Sleep disturbances have been associated with unemployment, but variation in sleep-wake patterns by labor force status has rarely been examined. With a population-based sample, we investigated differences in sleep-wake patterns by labor force status (, and ) and potential disparities by sociodemographic variables. The analysis included 130,602 adults aged 25-60 y, who participated in the American Time Use Survey between 2003 and 2019. Individual sleep-wake pattern was extracted from time use logs in a strict 24-h period (04:00 h-03:59 h). Functional nonparametric regression models based on dimensionality reduction and neighborhood matching were applied to model the relationship between sleep-wake patterns and labor force status. Specifically, we predicted changes in intra-person sleep-wake patterns under hypothetical changes of labor force status from to or . We then studied moderations of this association by gender, race/ethnicity and educational attainment. In comparison to the state, and states were predicted to have later wake-times, later bedtimes, and higher tendency for taking midday naps. Changes in labor force status led to more apparent shifts in wake-times than in bedtimes. Additionally, sleep schedules of Hispanics and those with higher education level were more vulnerable to the change of labor force status from to .

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http://dx.doi.org/10.1080/07420528.2023.2253904DOI Listing

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