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It is of interest to note that out of the 11 cross-sectional studies 19 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 that have reported an association between sleep duration and T2D biomarkers, only 4 studies 28 , 32 , 34 , 35 have presented results independent of adiposity and 2 studies 29 , 31 were conducted with obese children; however, in both studies short sleep duration was associated with insulin resistance independent of the level of adiposity.
For instance, Flint et al.
Javaheri et al. Similarly, Koren et al. This relationship remained after controlling for obstructive sleep apnea syndrome and level of obesity. Moreover, Koren et al. Although these two studies 30 , 31 have reported a U-shaped relationship between sleep duration and T2D biomarkers, similar to the relationship seen in adults, 11 , 12 , 13 other studies 19 , 25 , 26 , 27 , 28 , 29 , 32 , 33 , 34 , 35 in the pediatric population did not or could not report the linearity or the shape of the relationship between sleep duration and glucose homeostasis biomarkers.
A study by Tian et al. These findings are not surprising when considering that most studies, regardless of the methods or the study design used, have reported no association between sleep duration and blood glucose levels in children. Overall, these studies indicate that glucose may not be the prime marker in the association between short sleep duration and T2D in the pediatric population. A few studies in this section conveyed a different and noteworthy perspective on the relationship between sleep duration and T2D biomarkers.
De Bernardi Rodrigues et al. It is, however, difficult to compare this study with the others in this section as they did not isolate the relationship between short sleep duration and insulin resistance. Another study that stands alone in its findings is a study by Prats-Puig et al. The last observational study discussed in this section is by Matthews et al. Matthews et al. However, there are no studies on this relationship in adolescents. Additional sleep characteristics for example, architecture and quality , other than duration, have been studied. Six studies 15 , 18 , 26 , 29 , 31 , 35 out of the 21 presented in Table 1 assessed sleep characteristics other than duration and examined their associations with glucose homeostasis in the pediatric population.
In those studies, sleep quality was measured via questionnaire 18 , 26 and sleep architecture was measured by PSG. For example, PSG is considered the gold-standard measurement for sleep characteristics and the diagnostic tool for obstructive sleep apnea syndrome in the pediatric population 43 ; however, PSG studies have some limitations as they can be a poor representation of at-home sleep routine and PSG is an impractical measurement tool for prolonged measurement periods and epidemiological studies with large sample sizes.
Berentzen et al. Of note, a substantial limitation of this study, disclosed by the authors, was the time gap between questionnaire completion and the blood sample that is, up to a year , thereby possibly introducing errors that may include changes in sleep characteristics due to changes in season, in stressors and attainment of puberty, especially relevant to girls in this age group. The five other studies discussed in this section have found associations between sleep characteristics and T2D biomarkers. Sleep architecture was examined by Armitage et al.
Likewise, a study by Zhu et al. Two other studies 27 , 31 also found sleep architecture to be associated with numerous T2D biomarkers. In adults, many factors, such as sex, age, ethnicity, sleep-disordered breathing, adiposity and smoking contribute to the variability in sleep architecture. Overall, observational studies have provided valuable insights into the association between sleep and T2D in children and adolescents. Many studies in children and adolescents, discussed in this review, have reported a relationship between poor sleep duration and insulin resistance.
Yet, the shape of the relationship remains unclear in the pediatric population. A more linear or J-shaped relationship rather than U-shaped may be plausible in this population and could be explained by the fact that kids are generally healthier and long sleep is often a marker of poor health in adults that may confound the associations reported. Sleep architecture, more precisely the suppression of slow wave sleep SWS and rapid eye movement REM sleep, has also been shown to be associated with insulin resistance.
Type 2 diabetes in children and adolescents | British Columbia Medical Journal
The role of adiposity in the relationship between sleep and T2D in the pediatric population still remains unclear. There is also evidence that plasma glucose is a secondary risk marker in the association between sleep and T2D in the pediatric population when compared with insulin resistance measurements. Given the mixed results, in the presented cross-sectional studies it would be advantageous to investigate the association between inadequate sleep and T2D biomarkers in children and adolescents in a prospective manner in order to better understand the chronic effect of sleep duration on insulin resistance in the pediatric population.
Although, to our knowledge, no such studies exist in the pediatric population, Shan et al. Only two experimental studies have examined the effects of sleep restriction or disruption on glucose homeostasis in children and adolescents Table 2. The crossover study by Klingenberg et al.
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However, the similar amount of SWS in both conditions came at the substantial loss of REM sleep duration in the sleep-restricted condition. Furthermore, healthy adolescents may be less prone to insulin resistance based on acute SWS disruption than young adults. However, disregarding SWS disruption as a potential T2D risk factor in the pediatric population may be hasty in a context of preventive medicine.
Collectively, it appears evident that more experimental studies are needed in children and adolescents to better understand the effects of sleep restriction and fragmentation on T2D risk and the associated mechanisms. Studies in adults along with the contemporary emergence of evidence supporting an association between sleep deprivation and TD2 in children and adolescents has helped to partially elucidate the biological pathways.
Inadequate sleep as a contributor to type 2 diabetes in children and adolescents
It is known that sleep in humans is a refractory period for the stress hormones cortisol, norepinephrine and epinephrine. The hypothalamic—pituitary—adrenal axis downregulates these stress hormones at night during sleep; however, if sleep is insufficient it results in higher cortisol levels during the day.
In adults, an increased exposure to cortisol due to short sleep duration contributes to increased fat accumulation in the visceral region, 49 which may be one reasonable explanation for the link between insufficient sleep, adiposity level and insulin resistance. Inadequate sleep is also thought to be a stressor for the autonomic nervous system by increasing the activity of the sympathetic nervous system. Although the hypothalamic—pituitary—adrenal axis downregulates stress hormones while we sleep, leptin an anorexigenic hormone is upregulated by adipocytes.
The inhibition of leptin leads to an increase in hunger and a decrease in satiety. These effects can lead to an increase in energy intake and weight gain over time. The pathway between insufficient sleep and T2D biomarkers through the variation of neuroendocrine and metabolic hormones is presented in Figure 1.
Some other proposed mechanisms that link insufficient sleep to T2D biomarkers in adults include pro-inflammatory activity and increased ghrelin levels. Proposed pathways that link inadequate sleep with T2D in the pediatric population. Note: The full arrows represent directional association between the components, while the dashed line refers to the possible association, based on the limited observational evidence, between inadequate sleep and T2D in children and adolescents.
Arora and Taheri 51 recently reviewed the evidence on the efficacy of sleep improvement programs and their potential influence upon addressing obesity and metabolic disturbances. Collectively, the evidence in this field is scarce and much needs to be carried out on how best to improve sleep habits of children and adolescents, and whether such improvements translate into better glucose homeostasis outcomes. Of the 12 studies included in their review, 7 reported some positive sleep behavior changes postintervention. This is certainly an important area to investigate in future studies.
In adults, Leproult et al. Whether similar effects can be observed in the pediatric population remains to be seen. However, recent findings are encouraging and demonstrate that intervening on sleep duration in the pediatric population is possible and can lead to improvements in appetite control and body weight regulation. For example, Hart et al. Tan et al. Future studies should go beyond energy balance and weight loss and determine whether such sleep intervention programs also improve metabolic function, such as insulin sensitivity.
Before embarking in large randomized controlled trials to test the efficacy of sleep improvement programs in the pediatric population, further pilot studies are needed. Programs that apply an evidence-based psychological theory of behavior change for example, cognitive behavioral therapy have shown promise. Overall, improving sleep in the pediatric population is not an easy task especially in teenagers , and interventions should be individualized to maximize success. Until recently, T2D was rarely diagnosed in the pediatric population as evidenced by its previously popular name of adult-onset diabetes.
The pervasiveness of T2D in children and adolescents is increasing and this trend is not solely seen in America but worldwide. Sleep has an important role in the primary and secondary prevention of numerous cardiovascular diseases and metabolic conditions, including T2D. A multidisciplinary health-care approach with regular follow-ups has been shown to be the most successful at improving glycemic control in adults with T2D. A multidisciplinary approach is contingent on many factors, such as resource availability, location, expertise and subsidized programs.
We previously published an example of simple and quick questions that can be used to assess sleep as a vital health indicator. Although it is no easy task to get children and adolescents to adhere to recommendations, there is no harm in recommending more sleep and solutions should be individualized to the family by addressing root causes of the problem and finding feasible solutions. Some sleep duration guidelines do exist to help evaluate and recommend proper sleep duration. These h movement guidelines are the first in the world to include sleep recommendations alongside other movement behaviors.
The sleep duration recommendations are in line with the ones stipulated by the National Sleep Foundation. These new Canadian guidelines are a step in the right direction when it comes to repositioning efforts to include sleep as a modifiable risk factor and a vital health indicator that is equally important as physical activity for overall health and well-being. A holistic approach may be a more realistic way of tackling a problem as complex as T2D in children and adolescents as the reductionist approach of addressing only physical activity and nutrition has yielded no clear long-term benefits for the increasing rates of T2D diagnosis.
In summary, notwithstanding the fairly limited evidence in this population, all sleep characteristics appear to provide insights and are worth measuring to gain a better understanding of the association between sleep and glucose homeostasis in children and adolescents. Likewise, observational evidence tends to suggest that short sleep duration and poor sleep quality are associated with insulin resistance in children and adolescents.
Furthermore, sleep architecture namely SWS and REM sleep appears to have relevance when it comes to glucose homeostasis in the pediatric population.