Abstract:
Purpose: Obesity and poor sleep quality are interconnected health concerns with complex, multifactorial origins. While physiological pathways contribute to this two-way relationship, growing evidence highlights the role of social and behavioral factors in shaping this association. This study examines the relationship between obesity and sleep quality among U.S. adults using data from the 2017–2020 National Health and Nutrition Examination Survey (NHANES), with particular attention to the extent that this relationship is moderated by gender, age, race/ethnicity, food insecurity, physical activity, smoking, and alcohol consumption. Understanding how these variables influence the obesity–sleep link may inform more targeted and equitable health interventions.
Methods: A cross-sectional analysis was conducted using NHANES data from 2017 to 2020, including adults aged 18 years and older with complete data on body mass index (BMI), sleep quality, and relevant covariates. Obesity was defined as BMI ≥30 kg/m². Sleep quality was assessed using self-reported measures of perceived sleep problems. Moderating variables included gender, age group, race/ethnicity, food insecurity, physical activity, smoking, and alcohol use. Multivariable logistic regression models were used to examine the association between obesity and poor sleep quality, adjusting for demographic and socioeconomic factors. Stratified models explored moderation effects.
Results: In the overall sample, obesity was significantly associated with increased odds of reporting poor sleep quality with an adjusted odds ratio (aOR) = 1.97, 95% CI [1.75, 2.22], p < 0.001). This relationship varied across population subgroups. Men showed a slightly stronger association than women (aOR = 2.13 vs. 1.86, respectively; p< 0.001). Age moderated the association, with the strongest relationship observed among younger adults under 35 years compared to adults older than 65. Racial/ethnic differences were also evident: the association was statistically significant among non-Hispanic White, Black, and Asian adults (e.g., non-Hispanic Asian aOR = 2.35, 95% CI [1.48, 3.74], p < 0.001), but it was not observed among Mexican Americans (aOR = 1.01, 95% CI [0.66, 1.55], p > 0.05). Food insecurity moderated the association, although unexpectedly, the relationship between obesity and poor sleep was weakest among those with very low food security. Physical activity and smoking did not appear to influence the obesity–sleep relationship. However, excessive alcohol consumption (more than six drinks per day) significantly amplified the association (aOR = 2.70, p < 0.001), compared to those consuming 1–2 drinks daily (aOR = 1.88, p < 0.001).
Conclusion: The association between obesity and poor sleep quality is not uniform and is moderated by several demographic and behavioral factors. Gender, age, race/ethnicity, food insecurity, and alcohol use significantly influence the strength of this relationship, while physical activity and smoking showed no modifying effects in this sample. These findings underscore the importance of adopting nuanced, subgroup-sensitive approaches when designing strategies to address sleep disturbances among individuals with obesity. Tailored interventions that account for social context and behavioral risks may be more effective in reducing disparities and improving sleep- related outcomes in obese individuals.
