Epidemiologic Methods to Estimate Insufficient Sleep in the US Population

Girardin Jean-Louis, Arlener D. Turner, Azizi Seixas, Peng Jin, Diana M. Rosenthal, Mengling Liu and George Avirappattu
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Girardin Jean-Louis: Department of Population Health, New York University Medical Center, 180 Madison Ave, New York, NY 10016, USA
Arlener D. Turner: Department of Psychiatry, New York University Medical Center, 145 E 32nd St, New York, NY 10016, USA
Azizi Seixas: Department of Population Health, New York University Medical Center, 180 Madison Ave, New York, NY 10016, USA
Peng Jin: Department of Population Health, New York University Medical Center, 180 Madison Ave, New York, NY 10016, USA
Diana M. Rosenthal: 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
Mengling Liu: Department of Population Health, New York University Medical Center, 180 Madison Ave, New York, NY 10016, USA
George Avirappattu: School of Mathematical Sciences, Kean University, 1000 Morris Ave, Union, NJ 07083, USA

IJERPH, 2020, vol. 17, issue 24, 1-8

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.

Keywords: sleep; sleep health; insufficient sleep; race/ethnicity; relative risk; logistic regression; Poisson regression; population-level estimates (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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