Abstract
Background
We aimed to evaluate if there is association between hours of sleep and the risk of obesity among children and whether this association differs by sex.
Methods
A secondary data analysis, using information of the Young Lives study, was conducted. The outcome was obesity, based on the body mass index for age z-score; the exposure was child’s sleep duration (reported by parents) categorized using the National Sleep Foundation guidelines, and as a numerical variable. Baseline and three follow-ups information were used to evaluate association, reporting relative risks (RR) and 95% confidence intervals (95%CI), as well as coefficients and 95%CI.
Results
Data from 1949 children, baseline mean age 4.3 (SD: 0.3) and 962 (49.5%) females, was analyzed. Short sleep duration was present in 26.0% (95%CI: 24.0%; 28.0%) at baseline. After 9.6 years of follow-up, the incidence of obesity was 0.83 (95%CI: 0.70; 0.98) per 100 person-years at risk. In multivariable model (n=1579), there was no association between short sleep duration and obesity in the whole sample (p=0.13); but the risk of obesity was lower among girls (n=816; RR=0.45; 95%CI: 0.21; 0.96; p=0.03) compared to boys (n= 763; RR = 1.43; 95%CI: 0.95; 2.14; p=0.09). On the other hand, each additional hour of sleep was associated with an increase of boy’s BMI mean (0.05; 95%CI: 0.02; 0.08; p<0.001), but not among girls (-0.02; 95%CI: - 0.05; 0.01; p=0.11).
Conclusions
Our results evidenced a lower risk of obesity due to short sleep duration in girls, but not in boys. Each additional hour of sleep was associated with an increase of body mass index in boys but not in girls. Strategies are needed to guarantee adequate sleep duration in Peruvian children.
Keywords: obesity, sleep, sex, risk, longitudinal study
Introduction
Obesity is fast increasing worldwide among children and adolescents, reaching a plateau in high-income countries, but accelerating in low- and middle-income countries.1 In Latin America, there is a double burden of undernutrition and obesity among children,2 but rates of overweight and obesity continue to rise.3 Trends in Peru are not different; thus, among children aged between 5 and 9 years, the proportion of overweight and obesity has increased from 12.1% and 7.3% in 2008 to 18.3% and 11.1% in 2012-2013, respectively;4 whereas in adolescents between 10 and 19 years old, these numbers were 13.8% and 4.5% for overweight and obesity in 2008, and 17.5% and 6.7% in 2012-2013, respectively.
Several factors have been associated with childhood obesity, mainly a result of energy-dense food consumption and the adoption of sedentary lifestyle.2 Recently, sleep duration and its potential impact on obesity among children has been the focus of systematic reviews and meta-analysis.5–9 According to the most recent systematic review analyzing 42 prospective studies, there was a clear relationship between short sleep duration and the risk of developing overweight in infancy, early childhood, middle childhood and adolescence;8 but all of the included studies, except one from Brazil, were from high income countries. Moreover, limited evidence is available regarding the differential effect of sex on the association between sleep duration and the risk of obesity.5,6,8 As there are differences in prevalence of obesity among boys and girls in Peru,10 this leaves room to further study this association by sex, where other socio-economic features may determine sleep duration.
As low- and middle-income countries are fast undergoing nutrition transition, there is need of conducting epidemiological studies to assess the relationship between sleep duration and obesity in these countries. Therefore, using a prospective cohort study, this study aimed to assess whether there is association between short sleep duration and the risk of obesity among Peruvian children. In addition, we evaluated whether child’s sex was an effect modifier of the association of interest.
Methods
Study design
This is a secondary analysis using information of the younger cohort of children recruited in the Young Lives study, a longitudinal ongoing prospective cohort, established in 2002 in four different developing countries (Ethiopia, India, Peru and Vietnam).11 Currently, the Young Lives study has five assessment rounds, including a baseline and four follow-up evaluations.
Study participants
The Young Lives study comprises two different cohorts: the younger cohort recruited 2052 children aged between 6 and 18 months, whereas the older cohort included 1000 children aged between 7 and 8 years.12 For the present analysis, we used data from the second (2006-07), third (2009-10), fourth (2013-14), and fifth (2016-17) rounds of the younger cohort in Peru as data about sleep duration was available on those evaluations. Thus, data of children aged 4 to 5 years in the second round were considered our baseline, whereas information from the third, fourth and fifth rounds was included as follow-up assessments. Children with incomplete information in the variables of interest (e.g., sleep duration, body mass index, age and sex) were excluded from the analyses.
Sampling
The sampling strategy for the Peruvian cohort has been published elsewhere.13 Briefly, a sentinel site sampling strategy was used based on a multistage, cluster stratified, random sampling technique. The initial sample frame was conducted at the district level selecting 20 sentinel sites from a total of 1,818 districts available. The top 5% richest districts were not included as the aim was to oversample poor areas.
Then, maps of census tracts, comprising block of houses or set of houses, were utilized to randomly select one census tract in each district using a random number table. At last, all households in any given block or set of houses were visited to identify one household with at least one child accomplishing the inclusion criteria for study purposes. Different block or set of houses were approached until the total eligible households were completed. Three different teams, including fieldworkers, a data-entry clerk and supervisors, were responsible for six or seven sentinel sites.
Study variables
The outcomes of interest were obesity, defined according to the body mass index (BMI) z-score.14 Cut-offs for obesity were based on standard definitions using BMI-for-age z-score (i.e. ≥ 2 standard deviations). In addition, BMI-for-age z-score, as continuous variable, was also evaluated to determine changes over time using the information available from all the four follow-up rounds.
The exposure of interest was the parents’ report of the sleep duration of their child evaluated using the question: “How many hours does the child (NAME) sleep on a typical night?” For analysis purposes, this variable was categorized at baseline according to the age-specific National Sleep Foundation15 and split into two groups: recommended sleep duration (10 – 13 hours) vs. short sleep duration (<10 hours); long sleepers (>13 hours) were not included in incidence analysis as the sample size was very small. Besides, sleep duration, in hours, was also used as continuous variable in each of the assessments.
Other variables included in the analyses as potential confounders or effect modifiers and evaluated at baseline were: sex (boy or girl), age (<4 years or ≥4 years), socioeconomic status, based on a wealth index created using household assets and split in tertiles, household location (urban or rural), maternal and paternal education, based on years of education (<7 years, 7+ years), number of meals the child had the previous day (up to 5 times or >5 times per day, assuming three main meals and two snacks), physical activity, based on self-report of the number of days the child perform at least 1 hour per day of physical activity or exercise (<7 days or 7 days), and maternal BMI, split according to traditional guidelines (normal or overweight/obese).
Data analysis
Statistical analyses were performed using STATA 13 for Windows (StataCorp, College Station, TX, US). Initially, the description of the characteristics of the study population was tabulated according to recommended sleep duration definition. The prevalence and 95% confidence intervals (95% CI) of sleep duration were also estimated. Then, the incidence of obesity was estimated and reported per 100 person-years of follow-up, after excluding cases of obesity at baseline.
Crude and adjusted Poisson regression models, with link log and robust standard errors, were used to estimate the strength of the association between variables of interest (i.e. sleep duration and obesity), reporting relative risk (RR) and 95% CI. On the other hand, differences in BMI-for-age z-score, in standard deviations, during follow-up rounds and according to sleep duration (in hours), were assessed. Crude and adjusted linear mixed model with random intercepts, including three levels (assessments as level 1, subjects as level 2, and sentinel site as level 3), were fitted. Regression models were presented as coefficients and their respective 95% CI. Finally, sex was assessed as potential effect modifier of the association of interest using the likelihood ratio test.
Ethics
The Young Lives study was originally approved by the Ethics Committee Social Science Division, University of Oxford, UK, in 2006. In Peru, the approval was granted by the Research Ethics Committee of the Instituto de Investigacion Nutricional in Lima. The present secondary analysis was approved by the Ethical Committee at the Universidad Peruana de Ciencias Aplicadas (UPC), in Lima, Peru.
Results
Baseline characteristics of the study population
A total of 2052 children were originally enrolled in the Young Lives younger cohort. Of them, 103 (5.0%) were lost to follow-up, and then, 1949 were evaluated in the second round (Figure 1) and included in the baseline analysis, mean age was 4.3 (SD: 0.3) years and 962 (49.5%) were females. Based on sleep duration, 506 (26.0%; 95% CI: 24.0%; 28.0%) had short sleep duration, whereas only 4 (0.2%; 95% CI: 0.0%; 0.5%) were classified as long sleepers. Data from these latter four children were excluded, and thus, only 1945 records were further analyzed. The characteristics of the study population according to sleep duration are shown in Table 1. Of note, older age (p<0.001), higher socioeconomic status (p<0.001), urban household location (p<0.001), greater maternal (p=0.001) and greater paternal (p=0.004) education were associated with short sleep duration.
Figure 1. Flowchart of participants of the Young Lives younger cohort.
Table 1. Baseline characteristics of the study population according to sleep duration.
| Short N = 506 | Recommended N = 1439 | ||
|---|---|---|---|
| Age | |||
| Mean (SD) | 4.33 (0.26) | 4.38 (0.26) | 4.31 (0.26) |
| Sex | |||
| Boys | 983 (50.5) | 259 (51.2) | 724 (50.3) |
| Girls | 962 (49.5) | 247 (48.8) | 715 (49.7) |
| Socioeconomic status | |||
| Low | 643 (33.0) | 144 (28.5) | 499 (34.7) |
| Middle | 653 (33.6) | 144 (28.5) | 509 (35.4) |
| High | 649 (33.4) | 218 (43.0) | 431 (29.9) |
| Household location | |||
| Rural | 616 (31.7) | 114 (22.5) | 502 (34.9) |
| Urban | 1329 (68.3) | 392 (77.5) | 937 (65.1) |
| Maternal education | |||
| < 7 years | 862 (44.5) | 187 (37.0) | 675 (47.2) |
| 7+ years | 1074 (55.5) | 318 (63.0) | 756 (52.8) |
| Paternal education | |||
| < 7 years | 641 (33.0) | 137 (27.1) | 504 (35.0) |
| 7+ years | 1304 (67.0) | 369 (72.9) | 935 (65.0) |
| Number of meals the previous day | |||
| Up to 5 times/day | 1456 (75.1) | 383 (75.8) | 1073 (74.8) |
| >5 times/day | 483 (24.9) | 122 (24.2) | 361 (25.2) |
| Last week, physical activity (days) | |||
| < 7 days | 1261 (66.8) | 325 (66.7) | 936 (66.9) |
| 7 days | 626 (33.2) | 162 (33.3) | 464 (33.1) |
| Maternal BMI | |||
| Normal | 827 (44.7) | 214 (44.4) | 613 (44.8) |
| Overweight/Obese | 1023 (55.3) | 268 (55.6) | 755 (55.2) |
Some variables may not add the total due to missing values.
Incidence of obesity and related factors
After excluding 152 cases with obesity at baseline, a total of 1793 children were followed-up for 9.6 (SD: 0.3) years, with a total of 16,169.4 person-years at risk. A total 134 children developed obesity, with an incidence of 0.83 (95% CI: 0.70; 0.98) per 100 person-years at risk. Table 2 shows the incidence of obesity by baseline characteristics of the study population. Noteworthy, older age, higher socioeconomic status, greater maternal and greater paternal education, urban household location, and greater maternal BMI at baseline were associated with increasing incidence of obesity; whereas girls and those children with 7 days of physical activity had lower risk of obesity.
Table 2. Incidence (per 1000 person-years) of obesity by characteristics of the study population.
| Incidence per 100 person-years (95% CI) | Crude model RR (95% CI) | |
|---|---|---|
| Age | ||
| <4 years | 0.18 (0.21; 0.69) | 1 (Reference) |
| 4+ years | 0.97 (0.97; 1.33) | 5.45 (2.25; 13.21) |
| Sex | ||
| Boys | 1.08 (0.88; 1.33) | 1 (Reference) |
| Girls | 0.59 (0.45; 0.78) | 0.55 (0.39; 0.77) |
| Socioeconomic status | ||
| Low | 0.23 (0.13; 0.40) | 1 (Reference) |
| Middle | 0.84 (0.63; 1.11) | 3.62 (1.98; 6.63) |
| High | 1.51 (1.20; 1.90) | 6.56 (3.68; 11.70) |
| Household location | ||
| Rural | 0.22 (0.13; 0.39) | 1 (Reference) |
| Urban | 1.14 (0.95; 1.36) | 5.16 (2.89; 9.26) |
| Maternal education | ||
| <7 years | 0.44 (0.31; 0.62) | 1 (Reference) |
| 7+ years | 1.18 (0.97; 1.44) | 2.70 (1.84; 3.95) |
| Paternal education | ||
| <7 years | 0.49 (0.33; 0.71) | 1 (Reference) |
| 7+ years | 1.01 (0.83; 1.22) | 2.07 (1.37; 3.12) |
| Number of meals the previous day | ||
| Up to 5 times/day | 0.81 (0.67; 0.99) | 1 (Reference) |
| >5 times/day | 0.89 (0.64; 1.24) | 1.10 (0.76; 1.59) |
| Last week, physical activity | ||
| < 7 days | 0.93 (0.77; 1.14) | 1 (Reference) |
| 7 days | 0.64 (0.46; 0.89) | 0.69 (0.47; 0.99) |
| Maternal BMI | ||
| Normal | 0.39 (0.27; 0.57) | 1 (Reference) |
| Overweight/obese | 1.23 (1.01; 1.49) | 3.13 (2.08; 4.70) |
Sleep duration and risk of obesity
Hours of sleep was on average 10.1 (SD: 1.1) hours at baseline, and this number was decreasing over time: 9.7 (SD: 0.9), 9.5 (SD: 1.0), and 8.7 (SD: 1.1) hours in the first, second and last assessment (p<0.001); however, these trends were similar by sex.
In multivariable Poisson regression model, short sleep duration was not associated with obesity (p = 0.13; Table 3). On the other hand, sex was an effect modifier of the association between sleep duration and obesity (p = 0.006); and therefore, the risk of obesity due to short sleep duration was greater among boys (RR = 1.43; 95% CI: 0.95; 2.14) than girls (RR = 0.45; 95% CI: 0.21; 0.96).
Table 3. Overall and by sex association between sleep duration and the risk of obesity: crude and adjusted models.
| Overall sample | |||
| Recommended | 0.77 (0.62; 0.94) | 1 (Reference) | 1 (Reference) |
| Not recommended | 1.01 (0.75; 1.37) | 1.31 (0.93; 1.86) | 1.00 (0.71; 1.41) |
| By sex: boys | |||
| Recommended | 0.89 (0.68; 1.17) | 1 (Reference) | 1 (Reference) |
| Not recommended | 1.60 (1.14; 2.25) | 1.79 (1.19; 2.70) | 1.43 (0.95; 2.14) |
| By sex: girls | |||
| Recommended | 0.65 (0.48; 0.88) | 1 (Reference) | 1 (Reference) |
| Not recommended | 0.43 (0.22; 0.82) | 0.66 (0.32; 1.34) | 0.45 (0.21; 0.96) |
Adjusted by age, sex, socioeconomic status, household location, maternal education, number of meals the previous day, physical activity during last week, and maternal BMI. Sex was excluded from the model in stratified analyses.
Using linear mixed models and taking into account the variation of sleep duration over time and controlling for potential confounders at baseline, there was no association between hours of sleep and children’s BMI in multivariable model (p = 0.41) in the whole sample (Table 4). However, sex was an effect modifier of the association, with greater increase of BMI mean among boys (0.05; 95% CI: 0.02 – 0.08) than girls (-0.02; 95% CI: -0.05; 0.01).
Table 4. Association between hours of sleep and changes in BMI z-score: crude and adjusted models.
| Overall sample | ||
| Hours of sleep | 0.01 (-0.01; 0.04) | 0.01 (-0.01; 0.04) |
| By sex: boys | ||
| Hours of sleep | 0.05 (0.03; 0.08) | 0.05 (0.02; 0.08) |
| By sex: girls | ||
| Hours of sleep | -0.02 (-0.05; 0.00) | -0.02 (-0.05; 0.01) |
Linear mixed models were used taking into account the variation of hours of sleep over time.
Adjusted by age, sex, socioeconomic status, household location, maternal education, number of meals the previous day, physical activity during last week, and maternal BMI. Sex was excluded from the model in stratified analysis.
Discussion
Main findings
Although there was no association between short sleep duration and obesity in the whole study population, our results showed a lower risk of obesity given short sleep duration in girls, but not in boys. In addition, taking into account the variation of sleep hours over time and after controlling for potential confounders, each additional hour of sleep was associated with an increase of BMI-for-age z-score among boys during the nine years of follow-up, but not in girls.
Comparison with previous studies
Different longitudinal studies16–18 and systematic reviews5,19,20 have demonstrated the association of interest shown in our analysis; however, scarce information comes from low and middle income countries. Landhuis et al used parental reports of sleep times collected at different times,16 and found that short sleep duration increased the risk for obesity at 32 years of age. Some studies, however, have used long sleep duration as the reference group to compare those with short sleep duration 5 or did not take into account the change over time of sleep duration.19 In that line, our study compared only two groups, those who accomplished recommended number of hours of sleep vs. those who had lower hours of sleep based upon the 2018 National Sleep Foundation recommendations,15 and change over time of sleep duration patterns at different ages were also considered.
In the most recent systematic review,8 prospective studies were very heterogeneus and focused on different outcomes related to excess of weight, including obesity, BMI z-scores, or sex- and age-specific BMI cutoffs, with the need of assessing the relationship according to age strata, but not by child sex. Moreover, incidence of obesity was greater among boys than girls in bivariate analysis.Although not significant, our results were comparable to those from this latter systematic review but only for boys, as those identified as early childhood (aged 3 to 9 years), had 1.57 times higher risk of developing overweight or obesity. As described in literature,21 short sleep duration may increase the risk of obesity by affecting appetite control, insulin resistance, glucose homeostasis, and endothelial function. Nonetheless, reasons to find different risk association by sex are not clear. It has been described that boys with short sleep patterns are more prone to eat at irregular hours or to eat too much,22 which can increase the risk of obesity, though these hypotheses require further validation.
Our results using a hierarchichal longitudinal approach found that with every hour per day of increment of sleep duration, the BMI-for-age z-score increased 0.01 standard deviations during more than nine years of follow-up; but boys had greater increase of mean BMI z-score for each hour of sleep when compared to girls. These results are in contraposition to those reported by Ruan et al in a dose-response analysis,9 where each additional hour of sleep per day was associated with an annual reduction of 0.05 kg/m2, though a moderate heterogeneity between studies was also reported.
Finally, our results also show that a quarter of children aged between 4 and 5 years had short sleep duration. As BMI and fat mass changes related to short sleep duration have been described since as early as the age of 2 years,23 some emphasis should be done to guarantee appropriare children sleep duration.
Public health relevance and implications
Sleep duration is an important process involved in homeostasis, memory, and tissue restoration.21 Moreover, sleep has been described as an important modifiable factor for future obesity and cardiovacuslar health. Therefore, appropriate education strategies should be conducted to create parents’ awareness of sleep duration among children.
On the other hand, overweight and obesity are growing problems in low and middle income countries.3 Although many of the potential risk factors for excess of weight are related to diet patterns and physical activity levels, sleep duration should also be considered. Thus, our study emphasizes that medical staff need to ensure appropriate recommendations empowering parents, and children if possible, to improve sleep quantity and quality. As a result, some institutions, including the Office of Disease Prevention and Health Promotion in US are aware of the importance of increasing public knowledge of how sleep may improve health, productivity, wellness, and quality of life.24
Strength and limitations
To our knowledge, this is one of the few long-term longitudinal studies assessing the effect of sleep duration on body mass index and obesity in low and middle income countries. Moreover, our analysis is benefited by the use repeated measures of the exposure and the outcome. We have taken advantage of an existing prospective ongoing cohort study with four measures of the exposure and outcome over more than nine years of follow-up to assess the association of interest from childhood to early adolescence. However, this study has also limitations that should be highlighted. First, parents’ reports were used to assess sleep duration based on information of a typical night; and recall bias might arise as a concern. Nonetheless, this could have a small impact on results as a good correlation between objective and subjective sleep duration as per parental25 or children report.26 Second, the duration of naps or the season variation of sleep was not considered in calculations of sleep duration or analyses. Third, other obesity markers, such as central obesity (i.e. waist circumference), were not assessed in all the follow-ups and hence, were not used in this work. Fourth, recall bias could also be present in different confounders such as last week physical activity or number of meals the child ate the previous day. Fifth, some may argue that adjusting for sex and age could introduce overadjustment due to these variables are included in the definition of overweight and short sleep duration. However, in post-hoc analyses, when our models were run without age or sex as confounders, results were very similar (data not shown). Finally, some selection bias might arise as 5% richest districts in the sampling strategy were excluded and for instance could affect results. Moreover, in countries undergoing nutrition transition, changes in BMI are initially seen in the wealthiest individuals,27 which can have an impact in our estimates.
Conclusions
Although short sleep duration was not associated with increasing risk of obesity among children after nine years of follow-up, our results showed lower risk of obesity due to short sleep duration in girls, but not among boys. Moreover, each additional hour of sleep was associated with an increase of body mass index z-score in boys but not in girls. Short sleep duration was very common (25%) among children. Some strategies are needed to guarantee appropriate sleep duration among Peruvian children.
Financial support
AB-O is supported by a Wellcome Trust Research Training Fellowship in Public Health and Tropical Medicine (Grant number: 103994/Z/14/Z).
Footnotes
Author disclosure statement
The authors declare that no competing interests exist.
Contributor Information
Sofía I. Mercado-Gonzales, Email: u201210298@upc.edu.pe.
Antonella N. Carpio-Rodríguez, Email: u201210154@upc.edu.pe.
Rodrigo M. Carrillo-Larco, Email: Rodrigo.Carrillo@upch.pe.
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