44

角井信弘

特集：合同臨地訓練［ケニアの合同臨地訓練］
Prevalence and risk factors of malnutrition
Kariuki FN1), Monari JM2), Kibui MM3), Mwirichia MA4), Zani KK5),
Tetei M6), Aikawa R7), Waihenia E8), Osaki Y9)

Abstract
Objective: to assess the prevalence and risk factors of malnutrition of children 6 to 23 months.
Design: a cross-sectional study was done in Kibera an urban slum in Nairobi, Kenya. Cluster andrandom sampling methods were used. A sample size of 353 children and their mothers was targeted.
A structured questionnaire was administered to parents and caretakers to obtain information on social
economic status, immunization status, growth monitoring, morbidity, breastfeeding and weaning
practices. Anthropometrical measurements of weight and length were conducted in order to get thosechildren who were undernourished. The equipments used were Salter scales and supine length boards
respectively. 132 children aged from 6 to 23 months participated in this study. The three categories ofnutritional stunting, wasting and underweight were used as indicators of nutritional status for thechildren. The study took place from 13th to 18th October 1999.
Main outcome measures: nutritional status data was compared with National Centre of Health
Statistics (NCHS) references and presented as Z-scores with cut off point of -2 SD using indicators ofweight for age, weight for length and length for age to get those children who were underweight,
wasted and stunted respectively. The analysis of this study focused on stunting because it's the bestindicator for chronic malnutrition.
Results: The anthropometrical data revealed that malnutrition is a public health problem in Kibera.
34.6% of the study children were stunted, 6.2% wasted and 26.5% underweight. 97(73.4%) children in
the study area were sick two weeks prior to the study. The study revealed a significant relationshipbetween stunting and morbidity. Having children at an early age may be a risk factor to nutritional
stunting as shown in this study. 50% of children whose mothers were between 15-19 years werestunted. The risk decreased with the increase of age of the mothers, as the percentage of mother over
25 years who had stunted children was 30%. Large households with more than 5 people had more
stunted children compared to households with less than 5 people.
No association was found between stunting and education of the mother, mother's income,frequency of feeding, time weaning started and length of breastfeeding.
Conclusion: Malnutrition is a public health problem in slums. This study suggests that mothers below
20 years are not fully prepared for motherhood. Maybe there is household food insecurity in large
households causing malnutrition of children in slums. High morbidity among children maybe due todelayed diagnosis and treatment of ailments.
Key Words: Food security, Nutritional Assessment, Anthropometrics, Malnutrition, Slums, Household
size, Early pregnancy
1）Department of Community Nutrition, MTC Karen2）Department of Environmental Health Sciences, MTC
Nakuru3）Department of Environmental Health Sciences, MTC
Nyeri4）Department of Nursing, MTC Meru
5）Department of Environmental Health Sciences, MTC
Matuga6）Computer Supervisor, KMTC, Nairobi
7）Long term Nutritionist expert KMTC/JICA Nairobi8）Department of Nutrition, MTC Karen9）Short term expert, Tottori University, Japan
Kenya Medical Training College, P. O. Box 30195 Nairobi,
Kenya
Tel. 725711/4, Fax 722907, E-maill kmtc@nbnet.co.ke

J. Natl. Inst. Public Health, 51 (1) : 2002

Kariuki KN, Monari JM, Kibui MM, et al.

Introduction
Malnutrition is one of the most serious world healthproblems. Globally 67 million children are estimated to be
wasted and about 18 million weight less than they should
for their age. Over 200 million children under five years
in developing countries die each year and half of thedeaths is due to malnutrition (1). The most prevalent
form of malnutrition in Kenya is Protein, Energy
malnutrition (PEM). The term PEM is used to describe abroad array of clinical conditions ranging from mild
malnutrition mainfesting itself in poor growth to theserious type of kwashiorkor and marasmus which havehigh cases of fatality rate. Children with mild or
moderate malnutrition do not have any clinical signs but
are shorter or thinner for their age. Such children are at
risk of becoming severely malnourished. The
consequences of malnutrition on the quality of life of achild and the cost of rehabilitating malnourished children
calls for investing in programmes that prevent the
problem of malnutrition. Mild or moderate protein
energy malnutrition is diagnosed by taking
anthropometrics measurements of weight andheight/length (2,3)
In Kenya, chronic malnutrition is the most common
form of malnutrition. 34% of children below five years
are stunted while 8% and 23% are wasted andunderweight respectively (4). This is approximately 1.5
million Kenyan children under 5 years. The situation
could be worse due to increased poverty and declining
access to basic health care (5). Because of the serious
consequences of malnutrition on child's growth, health,and economic consequences for the nation, nutritional
status of children should be assessed periodically tomonitor the situation and appropriate action taken tocombat and prevent malnutrition. In Kenya, malnutrition
has been assessed every five years since 1997 by thegovernment. The results from these rural child surveys
have shown malnutrition to be a major public healthproblem. Theme number one in the national plan ofaction for nutrition is assessing and monitoring
nutritional situations (6). The 1990 world summit forchildren adopted a number of goals for children and oneof them was reduction of both moderate and severe
protein energy malnutrition in children under five years
by half of the 1990 levels over the 1990-2000 period.
Kenya decided to set a modest but achievable goal of
reducing malnutrition by 30% of its 1992 level (7).
Immediate causes of malnutrition are inadequate foodintake and infections. The underlying causes ofmalnutrition are many and some of the cited causes are45

poverty, poor feeding practices, poor childcare and poor
sanitation. These causes are interlinked and a multisectoral approach should be used to address the problemof malnutrition.
Policy makers to formulate appropriate interventions
will use the results of this study. Other researchers may
use the results for new knowledge and fill gaps. The
objective of the study was to assess the prevalence ofmalnutrition and identify the risk factors.

Materials and methods
This study was conducted in Kibera a slum area, 6km
away from Nairobi City center, capital of Kenya. Kibera
slum has 9 villages and it’s the largest in Kenya
occupying an area of 4 square kilometers. Kibera
population is estimated to be 500,000 people. The study
was conducted in Siranga village, which is situated 2 km
from the main road. The houses are semi-permanent andmost of the residents are tenants. The main road is good
but the feeder foods are poor and not accessible during
the rainy season. There is a government health center
5km away but the area also has many private clinics andpracticing herbalists. Tapped water is available but
expensive for the residents who have to buy water fromvendors.
A cross-sectional design was used to study a group of
132 children aged 6 to 23 months. The interviewers werea nutritionist and other ancillary health workers
undergoing community based research project in KMTC.
Structured questionnaires both in English and Kiswahili
be local language, were revised and amended to ensure
uniformity in asking the questions.
A structured questionnaire was used to interview
parents and caretakers on morbidity, immunization
status, socio-economic status, weaning and feeding
parctices of the children. A 24-hour dietary recall was
conducted to get information on the quality of the dietand frequency of feeding.
Undertaking of the survey was from 13th to 18th
October 1999 at dwellings of Siranga. Cluster sampling
procedure was used to identify dwellings and households
units were randomly selected. The guide andinterviewers zoned dwellings and identified the center ofthat to be studied. A pen was spanned to identify the
direction to follow. On reaching the end of the village thespinning was done again to continue until the survey
was completed. The response rate was 99%.
Anthropometrical measurements of weight and length
were taken using Salter scales and length boards
respectively. The researchers took the measurements inpairs to ensure data quality control. Mothers gave the

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46

Prevalence and Risk factors of Malnutrition

ages of their children and this was validated with thechild health card.
The sample size was calculated using the guidelines
for Nutrition Baseline Surveys in Communities (8).
Prevalence of National stunting, which is 34%, was used
to calculate the required sample size (4).
Collected data was cleaned and sorted in Microsoft
excel computer programme before analysis. Data wasanalyzed by appropriate tabulation and subjected tostatistical tests, simple tables, percentages and figures.
Nutritional status data was compared with National
Centre of Health Statistics (NCHS) references andpresented as Z-scores with cut off point of -2 SD asrecommended by WHO using indicators of weight forage, weight for length and length for age to get thosechildren who were underweight, wasted and stunted
respectively.
Nutritional status was evaluated by comparing how
these anthropometrics indices deviated from thereference population (2,3).
In this study the following definitions were employed
for the nutritional indices:
1．Underweight means a low weight for age. This isa weight below -2SD of reference population.
2．Stunting means a low length for age. This length
below -2SD of reference population. Stunted
children are of low stature than children of thesame age.
3．Wasting means a low weight for length. Children
are lean and below -2SD of reference weight for

length. Weight for length is a measure of wastingfor children who cannot stand and supine lengthis measured.
“Malnutrition” is used to mean under nutrition in thisstudy. Inadequate intake of energy and nutrients, whichhinders proper functioning of the body leads to protein
energy malnutrition.

Results
The socio-demographic characteristics of the study
units showed the following: The number of the mean
household members was 4.7, the mean age of children
was 22 months and the average number of children perhousehold was 2.4.
Most mothers were housewives (68%). Majority of themothers were married (89.4%). The average age of
mothers was 24 years. 61 boys and 71 girls participatedin this study. Mothers with primary education were 77%.
21% had attained secondary level education. The rest
had little education or no education at all. Children who
were not being taken for growth monitoring were 47%.
Most mothers were of low income as 74.2% earned lessthan 1000ksh per month. 68% of mothers werehousewives, 30% were self employed and 2% were inpaid employment. Ages of study children revealed thatthe majority of study children were over 12 months(50.8%), 7-11 months 30.3% and less than 7 months 18.9%.
Table 1 shows the socio economic characteristics.
The anthropometrics data revealed that malnutrition
is a public health problem in Kibera. Overall 34.6% of theTable 1. Socio-Demograhic characterstics.

Marital status

Educational level

Mothers occupation

Age of child in months

Frequency

Percentage

Married118

89

Single8

6

Divorced22

Separated

1

1

Widowed

3

3

None

2

2

Primary

102

77

Secondary

28

21

House wives

91

68

Self employed

39

30

Paid employment22<7 months

25

19≥7 months<12 months

40

30≥12 months

67

51

J. Natl. Inst. Public Health, 51 (1) : 2002

47

Kariuki KN, Monari JM, Kibui MM, et al.
Table 2. Distribution of malnourished children

Table 5. Distribution of maternal age by nutritional stunitingby nutritional status indicators
Maternal age
Indicators

Total

ServereModerate%

Young (15-19yrs)

Underwight

35

10

25

26.5

Middle (20-25yrs)

Wasted

8

4

4

6.2

Mature (>25yrs)

Stunted

45

20

20

34.6

Total

study children were stunted, 6.2% wasted and 26.5%
underweight. Table 2 shows the distribution of
malnourished children by nutritional status indicators.
There is high morbidity rate of young children in
Kibera. 97(73.4%) children in the study were sick two
weeks prior to the study. The study revealed asignificant relationship between chronic malnutrition andmorbidity. Table 3 shows that there is an association
between illness and malnutrition.
More children in large households (households withmore than 5 people) are likely to get malnourished thanchildren in small households (households with less than 5people). The results of the study revealed that 52% of
the study children in large households were stunted ascompared to 30.5% in small households. Table 4 showsthat there was a significant association between
household size and nutritional stunting.
Having children at an early age may be a risk factor tonutritional stunting although it was not significant asshown in this study. 50% of children whose mothers
were between 15-19 years were stunted. The risk
decreased as age of the mother increased. The
percentage of mothers over 25 years who had stunted

Table 3. Distribution of Malnourished children by morbidity
Long Short No illness
Stunted

18

16

11

Not stunted

33

31

21

Total

51

47

32

Chi-square

P-value

10.33

P<0.05

Table 4. Distribution of malnourished children
by household size
Stunted Not stunted Total %χ2 P=Value> 5 people

13

12

25 52 4.13 P<0.05≤ 5 people

32

73

105 30

Total

45

85

130

StuntedNot stunted

Total

9

9

18

20

40

60

16

37

54

45

86

132

children was 30%. Table 5 shows the relationshipbetween the age of the mother and malnutrition.
There was no significant relationship found between
stunting and eduction level of the mother, mother’s
income and sex of the child, breastfeeding frequency, age
weaning introduced, immunization status or frequency of
feeding. Table 6 shows feeding practices and healthseeking characteristics.
The study revealed that most mothers have almost
similar feeding practices. 79% of the mothers werebreastfeeding on demand and only 1% never breastfed atall. The length of breastfeeding reduced with the age ofthe child. By the time the children were 19 months, only
1% were breastfeeding. The two main reasons given forearly cessation of breastfeeding were child refusal tobreastfeed and the mother being sick. No significant
association was found between frequency ofbreastfeeding and chronic malnutrition. Many children(63%) were weaned earlier than the recommended age of
4 to 6 months. Majority of mothers fed their children
frequently, as 126 mothers fed the children 4-6 times perday, although 81% did not balance the food to provide all
the necessary nutrients. The quality of the diet was poor
as revealed by the 24-hour dietary recell. Children who
were not being taken for growth monitoring were 62(47%). The immunization coverage in the study area was
79%.

Discussion
Malnutritions is prevalent in Kibera as reported. In awell-nourished population, 2.3% of children are expected
to be below a cut-off point of -2SD of the well-nourised
reference population. Nutritional stunting in Kibera is 15
times higher than that. Results of this study compares
well with the fifth national nutrition survey (4) which
reported stunting level of 34%, wasting 8% andunderweight 22.5%. The Kenya demographic and healthsurvey of 1998 estimated chronic malnutrition to be 33%,
wasting 6% and underweight 22% (10). The malnutrition
prevalence levels for Nairobi and Stunting 30.2%, wasting
5.5% and underweight 22%(4).
In Kenya, chronic under nutrition is the most common

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48

Prevalence and Risk factors of Malnutrition

Table 6. Feeding practices and health seeking characteristics
Frequency

Percentage<7 months

21

16>6<11 months

1

1

On demand

85

64

Not applicable25

19

0-2 months

33

25

3-4 months

50

38

5-6 months

1310

7-8 months

979-10 months

3

2

Porridge

74

55

Mashed banana

37

27

Cereal1

1Ripe banana

6

5

Eggs

9

7

1-3 times

54

4-6 times

126

95>6 times

1

1

Balanced

25

19

Not balanced

107

81

Complete

79

60

Incomplete

21

16

Under age32

24

Being undertaken

70

53

Not being undertaken

62

47

A. Breastfeeding

B. Age weaning introduced

C. First solid foods introduced

D. Frequency of feeding

E. Quality of foods

F. Immunization coveragae

G. Growth monitoring

form of malnutrition and this study endeavored to findout the risk factors of nutritional stunting in Kibera.
Stunting and wasting show the level of socio-economic
development of a country. Well-targeted interventions
can reduce the problem (10). The Kenya demographic
survey of 1998 suggests that the level of malnutrition has
not changed since the 1994 nutritional survey except forunderweight that has reduced by 2%(11).
Having children early was identified as a risk factor.
Teenage pregnancies are socially disadvantaged. The
girl- child who is 15-18 years is not ready to take care ofanother child. These mothers depend on others toprovide for her needs and the others may be poor

especially in slums (12). They should be supported
through community initiatives to take care of theirchildren. They should also go back to school if they were
dropouts. Older mothers have more experience in childcare than young mothers and are likely to find solutions
to their problems. This finding agreed with anotherstudy done in Tanzania to find out the determinants ofnutritional status in a low income area in Tanzania (13).
Another study still done in Tanzania also reported thatmaternal age was significantly associated with nutritional
stunting (14). Strategies to delay motherhood should besought and implemented.
This study reveals that most girls in slums do not go
to seconedary school, probably due to lack of school fees
and as a result the girls get children.
Findings of this study confirm that infections that lastlong are a risk for chronic malnutrition. The highmorbidity in the area suggests that there is delayed
diagnosis and treatment of infections in slums maybe
due to poverty or ignorance of the consequences of
untreated infections. The presence of many herbalists inthe area suggests that traditional medicine is popular in
Kibera. Malnutrition and disease are co-factor and form a
vicious circle. Infections make malnutrition worse andpoor nutrition increases the severity of infectious
diseases. Infections have negative effects due toincreased metabolism, reduced nutrient intake and directloss through diarrhea and vomiting. Malnutrition
weakens the immune system predisposing malnourishedchildren to disease (15). The high prevalence ofunderweight in Kibera could have been due to the highmorbidity reported. The study in Tanzania mentioned
above supports this, as parasitics infections and diarrhea
are prevalent in poor communities especially in slums.
The environmental sanitation is poor and althoughtapped water is available, it’s expensive for the residents.
Several studies have shown that diarrhea precipitates
serious protein energy malnutrition.
There is one government health facility in the area,
which is 5km away. A health facility within 6km of
persons home is said to be accessible (11). There was an
association between stunting and household size.
Majority of monthers in the study had few children but
some households were large because of relatives fromthe rural areas. The extended family members maybe
jobless and hence dependent on the host for food andupkeep. An old study in Philippines in 1969 reported that
intake of energy and protein reduced with increase insize of household (17). Children are vulnerable in suchhouseholds if there is household food insecurity. It could
also be due to increased workload of a mother attending

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Kariuki KN, Monari JM, Kibui MM, et al.

to the needs of a big household at the expense of thewelfare of the young child. It is difficult to deal with the
problem since it's social norm to allow relatives to stay.
Although there was no association between stunting
and age weaning was started, inappropriate timing for
introducing breast milk supplements to a child may
affect his/her nutritional status. Introduction of the
supplements before the age of 3 months especially underunhygienic conditions could be an important cause ofdiarrhea and therefore a cause of malnutrition (16). This
study showed that the children did not consume foodwith all the necessary nutrients. This agreed with astudy done in the same slum but in a different village byuniversity of Nairobi students, Department of Applied
Nutrition in 1998, which showed that children below 5
years received inadequate amounts of energy andprotein. Children who are fed with diets that do not meet
the Recommended Dietary Allowances for energy andnutrients over a long period will definitely suffer fromprotein energy malnutrition regardless of whether they
are fed frequently or weaned at the right time (15). The
food given to the children was mainly composed of
cereal flours and starchy roots and tubers. This isprobably due to shortage of fuel as most of them wereusing kerosene, which is quite expensive. They opted forfoods that cook quickly.
Growth monitoring is useful in detecting growth
faltering (17). This study found out that a sizeable
percentage of mothers were not taking their children forweighing and this could have contributed to the highlevel of malnutrition since growth failure was notdetected early for remedial action to be taken. Having
growth monitoring centers within reach may motivate
the mothers to take their children for weighing. Suchcenters can be multi-purpose for nutrition and healtheducation. Community based growth monitoring has
worked well where the community has been empowered
to participate in improving its health and nutrition
status.
Immunization coverage was low in the study area andbelow the national figure. Efforts should be put in place
to improve coverage and thus protect children against
killer immunization diseases. Immunization campaigns
should sensitize the community on the issue.

Conclusion
Prevalence of malnutrition in slums is higher than thenational average. Children born to teenage mothers arelikely to get malnourished. Children in large households
are at risk of under nutrition probably due to inadequate
food intake. Malnutrition and disease are cofactors.

49

There are gaps either on knowledge or practiceconcerning child feeding.
This study was conducted as a Mid Level Manpower
Training (MLMT) program as part of KMTC/JICA
project (1999) and sponsored by JICA (Japan
International Cooperation Agency).

Acknowledgements
We would like to acknowledge the efforts of every one
who directly or indirectly contributed to the success of
this project. In particular, we are extremely indebted to
the Director of KMTC Mr. William K. Boit, JICA/KMTC
coordinator, Ms A. Kimeu, JICA experts, Dr. Osaki and
Ms. R. Aikawa, to all the lecturers, notably Dr. Nieru, Dr.
Rakwar, Dr. Muthwii and Mr. Lukhando. We are gratefulto Mr. Tetei, the computer instructor for his help. Special
appreciation goes to the District Officer, Chief, Guides
and the community of Siranga village for cooperration.

References
１．UNICEF. The state of the world’s children, Oxford
University Press, New York, 1998.
２．United Nations. How to weigh and measure children.
Assessing the nutritional status of young children inhousehold surveys, New York (1986).
３．Beghin I et al. A guide to nutritional assessment. WHO.
Geneva, 1988.
４．Fifth child nutrition survey, Central bureau of statistics,
Ministry of Planning and National Development, Nairobi,(1994), (1996).
５．Kenya human development report, Government of
Kenya, Nairobi (1999).
６．National plan of action for nutrition, Republic of Kenya,
Nairobi (1994).
７．Kenya’s programme of action for Children in the 1990's
Government of Kenya, Nairobi, (1992).
８．Gross R et al. Guidelines for Nutrition baseline surveys in
Communities version1.2, Jakarta (1997).
９．Ngare DK, Muttunga JN. Prevalence of Malnutrition in
Kenya, East Affrican Medical Journal 76: 376-380, 1999.
10．Demographic and health survey, Macro international Inc.
and council for population and development, Nairobi (1998).
11．UNICEF. A situation Analysis Children and women in
Kenya, Nairobi (1992).
12．Mbago MC, Namfua. Some determinants of nutritional
status of 1 to 4 yuear old children in low-income urban
areas of Tanzania. Journal of Tropical pediatrics, 1992.
13．Mugyabus LKJ, Masters Thesis University of Nairobi,
Nairobi (1995).
14．Latham CM, Human Nutrition in developing word, Rome(1997)
16．King FS, Helping mothers to breastfeed, AMREF, Nairobi(1985)J. Natl. Inst. Public Health, 51 (1) : 2002

50

Prevalence and Risk factors of Malnutrition

17．Den Hartog AP et al. Manual for social surveys on food
habits and consumption in developing countries, Pudoc
Wageningen, (1985).

18．Cameroon M, Hofvander, Manual on feeding infants andyoung children, (1990).

J. Natl. Inst. Public Health, 51 (1) : 2002