Risk factors modifying the double burden of malnutrition of young children in Thailand

Abstract

Thailand is now faced with a double burden of malnutrition. Using nationally representative data from the 2015–2016 Multiple Indicator Cluster Survey, we utilized multinomial logistic regression models to examine factors associated with stunting only, wasting only, overweight only, concurrent stunting and overweight, and concurrent stunting and wasting among children 0–59 months of age ( n = 11,068). The prevalences of <5 stunting only (height‐for‐age Z score < −2 SD) and wasting only (WHZ < −2 SD) were 8.5% and 4.7%, respectively. The prevalence of <5 overweight only (WHZ > +2 SD) was 7.8%. Children 12–23 months (risk ratio [RR], 95% confidence interval [CI]: 1.47 [1.18, 1.83]; p < .01) and 24–35 months (RR, 95% CI: 1.56 [1.26, 1.94]; p < .001) were at increased risk for stunting only, compared with children 48–59 months. The strongest risk factor for stunting only was low birth weight (RR, 95% CI: 3.42 [2.86, 4.10]; p < .001). Children 0–5 months were at highest risk for wasting only, compared with children 48–59 months (RR, 95% CI: 2.91 [2.16, 3.92]; p < .001). Children 48–59 months and male children were more likely to be overweight only. Higher household wealth and smaller household size were also significant predictors of overweight only. A small proportion of children were concurrently stunted and overweight (1.3%) and concurrently stunted and wasted (0.6%). A multipronged approach focused on adequate prenatal care, improving breastfeeding and complementary feeding practices, and mitigating the growing burden of overweight is needed to address the double burden of malnutrition in Thailand.

Malnutrition and contributing factors among newborns delivered at the University of Gondar Hospital, Northwest Ethiopia: a cross-sectional study

“…37 Wasting: newborns whose WHZ (weight-for-height) measurement was <(−2 SD). 16 Concurrent WaSt: newborns who were concomitantly wasted and stunted. 4 Overweight/obesity: newborns whose WHZ (weightfor-length) measurement was >(+2 SD.…”

Triple trouble: Understanding the burden of child undernutrition, micronutrient deficiencies, and overweight in East Asia and the Pacific

“…Poverty is likely to be significantly exacerbated by the COVID-19 pandemic particularly among vulnerable households. In this issue, nationally representative data was examined in Myanmar (Blankenship, Cashin, et al, 2020), the Marshall Islands , and Thailand (Okubo, Janmohamed, Topothai, & Blankenship, 2020)…”

“…Poverty is likely to be significantly exacerbated by the COVID‐19 pandemic particularly among vulnerable households. In this issue, nationally representative data was examined in Myanmar (Blankenship, Cashin, et al, 2020), the Marshall Islands (Blankenship, et al, 2020), and Thailand (Okubo, Janmohamed, Topothai, & Blankenship, 2020) to identify the key drivers of child malnutrition. Despite varying degrees of economic status and progression along the nutrition transition, in all three countries, the poorest households had the highest risk of child stunting, with the poorest households also having highest risk of wasting in Thailand.…”

“…Few countries in Asia and the Pacific have reliable data on birth weight due to recall bias and high prevalence of missing data. In this issue, Okubo et al (2020) found low birth weight to be the leading predictor of child stunting, concurrent stunting and overweight, and concurrent stunting and wasting in Thailand. The findings indicate that children born with low birth weight are at increased risk of not only undernutrition but also developing overweight.…”

A Survey of implementation status of child nutrition surveillance systems, registry systems and information systems: a scoping literature review protocol

“…Malnutrition exerts intense financial pressure on individuals and health systems. 12 The economic losses due to malnutrition have been reported in many studies. 13 14 Economic models also indicate that the return on investment in nutrition has a robust cost to benefit ratio.…”