To assess the relationship between short sleep duration and obesity-related variables in children involved in the ‘Québec en Forme’ Project.
A total of 422 children (211 boys and 211 girls) aged between 5 and 10 years from primary schools in the City of Trois-Rivières (Québec) were selected to participate in this study.
Body weight, height and waist circumference were measured. The children were classified as normal, underweight, overweight or obese, according to body mass index (BMI) per age. An exhaustive questionnaire was administered by telephone to the parents of children.
The percentage of overweight/obesity was 20.0% in boys and 24.0% in girls. When compared to children reporting 12–13 h of sleep per day, the adjusted odds ratio for childhood overweight/obesity was 1.42 (95% confidence interval 1.09–1.98) for those with 10.5–11.5 h of sleep and 3.45 (2.61–4.67) for those with 8–10 h of sleep after adjustment for age, sex, and other risk factors. Parental obesity, low parental educational level, low total family income, long hours of TV watching, playing videogames or computer utilization, absence of breastfeeding and physical inactivity were also significantly associated with childhood overweight/obesity. In addition, we observed a significant negative association adjusted for age between sleep duration and body weight (−0.33, P<0.01), BMI (−0.12, P<0.01) and waist circumference (−0.24, P<0.01) in boys.
An inverse association was observed between sleep duration and the risk to develop childhood overweight/obesity. Longitudinal research will be required to confirm a potential link of causality between these variables.
The increase in childhood obesity is a major public health concern in developed countries, and the prevalence has been increasing worldwide over the last decades.1, 2 Potential causes of obesity in children may be divided into genetic, such as parental obesity,3 and lifestyle factors, such as sedentary behavior and a high intake of energy-dense foods.4, 5, 6 A large prospective cohort study of more than 8000 children conducted in United Kingdom recently found eight factors in early life associated with an increased risk for obesity in childhood.7 In addition, several studies have reported a higher probability for obese children to remain obese in adulthood.8, 9, 10, 11 Owing to the fact that obesity in adults is difficult to treat,12 the prevention of obesity in childhood is highly desirable.
Because the prevalence of childhood obesity is increasing at an alarming rate, many researchers have focused on lifestyle factors in the development of obesity in order to better understand the causes of this epidemic for an optimal management. In this regard, sleep duration seems to be important in the regulation of body weight and metabolism by the modulation of key hormones such as leptin and ghrelin, as suggested by recent findings.13, 14 Accordingly, because sleep duration is a potentially modifiable risk factor, these findings might have important clinical implications for the prevention and treatment of obesity.
To our knowledge, only a small number of studies have examined the relationship between short sleeping hours and childhood obesity15, 16, 17, 18 and we believe that the recent findings of Spiegel et al.13 will renew the interest for this environmental variable in the field of obesity management. Thus, the primary aim of this study was to evaluate the relationship between sleeping hours and variations in body weight by an analysis of data obtained in the pilot study of the ‘Québec en Forme’ (QEF) Project. In addition, we also focused on the quantification of the risk to be overweight/obese in the short sleeper child.
Materials and methods
Overview of the project
The QEF Project is based on a new strategy to promote a healthy lifestyle by specifically focusing on sports and physical activity participation in children of low socio-economic status. This project is a partnership between the Lucie and André Chagnon Foundation and the Government of the Province of Québec (Canada). Its mission is to improve health and global autonomy of children and family by supporting the implementation of a long-term program for sports and physical activities by local community. Furthermore, the QEF objectives are to favor a better social integration, to improve physical health and academic performance, to establish partnerships and to influence the norms, practices and policies in favor of the adoption of a healthy and active lifestyle.
The QEF model is a community network called Local Action Committee (LAC) composed by local community health centers, community and recreational centers, municipalities and schools. There are several LACs per region, which are independently responsible for programming sports and physical activities.
The pilot study of the QEF Project was launched in the City of Trois-Rivières on September 2002 with four LACs involving 14 primary schools. The first evaluation was conducted in 1140 children attending these schools. Further details about this cohort are described in the next section.
The evaluation was performed between January and March 2003 in 1140 Caucasian children (591 boys and 549 girls) of first, second and fourth grade of the primary school program. Among these children, 701 were chosen at random and an exhaustive questionnaire was administered by telephone to the parents in order to better document the environment of the child. Because of the missing data in 279 subjects, the remaining 422 children (211 boys and 211 girls) represented the study population. Each subject and his/her parents gave their written consent to participate in this study, which received approval of the Sainte-Justine Hospital Ethics Committee in Montreal.
The questionnaire was administered by telephone to the parents of children chosen at random and the two questions on sleep were: ‘When does your child usually go to bed during the week?’. There were 10 options ranging from before 1900 to after 2300 and the second question was ‘When does your child usually get up in the morning during the week?’, with the seven options ranging from before 0600 to after 0830. When the bedtime or time for getting up had been given as the interval, for example, between 0700 and 0730, the time was set at the upper interval (e.g., 0730 here). If the time had been given as before or after an hour, the time was set as this specific hour (e.g., before 0600 was set as 0600). The sleeping time was calculated by the difference between bedtime and time for getting up. In addition, we considered the following potential risk factors for overweight/obesity in children:
Parental obesity: metric self-reporting, height in cm and weight in kg (body mass index (BMI)⩾30 kg/m2in either parent).
Parental education: highest level attained by either parent (ordinal).
Total family income: categorized into five groups ranging from <20 000$ to 80 000$ or more.
Single parenthood: dichotomous (yes/no).
Frequency of taking breakfast: rarely, sometimes, almost daily and daily.
Watching TV, playing videogames or computer utilization: all three were asked for by hours per day.
Frequency of practicing sports activities apart from school: categorized into five groups ranging from never to every day.
Breastfed: categorized into nine groups ranging from never to more than 16 months.
Anthropometric measurements and definition of obesity
Anthropometric measurements of children were undertaken in a context of group evaluation in physical education class by trained kinesiologists. The height and weight of children were measured with physical education clothing (shorts and T-shirts), but with shoes removed. Height was measured to the nearest 0.1 cm using a stadiometer, and weight was measured to the nearest 0.1 kg using a standard dual reading scale. The height and weight of parents were self-reported in the questionnaire. Body mass index was defined as weight/height2, and expressed in kg/m2 units. Waist circumference was measured at the umbilicus level over the T-shirt.
We used BMI as the index of obesity in childhood. Although there is no established BMI cutoff point for childhood obesity, age- and sex-specific cutoff points linked to adult cutoff points proposed by Cole et al.19 were used, and in cases with a BMI for age below the 5th percentile, the children were considered underweight.20 Parental overweight and obesity were defined as a BMI of 25 and 30 kg/m2, respectively, based on WHO criteria.21
Mean, standard deviation (s.d.) and frequency (%) were calculated for the statistical analysis. Student's t-test was used to compare the mean results and χ2 for comparison of frequencies between genders in the distribution of normal, underweight, overweight and obese children based on BMI/age. Logistic regression analysis was performed to evaluate the strength of the relationship between potential risk factors and childhood overweight/obesity. Multivariate logistic regression analysis was performed separately by gender, and the odds ratios (ORs) were adjusted for age and parental obesity. In multivariate analysis for both sexes combined, ORs were adjusted for age, sex and parental obesity. To control for potential risk factors for overweight/obesity in children, we also evaluated the relationship between short sleeping hours and overweight/obesity after adjustment for age, sex, parental obesity and other potential risk factors. Pearson's correlation coefficients controlling for age were calculated to quantify the associations between sleep duration and anthropometric variables in each gender. With regard to the correlation between BMI and sleeping hours, z scores were used. Indeed, even though the points were adjusted for age, the figure could be misleading because using absolute BMI in this age group is problematic. In addition, because the sampling method used a cluster design (four LACs involving 14 primary schools), we adjusted for clustering in the analyses. Data are given as means±s.d. unless otherwise noted. Statistical significance was established at a P-value<0.05. All statistical analyses were performed using the SAS statistical package (SAS Institute, Cary, NC, USA).
The mean age of children was 6.6±1.6 years for boys and 6.5±1.5 years for girls. Table 1 shows the frequency of healthy, underweight, overweight and obese children. The percentage of overweight/obesity was 20.0 and 24.0% in boys and girls, respectively.
The relationships between parental obesity and other potential risk factors known to interfere with childhood overweight/obesity are presented in Table 2. Parental obesity, low parental educational level, low total family income, long hours of TV watching, playing videogames or computer utilization, absence of breastfeeding and physical inactivity were significantly associated with childhood overweight/obesity.
Table 3 presents the relationship between short sleeping hours and overweight/obesity after adjustment for potential risk factors. In the model using children with 12–13 h of sleep as a reference, the adjusted odds ratio was 1.42 (1.09–1.98) for those with 10.5–11.5 h of sleep and 3.45 (2.61–4.67) for those with 8–10 h of sleep. Although age and sex are known to have the potential to interact with several variables affecting childhood overweight/obesity,22, 23 multiplicative interactions between age, sex and all other potential risk factors did not add to the relationship between risk factors and overweight/obesity in the model.
Finally, Figure 1 shows the correlations adjusted for age between sleep duration and body weight, BMI and waist circumference in male children. We observed a significant negative association between sleep duration and body weight (−0.33, P<0.01), BMI (−0.12, P<0.01) and waist circumference (−0.24, P<0.01). These relationships were not statistically significant in girls even though a trend was observed (P-values did not exceed 0.10), possibly caused by the more important dispersion in the scores obtained.
Many previous studies have reported that variables such as parental obesity, long TV watching and physical inactivity are associated with childhood overweight/obesity.3, 4, 5, 6, 15, 23 Our results are consistent with these studies and included many variables having the potential to influence energy balance in children. Furthermore, in agreement with previous studies,15, 16, 17, 18 we found that short sleeping hours was related to overweight/obesity. These findings are important to keep in mind because sleep duration is a potentially modifiable risk factor that could be important to consider in the prevention and treatment of obesity.
Recent evidence suggests a biological plausibility of the relationship between short sleeping hours and obesity. Indeed, it was found that short sleep duration was associated with decreased leptin levels, increased ghrelin levels and increased hunger and appetite.13, 14 In this respect, the changes observed in these two appetite regulatory hormones with sleep curtailment are provocative. If the findings prove to be reproducible and generalizable, and the hormonal changes of leptin and ghrelin owing to sleep curtailment cause changes in food intake over time, we could add sleep duration to the environmental factors that are prevalent in our society and that contribute to weight gain and obesity.
With regard to the quantification of the risk to be overweight/obese in the short sleeper child, results obtained in this study corroborate the findings observed in previous studies.15, 16, 18 Indeed, a dose–response relationship between short sleeping hours and childhood overweight/obesity is observed. In addition, it is not explained by a wide range of risk factors having the potential to influence the regulation of energy balance.
Besides sleep duration, body weight is regulated by many other factors. This study also led to the demonstration that parental, socio-economic and lifestyle factors contribute to favor a positive energy balance. Findings observed here are not surprising, with many previous studies having reported some related effects. Even though parental obesity seems to be the most significantly associated with childhood overweight/obesity among the factors entered in the model, we have to keep in mind that a multitude of factors have the potential to influence the regulation of energy balance. Therefore, in a context of preventive medicine, health professionals must consider the obesity problem in a wider context in order to be optimally managed.
Reduction in sleeping hours has become a hallmark of modern society. This later argument is well concordant with the high incidence of today's obesity. Previous data suggest that there may be an ‘ideal zone’ of sleep duration where detrimental effects of sleeping deviations could perturb energy balance.14 Nevertheless, it is somewhat paradoxical that sleeping, the most sedentary of all activities, may be associated with leanness. Although recommendations to get both a better night sleep and more exercise might superficially seem to be at odds with each other from the perspective of energy expenditure and energy balance, these simple goals may well become a part of our future approach to combating obesity.
It should also be noted that our study has several potential limitations. First, sleeping habits reported by parents were used in the analysis. As parents may report times for going to bed and rising rather than times for going to sleep and waking, reported sleeping hours may be longer than accurate sleeping hours assessed by electroencephalogram (EEG). However, the difference between time spent asleep and total recording period (the time from the start of recording at lights out to the end of the recording at rising) on EEG is small, ≈30 min in school children.24 Furthermore, the relationship between short sleeping hours and obesity may remain unchanged, because reported sleeping hours may be uniformly overestimated. Secondly, the relationship may be confounded by energy intake, which we did not measure in this study. Thirdly, obesity in children is sometimes accompanied by psychiatric and somatic problems, including obstructive sleep apnea syndrome (OSAS),25, 26 which could lead to sleep disturbances. However, the prevalence of OSAS in children is estimated to be 1–3% at a peak age of 2–5 years, and the main cause of OSAS in children is adenotonsillor hypertrophy.27 In this regard, the confounding effects of OSAS on the sleep–body weight relationship are therefore likely to be small.
In conclusion, owing to the fact that an important objective of the QEF Project is to prevent the development of obesity over the school years, our findings raise the attention on the relationship between parental, lifestyle and socio-economic factors and overweight/obesity with special reference to short sleep duration as a possible risk factor for obesity. Indeed, short sleep duration is associated with overweight/obesity in children involved in the QEF Project. Moreover, the effect of sleeping hours on overweight/obesity in children appears to be independent of other risk factors. However, longitudinal research will be required to confirm a potential link of causality.
Troiano RP, Flegal KM, Kuczmarski RJ, Campbell SM, Johnson JC . Overweight prevalence and trends for children and adolescents. The National Health and Nutrition Examination Surveys 1963–91. Arch Pediatr Adolesc Med 1995; 149: 1085–1091.
Lobstein T, Baur L, Uauy R . Obesity in children and young people: a crisis in public health. Obes Rev 2004; 5 (Suppl 1): 4–85.
Whitaker RC, Wright JA, Pepe MS, Seidel KD, Dietz WH . Predicting obesity in young adulthood from childhood and parental obesity. N Engl J Med 1997; 337: 869–873.
Guillaume M, Lapidus L, Bjorntorp P, Lambert A . Physical activity, obesity, and cardiovascular risk factors in children: The Belgian Luxembourg Child Study II. Obes Res 1997; 5: 549–556.
Anderson RE, Crespo CJ, Bartlett SJ, Cheskin LJ, Pratt M . Relationship of physical activity and television watching with body weight and level of fatness among children: results from the Third National Health and Nutritional Examination Survey. J Am Med Assoc 1998; 279: 938–942.
Maffeis C, Talamini G, Tato L . Influence of diet, physical activity and parents' obesity on children's adiposity: a four-year longitudinal study. Int J Obes Relat Metab Disord 1998; 22: 758–764.
Reilly JJ, Armstrong J, Dorosty AR, Emmett PM, Ness A, Rogers I, et al., Avon Longitudianl Study of Parents and Children Study Team. Early life risk factors for obesity in childhood: cohort study. BMJ 2005; 330: 1357–1363.
Freedman DS, Khan LK, Dietz WH, Srinivasan SR, Berenson GS . Relationship of childhood obesity to coronary heart disease risk factors in adulthood: the Bogalusa Heart Study. Pediatrics 2001; 108: 712–718.
Power C, Lake JK, Cole TJ . Body mass index and height from childhood to adulthood in the 1958 British born cohort. Am J Clin Nutr 1997; 66: 1094–1101.
Guo SS, Roche AF, Chumlea WC, Gardner JD, Siervogel RM . The predictive value of childhood body mass index values for overweight at age 35 y. Am J Clin Nutr 1994; 59: 810–819.
Serdula MK, Ivery D, Coates RJ, Freedman DS, Williamson DF, Byers T . Do obese children become obese adults? A review of the literature. Prev Med 1993; 22: 167–177.
NIH Technology Assessment Conference Panel. Consensus Development Conference, 30 March to 1 April 1992 (review). Ann Int Med 1993; 119: 764–770.
Spiegel K, Tasali E, Penev P, Van Cauter E . Brief communication: sleep curtailment in healthy young men is associated with decreased leptin levels, elevated ghrelin levels, and increased hunger and appetite. Ann Intern Med 2004; 141: 846–850.
Taheri S, Lin L, Austin D, Young T, Mignot E . Short sleep duration is associated with reduced leptin, elevated ghrelin, and increased body mass index. PLoS Med 2004; 3: e62.
Sekine M, Yamagami T, Handa K, Saito T, Nanri S, Kawaminami K et al. A dose–response relationship between short sleeping hours and childhood obesity: results of the Toyama Birth Cohort Study. Child Care Health Dev 2002; 28: 163–170.
Locard E, Marvelle N, Billette A, Miginiac M, Munoz F, Rey S . Risk factors of obesity in a five year old population: parental and environmental factors. Int J Obes Relat Metab Disord 1992; 16: 721–729.
Giugliano R, Carneiro EC . Factors associated with obesity in school children. J Pediatra 2004; 80: 17–22.
von Kries R, Toschke AM, Wurmser H, Sauerwald T, Koletzko B . Reduced risk for overweight and obesity in 5- and 6-y-old children by duration of sleep – a cross-sectional study. Int J Obes Relat Metab Disord 2002; 26: 710–716.
Cole TJ, Bellizzi MC, Flegel KM, Diets WH . Establishing a standard definition for child overweight and obesity worldwide: international survey. BMJ 2000; 320: 1240–1243.
Hammer LD, Kraemer HC, Wilson DM, Ritter PL, Dornbusch SM . Standardized percentile curves of body-mass index for children and adolescents. Am J Dis Child 1991; 145: 259–263.
World Health Organization. (1997) Obesity: preventing and managing the global epidemic. Report of a WHO Consultation presented at the World Health Organization, June 3–5. Publication WHO/NUT/NCD/98.1. WHO, Geneva, Switzerland.
Moore LL, Nyguyen VDT, Rothman KJ, Cupples LA, Ellison RC . Preschool physical activity level and change in body fatness in young children: the Framingham Children's Study. Am J Epidemiol 1995; 142: 982–988.
Berkey CS, Rockett HR, Field AE, Gillman MW, Frazier AL, Camargo Jr CA et al. Activity, dietary intake and weight change in a longitudinal study of preadolescent boys and girls. Pediatrics 2000; 105: 56–65.
Coble PA, Kupfer DJ, Taska LS, Kane J . EEG sleep of normal healthy children. Part I: findings using standard measurement methods. Sleep 1984; 7: 289–303.
Sheslow D, Hassink S, Wallace W, DeLancev E . The relationship between self-esteem and depression in obese children. Ann NY Acad Sci 1993; 699: 289–291.
Braet C, Mervielde I . Psychological aspects of childhood obesity: a controlled study in a clinical and a nonclinical sample. J Pediatr Psychol 1997; 22: 59–71.
Rosen CL . Obstructive sleep apnea syndrome (OSAS) in children: diagnostic challenges. Sleep 1996; 19: 274–277.
This study was supported by grants from the Lucie and André Chagnon Foundation and the Government of the Province of Québec.
About this article
Cite this article
Chaput, J., Brunet, M. & Tremblay, A. Relationship between short sleeping hours and childhood overweight/obesity: results from the ‘Québec en Forme’ Project. Int J Obes 30, 1080–1085 (2006). https://doi.org/10.1038/sj.ijo.0803291
- body mass index
- body weight
- waist circumference
- primary prevention
- physical activity
Pediatric Obesity (2020)
The effect of sleep duration on hemoglobin and hematocrit: observational and Mendelian randomization study
Longer sleep duration during infancy and toddlerhood predicts weight normalization among high birth weight infants
Early life socioeconomic status moderates associations between objective sleep and weight-related indicators in middle childhood
Sleep Health (2019)
Associations between commuting and well-being in the context of a compact city with a well-developed public transport system
Journal of Transport & Health (2019)