Abstract
Obesity is one of the major critical health conditions affecting many people across the world. One of the major causes of obesity is identified to be sedentary lifestyles and physical inactivity, which may be associated with environmental factors.
The study analyzes variations in obesity and physical inactivity in the State of South Carolina, US, and their association with healthcare capacity and the built environment.
Data were obtained from different secondary sources and surveys, 2012, and then linked on the county-level using ArcGIS. Global Moran's I was used to examine the spatial distribution at the state level, and Anselin's local Moran's I was used to detect any significant clusters at the county level. Ordinary least squares regression models were calculated for obesity and physical inactivity separately.
More than 70% of SC counties had high levels of obesity and physical inactivity. Spatial analysis showed statistical clusters of high obesity, high physical inactivity, and low access to exercise opportunities in rural areas compared to urban areas. Conversely, clusters of high density of health-care facilities appeared in urban areas. Through the regression models, the density of primary care physicians (p = 0.025) and access to exercise opportunities (p = 0.075) were negatively associated with obesity, while the low perception of own health (p = 0.001) and obesity rate (0.011) were positively associated with physical inactivity.
GIS was useful to illustrate and identify significant geographic variations and high clusters of obesity and physical inactivity in rural areas, compared with high clusters of access to exercise opportunities and health-care facilities in urban areas. The international health community is encouraged to utilize spatial information systems to examine variations and recommend evidence-based recommendations to redistribute equitable public health efforts. The development of strategies and initiatives toward reducing variation in health and sustainable development is key to promote the population wellbeing.