Geographic clustering and region-specific determinants of obesity in the Netherlands

Autor: Ge Qiu, Xiaojian Liu, Arsha Yuditha Amiranti, Mulimba Yasini, Tong Wu, Sherif Amer, Peng Jia
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Geospatial Health, Vol 15, Iss 1 (2020)
Druh dokumentu: article
ISSN: 1827-1987
1970-7096
DOI: 10.4081/gh.2020.839
Popis: As a leading cause of morbidity and premature mortality, obesity has become a major global public health problem. It is therefore important to investigate the spatial variation of obesity prevalence and its associations with environmental and behavioral factors (e.g., food environment, physical activity), to optimize the targeting of scarce public health resources. In this study, the geographic clustering of obesity in the Netherlands was explored by analyzing the local spatial autocorrelation of municipal-level prevalence rates of adulthood obesity (aged ≥19 years) in 2016. The potential influential factors that may be associated with obesity prevalence were first selected from five categories of healthrelated factors through binary and Least Absolute Shrinkage and Selection Operator (LASSO) regressions. Geographically Weighted Regression (GWR) was then used to investigate the spatial variations of the associations between those selected factors and obesity prevalence. The results revealed marked geographic variations in obesity prevalence, with four clusters of high prevalence in the north, south, east, and west, and three clusters of low prevalence in the north and south of the Netherlands. Lack of sports participation, risk of anxiety, falling short of physical activity guidelines, and the number of restaurants around homes were found to be associated with obesity prevalence across municipalities. Our findings show that effective, region-specific strategies are needed to tackle the increasing obesity in the Netherlands.
Databáze: Directory of Open Access Journals