A developmental perspective on sleep consistency: Preschool age through emerging adulthood

What does it mean to use the mean? The impact of different data handling strategies on the proportion of children classified as meeting 24-hr movement guidelines and associations with overweight and obesity

Background

Despite the widespread endorsement of 24-hour movement guidelines (physical activity, sleep, screentime) for youth, no standardized processes for categorizing guideline achievement exists. The purpose of this study was to illustrate the impact of different data handling strategies on the proportion of children meeting 24-hour movement guidelines (24hrG) and associations with overweight and obesity.

Methods

A subset of 524 children (ages 5-12yrs) with complete 24-hour behavior measures on at least 10 days was used to compare the impact of data handling strategies on estimates of meeting 24hrG. Physical activity and sleep were measured via accelerometry. Screentime was measured via parent self-report. Comparison of meeting 24hrG were made using 1) average of behaviors across all days (AVG-24hr), 2) classifying each day and evaluating the percentage meeting 24hrG from 10-100% of their measured days (DAYS-24hr), and 3) the average of a random sample of 4 days across 10 iterations (RAND-24hr). A second subset of children (N=475) with height and weight data was used to explore the influence of each data handling strategy on children meeting guidelines and the odds of overweight/obesity via logistic regression.

Results

Classification for AVG-24hr resulted in 14.7% of participants meeting 24hrG. Classification for DAYS-24hr resulted in 63.5% meeting 24hrG on 10% of measured days with <1% meeting 24hrG on 100% of days. Classification for RAND-24hr resulted in 15.9% of participants meeting 24hrG. Across 10 iterations, 63.6% of participants never met 24hrG regardless of the days sampled, 3.4% always met 24hrG, with the remaining 33.0% classified as meeting 24hrG for at least one of the 10 random iterations of days. Using AVG-24hr as a strategy, meeting all three guidelines associated with lower odds of having overweight obesity (OR=0.38, p<0.05). The RAND-24hr strategy produced a range of odds from 0.27 to 0.56. Using the criteria of needing to meet 24hrG on 100% of days, meeting all three guidelines associated with the lowest odds of having overweight and obesity as well (OR=0.04, p<0.05).

Conclusions

Varying estimates of meeting the 24hrG and the odds of overweight and obesity results from different data handling strategies and days sampled.

Substance use and sleep health in young adults: Implications for integrated treatment and harm reduction

In their systematic review and meta-analysis, Meneo and colleagues document distinct substance-sleep effects reported by young adults (ages 18-30) across multidimensional sleep health and different substances used in the naturalistic environment, including alarming rates of self-medication for sleep aid. Key innovations of Meneo et al.'s review include (a) a multidimensional approach to defining sleep health and (b) robust inclusion of various substances commonly used in young adults. Although future research will be essential to clarifying transdiagnostic risk mechanisms, interplay of co-used substances, and the role of expectancies in risk processes, the developing literature reviewed herein may inform much-needed clinical recommendations. This work by Meneo et al should prompt an emphasis on approaching young adult substance use and self-medication through a harm reduction lens, highlighting recommendations for integrated behavioral sleep treatment tailored to stage of change using motivational interviewing.

Daily relations between nap occurrence, duration, and timing and nocturnal sleep patterns in college students

OBJECTIVE/DESIGN

Sleep patterns change during college, and students may nap to compensate for lost sleep. Despite the increased prevalence of napping among students, few studies have investigated daily relations between napping and nocturnal sleep, as well as how timing of naps and nocturnal sleep might influence one another. The present study used daily diaries to capture the occurrence, timing, and duration of napping and relation to nocturnal sleep.

SETTING/PARTICIPANTS

Daily diary data, collected for 4-7 days, from 654 college students from a mid-sized midwestern university (81.5% female).

MEASUREMENT

Participants reported nightly sleep durations, bedtimes, and wake times as well as nap durations and nap start times.

RESULTS

Multilevel modeling (MLM) and multi-level logistic regressions revealed bidirectional relations between nocturnal sleep and napping. Regarding nocturnal sleep and its relation to next day napping, nocturnal sleep (including shorter duration and later bedtime) was associated with increased odds of napping and longer napping the following day. Shorter sleep duration was also associated with taking an earlier nap, while later bedtime was associated with a later nap the following day. Regarding napping and its association with same-night nocturnal sleep, taking a nap was associated with longer sleep duration that night, however, later nap start times and longer nap durations were associated with later bedtimes that night.

CONCLUSIONS

Findings provide evidence for bidirectional associations between napping and nocturnal sleep. Future studies are needed to explore how naps could be optimized to promote nocturnal sleep among college students, as well as for whom naps might be most beneficial.