Sleep Duration and Weight-Related Behaviors among Adolescents

Abstract

Background:

Insufficient sleep is widespread among adolescents and has consequences that extend far beyond hampering day-to-day functioning. It may influence eating and physical activity patterns and be an important determinant of adolescent overweight/obesity status.

Methods:

We assessed how self-reported sleep duration on school nights was associated with weight-related behaviors (eating, diet, and physical activity) and overweight/obesity at the baseline wave (ninth grade year) of the START study (n = 2134).

Results:

Fifteen percent of our sample reported optimal sleep duration (8.5–10.0 hours); nonwhites, participants of lower socioeconomic status, and girls were at greater risk for insufficient sleep. Suboptimal sleep was associated with various poor weight-related behaviors such as increased sugar-sweetened beverage consumption, decreased vegetable consumption, and decreased breakfast eating (p < 0.001). Fewer hours of sleep were also associated with less physical activity and an increased likelihood of obesity (p = 0.02 for both associations).

Conclusions:

The influence of adolescent sleep insufficiency on diet and activity could impact childhood obesity and following chronic disease risk especially if lack of sleep sets the stage for enduring, lifelong, poor, weight-related behavior patterns.

Introduction

According to 2013–2016 US national surveillance data, one-fifth (20.6%) of adolescents aged 12–19 years were obese.^1,2 Many features of youths' behaviors and environments can be disruptors of energy balance. In the last decade, public health research, intervention, and policy efforts have attempted to discover, define, and even intervene upon a multitude of factors that may be driving this epidemic.^3,4 Among these, deficiency in sleep has received increasing attention as being an important, potential causal factor in weight gain.

Previous research has revealed a cross-sectional correlation between short sleep duration and obesity risk in adolescence,^5–10 with one estimate showing that for each additional hour of adolescent sleep debt, the odds of being obese increase by 80%.¹¹ While there are no population-based experimental studies on sleep duration and obesity in adolescence, there have been a handful of observational longitudinal studies exploring this question. Results from these have been mixed, with some of the longitudinal research revealing that sleep-deprived adolescents were more likely to gain weight over time^12,13 and others reporting no association.^14–16 However, taking the longitudinal evidence together, two meta-analyses have concluded that children and adolescents who sleep for shorter durations increase their future odds of overweight and obesity.^17,18

Concurrent with the rise in childhood obesity in the United States,¹⁹ there has been a striking reduction in adolescent sleep duration over the past several decades.²⁰ Few US high school students (7.6%) report getting what is considered an optimal number of hours of nighttime sleep (nine or more hours) on weekday nights.^21,22 Studies have reported that somewhere between 30% and 70% of adolescents sleep <7 hours on school nights. This is likely largely due to US high schools'²³ very early start times, which are asynchronous with adolescent circadian biology.²⁴ Additionally, there are gender and socioeconomic status (SES) disparities, with girls and those from lower SES backgrounds being far more likely to report getting fewer than 7 hours of sleep compared with other groups.²⁰

Although there have been no published reports examining the impact of sleep duration on both physical activity and eating behaviors in population-based samples of adolescents, there is evidence for multiple mechanisms that may contribute to energy imbalance in sleep-deprived young people.^25–27

Short sleep duration and resulting exhaustion might curtail physical activity and/or increase sedentary time while awake; it may alter the metabolic rate or modify appetite and timing of eating in ways that promote weight gain. Explanations for why appetite might shift as a result of declining sleep include a change in the appetite regulatory hormones,²⁸ leptin and grelin,²⁹ or an increase in the intrinsic hedonic value of foods (the amount of pleasure one derives from eating) when one is feeling otherwise fatigued. For instance, although they did not report increased hunger, in an experimental trial, after five consecutive nights of restricted sleep, adolescents rated pictures of sweets and desserts as more appealing and consumed 11% more total calories and 52% more servings of sweets or desserts compared with the healthy sleep duration condition.^25,30 Similarly, an experimental study of 18 adolescents who regularly slept less than the recommended duration (5–7 hours) showed that intervening to extend their sleep resulted in decreased time spent in sedentary activity, although there was no change in time spent in moderate to vigorous physical activity.³¹

To unpack how sleep might be related to unhealthy weight gain, we sought to examine how sleep duration related to a variety of adolescent weight-related behaviors, which have not been explored in depth in the literature in population-based samples previously. We hypothesized that adolescents who report sleeping fewer hours would report less physical activity and less healthful weight-related (eating, diet, and physical activity) behaviors. We also hypothesized that (similar to previous studies) we could find that shorter sleep duration was associated with concurrently higher BMIs.

Methods

The START study is an NIH-funded evaluation of a natural experiment in high school start time modification that is following a cohort of students in five schools. For this article, we analyzed data from student surveys and anthropomorphic measurements collected during the baseline period (prepolicy change) when all study schools started between 7:30 and 7:45 am. All study procedures were reviewed and approved by the University of Minnesota Institutional Review Board (IRB) and the school districts' research review panels.

Study Population and Recruitment

The University of Minnesota IRB and the school districts' research review panels approved a waiver of informed consent for the procedures described in this article, in accordance with 45 CFR 46.1116 (d),³² due to the fact that this research (1) involved no more than minimal risk to participants, (2) the waiver would not adversely affect their welfare, and (3) the research could not be practicably carried out without the waiver.

Letters were sent to parents of all ninth grade students in five suburban and exurban Minneapolis, MN, metro area high schools, explaining the voluntary nature of the study and how to opt out of study procedures. On measurement days, participants who were not previously opted out by their parents or guardians were given information about the study—that it was voluntary—and were then able to assent to participating. In total, from the 2362 students enumerated in school-provided lists, 2134 students completed the survey, which yielded a 90% response proportion. Among the 228 students who did not complete a survey, we were able to determine that 19 were absent from school on survey days, 10 opted out (either by the student or their parent/guardian), and 13 were attending an alternative school despite appearing on the school list. We did not receive surveys from 186 students for unknown reasons.

Measures

Sleep duration was calculated from two survey items adapted from the Teen Sleep Habits Survey^33,34: “About what time do you usually go to bed on school days?” “About what time do you usually wake up on school days?” (response options were 15-minute intervals in appropriate evening/early morning and morning times, respectively). The time difference between the responses to these two questions provided a continuous variable (measured to the nearest 15-minute interval).

From the continuous variable, we created a five-level sleep duration measure based on the frequency distribution and guided by the research literature: <6.0, 6.0–6.75, 7.0–7.5, 7.75–8.25, and 8.5–10. The upper category, 8.5–10 hours of sleep per night, while above the National Sleep Foundation's recommended range for adolescents (8–10 hours of sleep),³⁵ comes closer to identifying youth who might be getting what is considered optimal³⁶ rather than merely adequate sleep.

The following demographics were self-reported on the survey: sex (male vs. female), race/ethnicity (seven categories collapsed to white vs. nonwhite for analytic models), highest level of parent–guardian education (five levels dichotomized to finished college vs. high school/some college), and whether the student qualified for free and reduced lunch (yes, no, or don't know).

We used and adapted survey measures from Project EAT to measure eating behaviors.^37,38 These included the frequency of eating meals and other eating habits and consumption of specific foods and beverages. The frequency of meals was measured as (1) frequency of eating breakfast during a normal school week (0–5 days dichotomized to 5 days vs. less often); (2) frequency of eating breakfast with family (0–7 days dichotomized to 1–7 days vs. 0 days); and (3) frequency of eating supper with family (0–7 days dichotomized to 5–7 days vs. fewer days). Three additional eating-related items included frequencies of the following: (1) stop eating when you feel full; (2) feel hungry through the school day; and (3) trust your body to tell you how much to eat (each had four response options that we collapsed to much of the time/almost always vs. sometimes/hardly ever).

Seven categories of specific food intake were measured with items adapted from the Dietary History Questionnaire (DHQ)³⁹ and these included daily fruit consumption and weekly consumption of salads, vegetables (other than potatoes), fried potatoes, nonfried potatoes, pizza, and fast food (each of these had nine response options collapsed to two). Mean number of times per month of consuming six types of beverages included water, 100% fruit juice, sugar-sweetened beverages (sum of soda, pop, coffee, and fruit drinks), diet beverages (sum of soda/pop, fruit drinks, and cold/iced tea), sports/energy drinks, and caffeinated beverages (sum of soda/pop, coffee, and ice/cold tea).

All beverage items had nine response options indicating the frequency of consumption that was converted to number of times per month. To calculate the frequency of sugar-sweetened, diet, and caffeinated beverages consumed, we used the follow-up survey item for the relevant type of beverage regarding the proportion of total consumption that was diet/sugar free and/or caffeine free.

The frequency of physical activity in the last 7 days was measured using two measures: (1) number of days being physically active at least 60 minutes per day (activity that increased the heart rate and made you breathe hard for some of the time); response options were collapsed to 3–7 versus 0–2; and (2) hours spent doing moderate (not exhausting) and strenuous (heart beats rapidly) physical activity⁴⁰—we summed responses to these two items and dichotomized to at least 7 hours versus fewer.

Height and weight were used to calculate BMI z-scores, which we then categorized as at or above the 85th percentile (overweight) and at or above the 95th percentile (obese), based on CDC/NCHS growth curve data.⁴¹ Height and weight were measured objectively for 75% of students on the class lists. For analyses involving BMI, we used objective height and weight measurements to calculate BMI if available. In cases where objective height and weight were not measured, we substituted them with self-reported height and weight from the survey. If a subjective BMI had a z-score greater or less than 3, it was judged invalid and not used (n = 1). We were able to use objective height and weight measurements for 78.2% of this sample, and self-reported height and weight were used for the remaining proportion. In all regression models that examined the BMI z-score as an outcome, we included an adjustment variable indicating whether an objective or subjective BMI z-score was used to control for confounding by measurement type.

Analyses

We first calculated descriptive statistics for all measures. Bivariate analyses (chi-square tests; p = 0.05) were used to examine associations between demographics and our sleep measure. We then computed two sets of regression models, 1) unadjusted and 2) adjusted for student age, free/reduced lunch eligibility, and race (white vs. not white), to examine associations between sleep duration and diet and weight measures. In both sets, we computed a separate regression model for each independent measure, with school included as a random effect to account for nesting of students within schools. We examined sleep-by-sex interaction terms to consider whether associations between sleep duration and outcomes differed by gender. All analyses were conducted using SAS 9.4 (SAS/STAT, Inc., Cary, NC).

Results

Our sample was 51% male and 88% white (Table 1). The majority (80%) of students reported that at least one of their parents finished college and 13% qualified for free or reduced lunch. Approximately one-third of our sample reported <7 hours of sleep on school nights and 15% reported optimal sleep duration (8.5–10.0 hours). Girls were more likely than boys to report insufficient sleep (Table 2). In addition, students in two of the nonwhite racial/ethnic categories (African American and Asian) were more likely to report shorter versus longer sleep duration, compared with whites. Lower SES (both measured by parent education and qualifying for free/reduced price lunch) was associated with shorter sleep duration.

Table 1.

Demographics and School Night Sleep Duration (n = 2134)

	N (%)
Sex
Male	1066 (50.9)
Female	1028 (49.1)
Race/Ethnicity (check all that apply)
White or Caucasian	1802 (87.7)
Black, African, or African American	118 (5.7)
Hispanic or Latino/a	73 (3.5)
Asian	180 (8.8)
American Indian or Alaskan Native	70 (3.4)
Native Hawaiian or other Pacific Islander	13 (0.6)
Something else	18 (0.9)
Parent education
Finished college	1502 (79.5)
High school or some college	388 (20.5)
Qualify for free/reduced lunch
Yes	258 (12.8)
No	1383 (68.6)
I don't know	374 (18.6)
Sleep duration (in hours)
<6.0	190 (9.1)
6.0–6.75	408 (19.6)
7.0–7.5	582 (27.9)
7.75–8.25	582 (27.9)
8.5–10.0	323 (15.5)

Due to missing values, ns for some variables total to less than 2134.

Table 2.

School Night Sleep Duration by Demographics (n = 2134)

	Hours of sleep (in 15-minute intervals)					p ^a
	<6	6–6.75	7–7.5	7.75–8.25	8.5–10	p ^a
Sex						0.002
Male	39.5%	47.9%	50.7%	51.8%	57.8%
Female	60.5	52.1	49.3	48.2	42.2
Race/Ethnicity
White or Caucasian	80.2	84.7	88.2	88.7	92.3	0.0007
Black, African, or African American	12.1	8.6	4.4	4.2	3.8	<0.0001
Hispanic or Latino/a	3.8	5.5	4.0	2.3	2.2	0.05
Asian	9.9	10.4	9.7	9.0	4.2	0.03
American Indian or Alaskan Native	4.4	2.9	3.5	3.7	3.2	0.90
Native Hawaiian or other Pacific Islander	1.1	0.3	0.5	0.7	1.0	0.64
Something else	0.6	1.6	0.5	0.9	1.0	0.59
Parent education						0.004
Finished college	69.3	77.8	83.0	80.3	80.7
High school or some college	30.7	22.2	17.0	19.7	19.3
Qualify for free/reduced lunch						0.001
Yes	23.2	13.7	10.6	11.7	10.6
No	57.5	66.2	71.4	70.4	71.9
I don't know	19.3	20.1	18.0	17.9	17.6

Chi-square or Fisher exact tests (bold text: p ≤ 0.05).

Analyses of the association of sleep with diet and weight-related behaviors revealed several associations in unadjusted models (Table 3) as well as in adjusted models (Table 4). Longer sleep duration was associated with eating breakfast regularly and eating breakfasts with family. Furthermore, shorter sleep duration was associated with more frequent consumption of sugar-sweetened, diet, caffeinated, and sports/energy beverages and lesser consumption of vegetables. Those reporting the shortest sleep durations were least likely to report physical activity on at least 3 days per week and those reporting 7–7.5 hours of sleep were most likely to state they were physically active on at least 3 days per week. Those who slept fewer hours were more likely to have a BMI z-score in the overweight or obese range. Since there were no sleep duration-by-sex interaction terms with p < 0.2, we did not report results stratified by sex.

Table 3.

School Night Sleep Duration by Diet and Weight-Related Behaviors (Unadjusted)

	Hours of sleep (in 15-minute intervals)					p^a (df = 4)
	<6	6–6.75	7–7.5	7.75–8.25	8.5–10	p^a (df = 4)
Eating behaviors
Eat breakfast 5 days/week	26.6%	37.9%	53.5%	61.6%	56.9%	<0.0001
Eat breakfast with family 1–7 days/week	23.0	29.2	35.3	40.0	44.0	<0.0001
Eat supper with family 5–7 days/week	46.7	48.6	55.8	58.5	66.2	<0.0001
Stop eating when feel full	81.0	80.8	84.0	81.7	81.2	0.73
Trust body: how much to eat	63.7	69.0	71.0	70.6	69.3	0.45
Feel hungry at school	59.3	58.7	50.3	48.1	47.4	0.002
Food consumption
Fruit daily	36.1%	42.5%	42.2%	43.0%	43.0%	0.55
Salads weekly	60.6	72.5	71.8	67.7	69.0	0.03
Vegetables other than potatoes weekly	73.1	84.3	87.5	83.6	88.1	<0.0001
Fried potatoes weekly	67.1	66.8	70.0	64.8	66.6	0.46
Nonfried potatoes weekly	55.1	61.8	62.9	59.7	60.6	0.41
Pizza weekly	58.4	63.7	68.0	63.7	60.8	0.10
Fast food weekly	66.9	68.9	69.6	67.2	61.9	0.20
Beverage consumption (mean number of times/day)
Water	3.2	3.3	3.5	3.5	3.5	0.38
100% Fruit juice	0.8	0.7	0.6	0.5	0.5	0.007
Sugar-sweetened beverages	1.9	1.3	1.1	0.9	0.9	<0.0001
Diet beverages	0.5	0.3	0.2	0.1	0.1	<0.0001
Sports/Energy drinks	0.7	0.4	0.4	0.3	0.3	<0.0001
Caffeinated beverages	1.2	0.7	0.5	0.4	0.4	<0.0001
Physical activity
Active 3–7 days/week	79.1%	83.4%	89.5%	86.7%	85.9%	0.007
Moderate–strenuous activity ≥7 hours/week	40.7	47.6	49.2	43.1	44.7	0.14
Weight status
BMI z-score: ≥85th percentile^b	34.5%	28.6%	25.2%	26.5%	20.7%	0.02
BMI z-score: ≥95th percentile^b	20.4	11.2	10.0	11.0	7.4	0.0007

Regression models adjusted for age, free/reduced lunch eligibility, and race (white vs. not white); school ID included as a random effect due to students nested within schools; bold text: p ≤ 0.05.

Objective height/weight data used when available.

Table 4.

Adjusted School Night Sleep Duration Proportions by Diet and Weight-Related Behaviors

	Hours of sleep (in 15-minute intervals)					p^a (df = 4)
	<6	6–6.75	7–7.5	7.75–8.25	8.5–10	p^a (df = 4)
Diet behaviors
Eat breakfast 5 days/week	27.2%	36.3%	50.5%	60.7%	54.2%	<0.0001
Eat breakfast with family 1–7 days/week	24.8	32.3	37.6	43.6	47.0	<0.0001
Eat supper with family 5–7 days/week	46.6	47.7	52.8	55.8	62.8	0.002
Stop eating when feel full	80.4	79.6	83.2	81.6	80.1	0.75
Trust body: how much to eat	63.5	65.8	67.4	67.9	64.3	0.79
Feel hungry at school	57.5	58.8	49.1	46.1	46.3	0.001
Consumption of specific foods
Fruit daily	35.6%	41.9%	42.1%	43.0%	42.7%	0.57
Salads weekly	57.3	73.6	72.8	69.1	70.0	0.003
Vegetables (other than potatoes) weekly	68.8	82.6	86.7	82.6	87.0	<0.0001
Fried potatoes weekly	67.7	66.8	70.1	65.7	67.0	0.65
Nonfried potatoes weekly	54.4	58.3	59.1	56.4	58.4	0.82
Pizza weekly	54.9	57.8	62.4	57.3	53.8	0.18
Eat fast food 1+ times/week	65.8	70.1	70.7	67.5	63.4	0.25
Beverage consumption (mean number of times/day
Water	3.4	3.4	3.6	3.6	3.6	0.45
100% Fruit juice	0.9	0.8	0.7	0.7	0.7	0.006
Sugar-sweetened beverages	1.9	1.3	1.1	0.9	1.0	<0.0001
Diet beverages	0.5	0.2	0.2	0.1	0.1	<0.0001
Sports/Energy drinks	0.7	0.4	0.4	0.3	0.3	<0.0001
Caffeinated beverages	1.2	0.6	0.5	0.4	0.3	<0.0001
Physical activity
Active 3–7 days/week	75.8%	81.1%	87.6%	83.8%	82.9%	0.02
Moderate–strenuous activity ≥7 hours/week	36.6	42.4	44.3	37.1	39.4	0.12
Weight status
BMI z-score: ≥85th percentile^b	36.7%	32.8%	28.0%	29.5%	23.4%	0.04
BMI z-score: ≥95th percentile^b	18.7	11.5	10.2	11.1	8.0	0.02

Regression models adjusted for age, sex, free/reduced lunch eligibility, and race (white vs. not white); school ID included as a random effect due to students nested within schools; bold text: p ≤ 0.05.

Objective height/weight data used when available.

Discussion

We found that adolescents who reported curtailed sleep reported several eating and diet behaviors that are considered less healthful. Most of these associations appeared to be graded with the probability of less healthful behaviors increasing as sleep hours diminished, culminating with those in the lowest sleep category (<6 hours of sleep per night) often having substantially poorer weight-related behaviors compared with adolescents who reported optimal sleep (8.5–10 hours of school night sleep). Sleep duration was related to obesity with roughly 19% of participants who reported <6 hours of sleep on school nights being obese compared with 8% of those who reported 8.5–10 hours of sleep per school night.

In the START study, similar to previous surveillance, short sleep duration was very common among adolescents. Only 15.5% of START study participants reported that they averaged at least 8.5 hours of sleep on school nights; furthermore, we documented sleep inequities, with girls, nonwhites, and lower SES participants more likely to report short sleep duration.

Although several authors have examined relationships between sleep and weight, to our knowledge, there have been no previously published population-based studies of adolescents that have examined the associations between sleep duration and the wide variety of weight-related behaviors that we report here. Several recent studies have reported on pieces of this. For instance, similar to what we found, a recent study reported that more sleep was associated with less sugar-sweetened beverage consumption among adolescents.⁴² In an older (young adults aged 20–30 years) population, Ogilvie et al. found, as we did with adolescents, associations between short sleep duration and an increased risk for breakfast skipping.⁴³ As we honed in on the particulars of diet, our analyses revealed that short sleepers reported eating fewer vegetables, which may relate to Weiss et al.'s report that short sleeping adolescents get slightly more (2%) calories from fat and fewer (3%) from carbohydrates compared with teens who net more sleep.⁴⁴ Research in adults has also shown that (similar to our findings) short sleepers are more likely to report a diet low in fruits and vegetables.⁴⁵

In the START study, the relationship between sleep duration and physical activity was not straightforward. The adolescents who slept the most and the least were less likely to report physical activity on at least 3 days per week; however, those in the middle category of sleep (7–7.5 hours per night) were the most likely to be active. There was a similar, although not statistically significant, pattern with the outcome of reporting at least 7 hours of moderate or vigorous physical activity per week. Previous research on sleep duration and physical activity among children has produced mixed findings, with several studies showing no association^46,47 and others suggesting that longer sleep is associated with greater moderate to vigorous physical activity.^48–50 Studies in adults have suggested that short sleepers, especially younger adults, may be less likely to exercise.^45,51 Further exploration is needed to better understand the relationship between sleep duration and physical activity, which could be bidirectional and a consequential avenue of research given how physical activity can promote multiple areas of health.

In both crude and adjusted models, risk of both overweight and obesity increased as reported hours of sleep decreased. However, whether changing sleep duration can change overweight/obesity risk deserves further inquiry. A recent cross-sectional study examining the influence of later school start times, an intervention which typically enhances adolescent sleep duration,⁵² on adolescent weight in nearly 30,000 Canadian adolescents found that later school start times were not associated with overweight or obese status (although they were associated with lower BMI z-scores⁵³). One possible explanation for this lack of association with overweight and obesity is that the less healthful weight behaviors seen in short sleepers may not be extreme enough to result in a meaningful net energy excess. In fact, an analysis of adults in NHANES revealed that short sleepers (≤6 hours), despite having less healthful eating behaviors, had a reported 24-hour energy intake that did not differ from that of average duration (7–8 hours) sleepers.⁵⁴

The analysis is limited by being cross-sectional, which means we cannot be sure that the sleep patterns we observed preceded the weight-related behaviors. Additionally, all of the behavior information we gathered was self-reported and solely reported by participants. Their behaviors may have been measured with errors, either due to adolescents not being able to accurately remember or report behaviors or due to participants reporting behavioral characteristics that they consider more socially desirable even though they are inaccurate. It is possible that there could be differential outcome measurement error as previous research has indicated that those who have difficulties sleeping report with greater random errors on surveys (although they have a lesser tendency to erroneously report for social desirability).⁵⁵ Furthermore, there is always a possibility that when both exposures and outcomes are reported by just a single individual, associations can be inflated because, for instance, individuals who tend to underestimate sleep hours might also tend to underestimate their frequency of eating vegetables.

The START sample was predominantly white, and it is unclear how transportable our findings may be to other racial/ethnic groups. There were potentially important school-level confounders that we did not have the ability to adjust for given that the START study included only five schools. For instance, exposure to an especially strong health education curriculum could conceivably have influenced both sleep duration and healthful eating, rendering the observed relationship between these two factors a mere artifact of this confounding variable. It is possible that the differences we observed are more due to chronotype (which START did not assess), rather than sleep duration, given that all participants' schools started between 7:30 and 7:45 am, constraining the range of wake-up times. Therefore, if one assumes that later chronotype adolescents are always unsuccessful at going to bed early, it would not be possible to disentangle the impact of simply having a later chronotype from that of accumulating fewer hours of sleep. Although we were able to calculate BMIs from objective height and weight measurements of 78% of the sample, there is a real possibility that the 22% of the sample where we relied on self-reported height and weight are miscategorized. When we examined objective and self-reported weights for those participants where we had both measures, participants tended to underreport their weights and participants who were objectively overweight or obese underreported to a greater degree. Even with adjustment for whether measures were objective or self-reported in the models, some bias may remain.

Despite these limitations, the study has many strengths, including the START study's high response proportion, especially for objective height and weight measurements, large sample size, and the fact that it is a population-based sample, all of which enhance the study's potential for generalizability.

Our study indicates that adolescents who are sleeping the least may be most prone to diet, eating, and activity patterns that are associated with excess weight gain over time. This is especially concerning when viewed through a health equity lens as our study and others have shown that there are important racial/ethnic, gender, and socioeconomic disparities in sleep duration where groups that typically face greater disadvantage get fewer hours of sleep.^56,57 The potential influence of adolescent sleep insufficiency on diet and physical activity could be quite impactful on chronic disease risk, especially if lack of sleep is setting the stage for enduring, lifelong, poor, weight-related behavior patterns and weight gain over time. Fortunately, adolescent sleep duration can be lengthened by delaying school start times, and these policies deserve prioritization.^52,58

Footnotes

Acknowledgments

The authors would like to thank the adolescents participating in the START study, the school districts that welcomed us to do research in their schools, our team of dedicated data collectors, and Mr. Bill Baker for his work to manage START data. Thank you to Dr. Kate Bauer for inspiring this work. This study is supported by funding from the National Institutes of Health's (NIH) Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) (R01 HD088176). We also gratefully acknowledge support from the Minnesota Population Center (P2C HD041023) which is funded through a grant from the Eunice Kennedy Shriver National Institute for Child Health and Human Development (NICHD).

Author Disclosure Statement

No competing financial interests exist.

References

Ogden

, Fryar

, Hales

, et al. Differences in obesity prevalence by demographics and urbanization in US children and adolescents, 2013–2016. JAMA, 2018; 319:2410–2418.

Hales

, Fryar

, Carroll

, et al. Trends in obesity and severe obesity prevalence in US youth and adults by sex and age, 2007–2008 to 2015–2016. JAMA, 2018; 319:1723–1725.

Healthy People. 2020. [Internet]. U.S. Department of Health and Human Services, Office of Disease Prevention and Health Promotion: Washington, DC. Available at www.healthypeople.gov/2020/topics-objectives/topic/nutrition-and-weight-status/objectives Last accessed July 22, 2015.

Office of the Surgeon General (US), Office of Disease Prevention and Health Promotion (US), Centers for Disease Control and Prevention (US), National Institutes of Health (US).. The Surgeon General's Call To Action To Prevent and Decrease Overweight and Obesity. Office of the Surgeon General (US): Rockville (MD). 2001. Available at www.ncbi.nlm.nih.gov/books/NBK44206 (Last accessed July 23, 2015.

Chen

, Beydoun

, Wang

. Is sleep duration associated with childhood obesity? A systematic review and meta-analysis. Obesity (Silver Spring), 2008; 16:265–274.

Garaulet

, Ortega

, Ruiz

, et al. Short sleep duration is associated with increased obesity markers in European adolescents: Effect of physical activity and dietary habits. The HELENA study. Int J Obes (Lond), 2011; 35:1308–1317.

Knutson

, Lauderdale

. Sleep duration and overweight in adolescents: Self-reported sleep hours versus time diaries. Pediatrics, 2007; 119:e1056–e1062.

Appelhans

, Fitzpatrick

, Li

, et al. The home environment and childhood obesity in low-income households: Indirect effects via sleep duration and screen time. BMC Public Health, 2014; 14:1160.

Nugent

, Althouse

, Yaqub

, et al. Modeling the relation between obesity and sleep parameters in children referred for dietary weight reduction intervention. South Med J, 2014; 107:473–480.

10.

Nielsen

, Danielsen

, Sørensen

TIA

. Short sleep duration as a possible cause of obesity: Critical analysis of the epidemiological evidence. Obes Rev, 2011; 12:78–92.

11.

Gupta

, Mueller

, Chan

, Meininger

. Is obesity associated with poor sleep quality in adolescents?. Am J Hum Biol, 2002; 14:762–768.

12.

Mitchell

, Rodriguez

, Schmitz

, Audrain-McGovern

. Sleep duration and adolescent obesity. Pediatrics, 2013; 131:e1428–e1434.

13.

Suglia

, Kara

, Robinson

. Sleep duration and obesity among adolescents transitioning to adulthood: Do results differ by sex?. J Pediatr, 2014; 165:750–754.

14.

Lytle

, Murray

, Laska

, et al. Examining the longitudinal relationship between change in sleep and obesity risk in adolescents. Health Educ Behav, 2013; 40:362–370.

15.

Calamaro

, Park

, Mason

TBA

, et al. Shortened sleep duration does not predict obesity in adolescents. J Sleep Res, 2010; 19:559–566.

16.

Guidolin

, Gradisar

. Is shortened sleep duration a risk factor for overweight and obesity during adolescence? A review of the empirical literature. Sleep Med, 2012; 13:779–786.

17.

Fatima

, Doi

, Mamun

. Longitudinal impact of sleep on overweight and obesity in children and adolescents: A systematic review and bias-adjusted meta-analysis. Obes Rev, 2015; 16:137–149.

18.

Ruan

, Xun

, Cai

, et al. Habitual sleep duration and risk of childhood obesity: Systematic review and dose-response meta-analysis of prospective cohort studies. Sci Rep, 2015; 16:160.

19.

Ogden

, Carroll

, Lawman

, et al. Trends in obesity prevalence among children and adolescents in the United States, 1988–1994 through 2013–2014. JAMA, 2016; 315:2292–2299.

20.

Keyes

, Maslowsky

, Hamilton

, Schulenberg

. The great sleep recession: Changes in sleep duration among US adolescents, 1991–2012. Pediatrics, 2015; 135:460–468.

21.

Eaton

, McKnight-Eily

, Lowry

, et al. Prevalence of insufficient, borderline, and optimal hours of sleep among high school students—United States, 2007. J Adolesc Health, 2010; 46:399–401.

22.

Perlus

, O'Brien

, Haynie

, Simons-Morton

. Adolescent sleep insufficiency one year after high school. J Adolesc, 2018; 68:165–170.

23.

Characteristics of Public Elementary and Secondary Schools in the United States: Results from the 2015–2016 National Teacher and Principal Survey. 2017. Available at https://nces.ed.gov/pubsearch/pubsinfo.asp?pubid=2017071 (Last accessed February 6, 2018.)

24.

Owens

, Au

, Carskadon

, et al. Insufficient sleep in adolescents and young adults: An update on causes and consequences. Pediatrics, 2014; 134:e921–e932.

25.

Beebe

, Simon

, Summer

, et al. Dietary intake following experimentally restricted sleep in adolescents. Sleep, 2013; 36:827–834.

26.

Hart

, Carskadon

, Considine

, et al. Changes in children's sleep duration on food intake, weight, and leptin. Pediatrics, 2013; 132:e1473–e1480.

27.

Klingenberg

, Chaput

J-P

, Holmbäck

, et al. Acute sleep restriction reduces insulin sensitivity in adolescent boys. Sleep, 2013; 36:1085–1090.

28.

Adamantidis

, de Lecea

. Sleep and metabolism: Shared circuits, new connections. Trends Endocrinol Metab, 2008; 19:362–370.

29.

Schmid

, Hallschmid

, Jauch-Chara

, et al. A single night of sleep deprivation increases ghrelin levels and feelings of hunger in normal-weight healthy men. J Sleep Res, 2008; 17:331–334.

30.

Simon

, Field

, Miller

, et al. Sweet/Dessert foods are more appealing to adolescents after sleep restriction. PLoS One, 2015; 10:e0115434.

31.

Van Dyk

, Krietsch

, Saelens

, et al. Inducing more sleep on school nights reduces sedentary behavior without affecting physical activity in short-sleeping adolescents. Sleep Med, 2018; 47:7–10.

32.

45 CFR 46: PROTECTION OF HUMAN SUBJECTS. Office for Human Research Protections, Department of Health and Human Services. Available at https://www.govinfo.gov/content/pkg/CFR-2016-title45-vol1/pdf/CFR-2016-title45-vol1-part46.pdf (Last accessed June 27, 2019.)

33.

Wahlstrom

, Dretzke

, Gordon

, et al. Examining the impact of later high school start times on the health and academic performance of high school students: A multi-site study. 2014. Available at http://conservancy.umn.edu/handle/11299/162769 Last accessed March 16, 2015.

34.

Sleep for Science. Available at www.sleepforscience.org/contentmgr/showdetails.php/id/93 Last accessed August 30, 2015.

35.

Hirshkowitz

, Whiton

, Albert

, et al. National Sleep Foundation's sleep time duration recommendations: Methodology and results summary. Sleep Health, 2015; 1:40–43.

36.

Short

, Weber

, Reynolds

, et al. Estimating adolescent sleep need using dose-response modeling. Sleep, 2018; 41. DOI: 10.1093/sleep/zsy011

37.

Neumark-Sztainer

, Wall

, Perry

, Story

. Correlates of fruit and vegetable intake among adolescents. Findings from Project EAT. Prev Med, 2003; 37:198–208.

38.

French

, Story

, Neumark-Sztainer

, et al. Fast food restaurant use among adolescents: Associations with nutrient intake, food choices and behavioral and psychosocial variables. Int J Obes, 2001; 25:1823–1833.

39.

Dietary History Questionare (DHQ). Available at https://epi.grants.cancer.gov/dhq2/forms/dhq2_pastyear.pdf (Last accessed June 27, 2019.)

40.

Godin

, Shephard

. A simple method to assess exercise behavior in the community. Can J Appl Sport Sci, 1985; 10:141–146.

41.

CDC Growth Charts. Centers for Disease Control and Prevention. Available at https://www.cdc.gov/growthcharts/cdc_charts.htm (Last accessed June 27, 2019.)

42.

Watts

, Miller

, Larson

, et al. Multicontextual correlates of adolescent sugar-sweetened beverage intake. Eat Behav, 2018; 30:42–48.

43.

Ogilvie

, Lutsey

, Widome

, et al. Sleep indices and eating behaviors in young adults: Findings from Project EAT. Public Health Nutr, 2018; 21:689–701.

44.

Weiss

, Xu

, Storfer-Isser

, et al. The association of sleep duration with adolescents' fat and carbohydrate consumption. Sleep, 2010; 33:1201–1209.

45.

Stamatakis

, Brownson

. Sleep duration and obesity-related risk factors in the rural Midwest. Prev Med, 2008; 46:439–444.

46.

Nixon

, Thompson

JMD

, Han

, et al. Short sleep duration in middle childhood: risk factors and consequences. Sleep, 2008; 31:71–78.

47.

Ekstedt

, Nyberg

, Ingre

, et al. Sleep, physical activity and BMI in six to ten-year-old children measured by accelerometry: A cross-sectional study. Int J Behav Nutr Phys Act, 2013; 10:82.

48.

Harrington

. Relationships of objectively measured physical activity and sleep with BMI and academic outcomes in 8-year-old children. Appl Nurs Res, 2013; 26:63–70.

49.

Chaput

J-P

, Katzmarzyk

, LeBlanc

, et al. Associations between sleep patterns and lifestyle behaviors in children: An international comparison. Int J Obes Suppl, 2015; 5:S59–S65.

50.

Felső

, Lohner

, Hollódy

, et al. Relationship between sleep duration and childhood obesity: Systematic review including the potential underlying mechanisms. Nutr Metab Cardiovasc Dis, 2017; 27:751–761.

51.

McClain

, Lewin

, Laposky

, et al. Associations between physical activity, sedentary time, sleep duration and daytime sleepiness in US adults. Prev Med, 2014; 66:68–73.

52.

Boergers

, Gable

, Owens

. Later school start time is associated with improved sleep and daytime functioning in adolescents. J Dev Behav Pediatr, 2014; 35:11–17.

53.

Gariépy

, Janssen

, Sentenac

, Elgar

. School start time and the healthy weight of adolescents. J Adolesc Health, 2018; 63:69–73.

54.

Kant

, Graubard

. Association of self-reported sleep duration with eating behaviors of American adults: NHANES 2005–2010. Am J Clin Nutr, 2014; 100:938–947.

55.

Barber

, Barnes

, Carlson

. Random and Systematic Error Effects of Insomnia on Survey Behavior. Organ Res Methods, 2013; 16:616–649.

56.

Jackson

, Redline

, Kawachi

, et al. Racial disparities in short sleep duration by occupation and industry. Am J Epidemiol, 2013; 178:1442–1451.

57.

Jackson

, Redline

, Emmons

. Sleep as a potential fundamental contributor to disparities in cardiovascular health. Annu Rev Public Health, 2015; 36:417–440.

58.

Dunster

, de la Iglesia

, Ben-Hamo

, et al. Sleepmore in Seattle: Later school start times are associated with more sleep and better performance in high school students. Sci Adv, 2018; 4:eaau6200.