Spatial Distribution of Obesity among West Virginia 5th Grade Children: Analysis of the Socioeconomic, Physical, and Personal Environment

<p>Childhood obesity defined as a body mass index (BMI) at or above the 95th percentile for children of the same age and sex, is considered an epidemic in the United States. Biology and lifestyle behaviors have been identified as important factors in the development of childhood obesity; however, researchers are beginning to place more emphasis upon the impact that continual environmental exposures have upon obesity development. Environmental risk factors associated with obesity are distributed continuously over space, yet evidence suggests that burden of risk may not be evenly dispersed across a community. West Virginia (WV), a rural Appalachian community has the tenth highest childhood obesity rate in the nation, yet little is known about the spatial distribution of the environmental risks and obesity within the state. The purposes of this study were threefold: 1) to determine which socioeconomics, physical, and personal environmental attributes contribute to a BMI equal to or greater than the 85th percentile for age, and gender; 2) to determine which socioeconomics, physical, and personal environmental attributes contribute to obesity (BMI equal to or greater than the 95th percentile for age, and gender); and 3) to assess the geographic distribution of attributes (socioeconomic, physical, and personal) in relation to BMI equal to or greater than the 85th percentile (overweight) and BMI equal to or greater than the 95th percentile (obese) among WV 5th graders.</p> <p>Secondary data analyses of cross-sectional statewide data were performed to examine the proposal that obesity is the consequence of environmental exposures and that the distribution of obesity disproportionally affects some WV communities greater than others. The study sample was comprised of 12,194 fifth grade children ranging in age from 10-12 years old with a verifiable zip code for the state of WV. Study indicators used to quantify socioeconomic, physical, and personal environmental attributes were derived from various data sources. Data were gathered for the academic school years of 2007/2008 and 2008/2009. Individual data for each child subject consisting of BMI percentile and family history (diabetes and heart disease) were coded at the zip code level. Aggregate data for socioeconomic, physical, and personal environmental attributes were computed per zip code. County level data (violent crime) and school level fitness (percent of children in the fitness zone per 5th grade class) were linked back to each child by means of county to school to zip code or school to zip code. Binary logistic regression methods were employed to determine which attributes (socioeconomic, physical, and personal environment) contributed to overweight and obesity. Geographic Information System (GIS) technology was utilized to explore obesity spatial distribution and the relationship of obesity and overweight to environmental attributes at the zip code level.</p> <p>Findings indicate that elements of the socioeconomic, physical, and personal environment are heterogeneous and independent, yet interact dynamically as predictors of obesity. Spatially groupings of overweight and obesity and identified risk factors were observed. Findings from this study support the need for additional research to examine the significance of spatial clusters and associated risk factors. </p>

Name thesis:degree_name

Doctor of Philosophy (PhD)

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Nursing

Year dc:date.available

2011

Author dc:creator

• Roper, Sherry

Contributors dc:contributor

• Patricia A. Cowan, Ph.D.

• Appalachian
• childhood obesity
• GIS
• obesogenic
• spatial analysis
• West Virginia
• Diseases
• Epidemiology
• Maternal and Child Health
• Medicine and Health Sciences
• Nutritional and Metabolic Diseases
• Public Health

Repository record dc:identifier

https://dc.uthsc.edu/dissertations/227

OAI identifier oai:identifier

oai:dc.uthsc.edu:dissertations-1224