Frontiers in epidemiology · 2026
Variability of obesity prevalence in US states: are obesity growth or deterioration rates constant for different income quantiles?
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Arbel Yuval, Arbel Yifat, Kerner Oriya, Kerner Miryam
Аннотация
BACKGROUND: Obesity remains a major public health concern in the United States, with evidence suggesting that its prevalence varies significantly across socioeconomic groups. This study investigates how annual changes in obesity rates differ by income quantiles across U.S. states from 2012 to 2020.
METHODS: An empirical model was developed incorporating income-quantile dummy variables and a linear time trend, allowing for differences in average annual changes in obesity prevalence across income groups. Annual change is defined as the year-to-year percentage change in age-adjusted obesity prevalence relative to the preceding year. The analysis draws on state-level data to evaluate baseline differences and subsequent yearly changes in obesity prevalence.
RESULTS: Obesity prevalence differs substantially across income groups in the baseline year, with lower-income groups exhibiting higher prevalence levels. All income groups experienced positive annual increases in obesity prevalence over the study period. Differences in annual changes among lower- and middle-income categories are relatively small in magnitude, while the highest income group (annual income above $75,000) exhibits a larger average annual increase relative to other groups. The estimated time trend is not statistically significant, indicating stable differences in annual changes across income groups over time.
CONCLUSION: The findings highlight persistent socioeconomic differences in obesity prevalence across U.S. states. While lower-income groups bear a higher overall obesity burden, rising obesity prevalence is observed across the entire income distribution. These patterns suggest that public health responses may benefit from accounting for income-related differences in obesity prevalence, particularly through voluntary approaches such as information campaigns, expanded access to healthy foods and opportunities for physical activity, and initiatives related to the built environment.
METHODS: An empirical model was developed incorporating income-quantile dummy variables and a linear time trend, allowing for differences in average annual changes in obesity prevalence across income groups. Annual change is defined as the year-to-year percentage change in age-adjusted obesity prevalence relative to the preceding year. The analysis draws on state-level data to evaluate baseline differences and subsequent yearly changes in obesity prevalence.
RESULTS: Obesity prevalence differs substantially across income groups in the baseline year, with lower-income groups exhibiting higher prevalence levels. All income groups experienced positive annual increases in obesity prevalence over the study period. Differences in annual changes among lower- and middle-income categories are relatively small in magnitude, while the highest income group (annual income above $75,000) exhibits a larger average annual increase relative to other groups. The estimated time trend is not statistically significant, indicating stable differences in annual changes across income groups over time.
CONCLUSION: The findings highlight persistent socioeconomic differences in obesity prevalence across U.S. states. While lower-income groups bear a higher overall obesity burden, rising obesity prevalence is observed across the entire income distribution. These patterns suggest that public health responses may benefit from accounting for income-related differences in obesity prevalence, particularly through voluntary approaches such as information campaigns, expanded access to healthy foods and opportunities for physical activity, and initiatives related to the built environment.