Disparities in Childhood Obesity Prevalence and Spatial Clustering Related to Socioeconomic Factors in Isaan, Thailand

Abstract

Globally, rapid economic growth has contributed to an overall increase in the incidence of childhood obesity. Although the prevalence of obesity has been well recognized, the disparities related to a region’s socioeconomic environment in terms of the incidence of obesity are still less understood. Therefore, the purpose of this study was to examine the spatial pattern of childhood obesity and identify the potential associations between childhood obesity and socioeconomic environment in the northeastern region of Thailand, Isaan. Using nationally collected obesity data from children aged 0–5 years in 2019, we employed a geographic information system (GIS) to perform obesity cluster analysis at the smaller regional level, investigating a total of 322 districts in study area. Global and local statistical approaches were applied to calculate spatial associations between the socioeconomic status of neighborhoods and childhood obesity. The study revealed that 12.42% of the total area showed significant clusters at the district level, with high values observed in the western and northeastern areas. The results of the spatial statistical model revealed that childhood obesity was significantly positively associated with areas exhibiting high levels of socioeconomic environment factors. Identifying the associated factors and highlighting geographic regions with significant spatial clusters is a powerful approach towards understanding the role of location and expanding the knowledge on the factors contributing to childhood obesity. Our findings, as a first step, offer valuable references that could support policy-makers and local authorities in enhancing policy development with the aim of reducing childhood obesity and improving public health.

Spatial Clusters of High Prevalences of Overweight and Obesity Among Children in Indonesia

“…First, the disparity of socioeconomic status between Western Indonesia and Middle/Eastern Indonesia might be responsible for cluster distributions within the country. Meanwhile, a study conducted in a middle-income country found that socioeconomic status can contribute to geographic disparities in the prevalence of obesity among children [ 10 ]. Regarding socioeconomic status, Western Indonesia, which encompasses Sumatra, Java, and Bali, is generally more affluent and prosperous compared to the eastern parts of Indonesia.…”

“…A systematic review study [9] identified that overweight and obesity among children results from a complex interplay between pre-and post-natal factors (e.g., high maternal weight gain during pregnancy and high birth weight), personal behaviors (e.g., excessive intake of carbohydrates, insufficient physical activity, prolonged screen time, and inadequate sleep duration), psychosocial factors (e.g., parental misperception of their child's body weight), and sociodemographic status (e.g., low social status). Recently, several studies have employed geographical data to gain a deeper understanding of the determinants and patterns of childhood obesity [10][11][12][13]. These studies indicate that the prevalence of childhood overweight and obesity showed a clustering pattern and that implementing targeted interventions in specific cluster regions could be an effective method for addressing childhood overweight and obesity.…”

Bayesian spatial modeling of childhood overweight and obesity prevalence in Costa Rica

“…Literature counting with a geographic component dedicated to the associations between weight and socioenvironmental factors has been growing recently [ 14 ]. Examples targeted specifically to children can be found in both developed and developing countries [ 15 – 18 ], with the limitation of being generally oriented to just one simultaneous categorical response (overweight, obesity or their combination). Even in restricted cases in which several nutritional states were contemplated [ 19 , 20 ], overweight and obesity were not included as separated conditions, although, their relationships with certain determinants, their health implications over overall health and consequent interventions can differ.…”