Structural Analysis of Environmental, Socio-demographic Determinants of Malnutrition in Children: A Study...

Structural Analysis of Environmental, Socio-demographic Determinants of Malnutrition in Children: A Study in Tumpat, Malaysia


Cheah Whye Lian Lecturer
Department of Community Medicine and Public Health, Faculty of Medicine and Health Sciences, Universiti Malaysia Sarawak,
Email: [email protected]

Zabidi-Hussin Zamh
Professor of Paediatrics
School of Medical Sciences
Universiti Sains Malaysia

Manan Wmw
Universiti Sains Malaysia

Wang YC
Universiti Malaysia Sarawak

Data from around the world show the causes underlying most nutrition problems have not changed much over the past 50 years. These causes are diverse, multi-sectoral, interrelated and entail biological, social, cultural, and economic factors. Their influences operate at various levels such as child, family, household, community and nation. If groups at risk are identified and the causes of malnutrition clearly understood, prevention becomes more feasible and cost effective. It is well established that child health outcomes are affected by factors operating both at the individual level and within the compositional and contextual situation in which the child resides. With the advancement of technology, many efforts have been undertaken in understanding the effects of geographical factors in influencing the outcome of child health especially utilizing the Remote Sensing and Geographic Information System technology. With the use of common overlaying functions and other multilevel modelling techniques it is possible to understand the multilevel models and the inter-relationship among the components, a capability which is more powerful than the traditional single-level statistical methods. By using a comprehensive analytical method such as Structural Equation Modeling (SEM), researchers can evaluate theoretical models that are measured by multiple variables or measurement instruments. It also provides depth of information that explores the direct and indirect relationships among socio-demographic, dietary intake measurement, anthropometic measurements, and geographical factors with regards to malnutrition and health outcomes. In this study we intend to develop a model for the relationship among socio-demographic, geographical factors, dietary intake measurement, anthropometric measurements, and malnutrition outcomes among children under the age of 5 residing in Tumpat, Kelantan, Malaysia, using this modelling technique. Previous studies using Weighted Overlay function in GIS identified that the majority of malnourished children were living in flood-prone areas, with mix horticulture and high moisture soil. Basic determinant such as poverty and other underlying determinants such as food availability and expenditure, demographic characteristics and government assistance seemed to have had had an impact on the feeding practice, dietary intake and health status of the children in Tumpat. The data obtained previously has shown that the number of malnourished children is as high as 50% in certain areas. However, an extension study in understanding the inter-relationship between the determinants is needed. SEM is chosen because of the complexity of the relationships between these determinants that can be both outcomes variables and explanatory variables at the same time. Moreover, SEM distinguishes between direct, indirect, and total effects. The model generated will not only predict the malnutrition cases but also provides in-depth information for policy makers and programme implementers in planning more effective intervention programmes in eradicating malnutrition in the area studied.

Key Words: Malnutrition, Geographic Information System (GIS), Structural Equation Modelling, Malaysia