Abstract
Background:
Although numerous studies have reported that obesity in adolescents is related to shorter sleep duration, few studies have reported the effect of sleep timing, particularly early wake-up time, on obesity.
Objectives:
To investigate the association between wake-up time and adolescent obesity.
Methods:
Using the Korean National Health and Nutrition Examination Survey VII data, 1301 middle school and high school students were selected and grouped according to BMI. Sleep timing and lifestyle factors were evaluated using self-reported questionnaires.
Results:
The mean bedtime and wake-up time were 00:09 am and 07:06 am, respectively. Despite similar bedtimes, the group with overweight/obesity woke up earlier than the group with underweight/normal weight. The BMI z-score and the overweight/obesity relative risk decreased as the wake-up time was delayed, even after adjustment for covariates. Participants who woke up before 06:50 am had a 1.82-fold higher risk of having overweight/obesity than those who woke up after 07:30 am. Participants who woke up late tended to sleep longer than those who woke up early.
Conclusions:
Waking up early is significantly associated with an increased BMI z-score in adolescents and may be a risk factor for overweight/obesity.
Keywords: adolescents, bedtime, obesity, shorter sleep duration, wake-up time
Introduction
Childhood obesity is a major health care concern worldwide, and many efforts are being made to decrease its prevalence by elucidating its causes. One of the most notable risk factors for obesity is short sleep duration.1 The decline in average sleep duration over time is proportional to the increase in obesity prevalence.2 Numerous studies in children have reported the association between short sleep duration and obesity.3–8 Studies in children have also demonstrated that short sleep duration is linked with unhealthy dietary habits,9–11 decreased energy expenditure, and increased leptin levels,9 which result in weight gain. Moreover, adequate sleep has been shown to reduce the risk of obesity in adolescents, even in those who consume excess calories.12
Consequently, these findings suggest the need for steps to increase sleep duration. Because sleep duration is determined by bedtime and wake-up time, analyzing the different aspects of sleep dimensions may help provide new opportunities for sleep-focused intervention strategies. Recent studies on the association of obesity with sleep chronotype demonstrated that a late bedtime was a significant risk factor for obesity in adolescents. A delayed sleep phase in children and adolescents increases the risk of having a higher BMI and obesity,13–15 which is associated with unhealthy eating habits, such as decreased consumption of fruits and vegetables,13,16 increased consumptions of sweetened beverages16 and junk food,17,18 and skipping of breakfast.17 In addition, a delayed sleep phase is associated with increased screen time per day15 and shorter moderate-to-vigorous physical activity duration.15,16
Adolescents have characteristic sleep habits, including a shorter sleep duration and later bedtimes, for biological reasons.19 Since late bedtime is a typical physiological characteristic of adolescents, their wake-up time will particularly affect sleep duration and could eventually be an important factor in adolescent health. In particular, adolescents are forced to wake up early owing to set school start times, even though they would naturally wake up later owing to their biology. Therefore, an in-depth study on the effect of wake-up time on obesity in adolescents is important. However, few studies exist on the association between wake-up time per se and obesity in adolescents. Most studies on the association between wake-up time and obesity have involved comparisons of the effects of different chronotypes, that is, between late bedtime/late wake-up time and early bedtime/early wake-up time.13–16 Few studies have investigated the independent effect of wake-up time on obesity.20
This study aimed to examine whether sleep dimensions, that is, sleep duration, bedtime, and particularly wake-up time, were associated with the body weight status in healthy adolescents. In addition, this study also investigated whether bedtime and/or wake-up time were independently associated with overweight/obesity and the BMI z-score, after adjusting for covariates (including sleep duration), using data from Korean National Health and Nutrition Examination Survey (KNHANES) VII, a nationally representative sample of middle school and high school students in South Korea. Consequently, we also investigated the association between wake-up time and weight-related factors.
Subjects and Methods
Data Sources and Study Population
Data from KNHANES VII, conducted between 2016 and 2018, were analyzed. The KNHANES has been conducted periodically since 1998 by the Korea Centers for Disease Control and Prevention. It is a large, cross-sectional, and nationally representative survey of the health and nutritional status of the South Korean population. Informed consent was obtained from all participants who participated in the survey; data from adolescents who were middle school or high school students were included (N = 1335). The institutional review board of the Yonsei University College of Medicine approved the study protocol (Approval No.: 4-2021-0531).
Of the 1335 participants selected from KNHANES VII, those who had metabolic and endocrine diseases diagnosed by a doctor (N = 1) and those without records of anthropometric data (N = 3) were excluded. Participants who had a calculated sleep duration of >14 hours (N = 1) or <4 hours (N = 9), those who went to bed before 8 pm (N = 2) or after 4 am (N = 5), and those who woke up after 10 am (N = 13) were considered outliers, and were thus, excluded. The final number of study participants was 1301 (Fig. 1).
Figure 1.
Design and flowchart of study population. †The participants who were either elementary school students or high school graduates (N = 347) were excluded owing to the difference in education level despite being in the same age group. *The participants with calculated sleep durations <4 hours (N = 9) or >14 hours (N = 1); bedtime before 8 pm (N = 2) or after 4 am (N = 5); and the wake-up time before 3 am (N = 0) or after 10 am (N = 13) were treated as outliers (total N = 30).
Anthropometry
KNHANES VII collected the participants' anthropometric measurements, such as age, sex, height, weight, and BMI. A portable stadiometer was used to measure height to the nearest 0.1 cm, whereas a digital scale was used to measure weight to the nearest 0.1 kg with the participants wearing light clothing and no shoes. Using a standard measuring tape, waist circumference was measured at the minimum circumference of the body, between the lowest rib and the iliac crest. BMI was calculated as weight (in kilograms) divided by the height (in meters) squared. Standard scores (z-scores) for BMI were obtained for the same ages and sex from the 2017 Korean Children and Adolescents Growth Chart. A BMI ≤5th percentile, 85th–95th percentiles, and ≥95th percentile were defined as underweight, overweight, and obesity, respectively, for the same age and sex. The four categories of weight status were combined to create a dichotomous variable (underweight/normal-weight) and (overweight/obesity).
Covariates
Adolescents were asked to report their sleep habits on weekdays when they were at home. The questionnaires used to assess sleep were developed for individuals aged 12 years and older by the Korea Centers for Disease Control and Prevention (Supplementary Table S1). The variables of interest were as follows: (1) sleep duration, (2) bedtime, and (3) wake-up time. Bedtime was defined as the time of falling asleep at the end of the day, and wake-up time was defined as the time of waking up from this sleep (i.e., daytime naps were not included). The values for bedtime and wake-up time were converted into minutes to calculate sleep duration in minutes and to analyze their effect on obesity as continuous variables.
The bedtime and wake-up time were calculated from midnight, for example, a person who slept at 11 pm and woke up at 8 am, the bedtime would be calculated as 23 × 60 = 1380 minutes and the wake up time would be stated as 8 × 60 = 480 minutes. However, if the bedtime was after midnight, it was calculated by adding 24 hours, that is, a person who slept at 1 am would be stated as having bedtime of (24 + 1) × 60 = 1500 minutes. The sleep duration was divided into <6, 6–7, 7–8, 8–9, and >9 hours. The wake-up time was divided into quartiles.
Covariate data collected from the lifestyle questionnaire included sex, physical activity, sedentary time, food intake amount, household income, and parents' education level. Physical activity data were measured as the number of days per week that the participant exercised at an intensity resulting in heavy breathing for >60 minutes during or beyond school hours. The participants also reported sedentary time as the time (hours and minutes) spent sitting each day in the past week. This duration was also divided into quartiles. Food intake was assessed by categorizing foods into grains, bean products, potatoes, meat, fish, seaweed, fruit, vegetables, milk products, and beverages.
Participants were required to recall the amount of each type of food eaten in the past 2 days and answer questions about whether the amount of food was more, similar, or less than their usual intake. Nutritionists assessed the food intake and converted this information into weight in grams and calories consumed. The cumulative income of the family was reported; the income level was partially adjusted for the number of family members and divided into quintiles according to the average monthly household income. The participants reported the education level of each parent, which was divided into four categories: elementary school, middle school, high school, and university or higher education.
Statistical Analyses
Statistical analyses were performed using SPSS (Version 26.0; IBM Corp., Armonk, NY, USA) and SAS version 9.4 (SAS, Inc., Cary, NC, USA). All the tests were two-tailed, with a significance level set at 0.05. SPSS and SAS survey procedures were used to describe the complex sampling design in the KNHANES. Sample weights were assigned to participants to represent the adolescent population of South Korea from 2016 to 2018 for all the analyses. The sample weights were generated by accounting for the complex sample design, which consisted of nonresponse rates of the target population, multistage stratification, and posterior stratification. The normality of data distribution of the variables was examined using univariate and histogram methods. We used frequency tests to assess the relationships between the variables. Sensitivity analyses comparing sex proportion, age, and BMI were conducted (Supplementary Table S2).
The mean values of sleep dimensions and other variables were compared between groups with underweight/normal-weight and those with overweight/obesity using a Complex Samples General Linear Model (CSGLM) for continuous variables and the Rao–Scott chi-square test for categorical variables. The potential association between each continuous sleep variable and the BMI z-score was investigated using a CSGLM. In addition, the potential relative risk for overweight/obesity conferred by each sleep variable was assessed using a Complex Samples Poisson Regression Analysis. The mean BMI z-score and the relative risk for overweight/obesity according to the wake-up time quartiles were investigated using a CSGLM and a Complex Samples Poisson Regression Analysis, respectively.
Trends were tested to assess the decremental mean BMI z-score over the wake-up time quartiles. Finally, factors associated with wake-up time and quartiles were evaluated. The relative risk for the group with overweight/obesity was calculated using the fourth quartile as the reference wake-up time. Various models were developed for the CSGLM and Complex Samples Poisson Regression Analysis. Model 1 was developed without adjusting for the covariates; conversely, Model 2 was developed after adjusting for age, sex, physical activity, sedentary time, household income, parents' education level, and total food intake (kJ). Model 3 was also developed after adjusting for the same covariates as those for Model 2, with the addition of sleep duration. All data are reported as mean ± standard error (SE) or N (%).
Results
Comparison of the Baseline Participant Characteristics Between the Group With Underweight/Normal-Weight and the Group With Overweight/Obesity
A total of 1301 participants (mean age 15.3 ± 0.06 years; males 52.4%) were included in the study (Fig. 1). Their characteristics are shown in Table 1. Except for the waist circumference, BMI z-score, and wake-up time, none of the characteristics differed significantly between the group with underweight/normal-weight and the group with overweight/obesity. The participants in the group with overweight/obesity woke up earlier (06:59 am, SE: 2.6) than did those in the group with underweight/normal-weight (07:06 am, SE: 1.5).
Table 1.
Characteristics of Study Participants Stratified by Weight Status
| Total analysis group (N = 1301) | Underweight/normal weight (N = 105/905)a | Overweight/obese (N = 124/167)a | p | |
|---|---|---|---|---|
| Age, mean (SE) | 15.3 (0.06) | 15.3 (0.07) | 15.4 (0.1) | 0.557 |
| Boys, N (weighted %) | 676 (52.4) | 514 (52.2) | 162 (53.8) | 0.950 |
| Waist circumference | 71.8 (0.3) | 68.1 (0.26) | 85.6 (0.64) | <0.001 |
| BMI z-score | 0.12 (0.05) | −0.45 (0.03) | 2.23 (0.07) | <0.001 |
| Sleep duration (hours), mean (SE) | 6.8 (0.04) | 6.9 (0.05) | 6.8 (0.10) | 0.421 |
| Sleep duration, n (weighted %) | 0.493 | |||
| <6 Hours | 246 (14.8) | 184 (19.7) | 62 (23.8) | |
| 6–7 Hours | 308 (25.1) | 246 (27.3) | 62 (25.2) | |
| 7–8 Hours | 392 (31.4) | 311 (30.6) | 81 (26.1) | |
| 8–9 Hours | 270 (19.8) | 205 (17.0) | 65 (19.2) | |
| >9 Hours | 85 (8.9) | 64 (5.4) | 21 (5.7) | |
| Bedtime (hour:minute), mean (SE) | 00:14 (2.6) | 00:14 (2.8) | 00:12 (5.7) | 0.747 |
| Wake-up time (hour:minute), mean (SE) | 07:04 (1.4) | 07:06 (1.5) | 06:59 (2.6) | 0.013 |
| Total physical activity (days/week), N (weighted %) | 0.573 | |||
| Not at all | 827 (62.4) | 638 (61.5) | 189 (65.9) | |
| 1 Days | 145 (12.0) | 110 (11.3) | 35 (14.6) | |
| 2 Days | 108 (9.0) | 92 (10.0) | 16 (5.3) | |
| 3 Days | 87 (6.5) | 64 (6.5) | 23 (6.4) | |
| 4 Days | 37 (2.1) | 31 (2.4) | 6 (1.0) | |
| >5 Days | 97 (7.9) | 75 (8.2) | 22 (6.7) | |
| Sedentary time, N (weighted %) | 0.467 | |||
| Q1 | 288 (21.2) | 226 (21.4) | 62 (20.5) | |
| Q2 | 389 (29.6) | 309 (30.7) | 80 (25.8) | |
| Q3 | 348 (27.1) | 266 (26.1) | 82 (30.7) | |
| Q4 | 274 (22.1) | 207 (21.8) | 67 (23.0) | |
| Household income, N (weighted %) | 0.069 | |||
| Q1 | 113 (9.5) | 82 (8.9) | 31 (11.9) | |
| Q2 | 211 (16.5) | 158 (16.2) | 53 (17.8) | |
| Q3 | 301 (22.3) | 240 (22.4) | 61 (21.7) | |
| Q4 | 350 (27.6) | 267 (26.5) | 83 (31.8) | |
| Q5 | 324 (24.1) | 262 (26.0) | 62 (16.8) | |
| Father's education level, n (weighted %) | 0.227 | |||
| Not response | 466 (38.4) | 358 (38.2) | 110 (39.2) | |
| Middle school or below | 58 (4.5) | 38 (4.0) | 20 (6.6) | |
| High school | 282 (20.8) | 214 (20.3) | 68 (22.6) | |
| University or more | 495 (36.2) | 402 (37.5) | 93 (31.5) | |
| Mother's education level, n (weighted %) | 0.057 | |||
| Not response | 172 (14.5) | 126 (13.6) | 46 (18.2) | |
| Middle school or below | 50 (3.7) | 38 (4.0) | 12 (2.5) | |
| High school | 490 (37.9) | 368 (36.6) | 122 (43.0) | |
| University or more | 589 (43.8) | 478 (45.9) | 111 (36.3) | |
| Total intake (kcal), mean (SE) | 2139.4 (32.8) | 2149.1 (36.5) | 2103.1 (62.2) | 0.312 |
| Carbohydrate intake (g), mean (SE) | 311.4 (5.0) | 314.1 (5.6) | 301.6 (9.3) | 0.220 |
| Fat intake (g), mean (SE) | 61.6 (1.3) | 61.5 (1.4) | 62.0 (2.9) | 0.374 |
| Protein intake (g), mean (SE) | 78.5 (1.5) | 78.6 (1.7) | 78.1 (2.9) | 0.444 |
| Water intake (g), mean (SE) | 811.5 (18.8) | 820.2 (21.2) | 779.0 (31.0) | 0.286 |
| Fiber intake (g), mean (SE) | 19.3 (0.4) | 19.2 (0.5) | 19.5 (0.9) | 0.068 |
| The frequency of breakfast in a week n (weighted %) (total N = 1067) | 0.219 | |||
| 1 Day | 627 (57.0) | 495 (56.7) | 132 (58.0) | |
| 2 Day | 161 (14.2) | 117 (13.3) | 44 (17.7) | |
| 3 Day | 134 (14.3) | 107 (15.1) | 27 (11.1) | |
| 4 Day | 145 (14.5) | 112 (14.9) | 33 (13.3) | |
All data were weighted values considering the complex sample design.
Categorization according to BMI z-score. Data are presented as mean (SE), or n (weighted %). Statistically significant results are expressed in bold font.
Q, quartile; SE, standard error.
Association Between Sleep Variables and Body Weight
Results of the linear regression model and Poisson regression analysis are shown in Supplementary Table S3 and Table 2. Sleep duration was grouped by hours (<6, 6–7, 7–8, 8–9, and >9 hours), and the mean BMI z-scores were compared among these groups. The mean BMI z-scores tended to be lower as sleep duration increased, but this was not statistically significant. Even after categorizing sleep duration into three groups, namely inadequate (<8 hours), adequate (8–9 hours), and excessive (>9 hours), the BMI z-score did not differ significantly among these groups as well. In addition, the relative risks of overweight/obesity were not significant among these categorizing sleep duration groups (Supplementary Table S3).
Table 2.
Linear Regression Analyses to Assess the Potential Association Between Sleep Duration (Hours), Bedtime, Wake-Up Time, and BMI z-Score and Poisson Regression Analysis to Assess the Potential Relative Risk Between Sleep Duration, Bedtime, Wake-Up Time, and Overweight/Obesity in Adolescents
| Β | p a | RR | 95% CI | |
|---|---|---|---|---|
| Sleep duration | ||||
| Model 1 | −0.02 | 0.230 | 0.97 | 0.908–1.041 |
| Model 2 | −0.04 | 0.082 | 0.96 | 0.882–1.048 |
| Model 3 | — | — | — | — |
| Bedtime | ||||
| Model 1 | 0.00 | 0.861 | 0.99 | 0.916–1.065 |
| Model 2 | 0.02 | 0.525 | 0.98 | 0.895–1.078 |
| Model 3 | — | — | — | — |
| Wake-up time | ||||
| Model 1 | −0.09 | 0.013 | 0.85 | 0.741–0.965 |
| Model 2 | −0.09 | 0.015 | 0.84 | 0.727–0.965 |
| Model 3 | −0.07 | 0.083 | 0.84 | 0.719–0.983 |
All data were weighted values considering the complex sample design. 1 U: 30 minutes.
Model 1: unadjusted.
Model 2: adjusted for age, sex, physical activity, sedentary time, household income, parents' education level, and total food intake (kJ).
Model 3: adjusted for age, sex, physical activity, sedentary time, household income, parents' education level, total food intake (kJ), and sleep duration.
Statistically significant results are expressed in bold font.
p for linear regression analyses of the potential association between sleep duration (hours), bedtime, wake-up time, and BMI z-score.
CI, confidence interval; RR, relative risk.
The sequential regression models for each sleep variable showed that only the mean wake-up time had a significant negative correlation with the BMI z-score even after adjusting for different variables (Models 1 and 2). In addition, a 30-minute delay in the wake-up time was found to decrease the relative risk of having overweight/obesity in all the tested models, whereas there was no association between either >30 minutes of sleep duration or an earlier bedtime by >30 minutes and the risk of having overweight/obesity (Table 2). Each 30-minute delay in the wake-up time reduced the risk of having overweight/obesity by a factor of 0.84, regardless of the covariates that included the sleep duration.
Association of Body Weight With the Wake-Up Time Quartiles in Adolescents
Wake-up time was divided into quartiles to examine its association with body weight in a more detailed manner. The mean BMI z-score decreased as wake-up time progressed to the fourth quartile (p for trend <0.001). In addition, participants waking up before 06:50 am had a 1.82-fold higher relative risk of having overweight/obesity than did those waking up after 07:30 am, regardless of the covariates. Although the confidence intervals included null values, the relative risks of having overweight/obesity in the first to the third quartile of wake-up time were higher than those in the fourth quartile (Fig. 2).
Figure 2.
Mean BMI z-score and relative risk for overweight/obesity divided into wake-up time quartiles. The RR was calculated against Q4. †, unadjusted RR; ‡, adjusted RR; CI, confidence interval; RR, relative risk.
Factors Associated With Body Weight According to Different Wake-Up Times
The associations of various covariates related to body weight according to different wake-up times were analyzed (Table 3). As wake-up time progressed from the first to the fourth quartile, the sleep duration lengthened, and the proportion of participants with either high household incomes or high fathers' education levels also increased. There was no association of physical activity and total dietary intake with the wake-up time.
Table 3.
Factors Associated With Body Weight According to Different Wake-Up Times
|
Wake-up time
|
|
|
||||
|---|---|---|---|---|---|---|
| Q1 | Q2 | Q3 | Q4 | p-trend | Q1 vs. Q4 | |
| Sleep duration (minutes) | 375.3 (4.3) | 405.8 (4.6) | 435.2 (5.2) | 444.7 (5.6) | <0.001 | <0.001 |
| Total intake (kJ) | 2189.8 (70.3) | 2081.8 (53.8) | 2208.6 (50.8) | 2060.6 (75.4) | 0.408 | 0.606 |
| Carbohydrate intake (g) | 313.0 (10.0) | 305.5 (8.5) | 322.2 (8.2) | 304.3 (10.2) | 0.829 | 0.546 |
| Protein intake (g) | 64.4 (2.9) | 59.2 (2.2) | 63.4 (2.0) | 58.8 (3.3) | 0.338 | 0.599 |
| Fat intake (g) | 82.4 (3.0) | 75.8 (2.5) | 81.2 (2.6) | 73.0 (3.3) | 0.100 | 0.942 |
| Fiber intake (g) | 828.8 (32.9) | 792.2 (27.0) | 841.2 (2.6) | 774.9 (40.4) | 0.473 | 0.989 |
| Water intake (g) | 19.5 (0.9) | 18.8 (0.7) | 20.0 (0.8) | 18.7 (0.9) | 0.722 | 0.976 |
| Sedentary time (minute) | 694.9 (12.1) | 679.5 (9.7) | 665.8 (9.8) | 672.5 (14.9) | 0.179 | 0.314 |
| Physical activity | 0.690 | 0.165 | ||||
| Household income | 0.007 | 0.017 | ||||
| Father's education level | 0.009 | 0.056 | ||||
| Mother's education level | 0.415 | 0.367 | ||||
| Breakfast frequency | 0.583 | 0.121 | ||||
All data were weighted values considering the complex sample design. Data are presented as mean (SE) or weighted %. Statistically significant results are expressed in bold font.
Discussion
This study investigated whether sleep timings, particularly wake-up time, are associated with body weight in adolescents. To the best of our knowledge, this study is one of the very few studies to have focused on the association of wake-up time with body weight, particularly in adolescents. It is unclear whether an early wake-up time affects obesity, since the association between wake-up time and obesity has not been sufficiently investigated. We found that wake-up time was associated with body weight. The BMI z-score decreased with delayed wake-up times after adjusting for the covariates, and the relative risk of having overweight/obesity was decreased with a 30-minute delay in the wake-up time independent of the sleep duration.
Particularly, participants who woke up before 06:50 am had a 1.82-fold higher relative risk of having overweight/obesity than did the group that woke up after 07:30 am. Compared with the group that woke up early, the group that woke up late had a longer sleep duration and a higher proportion of households with high income and fathers with higher education levels. The results of our study suggest that an early wake-up time could be associated with a higher risk of obesity.
Short sleep duration has previously been associated with obesity.3–7 A recent meta-analysis revealed that a short sleep duration in children and adolescents results in a 1.5- to 2-fold increase in the risk of having overweight/obesity.3,21–25 Shorter sleep durations decrease the metabolic rate during sleep26 and cause endocrine changes, such as increased insulin resistance,27 increased ghrelin levels, and decreased leptin levels, which promote increased food consumption.9,26,28–30 In this study, although a positive association was observed between sleep duration and the BMI z-score, it was not statistically significant.
Furthermore, when the sleep duration was categorized into three groups (insufficient, adequate, and excessive), a tendency was observed for longer sleep duration to decrease the BMI z-score and lower the risk of overweight/obesity; however, this association was not statistically significant. This finding may be attributed to several reasons. First, various factors other than sleep duration can contribute to obesity. Second, 75% of all participants had been exposed to the risk of overweight/obesity due to an insufficient sleep duration (<8 hours), potentially weakening the link between sleep duration and obesity.
Although research on the topic is limited, later bedtime is presumed to be associated with obesity.14,19,31–33 Compared with early bedtime/early wake-up time, later bedtime/later wake-up time was associated with a higher BMI31 and a 1.5 times higher risk of obesity15 in adolescents. Later bedtime was positively correlated with the BMI z-score,14 and the BMI increased by 2.1 kg/m2 for every additional hour of delayed bedtime, regardless of sleep duration.33 However, we found no significant association between bedtime and body weight in this study; consistent with our results, several previous studies also found no evidence of an association between the two.8,20,34 The authors of these studies suggested that the discrepant findings regarding the relationship between bedtime and body weight were attributed to limitations in the research methodology, such as a lack of an effective way to measure sleep timing,8 inadequate sample size,34 and heterogeneous composition of the study population.20
However, we consider that these inconsistent and statistically insignificant results could be attributed to the physiological changes in the sleep patterns in adolescents. Sleep patterns undergo reconstruction during adolescence: the sleep phase (bedtime and wake-up time) is delayed,35,36 sleep duration is shortened, and sleep patterns differ significantly between weekdays and weekends.37,38 In particular, adolescents exhibit “late chronotype” sleep behavior owing to psychosocial factors, and most importantly, biological mechanisms. For instance, pubertal stages and sex affect the sleep phase,38,39 and the delay in the sleep phase has been correlated with sexual maturity.36 Since late sleep time is caused by biological factors, a late wake-up time could compensate for the adverse effects of late sleep on obesity in adolescents.
Therefore, when considering the naturally delayed sleep patterns of adolescents, wake-up time may be a more important variable in terms of obesity. Waking up late is more natural for adolescents since it compensates for a delayed sleep time. Therefore, an in-depth analysis of the association between wake-up time and obesity, particularly in adolescents, is essential. In this study, despite the small difference in the mean wake-up time, waking up later lowered the risk of obesity in adolescents. Participants waking up before 06:50 am were 1.8 times more likely to have overweight/obesity as compared with those waking up after 07:30 am, even after adjusting for the confounding factors, such as sleep duration.
In fact, rather than concluding that small differences in wake-up time affect obesity, this finding suggests that even small differences in wake-up time could be a risk factor for obesity if they persist for several months. Therefore, further large-scale longitudinal studies are warranted to confirm our results and elucidate the mechanism. In addition, based on the findings of this study that a longer sleep duration is associated with a later wake-up time, it can be inferred that waking up later would naturally result in a longer sleep duration and potentially reduce the risk of obesity.
It is still too early to conclude that later wake-up time prevents obesity, since a discrepancy exists in the findings of studies on wake-up time and obesity.20 A recent study showed no statistically significant associations between wake-up time and the BMI z-score.20 However, the authors stated that since BMI z-scores are converted to relatively large BMI points, the obtained effects estimates could be considered clinically relevant even if they are not statistically significant.
The main strength of this study was its sample size and generalized nature, which made its findings generalizable for the entire South Korean adolescent population. Therefore, the findings of this study can be used to develop potential social/individual interventional targets for promoting weight management among adolescents. The major limitation of the study was that sleep timing was not objectively measured, but was measured using a questionnaire in which the participant self-reported their sleep timing. However, a previous study reported moderate correlations among actigraphy measurements, sleep diaries, and self-reported questionnaires in adolescents, which implies that adolescents can accurately recall their typical sleep patterns.40
In addition, owing to their relatively high costs, polysomnography and actigraphy were not performed in our study, similar to in other larger population-based studies.41 Similarly, the dietary and physical activity data were also collected through self-reported questionnaires, and the amounts of caloric intake and physical activity may have been under- or overestimated. Although these limitations can be statistically overcome by the inherent strengths of a large-scale research, further studies that are well controlled and objectively measure sleep and nutritional status are needed to evaluate the relationship between obesity and wake-up time in adolescents.
Another limitation of this study is that only weekday sleep timing was analyzed, and weekend wake-up time was not considered. Adolescents sleep and wake up later on weekends than on weekdays, and determining whether sleep time on weekends is associated with obesity would reinforce the findings of this study. Therefore, further studies focused on the relation between sleep timing on weekends and obesity in adolescents are warranted. The cross-sectional nature of the study is also a limitation. Therefore, to establish the causality between the early wake-up time and obesity, longitudinal studies are also necessary.
In conclusion, sleep may play an important role in preventing adolescent obesity, independent of other risk factors. Previous studies have focused only on the relationship between sleep duration and obesity, whereas this study revealed a significant relationship between earlier wake-up time and overweight/obesity in South Korean adolescents. Although further longitudinal studies are necessary to establish causality, these findings suggest that early wake-up time could be a risk factor for obesity in addition to sleep duration, and its regulation may be equally important in preventing obesity.
In addition, efforts should be made to improve the psychosocial factors and enhance education toward a change in the sociocultural perception of adolescent sleep. For example, it is necessary to adjust the school start time for adolescents to ensure adequate sleep. Moreover, sleep recommendations to date have been limited in recommending an appropriate sleep duration. Our results indicate the necessity for establishing appropriate bedtimes and wake-up times.
Supplementary Material
Acknowledgments
The authors express their gratitude for having access to these data, without which the study would not have been possible. The content is solely the responsibility of the authors.
The study analyzed the data collected from surveys conducted between 2016 and 2018 by the Korean National Health and Nutrition Examination Survey (https://knhanes.kdca.go.kr).
Authors' Contributions
A.K. made substantial contributions to the conception and design of the study, interpretation of data, and drafting of the article. H.I.L. and K.S. contributed to the conception and execution of the study. J.S. and H.W.C. made contributions to the conception and design of the study. S.K., M.L., and Y.C. contributed to the preparation of data and figures. H.Y.K. and M.L. contributed to the analysis and interpretation of data. H.-S.K. contributed to the critical revision of important intellectual content.
Funding Information
No funding was received for this article.
Author Disclosure Statement
No competing financial interests exist.
Supplementary Material
References
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