Associations between bedtime eating or drinking, sleep duration and wake after sleep onset: findings from the American time use survey.

Sleep hygiene recommendations discourage eating before bedtime; however, the impact of mealtime on sleep has been inconsistent. We examined gender-stratified associations between eating or drinking <1, <2 and <3 h before bedtime, sleep duration and wake after sleep onset (WASO >30 min). This study utilised 2003-2018 data from the American Time Use Survey, a nationally representative sample of USA residents aged ≥15 years. Participants recorded weekday/weekend activities during a 24-h period. Age-specific sleep duration and WASO were estimated categorically and continuously. Eating or drinking were identified from all activities recorded <1, <2 and <3 h before bedtime. Mean ± se sleep duration was 8·0 ± 0·006 h, and 6% of participants ate or drank <1 h prior to weekdays bedtime. Overall, eating or drinking <1 h prior to bedtime was associated with longer weekdays sleep duration. Women and men who ate or drank <1 h before bedtime, v. those who did not, had 35 min (95% CI (30,39)) and 25 min (95 % CI (21,29)) longer sleep duration, respectively, as well as increased odds of WASO; women (OR=2·03, 95% CI (1·66,2·49)) and men (OR=2·64, 95% CI (2·08,3·36)). As the interval of eating or drinking prior to bedtime expanded, odds of short and long sleep durations and WASO decreased. This population-based data linked eating or drinking <1 h before bedtime to longer sleep duration, but increased WASO. Eating or drinking further from bedtime lowers the odds of short and long sleep duration and WASO. Causal pathways are difficult to discern, though inefficient sleep after late-night eating could increase WASO and trigger compensatory increases in sleep duration.

Longitudinal activity monitoring and lifespan: quantifying the interface.

Understanding the relationship between activity over the entire lifespan and longevity is an important facet of aging research. We present a comprehensive framework for the statistical analysis of longitudinal activity and behavioral monitoring and their relationship with age-at-death at the individual level, highlighting the importance of advanced methodological approaches in aging research. The focus is on animal models, where continuous monitoring activity in terms of movement, reproduction and behaviors over the entire lifespan is feasible at the individual level. We specifically demonstrate the methodology with data on activity monitoring for Mediterranean fruit flies. Advanced statistical methodologies to explore the interface between activity and age-at-death include functional principal component analysis, concurrent regression, Fréchet regression and point processes. While the focus of this perspective is on relating age-at-death with data on movement, reproduction, behavior and nutrition of Mediterranean fruit flies, the methodology equally pertains to data from other species, including human data.