Epidemiologic Methods to Estimate Insufficient Sleep in the US Population

Population, Policy and Practice Research and Teaching Department, University College London Great Ormond Street Institute of Child Health, 30 Guilford St, London WC1N 1EH, UK

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School of Mathematical Sciences, Kean University, 1000 Morris Ave, Union, NJ 07083, USA

Author to whom correspondence should be addressed.

Int. J. Environ. Res. Public Health 2020, 17(24), 9337; https://doi.org/10.3390/ijerph17249337

Received: 1 October 2020 / Revised: 1 December 2020 / Accepted: 7 December 2020 / Published: 14 December 2020

(This article belongs to the Special Issue Sleep Quality, Well-Being and Mental Health among Adults)

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Abstract

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. View Full-Text

Keywords: sleep; sleep health; insufficient sleep; race/ethnicity; relative risk; logistic regression; Poisson regression; population-level estimates

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MDPI and ACS Style

Jean-Louis, G.; Turner, A.D.; Seixas, A.; Jin, P.; Rosenthal, D.M.; Liu, M.; Avirappattu, G. Epidemiologic Methods to Estimate Insufficient Sleep in the US Population. Int. J. Environ. Res. Public Health 2020, 17, 9337. https://doi.org/10.3390/ijerph17249337

AMA Style

Jean-Louis G, Turner AD, Seixas A, Jin P, Rosenthal DM, Liu M, Avirappattu G. Epidemiologic Methods to Estimate Insufficient Sleep in the US Population. International Journal of Environmental Research and Public Health. 2020; 17(24):9337. https://doi.org/10.3390/ijerph17249337

Chicago/Turabian Style

Jean-Louis, Girardin, Arlener D. Turner, Azizi Seixas, Peng Jin, Diana M. Rosenthal, Mengling Liu, and George Avirappattu. 2020. "Epidemiologic Methods to Estimate Insufficient Sleep in the US Population" International Journal of Environmental Research and Public Health 17, no. 24: 9337. https://doi.org/10.3390/ijerph17249337

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