An ecologic analysis of socioeconomic and environmental determinants of overweight and obesity prevalence among US adolescents using Bayesian small area estimation with 2003 and 2007 National Survey of Children's Health Open Access
Cook-Smith, Jessica Nicole (2012)
Published
Abstract
Objective: Childhood obesity continues to be a growing public health concern with 12.5 million (17%) school-age children and teens affected. We aim to predict county-level overweight and obesity prevalence among U.S. adolescents with Bayesian small area estimation. Using data from the 2003 and 2007 National Survey of Children's Health, we will explore the association of adolescent overweight and obesity prevalence with sociodemographic and physical environment characteristics.
Methods: We used a Bayesian hierarchical Poisson model based on the Markov chain Monte Carlo (MCMC) approach to estimate the county-level prevalence of childhood obesity nationwide. Negative binomial Poisson regression models will be used to perform an ecologic analysis of social and environmental determinants of health on adolescent overweight and obesity prevalence. Both the small area estimation and the county-level contextual analysis were performed for three excess weight prevalence outcomes: overweight including obesity, overweight alone, and obesity alone.
Results: Using small area estimation, 30.7% of US adolescents are overweight or obese. The South region and East South Central Census division have the highest prevalence. The geographic disparities differ when examining overweight and obesity separately. An increased risk of excess weight among adolescents is associated with certain county-level indicators of poor adult health, poor socioeconomic environment such as child poverty rate and high unemployment rates, home and school food assistance and racial composition.
Conclusions: The model-based childhood obesity prevalence estimates displayed a geographic pattern similar to that of adult obesity prevalence. Higher prevalence was predominantly seen in the southeast and in counties with indicators of poor social and physical environment and increased food assistance. The prevalence varies across and within states and contextually by county suggesting an opportunity for intervention at the local, state and national level. These results suggest that childhood obesity is a complex and multi-faceted issue and may be influenced by the combined effects of the social, economic and physical environments.
Table of Contents
TABLE OF CONTENTS
1. List of Tables...i
2. List of Figures...ii
3. List of Abbreviations...iii
4. Chapter 1: Background/Literature Review...1
5. Chapter 2.1: Manuscript 1 - Small area Bayesian model-based
estimation of overweight and obesity prevalence among US
adolescents (10-17 years) by county...19
6. Chapter 2.2: Manuscript 2 - Socioeconomic and environmental
correlates of county-level (small area) overweight and obesity
prevalence among US adolescent...33
7. Tables...46
8. Figures...57
9. Chapter 3: Summary, Public Health Implications, Possible Future
Directions...65
10. Appendix...77
11. References...88
LIST OF TABLES
Table 1. Basic descriptive statistics of state-level, public use
and county-level, restricted use 2003 and 2007 NSCH data (n, %
[unweighted]) for US children aged 10-17 years...46
Table 2. Basic descriptive statistics for model-based estimates for
overweight and obesity prevalence among 10-17 year old US
children...47
Table 3. Basic descriptive statistics of county-level contextual
variables...48
Table 4. Model-based prevalence estimates and basic statistics for
county-level covariates for counties that are below the national
overweight and obesity means (posterior mean and 95% credible
intervals exclude the national mean using 2003 and 2007
NSCH)...49
Table 5. Model-based prevalence estimates and basic statistics for
county-level covariates for counties that are above the national
overweight and obesity means (posterior mean and 95% credible
intervals exclude the national mean using 2003 and 2007
NSCH)...51
Table 6. Model fit comparison assessing for best fit when
considering all non-collinear covariates, geography (rurality and
Census-based region) and population (normal and log transformed
total population and population density...53
Table 7. Negative binomial regression model using standardized
covariates (following tests of correlation and collinearity) for
Overweight including obesity prevalence among US
adolescents...54
Table 8. Negative binomial regression model using standardized
covariates (following tests of correlation and collinearity) for
Overweight alone prevalence among US adolescents...55
Table 9. Negative binomial regression model using standardized
covariates (following tests of correlation and collinearity) for
Obesity alone prevalence among US adolescents...56
LIST OF FIGURES
Figure 1. Model-based predicted estimates of Overweight
including obesity prevalence among US children (10-17 years)
for US counties, using 2003 and 2007 NSCH data...57
Figure 2. Model-based predicted estimates of Overweight
alone prevalence among US children (10-17 years) for US
counties, using 2003 and 2007 NSCH data...57
Figure 3. Model-based predicted estimates of Obesity alone
prevalence among US children (10-17 years) for US counties, using
2003 and 2007 NSCH data...58
Figure 4. Model-based predicted estimates of Overweight
including obesity prevalence among US adolescents (10-17 years)
for US counties below and above the national mean (posterior mean
and 95% credible interval excludes the national mean...58
Figure 5. Model-based predicted estimates of Overweight
alone prevalence among US adolescents (10-17 years) for US
counties below and above the national mean (posterior mean and 95%
credible interval excludes the national mean...59
Figure 6. Model-based predicted estimates of Obesity alone
prevalence among US adolescents (10-17 years) for US counties below
and above the national mean (posterior mean and 95% credible
interval excludes the national mean...59
Figure 7. Model-based predicted estimates of Overweight
including obesity prevalence among US adolescents (10-17 years)
for US counties in the lowest and highest decile of the
mean...60
Figure 8. Model-based predicted estimates of Overweight
alone prevalence among US adolescents (10-17 years) for US
counties in the lowest and highest decile of the mean...60
Figure 9. Model-based predicted estimates of Obesity alone
prevalence among US adolescents (10-17 years) for US counties in
the lowest and highest decile of the mean...61
Figure 10. Sensitivity results for model-based Overweight
including obesity prevalence estimates among US children (10-17
years) for all US counties...62
Figure 11. Sensitivity results for model-based Overweight
alone prevalence estimates among US children (10-17 years) for
all US counties...63
Figure 12. Sensitivity results for model-based Obesity alone
prevalence estimates among US children (10-17 years) for all US
counties...64
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