A Spatial Analysis of Obesity in West Virginia (original) (raw)
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The Impact of Socioeconomic and Spatial Differences on Obesity in West Virginia
Annual Meeting, …, 2006
Obesity constitutes an important public policy issue since it causes external costs to society through increased healthcare costs borne by taxpayers. This study employed random and fixed effects estimations and spatial autoregressive approaches under a panel data structure to unravel possible socioeconomic and built environment factors contributing to obesity. Though there is no statistical evidence for time invariant fixed effects, empirical evidence shows that obesity is a spatially non-random event. Educational attainment that raises both human and social capital as well as changes in the built environment could play a vital role in controlling obesity.
International Journal of Environmental Research and Public Health
There is much ongoing research about the effect of the urban environment as compared with individual behaviour on growing obesity levels, including food environment, settlement patterns (e.g., sprawl, walkability, commuting patterns), and activity access. This paper considers obesity variations between US counties, and delineates the main dimensions of geographic variation in obesity between counties: by urban-rural status, by region, by area poverty status, and by majority ethnic group. Available measures of activity access, food environment, and settlement patterns are then assessed in terms of how far they can account for geographic variation. A county level regression analysis uses a Bayesian methodology that controls for spatial correlation in unmeasured area risk factors. It is found that environmental measures do play a significant role in explaining geographic contrasts in obesity.
International Journal of Environmental Research and Public Health, 2009
A recursive system of ordered self assessed health (SAH) and a binary indicator of obesity were used to investigate the impact of socioeconomic and environmental factors on health and obesity in the predominantly rural Appalachian state of West Virginia. Behavioral Risk Factor Surveillance System (BRFSS) data together with county specific socioeconomic and built environment indicators were used in estimation. Results indicate that an individual's risk of being obese increases at a decreasing rate with per capita income and age. Marginal impacts show that as the level of education attainment increases, the probability of being obese decreases by 3%. Physical inactivity increases the risk of being obese by 9%, while smoking reduces the risk of being obese by 14%. Fruit and vegetable consumption lowers the probability of being obese by 2%, while each hour increase in commuting time raises the probability of being obese by 2.4%. In addition, individuals living in economically distressed counties are less likely to have good health. Intervention measures which stimulate human capital development and better land use planning are essential policy elements to improving health and reducing the incidence of obesity in rural Appalachia.
2016
Scholars have established that our geographic environmentsincluding infrastructure for walking and food availability-contribute to the current obesity epidemic in the United States. However, the relationship between food, walkability, and obesity has largely only been investigated in large urban areas. Further, many studies have not taken an in-depth look at the spatial fabric of walkability, food, and obesity. The purpose of this study was twofold: 1) to explore reliable methods, using sociodemographic census data, for estimating obesity at the neighborhood level in one region of the U.S. made up of rural areas and small townssouthern Illinois; and 2) to investigate the ways that the food environment and walkability correlate with obesity across neighborhoods with different geographies, population densities, and socio-demographic characteristics. This study uses spatial analysis techniques and GIS, chiefly geographically weighted multivariate linear regression and cluster analysis, to estimate obesity at the census block group level. Walkability and the food environment are investigated in depth before the relationship between obesity and the built environment is analyzed using GIS and spatial analysis. The study finds that the influence of various food and walkability measures on obesity is spatially varied and significantly mediated by socio-demographic factors. The study concludes that the relationship between obesity and the built environment can be studied quantitatively in study areas of any size or population density but an open-minded approach toward measures must be taken and geographic variation cannot be ignored. This
Obesity, 2014
Objective: This study used spatial statistical methods to test the hypotheses that county-level adult obesity prevalence in the United States is (1) regionally concentrated at significant levels, and (2) linked to local-level factors, after controlling for state-level effects. Methods: Data were obtained from the Centers for Disease Control and Prevention and other secondary sources. The units of analysis were counties. The dependent variable was the age-adjusted percentage of adults who were obese in 2009 (body mass index >30 kg/m 2 ). Results: The prevalence of county-level obesity varied from 13.5% to 47.9% with a mean of 30.3%. Obesity prevalence across counties was not spatially random: 15.8% belonged to high-obesity regions and 13.5% belonged to low-obesity regions. Obesity was positively associated with unemployment, outpatient healthcare visits, physical inactivity, female-headed families, black populations, and less education. Obesity was negatively correlated with physician numbers, natural amenities, percent 65 years, Hispanic populations, and larger population size. A number of variables were notable for not reaching significance after controlling for other factors, including poverty and food environment measures. Conclusions: The findings demonstrate the importance of local-level factors in explaining geographic variation in obesity prevalence, and thus hold implications for geographically targeted interventions to combat the obesity epidemic.
Regional disparities in obesity prevalence in the United States: A spatial regime analysis
Obesity, 2014
Objective-Significant clusters of high and low obesity counties have been demonstrated across the United States (U.S.). This study examined regional disparities in obesity prevalence and differences in the related structural characteristics across regions of the U.S. Design and Methods-Drawing on model-based estimates from the Centers for Disease Control and Prevention, regional differences in county-level adult obesity prevalence (percent of the adult population [≥ 20 years] that was obese [BMI≥30kg/m 2 ] within a county, 2009) were assessed with a LISA (Local Indicators of Spatial Association) analysis to identify geographic concentrations of high and low obesity levels. We utilized regional regime analysis to identify factors that were differentially associated with obesity prevalence between regions of the U.S. Results-High and low obesity county clusters and the effect of a number of county-level characteristics on obesity prevalence differed significantly by region. These included the positive effect of African American populations in the South, the negative effect of Hispanic populations in the Northeast, and the positive effect of unemployed workers in the Midwest and West. Conclusions-Our findings suggest the need for public health policies and interventions that account for different regional characteristics underlying obesity prevalence variation across the U.S.
Healthy Food Accessibility and Obesity: Case Study of Pennsylvania, USA
Obesity is a continuing challenge for any town, city or country faced with this problem. Being obese increases your risk of physical disorders such as high blood pressure (BP), high blood cholesterol, diabetes, coronary heart disease, stroke, cancer and poor reproductive health. Higher obesity rates also leads to increased economic burden on society. In order to better understand and control obesity rates the influence of various factors on its prevalence should be investigated. We used Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR) models to analyze spatial relationships using a combination of socio-economic and physical factor for counties in Pennsylvania (PA), USA for 2010. Our findings suggest that the rate of obesity is impacted by local spatial variation and its prevalence positively correlated with diabetes, physical inactivity and the distance that a person must travel to get to a healthy food store. Additionally, GWR (AICc = 261.59; r-squared = 0.45) was found to significantly improve model fitting over OLS (AICc = 299.87; r-squared = 0.34). These results indicate that additional factors, including social, cultural and behavioral, are needed to better explain the distribution of obesity rates across PA.
An Economic Analysis of Adult Obesity in West Virginia
West Virginia reports the highest obesity level in the United States. Every 3 in 10 adults are obese, and the prevalence of obesity is nearly 8% higher than the national level. Obesity is linked with several diseases such as heart disease, diabetes II, hypertension, cancer, arthritis, asthma, and some psychological disorders. The reported economic burden associated with obesity is considerably high. This research study attempts to examine the use of exercise and cutting down of calorie intakes in controlling obesity in West Virginia using the 2009 Behavioral Risk Factor Surveillance System data. Three logit models were estimated. Results indicate that obese adults are less likely to engage in exercises to lose weight compared to non-obese adults. Among obese individuals only 15% cut down calorie intakes to lose weight where as the respective proportion from the entire population is 31%. Low income levels, and presence of diseases such as diabetes, hypertension, arthritis, and asthma, have positive effects on obesity in West Virginia. Obesity can significantly be alleviated through physical activities in West Virginia.
Obesity in West Virginia: Control and Costs
SSRN Electronic Journal, 2000
West Virginia reports a high obesity rate, and the prevalence of obesity is 8 percent higher than the national rate. Obesity is linked with several health diseases, certain psychological disorders, quality of life, premature deaths as well as healthcare costs. Prevention of obesity is a must and changing behavioral factors is one way of controlling obesity. This research study attempts to examine the potential use of physical exercise and fewer calorie intakes in controlling obesity, and to estimate costs of obesity in West Virginia using Behavioral risk Factor Surveillance System data of 2001 and 2009. Three logit equations were used in the analysis. Results reveal that potential of using physical exercise in controlling obesity in West Virginia has increased from 2001 to 2009, though the desire of engaging in physical exercise of obese people has decreased. However, the willingness of taking fewer calories of obese individuals has increased significantly from 2001 to 2009. The cost estimations indicate that direct medical cost of obesity and total costs associated with obesity have increased by 51millionand51 million and 51millionand704 million respectively from 2001 to 2009.