Cross-Sectional Relationship between Regular Bedtime and Weight Status and Obesity-Related Behaviors among Preschool and Elementary School Children: TX CORD Study

Abstract

Background:

This study examines the relations between a regular weekday bedtime with weight status, diet quality, physical activity, wellbeing, and parental rules among children 2 to 12 years of age from low-income populations.

Methods:

The study used baseline data collected in 2012, as part of a larger quasiexperimental study design. A convenience sample of parents of children in preschools, second, or fifth grade attending Head Start centers or elementary schools located in low-income catchment areas, in Houston and Austin, TX, were recruited to participate in the study (n = 32 elementary schools; n = 12 Head Start centers). Regular weekday bedtime was measured with the question “Does your child have a regular weekday bedtime?”

Results:

The sample of 1467 child–parent dyads were split approximately evenly by sex, and consisted of 44.4% Pre-K, 30.4% second grade, and 25.2% fifth grade students. Six hundred twenty-two (43.6%) children were overweight or obese. Children who had a regular bedtime had 15% lower odds of being overweight or obese (adjusted odds ratio [aOR]: 0.85, 95% confidence interval [CI]: 0.74–0.97, p-value: 0.017). Also, children who had a regular bedtime had 45% higher odds of eating the recommended number of fruits and vegetables (aOR: 1.45, 95% CI: 1.02–2.07, p-value: 0.039) and had physical activity more days of the week (β: 0.42, 95% CI: 0.26–0.57, p-value: <0.001).

Conclusions:

Having a regular weekday bedtime is associated with better weight status and several obesity-related health behaviors in children. Parental report of regular bedtimes for their children may be an indication of parenting skills related to other health-related behaviors for prevention of childhood obesity.

Background

Childhood obesity continues to persist in the United States, with 18.5% of children 2–19 years of age having body mass index (BMI) in the obesity category.¹ Sleep duration and timing have been identified as important factors that may contribute to obesity risk in children.² The relation between sleep duration with obesity and obesity-related behaviors such as diet and physical activity is well elucidated.^3–13 Shorter sleep duration and large variability in duration of sleep have been associated with greater intakes of added sugar, sugary beverages, and higher consumption of energy-dense diets, as well as less frequently engaging in physical activity.^9,13

Having a consistent bedtime routine (all of the activities that occur up to the time the child is put to bed), which includes having a regular daily bedtime, is associated with improved sleep quality, earlier bedtime, and longer sleep duration.¹⁴ However, when examining the relations among sleep, health behaviors, and weight status, many studies use sleep variables such as duration and timing without including other measures of sleep hygiene, such as regular bedtimes. The studies that do include bedtime focus on other sleep-specific factors such as sleep quality.¹⁴ Compared with other sleep variables such as duration and timing, having a consistent bedtime and bedtime routine could provide insight to the structural environment of the home and family functioning.¹⁴

The effects of having a consistent, regular bedtime on obesity/obesity-related behaviors, among children from low-income minority populations are not well studied. Few studies have examined the relations between bedtime and obesity or obesity-related behaviors. Children 9–16 years of age having a sleep pattern with an earlier bedtime and earlier wake time were less likely to have obesity and more likely to be physically active than children with a later bedtime and later wake time.¹² Later weekday bedtimes were also associated with poorer dietary habits in adolescents.⁸ The aforementioned studies show the relations between early bedtime and lower BMI; however, they do not address whether there are parent rules about children's bedtime. Understanding the associations between regular bedtime and childhood obesity and related behaviors provides another potential target to address childhood obesity.

The objectives of this study are to examine the cross-sectional associations between having a regular weekday bedtime with weight status, dietary habits, physical activity, wellbeing, and parental rules around eating among children 2 to 12 years of age using baseline data from the Texas Childhood Obesity Research Demonstration (TX CORD) project.

Methods

Study Design and Participants

The TX CORD study was conducted to address the persistent childhood obesity epidemic among low-income, ethnically diverse children ages 2 to 12 years. The TX CORD study consisted of a primary obesity prevention program and secondary prevention randomized controlled trial. The primary prevention program used a quasiexperimental study design with serial cross-sectional data collected across two time points at baseline, before implementation of intervention strategies (fall 2012) and 2-year follow-up (spring 2014) from elementary schools and Head Start preschools across intervention and comparison catchment areas in Houston and Austin, TX.¹⁵ The primary prevention intervention consisted of components, which included four evidence-based programs: Coordinated Approach To Child Health (CATCH) Early Childhood; CATCH Elementary School; training for teachers and community health workers; and implementation of the Next Steps program and brief counseling in health care clinics.¹⁵

Data from geographical information systems were used to select intervention and comparison catchment areas in Houston and Austin using socioeconomic characteristics that fit the target population: ethnically diverse population; lower-median household income; and lower home ownership rates. Intervention and comparison catchment areas were assessed for comparability across sociodemographic characteristics.¹⁶ Following this, a convenience sample of elementary schools and Head Start centers were recruited to participate in the study at baseline (n = 32 elementary schools; n = 12 Head Start centers). For the purposes of this study, baseline data from the TX CORD study collected in fall 2012 were used. The sample consisted of 1561 child–parent dyads with children from pre-K (n = 685), second grade (n = 485), and fifth grade (n = 391). There was a 94% response rate on survey items. Full descriptions of the TX CORD study design and methods have been provided elsewhere.^15,16

This study was reviewed and approved by the Institutional Review Boards at the University of Texas Health Science Center at Houston and Baylor College of Medicine and local school districts. Informed consent was obtained from personnel before assessment, and informed active consent of parents was obtained before measurement. Verbal or written assent was obtained from all school children.

Data Collection Measures

Sociodemographics

Parent and child demographics were collected at baseline using parent surveys, including child age, gender, race, and ethnicity. Parent demographics included parent age, gender, race, ethnicity, primary language spoken at home, income, and education level.

Child BMI

Height and weight of each child were measured using stadiometers (Perspective Enterprises) and digital scales (Tanita). All measurements were conducted by trained project staff using standard protocols. Height and weight were used to compute age and gender-specific BMI percentiles and z-scores using CDC growth charts to determine weight status.¹⁷ Weight status was dichotomized into healthy weight and overweight/obese categories, using CDC-defined 85th percentile BMI as the cut point. Recent studies show that BMI z-scores have a theoretical maximum; therefore, range of BMI values within the severe obesity category (>97th percentile) are expressed as very similar z-scores, particularly in children <10 years of age.¹⁸ %BMIp95 is not similarly restricted. Given that we are targeting those who are overweight/obese, we have a significant proportion of children who are >97th percentile, hence, we assessed both outcomes BMIZ and %BMIp95.

Parent Surveys

Parent surveys were sent home with the child. All surveys were offered in English or Spanish. The same survey was used regardless of child's grade and the primary parent/caregiver was asked to complete the survey. Parents were requested to send the completed surveys back to their child's school or Head Start center in sealed envelopes provided, which were then collected by a project staff.

The questions used to capture the measures were validated and were previously developed from the School Physical Activity and Nutrition (SPAN) survey and CORD common measures.^19–23

Regular weekday bedtime was measured with the question “Does your child have a regular weekday bedtime?” Response options were none of the time (0), some of the time (1), most of the time (2), and always (3).

A healthy eating score and an unhealthy eating score were used to determine the healthfulness of the overall diet of the adolescent, using the SPAN Healthy Eating Index.²³ The SPAN Healthy Eating Index is generated from the number of survey items that indicate consumptions of specific foods; this calculation is done separately for healthy and unhealthy foods. Healthy foods consist of nine items, which included consumption of fruits, vegetables, and water. Unhealthy foods consist of nine items, which included consumption of fruit-flavored drinks, soda, and punch.

Dietary behaviors were measured with questions that assessed the frequency of consumption of various foods, including fruit, vegetables, chips, fruit-flavored drinks, 100% fruit juice, sodas/soft drinks, and water. For example: “Yesterday, did your child eat any vegetables? Vegetables are all cooked and uncooked vegetables; salads. Do not count French fries, fried potatoes, or potato chips.” Response options included (1) no (2) 1 time, (3) 2 times, or (4) 3 or more times.^19–22 Response options were coded from 0 (No) to 3 (3 or more times). The USDA and HHS dietary guidelines were used to determine if a child met the national recommendations for fruit and vegetable consumption.²⁴

Parents reported “The number of days in a week that their child was physically active for a total of at least 60 minutes per day.” Response options included 0–7 days. Parents were also asked “Whether they are physically active with their child.” Response options included never (0), some of the time, most of the time, or all of the time (3).^19–22

Child wellbeing was captured with questions that asked the parents whether their child was satisfied with life, was happy, and if they had low energy levels in the past month. Response options included (1) never, (2) almost never, (3) sometimes, (4) often, or (5) almost always.^19–22 Response options were coded from 0 (never) to 4 (almost always).

Parental rules consisted of eight questions, each assessed individually that asked parents if they served fruit and vegetables as snacks or at dinner, and if they had rules limiting child portion sizes, fast food, sugary beverages, or screen time. For example, “Do you have the following rules about your child's eating? 1. Limit portion sizes?,” etc. Response option was binary (yes/no) to each rule.

Statistical Analyses

Descriptive statistics, including mean with standard deviations and frequencies with percent were calculated across the sociodemographic and the outcome variables for overall and by regular bedtime categories. Pearson chi-square tests were conducted to determine differences by categorical variables and one-way analysis of variance tests were used to determine difference by continuous variables. To understand the relationship between regular bedtime (independent variable) and weight status, diet, physical activity, child wellbeing, and parental rules (dependent variables), multilevel logistic regression models were calculated to determine odds ratios (OR) for categorical dependent variables, and multilevel linear regression models were calculated to determine beta coefficients for continuous dependent variables. School and Head Start centers were adjusted for as a random effect in the analysis to account for clustering effects. Covariates included parent education, city, child race/ethnicity, child sex, and grade, based on household size and income and was calculated by using poverty guidelines of the U.S. Department of Health and Human Services.²⁵ Results are presented as OR or beta-coefficients (β) with 95% confidence intervals (CIs). STATA 13.0 was used for all analyses (College Station, TX).

Results

The demographics of the study participants are presented in Table 1. The age of the children ranged from 2 to 12 years, consisting of 77.3% Hispanic, 18.1% non-Hispanic Black, and 4.6% non-Hispanic White/other children. The sample was split approximately evenly by sex and consisted of 44.4% of children in the Pre-K, whereas 30.4% were second grade students and 25.2% were fifth grade students. More than half the sample (57.5%) had a healthy weight, whereas 42.5% of the sample were overweight or obese. Almost half of the sample reported always had a regular weekday bedtime (47.6%), whereas 33.6% reported having a regular weekday bedtime most of the time, 14.6% some of the time, and 4.2% none of the time.

Table 1.

Demographics among Children Ages 2 to 12, TX CORD Study, 2012

	Child has regular weekday bedtime					p
	Overall	None of the time	Some of the time	Most of the time	Always
	N = 1467	N = 64	N = 208	N = 482	N = 713
Parent education, n (%)						0.026
None–Kindergarten	27 (1.8)	1 (3.8)	8 (30.8)	4 (15.4)	14 (50)
Grades 1–8	282 (19.2)	18 (6.5)	54 (19.2)	81 (28.6)	129 (45.7)
Grades 9–11	315 (21.5)	11 (3.6)	43 (13.6)	117 (37.2)	144 (45.6)
Grade 12 or GED	481 (32.8)	23 (4.7)	60 (12.5)	163 (33.8)	235 (49)
Some college	289 (19.7)	7 (2.5)	35 (12)	100 (34.6)	147 (50.9)
College grade	73 (5)	3 (4.3)	8 (11.4)	20 (27.1)	42 (57.2)
Child race/ethnicity, n (%)
Hispanic	1134 (77.3)	54 (4.8)	166 (14.6)	389 (34.3)	525 (46.3)	<0.001
Non-Hispanic Black	266 (18.1)	7 (2.6)	27 (10.2)	70 (26.3)	162 (60.9)
Non-Hispanic White/other	67 (4.6)	2 (3)	16 (23.9)	23 (34.3)	26 (38.8)
Child sex, n (%)
Male	707 (48.2)	25 (4.4)	105 (14.4)	228 (33.4)	349 (47.8)	0.950
Female	760 (51.8)	27 (4.3)	99 (14)	250 (32.4)	384 (49.3)
Child grade, n (%)
Pre-K	651 (44.4)	24 (3.6)	97 (14.9)	210 (32.3)	320 (49.2)	0.312
Second grade	446 (30.4)	16 (3.6)	58 (13)	147 (32.9)	225 (50.5)
Fifth grade	370 (25.2)	24 (6.5)	53 (14.3)	125 (33.8)	168 (45.4)

Pearson chi-square tests were used to determine differences.

GED.

Table 2 presents the descriptive results for child BMI, diet, physical activity, wellbeing, and parental rules, by regular bedtime categories. More children who were at a healthy weight always had a regular bedtime compared with those who were overweight or obese (51.9% vs. 44.7%; p = 0.03). The average sugary beverage consumption differed significantly across bedtime, in that children who always had a regular bedtime had the lowest average consumption (p = 0.008).

Table 2.

Frequencies of Child Regular Bedtime and Child Body Mass Index, Child Diet, Physical Activity, Wellbeing, and Parental Rules among Children Ages 2 to 12, TX CORD Study

	Regular Bedtime
	Overall	None of the time	Some of the time	Most of the time	Always
	N = 1467	N = 64	N = 208	N = 482	N = 713
BMI weight status, n (%)^**
Healthy weight	851 (58)	29 (3.4)	110 (12.9)	271 (31.8)	441 (51.9)
Overweight or obesity	616 (42)	35 (5.6)	95 (15.4)	211 (34.3)	275 (44.7)
%BMI_p95 (mean, SD)	92.34 (18.13)	93.89 (18.30)	92.95 (18.66)	92.38 (16.85)	91.54 (18.10)
BMIZ (mean, SD)	0.78 (1.21)	0.83 (1.40)	0.85 (1.14)	0.78 (1.16)	0.69 (1.24)
Diet
Recommended number of fruits, n (%)^**
Child did not meet	848 (57.8)	44 (5.2)	130 (15.3)	293 (34.6)	381 (44.9)
Child met	619 (42.2)	20 (3.3)	78 (12.5)	188 (30.4)	333 (53.8)
Recommended number of vegetables, n (%)
Child did not meet	1357 (92.5)	64 (4.7)	191 (14.1)	453 (33.4)	650 (47.9)
Child met	110 (7.5)	2 (1.9)	13 (12.1)	30 (27.1)	65 (58.9)
Recommended number of F&V, n (%)
Child did not meet	1375 (93.7)	65 (4.7)	197 (14.3)	456 (33.2)	657 (47.8)
Child met	92 (6.3)	0	10 (11.2)	25 (27)	57 (61.8)
Sum of F&V previous day [range: 0–6], (mean, SD)^**	2.76 (1.46)	2.30 (1.41)	2.57 (1.36)	2.65 (1.41)	2.90 (1.52)
Healthy eating score [range: 0–9], (mean, SD)	4.91 (1.93)	4.14 (1.95)	4.48 (1.82)	4.71 (1.86)	5.19 (1.94)
Unhealthy eating score [range: 0–9], (mean, SD)^*	1.93 (1.61)	2.70 (2.15)	2.39 (1.71)	1.91 (1.55)	1.74 (1.54)
Sugary beverage [range: 0–6], (mean, SD)^**	1.29 (1.23)	1.83 (1.57)	1.64 (1.28)	1.27 (1.21)	1.15 (1.19)
Physical activity
Parents PA w/child [range: 0–3], (mean, SD)	1.62 (0.83)	1.49 (0.91)	1.49 (0.82)	1.55 (0.80)	1.80 (0.85)
Number of days/wk child is PA [range: 0–7], (mean, SD)^**	4.68 (2.28)	3.58 (2.43)	4.09 (2.44)	4.66 (2.21)	4.94 (2.23)
Child wellbeing
My child is satisfied with life [range: 0–4], (mean, SD)	3.69 (0.66)	3.5 (0.80)	3.55 (0.82)	3.66 (0.67)	3.74 (0.64)
My child is happy [range: 0–4], (mean, SD)	3.71 (0.60)	3.48 (0.91)	3.65 (0.67)	3.66 (0.65)	3.76 (0.58)
My child has low energy [range: 0–4], (mean, SD)	0.60 (0.96)	0.77 (1.11)	0.74 (0.94)	0.58 (0.88)	0.52 (0.97)
Parental rules
Serve fruit as snacks [range: 0–4], (mean, SD)^***	1.89 (1.27)	1.41 (1.24)	1.57 (1.19)	1.88 (1.24)	1.98 (1.33)
Serve veggies as snacks, (mean, SD)^***	1.57 (1.24)	1.03 (1.11)	1.41 (1.16)	1.53 (1.16)	1.75 (1.33)
Serve veggies at dinner, (mean, SD) ^***	1.83 (1.26)	1.25 (1.09)	1.51 (1.10)	1.73 (1.20)	2.04 (1.35)
Limit child portion sizes, n (%)^***
No	491 (33.5)	36 (7.3)	79 (16.1)	162 (32.9)	215 (43.7)
Yes	976 (66.5)	26 (2.7)	114 (11.7)	322 (33)	513 (52.6)
Must eat dinner with family, n (%)^***
No	412 (28.1)	28 (6.8)	73 (17.7)	145 (35.3)	166 (40.2)
Yes	1055 (71.9)	37 (3.5)	133 (12.6)	341 (32.3)	545 (51.7)
Limit fast food, n (%)^***
No	261 (17.8)	25 (9.6)	63 (24.2)	76 (29.2)	97 (37)
Yes	1206 (82.2)	39 (3.2)	147 (12.2)	410 (34)	610 (50.6)
No sugary beverages, n (%)
No	634 (43.2)	31 (4.9)	91 (14.3)	228 (35.9)	285 (44.9)
Yes	833 (56.8)	32 (3.8)	98 (11.8)	272 (32.6)	431 (51.8)
Limit screen time <2 hours per day [range: 1–5], (mean, SD)	3.98 (1.22)	3.65 (1.46)	3.67 (1.28)	3.98 (1.18)	4.10 (1.18)

The mean and SD is presented for the numerical variables: BMI95pct, BMIZ, sum of F&V previous day, Healthy Eating Score, Unhealthy Eating Score, sugary beverage, parents PA w/child, number of days/week child is PA, my child is Satisfied with life, my child is happy, my child has low energy, serve fruit as snacks, serve veggies as snacks, serve veggies at dinner. The total and percentage are presented for categorical variables.

%BMI_p95 is the % above the BMI 95th percentile.

p < 0 · 05, ^**p < 0 · 01, ^***p < 0 · 001.

BMI, body mass index; PA; SD, standard deviation.

Table 3 presents the regression models examining the relationship between child regular bedtime and child BMI, diet, physical activity, wellbeing, and parental rules. Moving up one regular bedtime category results in children having 15% lower odds of being overweight or obese (adjusted OR [aOR]: 0.85, 95% CI: 0.74–0.97, p-value: 0.017). While similar associations were observed for BMI z-score and %BMI_p95, these results were not statistically significant.

Table 3.

Relationship between Child Regular Bedtime (Independent Variable) and Child Body Mass Index, Child Diet, Physical Activity, Wellbeing, and Parental Rules (Dependent Variables) among Children Ages 2 to 12, TX CORD Study

	Regular bedtime^a[none of the time (0), some of the time (1), most of the time (2), and always (3)]
	OR/beta coefficient	95% CI	p
	Adjusted OR (aOR)^b	95% CI	p
BMI: weight status [(0) = normal weight; (1) = overweight/obese]	0.85	0.74 to 0.97	0.017
Physical activity: parents PA w/child	1.40	1.22 to 1.61	<0.001
Child wellbeing
My child is satisfied with life	1.34	1.14 to 1.58	<0.001
My child is happy	1.28	1.09 to 1.51	0.003
My child has low energy	0.79	0.69 to 0.91	0.001
Parental rules
Serve fruit as snacks	1.43	1.25 to 1.62	<0.001
Serve veggies as snacks	1.31	1.17 to 1.47	<0.001
Serve veggies at dinner	1.52	1.33 to 1.73	<0.001
Limit child portion size	1.43	1.22 to 1.66	<0.001
Must eat dinner with family	1.39	1.19 to 1.62	<0.001
Limit fast food	1.73	1.46 to 2.07	<0.001
No sugary beverages	1.19	1.03 to 1.38	0.022
Limit screen time <2 hours per day	1.37	1.20 to 1.57	<0.001
Diet
Met recommended number of fruits consumed	1.32	1.12 to 1.55	0.001
Met recommended number of vegetables consumed	1.31	0.95 to 1.79	0.098
Met recommended number of F&V consumed	1.45	1.02 to 2.07	0.039
	Adjusted β coefficient^c
%BMI_p95	−0.63	−1.74 to 0.49	0.270
BMIZ	−0.05	−0.13 to 0.02	0.171
Diet
Sum of F&V previous day (range: 0–6)	0.19	0.10 to 0.30	<0.001
Healthy eating score (range: 0–9)	0.37	0.24 to 0.50	<0.001
Unhealthy eating score (range: 0–9)	−0.36	−0.47 to −0.25	<0.001
Sugary beverage (range: 0–6)	−0.13	−0.17 to −0.08	<0.001
Physical activity: number of days/week child is PA (range: 0–7)	0.42	0.26 to 0.57	<0.001

Referent for regular bedtime was moving up each category.

Multilevel logistic regression models were calculated to determine ORs adjusting for parent education, city, child ethnicity, child gender, and child grade.

Multilevel linear regression models were calculated to determine beta coefficients adjusting for parent education, city, race/ethnicity, sex, and child grade. Significance is set at p < 0.05. %BMI_p95 is the % above the BMI 95th percentile.

aOR, adjusted odds ratio.

Moving up one regular bedtime category results in children having 32% higher odds of eating the recommended number of servings of fruits (aOR: 1.32, 95% CI: 1.12–1.55, p-value: 0.001), and 45% greater odds of eating the recommended servings of fruits and vegetables combined (aOR: 1.45, 95% CI: 1.02–2.07, p-value: 0.039). There was no association between regular bedtime and percent consuming recommended number of servings of vegetables. They also had an overall healthier diet based on the SPAN healthy eating score (adjusted β: 0.37, 95% CI: 0.24–0.50, p-value: <0.001). Moving up one regular bedtime category also resulted in greater consumption of more fruits and vegetables, and less sugary beverages.

There was a positive relationship between regular bedtime and physical activity variables such that, moving up one regular bedtime category results in children being physically active more days of the week (adjusted β: 0.42, 95% CI: 0.26–0.57, p-value: <0.001) and having parents who participate in physical activity with them more often (aOR: 1.40, 95% CI: 1.22–1.61, p-value: <0.001). Moving up one regular bedtime category resulted in children who were more satisfied with life (aOR: 1.34, 95% CI: 1.14–1.58, p-value: <0.001), were happier (aOR: 1.28, 95% CI: 1.09–1.51, p-value: 0.003), and had low energy levels less frequently (aOR: 0.79, 95% CI: 0.69–0.91, p-value: 0.001).

Having a regular weekday bedtime was also significantly associated with various parental rules. Moving up each regular bedtime category was associated with children having parents who more frequently served fruit as snacks (aOR: 1.43, 95% CI: 1.25–1.62, p-value: <0.001), parents that served veggies as snacks more often (aOR: 1.31, 95% CI: 1.17–1.47, p-value: <0.001), and parents that served veggies at dinner more often (aOR: 1.52, 95% CI: 1.33–1.73, p-value: <0.001). They also had 43% higher odds of having rules in place to limit portion sizes (aOR: 1.43, 95% CI: 1.22–1.66, p-value: <0.001), 39% higher odds of having a rule in place requiring that they eat dinner with the family (aOR: 1.39, 95% CI: 1.19–1.62, p-value: <0.001), 73% higher odds of having a rule that limits fast food intake (aOR: 1.73, 95% CI: 1.46–2.07, p-value: <0.001), 19% higher odds of having a rule in place for no sugary beverages (aOR: 1.19, 95% CI: 1.03–1.38, p-value: 0.022), and 37% higher odds of having a rule in place to limit screen time to <2 hours per day (aOR: 1.37, 95% CI: 1.20–1.57, p-value: <0.001).

Discussion

In contrast to this study, most studies in the literature methodologically assess sleep through sleep duration, early or late bedtime, wake time, or bedtime shifts between weekdays and weekends. To our knowledge, this study is the first to examine the relationship between having a regular weekday bedtime (without an indication of when the bedtime is or the duration of sleep) and weight status, diet, physical activity, wellbeing and parental rules in pre-K, second grade, and fifth grade children ages 2 through 12. Understanding whether a child has a regular bedtime provides another way to assess the parent rules, and potentially, the quality of sleep should be included in future studies.

The results of our study indicate that, children who more frequently had a regular weekday bedtime had higher odds of having a healthy weight, eating the recommended number of fruits and vegetables, having an overall healthy diet, engaging in physical activity, and having an overall greater sense of wellbeing. Children with a regular weekday bedtime also had higher odds of having parental rules in place with regard to their diets and limiting screen time. While many studies use sleep variables such as duration and timing, the present study specifically focused on regular weekday bedtime. This is significant because multiple studies have concluded that having a bedtime routine, which includes having a regular daily bedtime, is associated with improved sleep quality, earlier bedtime, and longer sleep duration.¹⁴ Lack of a regular bedtime could be related to later bedtimes and insufficient sleep, which are risk factors for obesity and obesity-related behaviors.^3–12

Late bedtimes and shorter sleep duration have been associated with a higher risk of being obese.^3–7 Preschool-aged children who had early weekday bedtimes, considered 8:00 pm or earlier, were half as likely to have obesity as preschool children with late bedtimes.⁷ Short sleep duration was also shown to increase the risk of developing obesity in infants, children, and adolescents.⁴ The findings from the present study are similar in that having a regular weekday bedtime was significantly associated with lower odds of being overweight or obese. This indicates that in addition to sleep duration and late bedtimes, bedtime consistency has a relationship with weight status as well. These findings from the previous studies mentioned and the present study could suggest that establishing a regular sleep schedule may lead to healthier sleep habits which could prevent the onset of obesity; as this study is cross-sectional, we cannot make a definitive conclusion on this.

Late bedtimes and short sleep duration have been associated with poor diet quality, and unhealthy dietary habits in children and adolescents.^8–11 Sleep duration was negatively associated with energy density of the diet,^9,10 whereas later bedtimes were associated with poorer diet quality, and unhealthier dietary habits, including consuming less fruits and vegetables and more sugary beverages and foods.^8,10,11 In the present study, children who had a regular weekday bedtime had higher odds of eating the recommended number of fruits and vegetables and consuming healthy foods and lower odds of consuming unhealthy foods and sugary beverages. Lack of bedtime consistency could lead to insufficient sleep, which has been linked to lack of impulse control around food, and alteration in mood, which can lead to unhealthy eating and subsequently obesity.^2,26

Late bedtimes and short sleep duration have also been associated with less physical activity, and more sedentary activity and screen time in children and adolescents.^11,12 Children and adolescents with early bedtimes were more likely to be physically active and less likely to engage in sedentary behaviors compared with those with late bedtimes.^11,12 A short sleep duration was also associated with being more sedentary and spending more time watching TV during the weekday.¹¹ Children who had a regular weekday bedtime also had higher odds of being physically active more days of the week and having parents participate in physical activity with them. Lacking a regular bedtime could lead to increased tiredness due to shorter sleep duration, which is associated with an increase in sedentary behaviors such as television watching.¹¹ Children who lack a bedtime consistency also go to bed late and engage in more screen time between 7 pm to midnight, which could account for the differences in screen time.¹²

A unique finding in our study is that children who were reported to have a regular weekday bedtime also had several parental dietary rules in place. These included serving fruits as snacks, serving vegetables as snacks, serving vegetables at dinner, limiting child portion sizes, eating dinner with the family, limiting fast food, limiting sugary beverages, and limiting screen time. These findings indicate that poor bedtime routine could be indicative of lack of household routines around other behaviors, including food and activity. Children exposed to a variety of household routines, such as eating dinner as a family, obtaining adequate sleep, and limiting screen time, have significantly lower odds of obesity.²⁷ Parents who have household rules in place may also have rules in place regarding bedtime, meaning a healthier, more beneficial, home environment for their child. Thus, the regular bedtime could be a signal of a more structured home life and not directly influence weight.

The current study is significant in that it examines health behaviors associated with having a regular bedtime in a predominately low-income, Hispanic cohort (77% Hispanic; 75% of parents with ≤ high school diploma/GED). Our findings indicated that 81% of Hispanic children had regular bedtimes, all or most of the time, in contrast to other studies that have shown that Hispanic children from disadvantaged households with parents who have low educational attainment have significantly lower odds of having regular bedtimes, bedtime routines, and less frequently used bedtimes that were in place.²⁸ Another study also demonstrated that Hispanic children have lower odds of using regular bedtimes and bedtime routines.²⁸ The current study is also consistent with the finding that parents with a college degree had a greater frequency of having a regular bedtime in place for their children, but contradicted the findings that Hispanic children less frequently had a regular weekday bedtime when compared with white children.

Findings such as these could have implications for pediatric practice and clinical care. Pediatricians and pediatric clinics have been included as important agents in the obesity-prevention effort and their role has been stated to identify children on the path to obesity and to incorporate prevention efforts to reduce high-risk dietary and sedentary activity behaviors.²⁹ Despite this, many pediatricians cite insufficient time as a barrier to assessing lifestyle behaviors.^30,31 With the limited time that pediatricians and clinicians have, assessing and screening regular bedtime in children using validated items such as the ones in our study could serve as a proxy for household rules that are associated with obesity-related behaviors.

This study does have some limitations. The cross-sectional analysis is exploratory, hypotheses generating, and prevents causal inferences between regular weekday bedtime and health-related behaviors and weight status. However, the sample in which the associations were examined was geographically and ethnically diverse and large. Survey data were obtained from parental self-report, which could result in potential recall bias, underreporting and social desirability bias. Although data were obtained from self-report, survey items have been assessed for validity and reliability among this study population.^19–23 Another limitation is that the findings are from a convenience sample, which may limit the generalizability. Bedtime routine was assessed using only one variable in this study, which is a potential limitation because other factors such as sleep duration are not considered in this study. However, we believe that this provides additional insight whether a regular bedtime exists and how it relates to obesity and other dietary behaviors which remains understudied in low-income, ethnically diverse populations. Future studies should consider additional factors such as duration, variation between weekdays and weekends, and timing of putting the child to bed.

Conclusion

Having a regular weekday bedtime may be associated with lower weight status and several healthy behaviors in children. Future research should focus on understanding these relationships longitudinally to assess causality and if these relationships persist in adolescents and young adults. Future studies could also examine how multiple behaviors when clustered together can affect weight status.

Ethics Approval and Consent to Participate

Footnotes

Funding Information

This research was supported by cooperative agreement RFA-DP-11-007 from the CDC. Additional support was provided by the Michael and Susan Dell Foundation through the Michael & Susan Dell Center for Healthy Living. This work is a publication of the USDA (USDA/ARS) Children's Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, Texas, and had been funded, in part, with federal funds from the USDA/ARS under Cooperative Agreement No. 58-6250-0-008.

Author Disclosure Statement

No competing financial interests exist.

References

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.

Miller

, Lumeng

, LeBourgeois

. Sleep patterns and obesity in childhood. Curr Opin Endocrinol Diabetes Obes, 2015; 22:41–47.

, Gong

, Zou

, et al. Short sleep duration and obesity among children: A systematic review and meta-analysis of prospective studies. Obes Res Clin Pract, 2017; 11:140–150.

Miller

, Kruisbrink

, Wallace

, et al. Sleep duration and incidence of obesity in infants, children, and adolescents: A systematic review and meta-analysis of prospective studies. Sleep, 2018; 41:zsy018.

, Zhang

, Huang

, et al. Sleep duration and obesity in children: A systematic review and meta-analysis of prospective cohort studies. J Paediatr Child Health, 2017; 53:378–385.

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.

Anderson

, Andridge

, Whitaker

. Bedtime in preschool-aged children and risk for adolescent obesity. J Pediatr, 2016; 176:17–22.

Hayes

, Balantekin

, Altman

, et al. Sleep patterns and quality are associated with severity of obesity and weight-related behaviors in adolescents with overweight and obesity. Child Obes, 2018; 14:11–17.

Kjeldsen

, Hjorth

, Andersen

, et al. Short sleep duration and large variability in sleep duration are independently associated with dietary risk factors for obesity in Danish school children. Int J Obes, 2014; 38:32.

10.

Golley

, Maher

, Matricciani

, et al. Sleep duration or bedtime? Exploring the association between sleep timing behaviour, diet and BMI in children and adolescents. Int J Obes, 2013; 37:546.

11.

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, 2011; 35:1308.

12.

Olds

, Maher

, Matricciani

. Sleep duration or bedtime? Exploring the relationship between sleep habits and weight status and activity patterns. Sleep, 2011; 34:1299–1307.

13.

Gong

, Li

, Zhang

, et al. Associations between sleep duration and physical activity and dietary behaviors in Chinese adolescents: Results from the Youth Behavioral Risk Factor Surveys of 2015. Sleep Med, 2017; 37:168–173.

14.

Mindell

, Williamson

. Benefits of a bedtime routine in young children: Sleep, development, and beyond. Sleep Medicine Reviews, 2018; 40:93–108.

15.

Hoelscher

, Butte

, Barlow

, et al. Incorporating primary and secondary prevention approaches to address childhood obesity prevention and treatment in a low-income, ethnically diverse population: Study design and demographic data from the Texas Childhood Obesity Research Demonstration (TX CORD) study. Child Obes, 2015; 11:71–91.

16.

Oluyomi

, Byars

, Byrd-Williams

, et al. The utility of geographical information systems (GIS) in systems-oriented obesity intervention projects: The selection of comparable study sites for a quasi-experimental intervention design—TX CORD. Child Obes, 2015; 11:58–70.

17.

Kuczmarski

, Ogden

, Grummer-Strawn

, et al. CDC growth charts: United States. Adv Data, 2000;:1–27.

18.

Freedman

, Berenson

. Tracking of BMI z scores for severe obesity. Pediatrics, 2017; 140:e20171072.

19.

Hoelscher

, Day

, Kelder

, et al. Reproducibility and validity of the secondary level School-Based Nutrition Monitoring student questionnaire. J Am Diet Assoc, 2003; 103:186–194.

20.

Penkilo

, George

, Hoelscher

. Reproducibility of the School-based Nutrition Monitoring Questionnaire among Fourth-grade Students in Texas. J Nutr Educ Behav, 2008; 40:20–27.

21.

Thiagarajah

, Fly

, Hoelscher

, et al. Validating the Food Behavior Questions from the Elementary School SPAN Questionnaire. J Nutr Educ Behav, 2008; 40:305–310.

22.

O'connor

, Lee

, Mehta

, et al. Childhood obesity research demonstration project: Cross-site evaluation methods. Child Obes, 2015; 11:92–103.

23.

Ranjit

, Wilkinson

, Lytle

, et al. Socioeconomic inequalities in children's diet: The role of the home food environment. Int J Behav Nutr Phys Act, 2015; 12:S4.

24.

US Department of Health and Human Services. US Department of Agriculture. 2015–2020 Dietary Guidelines for Americans. December 2015. 2019.

25.

US Department of Health and Human Services. 2011–2012 Data documentation, codebook, and frequencies: Demographic variables and sample weights (DEMO_G). National Health and Nutrition Examination Survey, 2013:2011–2012.

26.

Chaput

, Després

, Bouchard

, et al. The association between short sleep duration and weight gain is dependent on disinhibited eating behavior in adults. Sleep, 2011; 34:1291–1297.

27.

Anderson

, Whitaker

. Household routines and obesity in US preschool-aged children. Pediatrics, 2010; 125:420–428.

28.

Hale

, Berger

, LeBourgeois

, et al. Social and demographic predictors of preschoolers' bedtime routines. J Dev Behav Pediatr, 2009; 30:394–402.

29.

Daniels

, Hassink

, Committee on

Nutrition

. The role of the pediatrician in primary prevention of obesity. Pediatrics, 2015; 136:e275–e292.

30.

Nelson

, Vos

, Walsh

, et al. Weight management-related assessment and counseling by primary care providers in an area of high childhood obesity prevalence: Current practices and areas of opportunity. Child Obes, 2015; 11:194–201.

31.

Kolagotla

, Adams

. Ambulatory management of childhood obesity. Obes Res, 2004; 12:275–283.