Socioeconomic profile and nutritional status of children in rubber smallholdings

This paper will present the socioeconomic profile and nutritional status of children aged 1-6 years in the rubber smallholdings of Peninsula Malaysia. A total of 323 households were involved in this study. The sociodemographic data were obtained through interviews with heads of households using a set of questionnaires. Anthropometric measurements were taken from 506 children aged 1-6 years from these households. The weight and height of the children were compared with the reference values of the National Center for Health Statistics (NCHS) and the nutritional status was classified based on the recommendations of WHO. The average age of the fathers was 39.9+/-8.6 years and 34.4+/-7.0 years for the mothers. The mean household size was 6.67+/-2.27. The majority (49.7%) of the heads of households received 4-6 years of formal education and 7.9% received no formal education. Based on the monthly per capita income, 24.0% were found to be in the hardcore poor category, 38.3% fall into the poor category and 37.7% in the above poverty income group. The prevalence of stunting and underweight among children between the ages of 1-6 years were highest among children from the hardcore poor, followed by the poor category and above the poverty line income group. Wasting was present in all income groups, with a prevalence of 4.2% found among the hardcore poor, 9.4% among the poor group and 8.4% in the above poverty income group. The Pearson Product Moment Correlation showed significant relationships between household total income and height-for-age (r = 0.131, P = 0.05) and weight-for-age (r = 0.127, P = 0.05). There were also significant correlations between monthly per capita income with height-for-age (r = 0.16, P < 0.01) and weight-for-age (r = 0.13, P < 0.05). The acreage of land utilised was correlated with height-for-age (r = 0.11, P < 0.05), weight-for-age (r = 0.17, P < 0.05) and weight-for-height (r = 0.16, P < 0.05). However, stepwise multiple regression analysis indicated that the predictor of height-for-age was monthly per capita income (R2 = 0.03, P < 0.01) and acreage of land utilised was a predictor for weight-for-age (R2 = 0.03, P < 0.01) and weight-for-height (R2 = 0.01, P < 0.01). Because income and acreage of land utilised have been shown to be associated with nutritional status, it is recommended that intervention programs that focus on generation of income and diversification of land utilisation should be undertaken. A multidiscipline approach involving the family, community and government agencies should be applied to any type of intervention program.