Association Between Sleep Characteristics and Anthropometric Indices Among Adults: A Cross-Sectional Study From the...

Sleep characteristics have been increasingly recognized as important determinants of obesity and metabolic health. This study aimed to investigate the association between sleep characteristics and obesity indices among adults participating in the Prospective Epidemiological Research Studies in Iran (PERSIAN) Guilan Cohort Study (PGCS).

This cross-sectional analytical study included 10,520 adults aged 35-70. Demographic, lifestyle, anthropometric, and sleep-related data were collected using standardized questionnaires. Obesity indices included body mass index (BMI), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR). Associations between sleep characteristics and obesity indices were evaluated using chi-square tests and logistic regression analyses. Adjusted odds ratios (aORs) and 95% confidence intervals (95% CIs) were calculated after controlling for potential confounders.

The mean age of participants was 51.52 ± 8.90 years, and 53.5% were women. Overall, 32.7% of participants were obese based on BMI, with significantly higher prevalence among women than men (47.0% vs. 16.1%, p < 0.001). Short sleep duration (< 7 h) was reported by 43.7% of participants. In men, sleeping 7-9 h and > 9 h was associated with lower odds of BMI-defined obesity compared with sleeping < 7 h (aOR = 0.75, 95% CI: 0.64-0.88 and aOR= 0.54, 95% CI: 0.38-0.78, respectively). Longer sleep duration was also associated with lower odds of WHR- and WHtR-defined obesity in men (p < 0.05). Conversely, daytime sleeping and daytime napping were associated with higher odds of central obesity among men (p < 0.05). In women, later bedtime was independently associated with higher odds of obesity, while waking between 06:00 and 09:00 was associated with lower odds of central obesity (p < 0.05).

Sleep characteristics were significantly associated with general and central obesity, with notable sex-specific differences. These findings support the integration of sleep assessment into obesity prevention and management strategies.