Nutritional Assessment of Pre School Chi, LATEST AND FULLY ANSWERED
3 views 0 purchase
Course
Nursing
Institution
Nursing
Nutritional Assessment of Pre-School Children in Rural Villages of the Family
Dynamics, Lifestyles and Nutrition Study ()
II. Prevalence of Undernutrition and Relationship to Household SocioEconomic Indicators
Chee Heng Leng1
, Khor Geok Lin2
, Fatimah Arshad3
, Wan Abdul Manan Wan Muda4
...
Nutritional Assessment of Pre-School Children in Rural Villages of the Family
Dynamics, Lifestyles and Nutrition Study (1997-2001)
II. Prevalence of Undernutrition and Relationship to Household Socio-
Economic Indicators
Chee Heng Leng1, Khor Geok Lin2, Fatimah Arshad3, Wan Abdul Manan Wan Muda4,
Mohd Nasir Mohd Taib2, Nik Shanita Safii3, Norimah Abdul Karim3, Norlela Mohd
Husin5, Normah Hashim2, Pob Bee Koon3, Rokiab Mohd Yusof2
1
Department of Community Health, Faculty of Medicine and Health Sciences, Universiti Putra
Malaysia, 43400 UPM Serdang, Selangor
2
Department of Nutrition and Health Sciences, Faculty of Medicine and Health Sciences,
Univeisiti Putra Malaysia, 43400 UPM Serdang Selangor
3
Department of Nutrition and Dietetics, Faculty of Allied Health Sciences, Universiti
Kebangsaan Malaysia, Jalan Raja Muda Abdul Aziz, 50300 Kuala Lumpur
4
School of Health Sciences, Universiti Sains Malaysia, 16150 Kubang Kerian, Kelantan
5
Division of Family Health Development, Ministry of Health, Jalan Dungun, Bukit Damansara,
50490 Kuala Lumpur
ABSTRACT
This paper describes the nutritional status of pre-school children and analyzes its relationship to
various household socio-economic indicators. Padi, rubber and fishing villages from the
Functional Groups Study (1992-1996) were selected for having a high prevalence of child
undernutrition, and all children between the ages of 12 and 72 months were measured for their
weights and heights in April-May 1998. The NCHS reference values were used to calculate z-
scores, which were categorised according to WHO (1983) recommendations. Children between
minus 2SD and minus 1SD of reference median were classified as mildly malnourished.
Prevalence of underweight was higher (30.5%) than stunting (22.3%), while wasting was only
9.7%. Padi villages had the highest prevalence of undernutrition, followed by fishing, and then
rubber villages. Mean household incomes were found to be significantly lower for children with
worse nutritional status, and undernutrition was higher in households below the poverty line
income. The odds ratios for having stunted children were significantly higher for households
whose heads were agricultural own-account workers (OR 3.66, 95% CI = 1.37-9.79), agricultural
waged workers (OR 2.75, 95% CI = 1.06-7.10), and non-agricultural manual workers (OR 2.49,
95% CI = 1.04-6.00) compared to non-manual workers. Various household socio-economic
indicators showed significantly higher odds ratios for underweight, stunting and wasting. After
adjusting for confounding effects by logistic regression analysis, however, only mother’s
education was found to be a significant predictor for stunting, while poverty level and access to
piped water supply were significant predictors for both underweight and stunting. Households
without livestock were significant predictors for wasting. Thus, this study identified specific
socio-economic factors that should be prioritized for policy and research towards the
amelioration of childhood malnutrition in rural areas.
, Chee, Khor, Fatimah et al.
INTRODUCTION
In the UNICEF model that seeks to explain the etiology of child undernutrition (UNICEF, 1998),
the three major contributing factors at the household level are the insufficient access to food,
inadequate maternal and child caring practices, and poor water and sanitation and inadequate
health services. Income, poverty, and other socio-economic indicators impinge and intertwine
with these factors in straightforward as well as complex ways.
The link between poverty and household food insecurity is well elucidated, but whether or not
poverty leads directly and inevitably to child undernutrition has been a matter of debate. DeRose,
Messer & Millman (1998), in reviewing research in Kenya and the Philippines, point out that the
relationships between child anthropometric indicators and household indicators such as income,
food acquisition and calorie consumption, are found to be weak.
Nevertheless, it has been pointed out (Osmani, 1997) that nutrient and calorie availability could
be more responsive to household incomes at the lower levels. Household incomes, particularly at
lower levels, influence the accessibility to adequate sanitation and health care, which in turn, are
co-determinants of child undernutrition. Furthermore, low income may not directly affect the
availability of the relatively small amount of food necessary to feed a preschool child, but it
could result in a household situation where the parents are unable to spare the time and attention
necessary for a healthy and well fed child (Mason et al., 2001).
In exploring the complex web of causes for child undernutrition, the observation that ‘not all
poor children are malnourished’ have led to investigations for other factors, such as the
behaviour and practices of mothers, fathers, siblings and child care providers, as well as the
intra-family dynamics that might affect child feeding and food intake (Mason et al., 2001). The
Family Dynamics Study was motivated by such an observation made during an earlier study of
the nutritional status among five major functional groups.1
In this paper, we report the anthropometric results from the Family Dynamics Study, and explore
the relationship between child undernutrition and various socio-economic variables. Specifically,
the objective is to identify the socio-economic variables, including household income, poverty
status, occupation of household heads, ownership of household items, and availability of Piped
water, that may predict child undernutrition in rural households.
MATERIALS & METHODS
The villages covered by the Family Dynamics Study were selected on the basis of having high
prevalence of child undernutrition. Details of the selection procedure and the list of villages
selected are in the preceding article of Chee et al. (2002). These villages have been categorised
as padi, rubber and fishing villages, based on their original selection criteria to be villages
representative of padi, rubber and fishing areas. In every village selected, all households with at
1
The preceding art icle, Chee et al. (2002), make some socio-economic comparisons bet ween t he t wo
st udies. Also ref er t o Chee et al. (1997) and Khor & Tee (197) f or f indings of t he earlier st udy on
f unct ional groups.
, Prevalence of Undernutrition and Relationship to Household Socio-Economic Indicators
least one child who is 12-72 months old were included in the study. The socio-economic and
anthropometric data reported in this paper were collected in April-May 1998. Interviews were
conducted by trained research assistants using a structured questionnaire.
The heights, weights, and birthdates of all children between the ages of 12 and 72 months were
taken during home visits. Smaller children were weighed on a KUBOTA pediatric scale
(maximum weight 12 kg) to the nearest 50g, while bigger children were weighed on a TANITA
electronic balance to the nearest 100g. When it was not possible to weigh the child individually,
the weight of the child was obtained by subtracting the weight of the mother from the combined
weight of the mother and child. Heights were measured by using a microtoise tape (Stanley-
Mabo Besancon) to the nearest 0.1 cm. Age was calculated from the birth date to the day the
measurement was taken.
The National Centre for Health Statistics (NCHS) reference values were used to calculate the Z
scores of the children. The children were categorised according to the recommendations of WHO
(1983). Children with weight for age below minus 2SD from the NCHS median were categorised
as underweight, height for age below minus 2SD were categorised as stunted, and weight for
height below minus 2SD were categorised as wasted, while those with these indicators falling
between minus 2SD to minus 1SD were considered to be mildly underweight, stunted and
wasted respectively. Children whose weight for height were above 2SD were considered as
overweight.
Analysis was carried out by the SPSS Version 10.0. Differences in household size and income
among children in various categories of nutritional status were tested using the Kruskal-Wallis
and Mann-Whitney U tests because the income distribution for most nutritional categories was
found to be skewed (Levene’s test yielded a statistically significant result). The Kruskal-Wallis
test was first used to test the overall difference in mean ranks, following which the Mann-
Whitney U test was used to test each pair of differences. The significance level was set at p <
0.05.
Bivariate analysis was carried out, using the odds ratio (OR) to test for associations between
various socio-economic indicators and nutritional status. An OR with a 95% confidence interval
that does not include the value of 1.00 in its range is considered statistically significant. For each
indicator of undernutrition (underweight, stunting, wasting) at the cut-off points of minus 2SD
and minus 1SD, logistic regression models were run for poverty (cut-off point of RM107 per
capita monthly household income) and hard-core poverty (cut-off point of RM54 per capita
monthly household income) to yield adjusted ORs. Only variables that were significantly related
to undernutrition in the bivariate analysis were included as covariates in the logistic regression
models.
RESULTS
Prevalence of malnutrition
The benefits of buying summaries with Stuvia:
Guaranteed quality through customer reviews
Stuvia customers have reviewed more than 700,000 summaries. This how you know that you are buying the best documents.
Quick and easy check-out
You can quickly pay through credit card or Stuvia-credit for the summaries. There is no membership needed.
Focus on what matters
Your fellow students write the study notes themselves, which is why the documents are always reliable and up-to-date. This ensures you quickly get to the core!
Frequently asked questions
What do I get when I buy this document?
You get a PDF, available immediately after your purchase. The purchased document is accessible anytime, anywhere and indefinitely through your profile.
Satisfaction guarantee: how does it work?
Our satisfaction guarantee ensures that you always find a study document that suits you well. You fill out a form, and our customer service team takes care of the rest.
Who am I buying these notes from?
Stuvia is a marketplace, so you are not buying this document from us, but from seller NGOCHIMANE. Stuvia facilitates payment to the seller.
Will I be stuck with a subscription?
No, you only buy these notes for $15.99. You're not tied to anything after your purchase.
