Mapping Obesity in the United States: Statewise Demographic Trends and Implications

Abstract

Background: Obesity is a major public health challenge associated with numerous chronic conditions, including diabetes, polycystic ovarian syndrome(PCOS), hypertension, stroke, gastroesophageal reflux disease( GERD), metabolic dysfunction-associated steatotic liver disease (MASLD), cancer, and depression. The prevalence in the United States continues to rise and varies significantly across racial, geographic, and demographic groups. This study analyzes obesity trends from 2011 to 2023, focusing on regional and population-level differences to better understand the distribution and inferred clinical implications of obesity, using a multi-level, population-based framework to identify obesity determinants and guide targeted, evidence-based lifestyle interventions Methods: Data were obtained from the National Health and Nutrition Examination Survey (NHANES) between 2011 and 2023. Obesity prevalence was stratified by race/ethnicity and geographic region (South, Midwest, West, Northeast). Descriptive statistics and graphical illustrations were used to identify trends. Findings were contextualized with peer-reviewed literature addressing the associations between obesity, medical conditions, and sociodemographic variables. Results: Obesity prevalence was highest in the South and Midwest, with women exhibiting slightly higher median values than men. The regression model shows a strong relationship between year and obesity rate (R = 0.956, R² = 0.914), meaning 91.4% of the changes in obesity rates can be explained by the year. The model fits well (Adjusted R² = 0.906, Standard Error ≈ 0.70), and the obesity rate is increasing by about 0.561% per year in the South among Non-Hispanic Black adults (p = 0.060), the overall model is still statistically significant, and the coefficients have strong significance (p < 0.0001). Overall, this model suggests a clear upward trend and can be used to forecast future obesity rates if the pattern continues. Adjusted R² (0.906) accounts for the number of predictors in the model, and it's slightly lower than R², suggesting the model is robust and doesn't overfit the data, with Standard Error of the Estimate = 0.70048 that represents the average distance that the observed values fall from the regression line indicating better predictive accuracy(p < 0.0001,95% CI 0f 0.447 to 0.675).  Conclusion: The continuing rise of obesity prevalence, particularly in minority populations such as African Americans, has critical implications for GI health. The study indicates that generally, obesity is concentrated in Non-Hispanic Black and Hawaiian/Pacific Islander populations. Obesity is generally more prevalent in southern and midwestern regions. Screening, prevention, and management strategies for GI disorders should be redefined to integrate obesity reduction interventions, including pharmacologic therapies, dietary counseling, and lifestyle modifications. Providers serving high-risk communities must adopt these approaches to improve outcomes and reduce obesity-related GI morbidity.