Associations of Bedtime Schedules in Childhood with Obesity Risk in Adolescence

Abstract

We investigated whether bedtime schedules and bedtimes in childhood were associated with obesity risk and adiposity in adolescence. We analysed the data of 12,645 singleton children classified as not obese at 7 years from the Millennium Cohort Study in the United Kingdom. Bedtimes and the regularity of bedtimes of 7-year-olds were reported by parents. Bio-electric impedance body fat percentage (BFP) measurements and obesity at 11 and 14 years were the considered outcomes. The International Obesity Task Force age- and sex-specific thresholds were used to define obesity. Obesity risk at 11 and 14 years was higher among children with never-regular bedtimes at 7 years compared with those with always-regular bedtimes (risk ratio, RR, 2.8 (95% CI, 1.8–1.4) and 2.3 (95% CI, 1.5–3.6), respectively). An increasing irregularity in childhood bedtime was associated with an increasing risk of obesity at both 11 and 14 years in a dose–response manner (p trend < 0.001; and p trend = 0.002, respectively). BFP at 11 years increased by 1.1% (95% CI, 0.8–1.5) for boys and 1.0% (95% CI, 0.6–1.4) for girls for every hour delay in childhood bedtime. Irregular bedtime schedules and later bedtimes in childhood were associated with an increased risk of obesity in early- and mid-adolescence in a dose–response manner. There was marginal, but significant, increases in BFP during adolescence for children with later bedtimes.

1. Introduction

Obesity remains a major paediatric and public health concern worldwide. Over the last 40 years, the prevalence of paediatric obesity has increased by approximately 10-fold with about 41 million 4- to 16-year-olds classified as overweight or obese, globally [1,2]. In England, the current prevalence of obesity among 10- to 11-year-olds is 25.5%, representing an 8% rise from 2006/2007 levels and a 4.5% rise from 2019/2020 levels [3]. The UK Royal College of Paediatrics and Child Health reports that the rise in obesity prevalence remains noticeable among adolescents [4]. The economic and public health consequences of obesity are immense; obesity-related chronic diseases can impose physical limitations on daily activities as much as psychological effects can persist or even become aggravated later in life [5,6,7]. While ongoing physiological and psychological development during childhood can make it a vulnerable phase for adverse consequences of obesity, it may also provide a critical window for the implementation of healthy interventions that could have lasting benefits.

The conceptual framework for the aetiology of obesity in childhood has been explored using multiple approaches [8,9]. Irrespective of the approach, the framework accepts the role of sleep duration during childhood, within the family structure, as a modifiable risk factor for obesity [8,9]. This is consistent with two recent meta-analyses that show an approximately two-fold increased risk of obesity among children who are short sleepers relative to long sleepers [10,11]. Further, a recent review suggests that from a developmental perspective, the relationship between sleep among prepubescent school-aged children and obesity risk in adolescence appears stronger than that sleep among adolescents and obesity risk in adolescence [12]. Optimal sleep duration and quality is important for biochemical functions such as hormonal regulation and carbohydrate metabolism [13,14]. Specifically, a short and restricted sleep duration is associated with impaired glucose tolerance and insulin response to glucose compared to sufficient sleep [15]. Regulation of the appetite stimulating hormone, ghrelin, is also reported to be influenced by sleep debt, resulting in an increasing hunger among those with restricted sleep [16]. Notwithstanding the emerging evidence of the role of sleep in childhood on obesity risk, global and UK guidance to tackle the obesity epidemic in children rarely discusses sleep [17,18]. Instead, the guidance is mainly, and in some instances solely, focused on diet and physical activity which are the critical components of energy intake and expenditure [17,18].

During childhood, there is an increased physiological demand for a long sleep duration and this tapers off with age [19]. For school-aged children, fixed school schedules and social activities tend to further delay bedtime and potentially reduce sleep duration beyond the physiological decline [20]. In fact, recent studies suggest an historic rise in the proportion of school-aged children having insufficient sleep over the past decades [21,22]. While sleep duration in childhood is suggested to be a modifiable risk of obesity, for school-aged children, early and regular bedtimes appear to be the most modifiable components of sleep duration (relative to sleep latency or wake time) [23]. The limited literature on children’s bedtime schedules and health suggest that those with less structured bedtimes are at risk of an insufficient sleep duration and poor cognitive development [24,25]. In these studies, regular bedtime schedules were defined from the parent-reported frequency of children’s bedtimes (from never-regular to always-regular). Studies investigating the associations between bedtime schedules in childhood and adolescent obesity are also scant; while few used objective anthropometric measures, none assessed body fat [26,27,28,29]. Although age and sex-adjusted BMI centiles in children provide a good proxy for adiposity in children, the assessment of body fat mass from bioelectric impedance analysis provides a relatively better body fat assessment, thereby minimising any misclassification bias [30]. The present study, therefore, goes beyond previous studies by using a larger national longitudinal cohort with objective anthropometric measures and bioelectric impedance measurements of body fat percentage (BFP) to investigate the longitudinal associations between bedtime schedules in a non-obese childhood and obesity risk later in early- and mid-adolescence.

2. Materials and Methods

2.1. Data Sources

Data from adolescents participating in the UK Millennium Cohort Study (MCS) were used. The UK MCS is a nationally representative prospective cohort of children born in the UK between 09/2000 and 01/2002. The detailed sampling and recruitment strategies are explained elsewhere [31]. Briefly, children who were eligible beneficiaries of a government child support scheme, with almost universal coverage, were recruited into the MCS when they were 9 months old [31]. The MCS sample was drawn from 398 electoral wards nested in 9 sampling strata, two from each of the four nations of the UK (England, Scotland, Wales, and Northern Ireland), and an ethnic minority stratum for England [32]. To date, there have been seven sweeps of MCS follow-up, but the most recent data available are the sixth sweep (MCS6), when children were approximately 14 years old (01/2015–04/2016) [33]. The baseline sample for the present study was a subpopulation of non-obese singleton children from the fourth sweep (MCS4, at 7 years, N = 12,645) who were followed at the MCS5 (at 11 years, N = 11,044, 87.3%) and at the MSC6 (N = 9898, 78.3%) (Figure 1). Since the MCS is an open cohort, children who participated in the MCS4, but missed the MCS5, could return at the MCS6.

2.2. Measures

2.2.1. Bedtimes and Bedtime Schedules

At the MCS4, mothers responded to questions about their children’s bedtime. Specifically, the mothers were asked “On weekdays during term-time, does your child go to bed at a regular time?” and given the following response options (never, sometimes, usually, and always). Mothers who chose any of the latter three options were further probed for the weekday term-time bedtime of their children. Where the mothers provided a time range, the earliest was recorded. For this paper, bedtime was used as both a continuous variable and a categorical variable (7:30 PM or earlier, 7:31–8:00 PM, 8:01–8:30 PM, 8:31–9:00 PM, and after 9:00 PM). Considering that children’s bedtimes were unlikely to be at a precise minute during term-time, categorising the data in 30 min intervals ensured that the results were presented in a manner that is easily interpretable.

2.2.2. Anthropometric and BFP Measures

Anthropometric and BFP measures of children at 7, 11 and 14 years using electronic Tanita™ scales for weight and BFP, and Leicester Height Measure Stadiometers for height were taken by trained investigators. Each child’s body mass index (BMI) estimated in kg/m² was transformed to standardised scores. The obesity and overweight status were determined by the International Obesity Task Force (IOTF) age- and sex-specific BMI thresholds [34]. The prevalence of obesity at 7 years among the singleton children was 5.7%. To accurately investigate the relationship between childhood bedtime habits and the incidence of obesity in adolescence, statistical analyses were performed only on the subpopulation of children who were not obese at 7 years. BMI data was available for 10,780 (97.6%) and 9391 (94.9%) of those were followed at 11 and 14 years, respectively (Figure 1).

2.2.3. Sociodemographic Data

Variables in the MCS database at the baseline were listed and selected based on their relationship with both bedtime and obesity/BFP [33]. Potential confounders, from the variables selected a priori from the MCS household and parent-derived datasets, were identified using directed acyclic graphs (DAGs) developed by DAGitty (Figure 2) [35,36]. The confounders had to be identified as the ancestors of bedtime/bedtime schedules in childhood and obesity in adolescence, but not in the causal pathway in the DAG. The following variables were identified as confounders: child’s age, sex, ethnicity, parental socioeconomic status (SES), highest level of parental education/vocational training, and number of people in a household at bedtime assessment (Figure 3). The higher SES class of either parent (where both were available) was selected from the National Statistics Socioeconomic Classification (NS-SEC, 3-level version) with a fourth level when the only parent or both parents were unemployed. The higher of either parent’s highest level of education or vocational qualification was also chosen. Covariates that were not identified as confounders by DAGs, because they exhibited a plausible bidirectional relationship with the exposure and/or outcome, were included in subsequent models as sensitivity analyses (Figure 3). These included the frequency of TV hours on weekdays, computer hours on weekdays, frequency of physical activity, and frequency of bedwetting. The covariates were assessed via a parent-responded questionnaire. The categorical options ranging from “None” to “7 h or more” were provided for the questions on the frequency of computer and TV hours. The categorical options for physical activity ranged from “Five or more days a week” to “Not at all” while that of bedwetting ranged from “Never wets the bed at night” to “Wears nappies or pull-ups at night”.

2.3. Statistical Analysis

Poisson regression models were performed to assess the risk ratio (RR) of obesity at 11 and 14 years in relation to childhood bedtime regularity (reference category: always regular), or in relation to bedtime (reference category: 7:30 PM or earlier). Plausible linear trends in bedtime regularity categories and the risk of obesity were examined. Linear regression analyses were performed to examine the associations between childhood bedtime regularity or bedtime and BFP. The mean differences (MD) in BFP between each of the categories and the corresponding reference category were calculated. Where bedtime was used as a continuous variable, regression coefficients were calculated instead. The confounders and covariates were child, parent and household characteristics collected at 7 years.

All models were adjusted for previously mentioned confounders as shown in Figure 2 (Model I). Sensitivity analyses were performed on the adjusted models under various conditions: (i) further adjustment for baseline overweight status or BFP (considering that among the children who were overweight at the baseline, 17.1% became obese by 11 years and 20.7% were obese by 14 years, compared to 0.7% and 1.8% at 11 years and 14 years, respectively, for those who were not overweight at the baseline)—Model II, (ii) the inclusion of bedtime regularity and bedtime in the same model adjusting for the same confounders as in Model II–Model III, and (iii) the additional adjustment of Model III for TV and computer hours, and the frequency of physical activity and bedwetting at the baseline—Model IV.

Since there is strong evidence for age at menarche and the BFP in adolescent girls [37], the analyses of bedtime or bedtime regularity and BFP were stratified by sex and adjusted for menarche status (at 11 years) and age at menarche (at 14 years) for girls.

Complete-case analyses were employed in all the statistical analyses using Stata SE/13.1 (Stata Corp, College Station, TX, USA). All analyses accounted for the survey weights which consisted of sampling and attrition weights as well as a population correction factor. The significance was defined as p < 0.05 from two-tailed hypothesis tests.

3. Results

3.1. Sample Characteristics

Baseline characteristics for the obesity- and bedtime-related measures were similar between children lost to the follow-ups at 11 and 14 years; however, those lost to follow-up were more likely to have been boys, black, slightly older, to have had parents with low/no academic or vocational qualification, and to have been from a low SES family (

Table A1. Comparison of baseline characteristics (at 7 years) between the followed sample and those lost to follow-up (FU) at 11 and 14 years.

Baseline Characteristics	At MCS5		At MCS 6
	Lost to FU	Sample	Lost to FU	Sample
	N = 1601	N = 11,044	N = 2747	N = 9898
Child’s age, y, mean (SE) a	7.3 (0.00)	7.2 (0.00)	7.2 (0.00)	7.2 (0.00)
Child’s sex a
Boy	57.3	50.8	55.0	50.7
Girl	42.7	49.2	45.0	49.3
Child’s ethnicity a
White	84.2	86.3	86.7	85.9
Pakistani and Bangladeshi	3.9	4.6	3.1	4.9
Black or Black British	5.7	2.6	4.0	2.7
Mixed	3.4	3.2	3.6	3.1
Indian	1.2	2.1	1.4	2.1
Other ethnic groups	1.7	1.3	1.3	1.4
Frequency of physical activity
5 days/week	64.9	66.4	69.0	65.4
4 days/week	5.7	5.8	4.6	6.1
3 days/week	7.3	7.7	7.0	7.8
2 days/week	7.9	8.2	7.6	8.3
1 day/week	6.5	5.6	5.4	5.8
Less often	1.7	1.8	1.6	1.9
Not at all	6.1	4.5	4.8	4.7
TV hours on weekdays a
None	1.4	1.8	1.6	1.8
<1 h	16.4	18.0	15.8	18.3
<3 h	62.3	65.2	63.6	65.2
<5 h	13.4	10.7	14.1	10.2
<7 h	3.1	2.0	2.4	2.1
≥7 h	3.5	2.4	2.6	2.5
Computer hours on weekdays a
None	14.8	12.0	13.5	11.9
<1 h	46.5	53.0	47.9	53.4
1–<3 h	33.2	31.1	33.8	30.7
3–<5 h	4.0	2.8	3.4	2.8
5–<7 h	0.8	0.6	0.7	0.6
≥7 h	0.7	0.5	0.8	0.5
Frequency of bedwetting
Never	83.5	85.4	84.5	85.4
Occasionally	10.4	10.1	10.1	10.2
1–2 times/week	0.9	1.0	1.0	0.9
3–4 times/week	2.1	1.3	1.6	1.3
Wears nappies at night	3.2	2.2	2.9	2.2
Overweight status
Not overweight	83.1	84.8	83.3	85.0
Overweight	16.9	15.2	16.8	15.0
BFP (%), mean (SE)	20.5 (0.1)	20.2 (0.1)	20.4 (0.1)	20.2 (0.1)
Highest level parental SES a
Managerial	27.8	44.1	29.9	45.5
Intermediate	19.6	20.5	20.8	20.3
Routine	25.5	19.8	25.9	19.0
Unemployed	27.1	15.6	23.4	15.3
Highest level of parental education (NVQ) a
Level 5	8.0	13.0	7.4	13.7
Level 4	26.7	36.9	27.9	37.8
Level 3	16.4	16.1	17.8	15.7
Level 2	28.8	22.7	29.1	21.8
Level 1	7.5	5.0	7.0	4.8
None of the above	12.7	6.4	10.8	6.1
Bedtime regularity
Always regular	60.0	59.5	60.0	59.3
Usually regular	30.6	31.4	29.9	31.7
Sometimes regular	5.8	5.4	5.8	5.3
Never regular	3.6	3.8	4.3	3.6
Bedtime, pm, mean (SE)	8.00 (0.01)	8.00 (0.01)	8.00 (0.01)	8.00 (0.01)
7:30 PM or earlier	34.7	32.8	33.1	33.1
7:31–8:00 PM	34.5	37.8	36.0	37.7
8:01–8:30 PM	16.3	16.8	17.2	16.6
8:31–9:00 PM	11.3	10.5	11.3	10.5
After 9:00 PM	3.3	2.1	2.4	2.2
Household size, mean (SE)	4.5 (0.05)	4.5 (0.02)	4.5 (0.03)	4.5 (0.03)

Unless otherwise stated, this represents the weighted percentage of categories within a variable; SE: linearised standard error of the weighted mean; BFP: body fat percentage; SES: socioeconomic status; NVQ: national vocational qualification. ^a Statistically significant differences in baseline characteristic between participants lost to follow-up and those not lost to follow-up at 11 and 14 years (p < 0.05). Where there was a difference in the distribution of a baseline characteristic, it was consistent at both ages of follow-up.

in Appendix A). The prevalence of being overweight among the non-obese 7-year-olds was approximately 15%. Of the sample followed at 11 and 14 years, 59.5% and 59.3% had an always-regular bedtime schedule, while 3.8% and 3.6% had never-regular bedtime schedules, respectively. The weighted mean bedtime was 8:00 PM (95% CI, 7:58–8:01) and about two-thirds of the children went to bed by 8:00 PM. There was no sex-difference in the distribution of the regularity of bedtime schedules nor bedtimes. On average, children whose bedtimes were usually- and sometimes-regular had 10.8 min (95% CI, 9.0–12.7) and 27.3 min (95% CI, 23.6–31.2) later bedtimes than those who had always-regular bedtime schedules, respectively.

While the incidence of obesity in the entire cohort at 11 and 14 years was 2.9% and 4.9%, respectively, the incidence was highest (7.8% and 11.0%, respectively) among the children who had a never-regular bedtime schedule at 7 years (Figure 4). Likewise, obesity incidence at both adolescent years was the lowest for those whose childhood bedtime was before/at 7:30 PM and the highest for those who went to bed after 9:00 PM (2.2% vs. 5.1%; and 3.5% vs. 10.0%, respectively,

Table A2. Obesity incidence at 11 and 14 years by weekday bedtime schedules at 7 years.

	MCS5 (11 Years)	MCS6 (14 Years)
	% Obese (95% CI)	% Obese (95% CI)
All non-obese 7-year-olds	2.9 (2.6 to 3.4)	4.9 (4.3 to 5.5)
Regularity of bedtime
Always regular	2.4 (2.0 to2.9)	4.5 (3.8 to 5.4)
Usually regular	2.9 (2.3 to 3.6)	4.5 (3.6 to 5.5)
Sometimes regular	5.4 (3.6 to 7.9)	7.0 (4.7 to 10.4)
Never regular	7.8 (5.3 to 11.3)	11.0 (7.4 to 16.1)
Bedtimes
7:30 PM or earlier	2.2 (1.7 to 2.8)	3.5 (2.7 to 4.5)
7:31–8:00 PM	2.5 (2.0 to 3.0)	4.5 (3.7 to 5.5)
8:01–8:30 PM	3.1 (2.3 to 4.2)	4.8 (3.6 to 6.6)
8:31–9:00 PM	4.3 (3.1 to 6.0)	7.1 (5.2 to 9.5)
After 9:00 PM	5.1 (2.8 to 9.2)	10.0 (6.1 to 16.0)

). Additionally, the mean BFP was lowest for the children who went to bed by 7:30 PM, namely, 20.6% at both 11 and 14 years, while those who went to bed after 9:00 PM, recorded the highest mean BFP at adolescence, namely, 23.5% and 23.4%, respectively (

Table 1. Weighted mean body fat percentage (95% CI) at 11 and 14 years by term-time bedtimes and bedtime schedules of non-obese children at 7 years.

	MCS5 (11 Years)			MCS6 (14 Years)
	All	Boys	Girls	All	Boys	Girls
All children	21.4 (21.2; 21.6)	19.2 (19.0; 19.4)	23.8 (23.6; 24.0)	21.1 (20.9; 21.3)	16.1 (15.8; 16.4)	26.6 (26.3; 26.8)
Regularity of bedtime
Always regular	21.3 (21.1; 21.5)	19.1 (18.8; 19.3)	23.7 (23.4; 24.0)	21.0 (20.6; 21.3)	16.1 (15.7; 16.5)	26.5 (26.2; 26.9)
Usually regular	21.4 (21.1; 21.7)	19.1 (18.8; 19.5)	23.7 (23.3; 24.1)	21.1 (20.7; 21.4)	16.0 (15.5; 16.5)	26.4 (26.0; 26.8)
Sometimes regular	22.2 (21.5; 22.9)	20.3 (19.3; 21.3)	24.2 (23.3; 25.2)	21.8 (20.8; 22.8)	16.5 (15.5; 17.8)	27.7 (26.7; 28.7)
Never regular	22.6 (21.8; 23.5)	20.6 (19.3; 21.8)	24.5 (23.5; 25.6)	22.6 (21.3; 23.9)	17.6 (15.8; 19.3)	27.3 (25.9; 28.8)
Bedtimes
7:30 PM or earlier	20.6 (20.3; 20.9)	18.2 (17.8; 18.6)	23.0 (22.6; 23.4)	20.6 (20.1; 21.0)	15.4 (15.0; 15.9)	25.9 (25.4; 28.4)
7:31–8:00 PM	21.3 (21.0; 21.6)	19.0 (18.7; 19.4)	23.8 (23.4; 24.2)	20.9 (20.5; 21.2)	16.0 (15.5; 16.4)	26.5 (26.2; 26.9)
8:01–8:30 PM	21.9 (21.5; 22.3)	19.8 (19.3; 20.3)	24.2 (23.7; 24.7)	21.2 (20.6; 21.8)	16.0 (15.4; 16.6)	27.1 (26.5; 27.7)
8:31–9:00 PM	22.8 (22.3; 23.3)	20.9 (20.3; 21.6)	24.8 (24.2; 25.5)	22.5 (21.8; 23.2)	17.9 (16.9; 18.9)	27.6 (26.8; 28.3)
After 9:00 PM	23.5 (22.5; 24.5)	21.6 (20.0; 23.1)	25.4 (23.9; 26.8)	23.4 (22.0; 24.7)	18.5 (16.7; 20.4)	28.0 (26.4; 29.6)

). There were no sex-differences in obesity incidence at both 11 and 14 years; however, as expected, girls had 4.6% (95% CI, 4.3–4.9) and 10.4% (95% CI, 10.0–10.8) more PBF than boys, respectively.

3.2. Obesity Risk by Bedtime and Bedtime Regularity

Compared to children who had always-regular bedtimes, the risk of obesity at 11 years was two- and three-folds higher among those whose bedtimes were sometimes-regular and never-regular, respectively (

Table 2. Risk ratios (95% CI) of obesity at age 11 and 14 years by bedtime regularity and bedtimes at 7 years.

	Model I	Model II	Model III	Model IV
Obesity at 11 years
Regularity of bedtime
Always regular (Ref)	1.0	1.0	1.0	1.0
Usually regular	1.2 (0.9 to 1.7)	1.2 (0.9 to 1.6)	1.2 (0.9 to 1.6)	1.2 (0.9 to 1.7)
Sometimes regular	2.1 (1.4 to 3.3)	2.0 (1.3 to 3.0)	1.9 (1.2 to 2.8)	1.9 (1.2 to 2.8)
Never regular	2.8 (1.8 to 4.4)	2.9 (2.0 to 4.2)	-	-
p trend	<0.001	<0.001	0.013	0.008
Bedtimes (continuous) a	1.5 (1.2 to 1.8)	1.2 (1.0 to 1.5)	1.2 (1.0 to 1.4)	1.2 (1.0 to 1.4)
7:30 PM or earlier (Ref)	1.0	1.0	-	-
7:31–8:00 PM	1.1 (0.8 to 1.6)	1.0 (0.7 to 1.4)	-	-
8:01–8:30 PM	1.5 (1.0 to 2.2)	1.2 (0.8 to 1.7)	-	-
8:31–9:00 PM	1.9 (1.2 to 3.7)	1.4 (0.9 to 2.0)	-	-
After 9:00 PM	2.4 (1.1 to 5.0)	1.6 (0.8 to 3.1)	-	-
Obesity at 14 years
Regularity of bedtime
Always regular (Ref)	1.0	1.0	1.0	1.0
Usually regular	1.0 (0.7 to 1.3)	1.0 (0.7 to 1.2)	0.9 (0.7 to 1.2)	0.9 (0.7 to 1.2)
Sometimes regular	1.5 (1.0 to 2.3)	1.3 (0.9 to 1.9)	1.2 (0.8 to 1.8)	1.2 (0.8 to 1.7)
Never regular	2.3 (1.5 to 3.6)	2.3 (1.5 to 3.4)	-	-
p trend	0.002	0.002	0.760	0.900
Bedtimes (continuous) a	1.5 (1.2 to 1.8)	1.3 (1.1 to 1.5)	1.2 (1.0 to 1.5)	1.2 (1.0 to 1.5)
7:30 PM or earlier (Ref)	1.0	1.0	-	-
7:31–8:00 PM	1.4 (1.0 to 1.8)	1.1 (0.9 to 1.5)	-	-
8:01–8:30 PM	1.5 (1.0 to 2.1)	1.2 (0.8 to 1.7)	-	-
8:31–9:00 PM	2.0 (1.3 to 3.0)	1.5 (1.0 to 2.1)	-	-
After 9:00 PM	2.6 (1.3 to 5.0)	2.0 (1.2 to 3.3)	-	-

^a Represents RR (95% CI) of obesity per hour delay of bedtime. Model I adjusts for sex and age, ethnicity, parental SES, parental education, and number of people in household; Model II–Model I further adjusted for overweight status at 7 years; Model III–includes both bedtime regularity (categorical) and bedtime (continuous) and adjusts for the same covariates as in Model II; Model IV–Model III further adjusted for TV hours on weekdays, computer hours on weekdays, frequency of physical activity, and frequency of bedwetting.

). The risk of obesity at 14 years remained higher among those with never-regular bedtimes at 7 years compared with those with always-regular bedtimes (RR, 2.3; 95% CI, 1.5–3.6). There was a significant linear gradient of increasing obesity risk at both 11 and 14 years with an increasing irregularity of bedtimes at 7 years, even after adjusting for the confounders and baseline overweight status (p trend < 0.001 and p trend = 0.002, respectively). After adjusting for several covariates and including both the bedtime regularity and bedtimes in the sensitivity analyses (Model IV), the trend in increasing obesity risk with an increasing bedtime regularity persisted at 11 years (p trend = 0.008), but not at 14 years. For those not in the never-regular bedtime category, bedtimes after 8:30 PM were consistently associated with a higher risk of obesity at 11 and 14 years. An hourly delay in bedtimes at 7 years was, however, associated with a 50% higher risk of obesity across both adolescent years, although attenuated to 20% in the sensitivity analyses (Model IV in Table 2).

3.3. BFP by Bedtime and Bedtime Regularity

Mean differences in the BFP, for all adolescents, between each of the bedtime regularity categories and the always-regular category were generally not statistically significant except for those with never-regular bedtimes who had 0.9% higher body fat (95% CI, 0.0–2.2) at 11 years (Figure 5). The mean BFP for any irregular bedtime category was not significantly different from the mean BFP for the always-regular category for both sexes after stratification and adjustment for the menarche status for girls (

Table 3. Associations between bedtime regularity and bedtimes at 7 years and BFP at 11 and 14 years among boys and girls.

	Boys		Girls
	Model IA	Model IVA	Model IB	Model IVB
BFP at 11 years
Regularity of bedtime
Always regular (Ref)	0.0	0.0	0.0	0.0
Usually regular	0.0 (−0.4 to 0.5)	0.0 (−0.3 to 0.4)	0.1 (−0.4 to 0.5)	0.1 (−0.2 to 0.5)
Sometimes regular	1.0 (0.0 to 2.1)	0.1 (−0.8 to 0.9)	0.4 (−0.7 to 1.4)	0.1 (−0.7 to 0.8)
Never regular	1.1 (−0.3 to 2.5)	-	0.9 (−0.4 to 2.1)	-
p trend	0.040	0.826	0.184	0.550
Bedtimes (continuous) a	1.1 (0.8 to 1.5)	0.8 (0.5 to 1.1)	1.0 (0.6 to 1.4)	0.2 (0.0 to 0.5)
7:30 PM or earlier (Ref)	0.0	-	0.0	-
7:31–8:00 PM	0.6 (0.1 to 1.1)	-	0.8 (0.2 to 1.4)	-
8:01–8:30 PM	1.2 (0.6 to 1.8)	-	1.0 (0.3 to 1.7)	-
8:31–9:00 PM	1.9 (1.1 to 4.6)	-	1.6 (0.7 to 2.5)	-
After 9:00 PM	2.5 (0.6 to 8.8)	-	2.4 (0.6 to 4.2)	-
BFP at 14 years
Regularity of bedtime
Always regular (Ref)	0.0	0.0	0.0	0.0
Usually regular	−0.2 (−0.8 to 0.4)	0.0 (−0.5 to 0.5)	0.2 (−0.3 to 0.6)	0.1 (−0.3 to 0.5)
Sometimes regular	0.2 (−1.1 to 1.5)	−0.6 (−1.8 to 0.5)	1.1 (0.0 to 2.1)	0.5 (−0.3 to 1.4)
Never regular	1.1 (−0.9 to 3.1)	-	0.3 (−1.2 to 1.9)	-
p trend	0.504		0.152	0.254
Bedtimes (continuous) a	0.8 (0.3 to 1.3)	0.6 (0.1 to 1.1)	0.8 (0.4 to 1.2)	0.3 (−0.1 to 0.6)
7:30 PM or earlier (Ref)	0.0	-	0.0	-
7:31–8:00 PM	0.3 (−0.3 to 1.0)	-	0.4 (−0.2 to 1.0)	-
8:01–8:30 PM	0.2 (−0.6 to 1.0)	-	0.9 (0.2 to 1.6)	-
8:31–9:00 PM	1.7 (0.6 to 2.8)	-	1.3 (0.5 to 2.2)	-
After 9:00 PM	2.3 (0.1 to 4.6)	-	1.9 (−0.1 to 3.8)	-

^a Represents regression coefficient (95% CI) of BFP per hour delay of bedtime. Model IA adjusts for age, ethnicity, parental SES, parental education, number of people in household; Model IB adjusts for menarche and the same covariates in model IA; Models IVA and IVB—each model includes both bedtime regularity (categorical) and bedtime (continuous) and adjusts for BFP at 7 years, frequency of TV hours on weekdays, computer hours on weekdays, frequency of physical activity, and frequency of bedwetting, in addition to confounders adjusted for in Models IA and IB, respectively.

); however, the BFP at 11 years increased by 1.1% (95% CI, 0.8–1.5) and 1.0% (95% CI, 0.6–1.4) for every hour delay in bedtime at 7 years for boys and girls, respectively. This linear increase persisted, albeit attenuated to 0.8%, at 14 years across both sexes.

The marginal increase in BFP with late bedtimes was more evident in early adolescence with childhood bedtimes even as early as 7:31–8:00 PM, being significantly associated with a significantly higher BFP at 11 years (MD, 0.6%; 95% CI, 0.1–1.1 and 0.8%; 95% CI, 0.2–1.4, for boys and girls, respectively), compared to bedtimes before/at 7:30 PM. The dose–response association between later bedtimes in childhood and a higher BFP in adolescence persisted even after adjusting for bedtime regularity and several covariates including the baseline BFP in the sensitivity analyses (Models IVA and IVB in Table 3).

4. Discussion

In this study, we found that an increasing frequency in irregular bedtimes at 7 years was associated with an increasing risk of obesity at both 11 and 14 years in a dose–response pattern. It was notable that even among children who had some degree of bedtime regularity, similar dose–response relationships were apparent between the time children went to bed and the subsequent risk of obesity. Seven-year-olds with bedtimes after 8:30 PM consistently had an approximately two- to three-fold higher risk of obesity at 11 and 14 years relative to those with bedtimes at 7:30 PM or earlier; an association which remained consistent among teenage girls after adjusting for menarche. Every hour delay in bedtime at 7 years was associated with an approximately 1% increase in BFP at 11 and 14 years for both sexes.

This study contributes to the expanding literature showing that an early bedtime in childhood is associated with a lower risk of obesity in adolescence [26,27,28]. While previous studies had a baseline sample of pre-school age children (~5-year-olds) among whom the reference/optimal bedtime was defined as before/at 8:00 PM (25%) [24] or as late as 8:30 PM (27%) [25], our sample was 7-year-olds, the majority of whom went to bed before 8:30 PM (87%). These differences in the baseline sample age distribution and reference bedtime categories did not result in contradictory findings between the earlier studies and the present study. Nevertheless, our findings show that even among 7-year-olds, term-time bedtimes at 7:31–8:00 PM relative to 7:30 PM or earlier, were associated with a 0.6% and 0.8% increase in BFP at 11 years for boys and girls, respectively. Although these marginal increases in BFP did not necessarily manifest in increased obesity risks for children in this bedtime category, they highlight the potential contributory factor of even minimal delays in children’s bedtime on body composition in adolescence. It is, however, worth noting that the linear relationship between bedtime and BFP was attenuated for girls after adjusting for baseline BFP and bedtime regularity in the sensitivity analysis.

In comparison with bedtimes and obesity in children, there is adequate literature on the relationship consistently showing that a short sleep duration in childhood is a risk factor for obesity in adolescence [14,26,38,39,40,41]. An insufficient age-appropriate sleep duration is hypothesised to be associated with changes in normal metabolic and endocrinal functions including dysregulation of the neuroendocrine control of the appetite hormones leptin and ghrelin, which increase food consumption and decrease non-insulin-dependent glucose uptake, resulting in increased fat deposition [13,42,43,44]. Similar mechanisms are suggested to explain the link between irregular/misaligned sleep patterns and obesity risk [44,45]. While sleep duration is an important factor in relation to obesity risk, fixed wake times likely due to school start times and other social demands for early school-age children imply that the most probable and modifiable risk factor to ensure a sufficient sleep duration is an early bedtime and regular bedtime schedules [24,46]. Metabolic and endocrinal dysregulation arising from shorter sleep duration and irregular sleep patterns may explain the observed relationships between bedtime irregularity, late bedtimes, and increased adiposity in our study. The relationship between late bedtimes and a higher obesity risk may also be partially explained by the time available to eat and the likelihood of late night eating [42,47]. Irregular bedtime schedules in children have also been linked to poor health and development and may be indicative of an unfavourable and poorly-structured home environment beyond the household and socio-economic confounders considered in our analysis [24,25,48,49].

Attrition is a common problem for prospective cohort studies. In this study, 13% and 22% of the baseline sample were lost to follow-up at 11 and 14 years, respectively; however, the sampling and attrition weights were considered for all analyses. Objective bedtime data from actigraphy would have minimised the risk of potential recall bias and exposure misclassification. In addition, the study lacked other sleep-related parameters such as sleep quality/disturbance and sleep duration to differentiate the relevance of different components of sleep during childhood on the risk obesity and adiposity in adolescence. A recent study investigating the cross-sectional associations between sleep timings and obesity in adolescence reported an association between late sleep timing and increased BFP [50]. Further, the data collectors only recorded the earliest bedtimes when mothers provided a time range for their children’s bedtime. This implies that the actual bedtimes of children are likely to be later than the reported bedtimes in this study. Additionally, due to the relatively smaller percentage of children in the never-regular and after 9 PM bedtime categories, adjusting for multiple covariates and restricted analysis among girls only resulted in wider confidence intervals for these groups which resulted in nonsignificant differences in some instances.

A major strength of this study is the use of prospective data from a large nationally representative cohort of UK children. While this is insufficient to make a causal inference of the relationship between bedtime schedules in childhood and subsequent obesity risk, it suggests temporality in this relationship considering that none of the children were classified as obese at the baseline. Besides the estimation of obesity from anthropometric measurements, we also measured the BFP, which is a better marker of adiposity in children [51,52]. In this study, mothers who reported that their children never had regular bedtimes were not asked for a bedtime. In the MCS, bedtimes were only collected from mothers who reported always, usually, or sometimes regular bedtimes for their children. Exclusion of children with completely irregular bedtimes when investigating the association between the time a child went to bed and obesity may have provided less biased results. In addition, confounders were identified through DAGs, and we also accounted for several covariates in the sensitivity analyses, including the age at menarche and baseline overweight status or BFP.

5. Conclusions

Our findings suggest that irregular bedtime schedules and later bedtimes in childhood are independently associated with an increased risk of obesity and higher BFP in early- and mid-adolescence. Later bedtimes in childhood, irrespective of bedtime regularity, are associated with marginal increases in BFP in adolescence. The study contributes to the growing body of empirical evidence highlighting the importance of regular and early bedtimes, and sufficient sleep during childhood as important modifiable risk factors for obesity in adolescence. Further studies are needed to assess whether improvements in the bedtime schedules in childhood may mitigate the potential risk of obesity in adolescence.