Abstract
BackgroundChildhood stunting, defined as the height-for-age standardized score lower than minus two, is one of the key indicators for assessing well-being and health of a child; and can be used for monitoring child health inequalities. Thailand has been successful in improving health and providing financial protection for its population. A better understanding of the determinants of stunting will help fill both knowledge and policy gaps which promote children’s health and well-being. This study assesses the factors contributing to stunting among Thai children aged less than five years.MethodsThis study obtained data from the Multiple Indicator Cluster Survey Round 4 (MICS4), conducted in Thailand in 2012. Data analysis consisted of three steps. First, descriptive statistics provided an overview of data. Second, a Chi-square test determined the association between each covariate and stunting. Finally, multivariable logistic regression assessed the likelihood of stunting from all independent variables. Interaction effects between breastfeeding and household economy were added in the multivariable logistic regression.ResultsIn the analysis without interaction effects, while the perceived size of children at birth as ‘small’ were positively associated with stunting, children in the well-off households were less likely to experience stunting. The analysis of the interactions between ‘duration of breastfeeding’ and ‘household’s economic level’ found that the odds of stunting in children who were breastfed longer than 12 months in the poorest household quintile were 1.8 fold (95% Confidence interval: 1.3–2.6) higher than the odds found in mothers from the same poorest quintiles, but without prolonged breastfeeding. However prolonged breastfeeding in most well-off households (those between the second quintile and the fifth wealth quintile) did not show a tendency towards stunting.ConclusionsChildhood stunting was significantly associated with several factors. Prolonged breastfeeding beyond 12 months when interacting with poor economic status of a household potentiated stunting. Children living in the least well-off households were more prone to stunting than others. We recommend that the MICS survey questionnaire be amended to capture details on quantity, quality and practices of supplementary feeding. Multi-sectoral nutrition policies targeting poor households are required to address stunting challenges.
Highlights
Childhood stunting, defined as the height-for-age standardized score lower than minus two, is one of the key indicators for assessing well-being and health of a child; and can be used for monitoring child health inequalities
This study aimed to assess potential factors contributing to stunting amongst Thai children below 5 years of age, in particular those who were breastfed beyond 12 months
As this study focused on factors that significantly contribute to stunting, the effects of prolonged breastfeeding, we limited our analysis only to children aged over 12 months, numbering 7018 in total
Summary
Childhood stunting, defined as the height-for-age standardized score lower than minus two, is one of the key indicators for assessing well-being and health of a child; and can be used for monitoring child health inequalities. To rectify the unfinished MCH goals in the MDG era, the Sustainable Development Goals (SDG)-3, established the ambitious targets of global maternal mortality reduction to less than 70 deaths per 100,000 live births, and to ending preventable deaths of children under 5 years of age by 2030 [3]. The World Health Organisation (WHO) proposed 11 indicators for MCH monitoring—maternal mortality, prevalence of stunted children, exclusive breastfeeding for 6 months after birth, and skilled birth attendants, to name a few [5]. Amongst these indicators, De Onis and Branca suggest that childhood stunting is ‘the best overall indicator of children’s well-being and an accurate reflection of social inequalities’ [6]. The World Bank suggested that a 1% increase in loss of height is associated with a 1.4% loss in economic productivity [9]
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