Epidemiologic Methods to Estimate Insufficient Sleep in the US Population

• Main Authors: Girardin Jean-Louis, Arlener D. Turner, Azizi Seixas, Peng Jin, Diana M. Rosenthal, Mengling Liu, George Avirappattu
• Format: Article
• Language: English
• Published: MDPI AG 2020-12-01
• Series: International Journal of Environmental Research and Public Health
• Subjects: sleep; sleep health; insufficient sleep; race/ethnicity; relative risk; logistic regression
• Online Access: https://www.mdpi.com/1660-4601/17/24/9337
• ISSN: 1661-7827; 1660-4601

This study explored the divergence in population-level estimates of insufficient sleep (<6 h) by examining the explanatory role of race/ethnicity and contrasting values derived from logistic and Poisson regression modeling techniques. We utilized National Health and Nutrition Examination Survey data to test our hypotheses among 20–85 year-old non-Hispanic Black and non-Hispanic White adults. We estimated the odds ratios using the transformed logistic regression and Poisson regression with robust variance relative risk and 95% confidence intervals (CI) of insufficient sleep. Comparing non-Hispanic White (10176) with non-Hispanic Black (4888) adults (mean age: 50.61 ± 18.03 years, female: 50.8%), we observed that the proportion of insufficient sleepers among non-Hispanic Blacks (19.2–26.1%) was higher than among non-Hispanic Whites (8.9–13.7%) across all age groupings. The converted estimated relative risk ranged from 2.12 (95% CI: 1.59, 2.84) to 2.59 (95% CI: 1.92, 3.50), while the estimated relative risks derived directly from Poisson regression analysis ranged from 1.84 (95% CI: 1.49, 2.26) to 2.12 (95% CI: 1.64, 2.73). All analyses indicated a higher risk of insufficient sleep among non-Hispanic Blacks. However, the estimates derived from logistic regression modeling were considerably higher, suggesting the direct estimates of relative risk ascertained from Poisson regression modeling may be a preferred method for estimating population-level risk of insufficient sleep.