1) The better off has their houses built in stone near the main road; they look much more costly than the shanty huts. They have rooms for small businesses and for living quarters. 2) The middle class is a combination of stone structures and shanty mud huts or iron sheets. 3) The poor are living in iron sheets structures built by individuals and tiny mud shanties. 4) The very poor in the bottom of the valley. Along the river are tightly squeezed together and usually overblown or destroyed during the rainy season and entire families swept away by the river. Waste from the upper levels buildings rushes down into the valley, adding to the already accumulated filth and human excrement. In terms of employment, about 56% of the households have casual jobs or small scale business and 13% have regular jobs. Unemployment is high amongst the population of the slum and the presence of an unemployed member in a household is strongly correlated with poverty. Under/unemployment is a common problem amongst the single father, youth and bachelor men and ladies blamed for high crime rates, especially in villages like Kosovo and village 2 where 67% to 80% are involved in criminal activities (e.g., burglaries, shoplifting, robbery, smuggling of stolen goods, mugging, hijacking, etc.). Mathare slum has experienced a huge amount of violence throughout years. On all levels, social, political or economical, the population of the slum was left aside with no perspective. Coping strategies such as prostitution, criminality or brewery are spread to the entire population which is 9

10 represented by more than 50 % of great poverty. Single mothers and child s community are the most vulnerable social categories, forced to use prostitution as the main source of income (an average around 30 to 50 % in both categories) with high risks of HIV/AIDS.III. METHODOLOGY III.1 Type of Survey and Sample Size Two-stage cluster sampling using SMART methodology was applied to randomly identify clusters with the probability of being selected proportional to the population size in each cluster. Population data of all accessible villages in the survey area was obtained from the MSF-France Draft Rapid Assessment of Mathare slum, April The geographical units and their respective population were then entered into Nutrisurvey for SMART software October 2007 for cluster selection. A total of 36 clusters were sampled from the 26 villages comprising the Mathare Valley area. At least 18 children were measured in each cluster and 35 households enumerated for mortality. In total, 786 children were covered. For the mortality survey, a total of 1455 households were visited covering 6159 residents. The total population for all accessible villages in the 36 clusters in the surveyed area was estimated as following: Table 4: Population Figure, Prevalence, Precision and Sample Sizes, Mathare slums Anthropometric survey Mortality survey Population 88, ,000 Estimated prevalence ± desired precision % Design effects Sample sizes The anthropometric sample size was increased by 15% to cater for unforeseen contingencies. The final minimum sample size of 662 children was divided by 20 to obtain 33 clusters. Considering the high risks of clusters not being accessible (security reasons mainly), 3 extra clusters were added for safety, leading the total to 36 clusters of 20 children. A total of 788 children were finally surveyed during the exercise. At the first stage, the sample size was determined by entering necessary information into the ENA for SMART software for both anthropometric and mortality surveys. The information included estimated population sizes, estimated prevalence rates of mortality and malnutrition, the desired precision and design effect. In each selected cluster, teams moved near the centre of the village and spun a pen. This determined the starting direction towards which the teams walked to the edge. At the village s periphery, the pen was respun. This time round; households at an arm s length along the pointed direction were counted till the end. Simple balloting was used in determining the starting point (household). In every selected household, both the anthropometric and mortality questionnaires were administered accordingly. The subsequent households were determined through proximity. All eligible children were assessed till a target of 18 was 10

11 obtained. Ages of the children were estimated through use of birth cards and also by use of calendar of events. Measurers and data collectors (field participants) were subjected to a standardization test to ascertain their capability in taking accurate and precise measurements, so as to minimize errors during data collection Data Collection III.2.1 Anthropometrical survey For each eligible child aged 6-59 months, information was collected during the anthropometric survey using an anthropometric questionnaire. The information included (See appendix). Age: determined with a birth card. In cases where the caretaker did not have a birth card for their children, a local calendar of events that had been developed for this purpose was used to ascertain the age. (See appendix) Sex: recorded as m for male and f for female Weight: Children were weighed to the nearest 100 g with a bathroom Scale of 25 kg. All scales were checked daily by using a standard weight of 5 kg and adjusted to 0 before each measurement. Both boys and girls were measured while undressed. For the children who were difficult to measure while undressed, minimum clothing was ensured while taking the measurements. If the caretaker refused to have the child weighed by the above described methodology, child s own cloth was used to adjust the scale to zero. The child was then redressed to be weighed. Height: children were measured on a measuring board (precision of 0.1cm). Children less than 85cm were measured lying down on the measuring board, while those greater than or equal to 85cm were measured standing up. Mid-Upper Arm Circumference: MUAC was measured in cm at mid-point of left upper arm (between olecranon and the acromion process) to the nearest 0.1 cm with a non-stretchable tape. Bilateral Oedema: assessed by the application of moderate thumb pressure for at least 3 seconds to both feet (upper side). Only children with bilateral oedema were recorded as having nutritional oedema. Measles vaccination: Measles vaccination status for children aged 9-59 months was copied from their vaccination cards. If no card was available at the time of the survey, the caretaker was asked if the child had been immunized against measles or not. For children with confirmed immunization (by date) on the vaccination card, the status was recorded as C (Card) otherwise as N (No). Oral confirmation without proof was recorded as M (Mother confirmed). N was also recorded if the child was less than 9 months old. 11

12 III.2.2 Mortality survey Each family selected at random (even if there was no child aged 6-59 months), was asked to state all family members and indicate their age and sex. The family was then asked to indicate which of the listed family members were present now and at the beginning of the recall period, which members joined or left during the recall period, and whether there was any birth or death in the family during the recall period. The recall dates were from 15 th (mid) August 2008 to 25th November 2008, hence a recall period of around 100 days. III.2.3 Qualitative data The following key informants were interviewed to generate relevant information in their areas of jurisdiction: District Medical Officer of Health District Nutritionist Area Chiefs III.2.4 Indicators, Guidelines, and Formula s Used Acute Malnutrition Weight for Height Index Acute malnutrition rates are estimated from the weight for height (WFH) index values combined with the presence of oedema. The WFH indices are expressed in both Z-scores (standard deviation or SD score) and percentage of the median, according to both, NCHS 8 and WHO references 9. The complete analysis is, however, done with the NCHS reference. The expression in Z-scores has true statistical value and allows inter-study comparison. The percentage of the median, on the other hand, is commonly used to identify children eligible for admission to feeding programmes. Guidelines for the results expressed in Z-score: Severe acute malnutrition.wfh < -3 SD and/or existing bilateral oedema Moderate acute malnutrition.wfh < -2 SD and -3 SD and no oedema Global acute malnutrition..wfh < -2 SD and/or existing bilateral oedema Guidelines for the results expressed in percentage of median: Severe acute malnutrition.wfh < 70 % and/or existing bilateral oedema 8 NCHS: National Center for Health Statistics (1977) NCHS growth curves for children birth-18 years. United States. Vital Health Statistics. 165, WHO reference,

13 Moderate acute malnutrition.wfh < 80 % and 70 % and no oedema Global acute malnutrition..wfh < 80 % and/or existing bilateral oedema Mid-Upper Arm Circumference (MUAC) The weight for height index is the most appropriate index to quantify wasting in a population in emergency situations where acute forms of malnutrition are the predominant pattern. However, the mid-upper arm circumference is a useful tool for rapid screening of children at a higher risk of mortality. MUAC measurements are significant for children with a height of 65 cm or one year and above. The guidelines are as follows: MUAC < 110 mm MUAC 110 mm and <120 mm MUAC 120 mm and <125 mm MUAC 125 mm and <135 mm MUAC 135 mm severe acute malnutrition and high risk of mortality moderate acute malnutrition and moderate risk of mortality high risk of acute malnutrition moderate risk of acute malnutrition adequate nutritional statuses III.2.5 Mortality Mortality data was collected using Standardized Monitoring and Assessment of Relief and Transition (SMART). The crude mortality rate (CMR) is determined for the entire population surveyed for a given period. The CMR is calculated using Nutrisurvey for SMART software for Emergency Nutrition Assessment. The formula below is applied: Crude Mortality Rate (CMR) = 10,000/a*f/ (b+f/2-e/2+d/2-c/2), Where: a = Number of recall days 10 b = Number of current household residents c = Number of people who joined household d = Number of people who left household e = Number of births during recall 10 See chapter 3.2 for specific recall days used in each survey 13

14 f = Number of deaths during recall period The result is expressed per 10,000-people / day. The thresholds are defined as follows 11 : Crude Mortality Rate (CMR): Alert level: Emergency level: 1/10,000 people/day 2/10,000 people/day Under Five Mortality Rate (U5MR): Alert level: Emergency level: 2/10,000 people/day 4/10,000 people/day III.2.6 Field Work The survey was carried out by four teams, each team comprising five members i.e. 1 team leader, 2 data collector (Field Participants) and 2 measurers. 3 of the 4 team leaders were Trainer of Trainers from the Ministry of Medical Services and the Kenya National Bureau of Statistics. 1 team leader and the 8 data collectors were MoH staff from various Districts throughout the country. The field participants underwent training on the SMART methodology for a period of 5 days at Jumuia Conference in Limuru prior to the start of the survey. This was a capacity building training to provide them with theoretical and practical approach for using SMART methodology and ENA software in conducting surveys. Local measurers were recruited for the survey with the help of the local logistician for Mathare. A total of 8 local measures were recruited who were residents of Mathare slum and were familiar with the situation in the slum. The local measurers underwent 2 day training on standardization of equipment and accurate taking of measurement. They also assisted in developing the local calendar of events to be used during the survey period. All field participants and local measures performed a standardization test and also participated in a pilot in a village in Mathare that had not been included in the actual survey sample. All teams were closely guided and supervised during their field work throughout the whole survey time by the ACF Nutritionist with help from the team leaders and local logistician. The survey (including training, data collection and travelling) were carried out in a time period of 16 days. III. 2.7 Data Analysis Data was entered on a daily basis into ENA database by the team leaders and analyzed for plausibility for immediate feedback to the field teams next morning. Data processing and analysis for both, anthropometric and mortality were carried out using Nutrisurvey for SMART software, October Health and nutrition information systems among refugees and displaced persons, Workshop report on refugee s nutrition, ACC / SCN, Nov

15 version with both, NCHS and WHO references. MS Excel was used to carry out analysis on MUAC, measles immunization coverage, and household composition..iv. RESULTS OF THE ANTHROPOMETRIC SURVEY.IV.1 Anthropometric results The final analysis included 761 children after exclusion of 27 children due to incoherency according NCHS 1977 reference table. Analysis in reference to WHO 2005 included 751 children (37 exclusions). Only 758 children were included in the age groups calculations as 3 data showed age missing..iv.2 Distribution by Age and Sex The distribution of the nutrition survey sample by sex and age group shows a total boy/girl sex ratio of 1.1 which is within the normal limits ( ). Similarly, sex ratio within the age groups indicates a normal distribution. Table 6. Distribution by age and sex in Mathare Boys Girls Total Ratio N % N % n % Boy / girl 6-17 months months months months months Total

16 Fig. 1 Distribution by age group and sex Distribution by age and sex, Mathare anthropometric survey, Nov boys girls IV.3 Anthropometric Analysis Distribution of Acute Malnutrition in Z-Scores In the age groups sample, the prevalence of global acute malnutrition was 3.5%, severe acute malnutrition 0.1%. Table 7: Weight for Height distribution by age groups in Z-scores, Mathare, November 2008 (NCHS Reference) Age (months) N Severe wasting (<-3 z-score) Moderate wasting (>= -3 and <-2 z-score ) Normal (> = -2 z score) Oedema N % N % n % n % Total As shown in Table 8 below 4 cases of nutritional oedema were found in the surveyed population. 16

17 Table 8: Weight for height vs. oedema in Mathare, November 2008 (NCHS Reference) <-3 z-score >=-3 z-score Edema present Marasmic kwashiorkor Kwashiorkor Edema absent Marasmic Normal Fig. 2 & 3 show the weight for height distribution curves of the survey sample in Z-scores for both the NCHS and the WHO reference populations. The entire weight for height distribution curve of the sample is very slightly shifted to the left. The mean Z-score was 0.00 ± 1.07 indicates a suboptimal nutrition status compared to the NCHS reference population, while the mean reached 0.00 ± 1.02 when comparing to the WHO reference population. These results indicate a nutritional status very close to the normal. Fig. 2 & 3 Z-scores distribution Weight-for-Height, Mathare, November 2008, WHO and NCHS standards 17

18 Table 9: Global and Severe Acute Malnutrition in Z-score Global acute malnutrition Severe acute malnutrition NCHS Reference 4.1% [2.7% -5.5%] 0.7% [0.0% - 1.4%] WHO Reference 3.9% [2.5% - 5.2%] 0.5% [0.0% - 1.2%] Distribution of Malnutrition in Percentage of the Median Table 10. Distribution of Weight/Height by age groups in percentage of the median in Mathare (NCHS Reference) Age (months) N Severe wasting (<70% median) Moderate wasting (>=70% and <80% median) Normal (> =80% median) Oedema N % N % n % n % Total Table 11: Global and Severe Acute Malnutrition in % of the median 18

19 Global acute malnutrition Severe acute malnutrition NCHS Reference 2.1% [0.9% - 3.3%] 0.5% [ %] WHO Reference 0.8% [0.0% - 1.6%] 0.5% [0.0% - 1.2%] Risk of Mortality: Children s MUAC All children measured with a height >= 65 cm were included in the MUAC analysis (Table 13). According to the MUAC 0.3 % of the children were found to be severely malnourished, 1.5 % were under acute malnutrition criteria and 11.9 % were found at risk of malnutrition (>=120 and <135mm). Table 12: MUAC distribution in Mathare MUAC (mm) >= 65 cm to >=75 cm to >=90 cm height Total < % 1 0.3% 0 0.0% 2 0.3% 110<= MUAC< % 1 0.3% 0 0.0% 9 1.2% 120<= MUAC< % 3 0.9% 0 0.0% % 125<= MUAC < % % 6 2.6% % MUAC>= % % % % TOTAL % % % % IV.4 Immunization coverage All children who were greater or equal to 9 months of age and whose measurements were taken were included in the measles immunization coverage analysis. Results in table 14 below indicate that 47.3% of the children had been immunized by card, 43.2% of the children had been immunized according to the caretaker, and 9.6% of the children had not received any measles immunization. 19

20 Table 13: Measles Immunization Coverage for Mathare Measles immunization coverage N=595 children >9 months old By card 47.3% (43.6%-50.9%) According to caretakers 43.2% (39.6%-46.7%) Not immunized 9.6% (7.5%-11.7%) Table 14 below gives an outline of households visited in the surveyed area. Most households in the area surveyed had children who were below 5 years of age. Households without children under five were mainly inhabited by single adults male/female or newly wedded couples. Empty houses were as a result of people having gone to work or other engagements, and children gone to school. In total of 1129 households had children less than five years, while 326 households did not have children less than five years of age. A total of 1455 households were surveyed. 100% of the households surveyed during anthropometry data collection were residents. Table 14: Household Status Mathare N % Households with children < % Households without children < % Total % IV.5 Composition of the households The survey showed a percentage of under five which is normal for developing countries (Table 16). Average number of people in a household was measured at 4.2 (Table 17). 20

21 Table 15: Age group proportion Age groups Mathare N % Less than 5 years % More than 5 years 4, % Total 6, % Table 16: Household Composition Average number of people per household Average number of <5 per household Mathare

22 .V. RESULTS OF THE RETROSPECTIVE MORTALITY SURVEY Mortality rates with a recall period of three months 12 were calculated from the figures collected from families with or without children under 5 years and are presented in Table 18 below. Table 17: Demographic information Demographic data Mathare Current resident HH 6,096 Current resident < 5 years old 1,506 People who joined HH 262 < 5 years old who joined HH 87 People who left HH 223 < 5 years old who left HH 31 Birth 60 Death 17 Death < 5 years old 8 Recall period (days) 90 CMR (Deaths /10,000 people/day) 0.31 [ ] U5MR (Deaths in children<5/ 10,000 / day ) 0.61 [ ] Both, CMR and U5MR are below the alert levels of 1/10,000 and 2/10,000 per day, respectively. This could be attributed to the fact that there are regular child welfare campaigns in the area such as the Day of the African Child and Malezi Bora campaigns conducted by Ministry of Health annually which sensitize mothers on good child care practices for their children. The accessibility to health facilities to some of the villages surveyed such as the Mathare North Clinic, Blue House Clinic, and Baraka Feeding Centre have played a role in promoting the welfare, health and nutrition status of children as they offer screening and treatment of severely malnourished children. 12 Specific recall period in days for the survey is indicated in the appendices 22

23 .VI. DISCUSSION AND CONCLUSION The prevalence of Global Acute Malnutrition (GAM) in Mathare was found to be 4.1% [2.7%- 5.5%] (NCHS 1977), while the prevalence of Severe Acute Malnutrition (SAM] was found to be 0.7% [0.0%-1.4%] (NCHS).These figures are below the emergency rates. Though the malnutrition is below the emergency cut off the cases of malnutrition are quite high as a result of high density population, with the current rates it means that over 3,600 children are estimated to be moderately malnourished while 625 are severely malnourished according to NCHS Z-score, these numbers are alarming given that also 4 Oedemas were detected in the survey, that are hard to find in many surveys in Kenya. It has to be noticed that the rates of GAM in z-score are similar between the NCHS reference and the WHO reference. Such situation has been noticed through many nutrition surveys. Further analysis is necessary, considering a large number of nutrition surveys, in order to provide a proper analysis of the comparison between the two references. The comparison between the NCHS % of the median and the WHO z-score however shows a significantly higher GAM rate when using the WHO standards which would have a significant impact on the attendance in nutritional centres depending on which criteria is used for the admission of the malnourished children. According to the survey results the chronic malnutrition (stunting) was 31.6% [27.8%-35.4%] those below - 2 Z-scores (NCHS), according to WHO classification the severity of chronic malnutrition is considered to be high. This is an indication the urban poor are suffering from chronic malnutrition clear sigh of poverty Measles immunization coverage among children more than or equal to 9 months of age was investigated during the survey. Measles immunization was found to be very high at 47.3 %( confirmed by card), and 43.2% (according to caretaker). The percentage of children who were not immunized was low, at only 9.6 %. The high rates of measles immunization could be attributed to the mothers awareness on the importance of immunizing their children through attending regular clinics/hospitals and also through sensitization campaigns from institutions operating on the ground through their community health workers. Total crude retrospective mortality (last 3 months)/10000/day was found to be 0.31%. Under five crude retrospective mortality (U5MR) /10 000/day was found to be 0.61%. Retrospective mortality rates (CMR and U5MR) are shown to be below their respective alarming levels, and are therefore acceptable. 23

24 Factors that determine the nutritional status of children under fives years Lack of access to adequate health care services There are very few health care centres for the high population in this area. In some of the poorest villages surveyed, people lacked knowledge on the available healthcare facilities where they could take their children for immunization and other crucial health care services. Lack of safe drinking water and poor sanitation facilities Availability and accessibility of safe water for household use is a major problem in Mathare valley slums. There was no apparent presence of clean piped water within the slum during the time of the survey. The villagers obtain their water from common water tanks positioned around the villages. Open sewage flows freely through and in between the housing structures in the slums. The situation is made even worse by the lack of toilets or pit latrines. A lot of human waste could be seen along the paths separating the housing structures, and even right outside people houses. This could be attributed to lack of toilets/pit latrines in the area. Uncollected garbage lie every where. This has attracted a lot of flies and other animals. In such pathetic conditions, it would be almost impossible for the slum dwellers to access any reasonable form of clean safe water for household use. Food insecurity High unemployment rates and the accompanying high poverty levels are very common among Mathare slum dwellers. The recent soaring prices of commodities such as food, fuel and other basic household needs such as housing has aggravated the situation. The purchasing power of most people has been reduced due to this inflation making them unable to afford basic needs such as food rations. Food insecurity can also be caused by unequal food distribution within the household itself. In some homes, most of the food is eaten by adults, especially the household head, while children are given very little or none at all. For the children who attend school where there are no feeding programmes going on, they spend a lot of time hungry. The children whose parents are ailing from HIV/AIDS infection, they are also condemned to hunger as they have no one to fend for them. Lack of knowledge on nutrition/malnutrition and health issues Majority of the mothers and care givers have inadequate knowledge on nutrition and health issues. This can be attributed to the low level of education among the slum dwellers. They lack adequate knowledge on importance of exclusive breasting for children for at least the first six months of life, good nutritious foods for weaning children, importance of eating a well balanced diet for pregnant and lactating mothers and good cooking methods of their foods. Therefore, food consumed by children is little and of poor quality predisposing children to a high risk of malnutrition as they lack essential nutrients required for their optimal growth. Lack of knowledge on risk factors associated with malnutrition and associated diseases can also be attributed to the malnutrition that was found in some children. Poor child care and feeding practices 24

25 High poverty levels, alcohol abuse, prostitution and high rates of unemployment are very common in the Mathare valley slums. The hygiene and sanitation situation is very low. In cases where women are involved in alcohol abuse, prostitution or in cases where they live under extreme poverty situation, this tends to affect their child rearing and feeding practices. This results in poor breastfeeding for infants and younger children, reduces the number of meals and/or amount of food prepared taken during the day by children and also no proper hygiene practices for their children..vii. RECOMMENDATIONS The prevalence of Global Acute Malnutrition (GAM) in the surveyed area for children 6 to 59 months of age was found to be 4%. This is below the alarming rate of 15% for children below 5 years of age. However, the situation needs to be addressed, as even with low rates, the very high density of population leads to a high number of acutely malnourished children. Factors such as poor health and nutrition practices, poor hygiene and sanitation practices, high poverty levels, and food insecurity normally act in combination to determine the nutritional status among children. Below are some recommendations aimed at improving the nutritional status of children in the surveyed area. Health and nutrition To develop programmes aimed at improving health and nutrition education to households through community health workers (CHWs), schools, churches, women and youth groups, and at any other levels so as to enable the people to understand and appreciate the role that good nutrition practices play in life To ensure adapted access to screening and treatment for severely and moderately malnourished children at the nearest clinics and health centres To integrate nutrition treatment activities in the existing health facilities to ensure sustainability in the long run Instituting an elaborate program on the promotion of infant care practices with emphasis on breastfeeding and weaning. To capacity-build the MoH staff attached to the area on the screening and treatment of malnourished children Water, Hygiene and Sanitation The water, hygiene and sanitation status of Mathare valley slum is wanting. There should be urgent measures by relevant stakeholders to curb the situation through: Provision of clean tap water to the villages Initiation of programmes aimed at educating the villagers on the importance of observing good hygiene practices Expansion of sanitation programmes such as water protection, proper garbage disposal and safe human waste disposal. 25

26 Food Security The villagers are mostly food insecure at the household level due to the high rates, of unemployment, diseases such as HIV/AIDS that robe many adults the inability to be actively involved in employment, high rates of alcohol and changaa abuse and the accompanying extreme poverty levels. This can be controlled by: Encouraging the establishment of Income Generation Activities (IGA) within the slums to improve the access to income hence enhancing food security. 26

27 .VIII. APPENDIX A: Sample Size and Cluster Determination for Mathare slum Villages surveyed and clusters assigned Geographical unit Population size Assigned cluster Village 3A ,2 Village 2C ,4 VILLAGE 2B Village 3B ,7 Village 3C ,9 Manoki ,11 Mabatini/Mashimoni ,13 Kwa Nungari ,15 Thayu/Mtoni ,17 Mathare Mashimoni ,20 Kosovo/DP/CDF Kosovo/Daraja Kosovo/Shooting range Village Kwa Ndururu Village 2B Village 4B ,28 Village 4A Mathare North Area ,31 Mathare North Area ,33 Mathare North Area ,35 Mathare North Area

28 B: Anthropometric survey data form, Nutrition survey Mathare slum, November 2008 Division: Location: Village: Date: Cluster number: Team number: Child No. HH no. Sex (F/M) Age in months Weight ##.# kg Height ###.# cm Weigh-forheight % Oedema (Y/M) MUAC ##.# cm Vaccination (C, M, N) Remarks Signature: (Team leader) Target number of children per cluster: Name: 28

29 C: Household Mortality Household Mortality Questionnaire (one sheet/household) Division: Location: Village: Cluster number: HH number: Date: Team number: ID HH member Present now Present at beginning of recall (include those not present now and indicate which members were not present at the start of the recall period ) Sex Date of birth/or age in years Born during recall period? Died during the recall period Tally (these data are entered into Nutrisurvey for each household): Current HH members total Y in col 2 Current HH members - < 5 Current HH members who arrived during recall (exclude births) X in col 3 Current HH members who arrived during recall - <5 Past HH members who left during recall (exclude deaths) X in col 2 Past HH members who left during recall - < 5 Births during recall Birth in col 3 and 6 Total deaths Dead in col 2 and 7 Deaths < 5 29

30 D: Questionnaire for mortality rate calculation (one sheet/cluster) Division Location: Village: Date: Cluster number: Team number: N Current HH member Current HH members who arrived during recall (exclude births) Past HH members who left during recall (exclude deaths) Births during recall Deaths during recall Total < 5 Total <5 Total < 5 Total < Signature of Team leader: Target of number of people present now: 30

31 E: Local Events Calendar Mathare Survey Nov 2008 MONTH SEASONS MAIN ACTIVITIES JANUARY HOT SEASON Post election violence FEBRUARY MARCH HOT SEASON HOT SEASON Valentine Valentine Valentine Valentine Valentine Mathare Area Restriction Michuki Matatu Rules/Matheri killed Simon Matheri killed Grand Coalition Kibaki/Raila APRIL LONG RAINS School holidays/easter/fools School holidays/easter School holidays/easter School holidays/easter School holidays/easter School holidays/easter MAY LONG RAINS JUNE JULY AUGUST SEPTEMBER OCTOBER LONG RAINS COLD SEASON COLD SEASON Labour day Madaraka/Budget Day/African Child Day/malezi bora day Mungiki flash out Electricity/water restriction Shinke Ins Sec School School holidays School holidays School holidays School holidays School holidays School holidays COLD SEASON Obama visit SHORT RAINS Moi day/kenyatta Day NOVEMBER SHORT RAINS Polio campaigns DECEMBER SHORT RAINS School holidays/christmas/ja mhuri/new year/boxing day/world AIDS day School holidays/christmas/ja mhuri/new year/boxing day/world AIDS day School holidays/christmas/ja mhuri/new year/boxing day/world AIDS day School holidays/christmas/ja mhuri/new year/boxing day/world AIDS day School holidays/christmas/ja mhuri/new year/boxing day/world AIDS day School holidays/christmas/ja mhuri/new year/boxing day/world AIDS day 31

32 F: Plausibility check Mathare Nutrition Survey NCHS Anthropometric Indices out of usual range (mean -3.0, mean +3.0): Age distribution: Month 6 : ####### Month 7 : ######### Month 8 : ################ Month 9 : ########## Month 10 : ########### Month 11 : ###################### Month 12 : ###################################### Month 13 : ############### Month 14 : ######################## Month 15 : ################### Month 16 : ######################## Month 17 : ############# Month 18 : ############# Month 19 : ################### Month 20 : ########################## Month 21 : ############## Month 22 : ############### Month 23 : ################### Month 24 : ######### Month 25 : ################## Month 26 : ######################### Month 27 : #################### Month 28 : ############ Month 29 : ############### Month 30 : ################ 32

33 Month 31 : ############ Month 32 : ############# Month 33 : ############# Month 34 : ############## Month 35 : ############# Month 36 : ############### Month 37 : ############### Month 38 : ########### Month 39 : ############## Month 40 : ################ Month 41 : ############### Month 42 : ############ Month 43 : ############# Month 44 : ########### Month 45 : ############## Month 46 : ######### Month 47 : ############ Month 48 : ############### Month 49 : ######### Month 50 : ######### Month 51 : ########## Month 52 : ################ Month 53 : ####### Month 54 : #### Month 55 : # Month 56 : ##### Month 57 : ####### Month 58 : ##### 33

34 Month 59 : ############ Month 60 : ######### Month 61 : ## Month 62 : # Digit preference Weight: Digit.0 : ################################## Digit.1 : ######################################## Digit.2 : ############################################## Digit.3 : ##################################### Digit.4 : ########################################### Digit.5 : ############################# Digit.6 : ###################################### Digit.7 : ###################################### Digit.8 : ###################################### Digit.9 : ##################################### Digit preference Height: Digit.0 : ###################################### Digit.1 : ############################### Digit.2 : ############################################## Digit.3 : ####################################### Digit.4 : ###################################### Digit.5 : ##################################################### Digit.6 : ########################################### Digit.7 : ################################## Digit.8 : ######################### Digit.9 : ################################## Standard deviation of WHZ: Standard Deviation SD: (The SD should be between 0.85 and 1.10) 34

35 Prevalence (< -2) counted: 3.6% Prevalence (< -2) calculated with current SD: 3.9% Prevalence (< -2) calculated with a SD of 1: 4.3% Standard deviation of HAZ: Standard Deviation SD: (The SD should be between 1.10 and 1.30) Prevalence (< -2) counted: 31.6% Prevalence (< -2) calculated with current SD: 32.1% Prevalence (< -2) calculated with a SD of 1: 29.7% Skewness and Kurtosis of WHZ: Skewness of WHZ: => probably skewed (value > 2*(6/n)½) (Skewness characterizes the degree of asymmetry around the mean, positive skewness indicates a long right tail, negative skewness a long left tail) Kurtosis of WHZ: => probably no kurtosis problem (value < 2*(24/n)½) (Kurtosis characterizes the relative peakedness or flatness compared with the normal distribution, positive kurtosis indicates a relatively peaked distribution, negative kurtosis incidates a relatively flat distribution) Detailed Team Evaluation Team Digit preference Weight (%):.0 : : : : : : : : : : Digit preference Height (%): 35