Literature DB >> 31463284

Sleep quality and insulin resistance in adolescent subjects with different circadian preference: A cross-sectional study.

Anita Rawat1, Anil Kumar Gangwar2, Sunita Tiwari2, Surya Kant3, Ravindra Kumar Garg4, Prithvi Kumar Singh5.   

Abstract

BACKGROUND: Studies have shown that alterations in the sleep cycle can predispose to several disorders. Most of the previous studies were done on the adults. Hence, the aim of the study was to see the effect of circadian disruption on the health of adolescent population.
MATERIALS AND METHODS: In this cross-sectional study, 203 subjects were enrolled. Study subjects were divided into three groups: definite evening chronotype, intermediate chronotype, and definite morning chronotype. Sleep quality was measured by Pittsburgh Sleep Quality Index (PSQI). Daytime sleepiness and chronotype were measured by Epworth Sleepiness Score and Morningness-Eveningness Questionnaire Self-Assessment version, respectively. Two hours postprandial glucose was measured after oral glucose tolerance test. Fasting blood glucose and fasting insulin were measured. Homeostasis model of assessment for insulin resistance (HOMA-IR) was calculated. Data were summarized as mean ± standard deviation. Crude odds ratios and Karl Pearson's correlation coefficient of metabolic parameters with poor sleep were calculated.
RESULTS: Statistically significant difference was found in the mean value of poor sleep quality, 2 h postprandial blood glucose level, and insulin resistance among subjects of three groups. Subjects of evening chronotype have more significant positive correlation of 2 h postprandial blood glucose level and HOMA-IR value with poor sleep quality when compared with subjects of intermediate and morning chronotypes.
CONCLUSION: Subjects with evening chronotype are more prone for development of metabolic syndrome compared with subjects of intermediate and morning chronotypes if proper health policies are not adopted for adolescents.

Entities:  

Keywords:  Daytime sleepiness; insulin resistance; morningness–eveningness; sleep quality

Year:  2019        PMID: 31463284      PMCID: PMC6691405          DOI: 10.4103/jfmpc.jfmpc_400_19

Source DB:  PubMed          Journal:  J Family Med Prim Care        ISSN: 2249-4863


Introduction

Three types of circadian typology have been described in human beings: morning (larks), evening (owls), and intermediate. Each type shows individual preferences for activity realization during a specified period of the day.[1] The evening-type individuals showed worse quality of sleep when compared with the morning and intermediate types.[23] Sleep modulates metabolic-[45] and endocrine[5]-related functions of human beings. Epidemiological and clinical studies on adults have shown that poor sleep quality and alterations in the sleep cycle can predispose to several disorders, such as impaired glucose metabolism and diabetes.[45] Therefore, healthy sleep is necessary for body functions. Since the past few years, prevalence of obesity and impaired glucose tolerance and type 2 diabetes mellitus has increased in children.[67] Studies conducted in the United States[8] and India[9] have shown that high school–aged students and adolescents do not get enough sleep, and the average total sleep duration has decreased to less than 8 h. Disrupted circadian rhythm changes sleep–wake habits that lead to poor sleep quality. Disrupted sleep–wake cycle and poor sleep quality can lead to alteration in glucose metabolism and metabolic syndrome[101112] But most of the previous studies were done on the adult and middle-aged population. Hence, the aim of the study is to see the consequences of circadian disruption and sleep quality on the health of adolescent population so that early measures can be adopted to prevent the development of metabolic syndrome in future life.

Materials and Methods

In this cross-sectional study, a total of 203 subjects were enrolled on the basis of inclusion and exclusion criteria. All study subjects were divided into three groups: group 1 (definite evening chronotype), group 2 (intermediate chronotype), and group 3 (definite morning chronotype) on the basis of morningness–eveningness score.[13] Subjects with any known sleep problem, oronasal disease, and head injury were excluded from the study. Subjects with known case of any chronic illness (such as diabetes, hypertension, and chronic respiratory disease) were also excluded from the study. Informed written consent was taken from all subjects after ethical clearance by institutional ethical committee. Anthropometric measurements such as height, weight, body mass index (BMI), and blood pressure were taken by trained nursing staff. Sleep quality and sleep duration were measured by Pittsburgh Sleep Quality Index.[14] Daytime sleepiness and chronotype were measured by Epworth Sleepiness Score[15] and Morningness-Eveningness Questionnaire Self-Assessment version,[13] respectively. Two-hour postprandial glucose was measured after oral glucose tolerance test (OGTT) with 75 g oral glucose. OGTT was performed after overnight fasting.[16] Fasting blood glucose and 2 h postprandial blood glucose were measured by glucose oxidase and peroxidase method based on commercially available kit with semi-autoanalyzer, and fasting insulin was by commercially available kit by enzyme-linked immunosorbent assay method. Homeostasis model of assessment for insulin resistance (HOMA-IR) was calculated (HOMA-IR = fasting insulin × fasting glucose/22.4).[17] The Statistical Package for Social Sciences (SPSS) (IBM SPSS Statistics, Armonk, NY, USA), version 21 was used for data analysis. Data were summarized as mean ± standard deviation, and the crude odds ratio (OR) and Karl Pearson's correlation coefficient of metabolic parameters with poor sleep quality were calculated for all the three groups.

Results

On comparison of the three groups according to circadian typology, we found that statistically significant difference was found in the mean value of BMI, poor sleep quality, short sleep duration, fasting blood glucose level, 2 h postprandial blood glucose level, insulin resistance, and daytime sleepiness among subjects of groups 1, 2, and 3. We found that group 1 subjects had higher mean value of BMI, fasting blood glucose level, 2 h postprandial blood glucose level, insulin resistance, and daytime sleepiness compared with subjects of groups 2 and 3. Similarly, we also found that group 2 subjects had higher mean value of the above parameters compared with subjects of group 3. We also observed that group 1 and 2 subjects exhibited poor sleep quality and short sleep duration compared with group 3 subjects. There were more number of subjects in group 1 (90.4%) who exhibited poor sleep quality compared with subjects of group 2 (76.16%) and group 3 (39.34%) [Table 1].
Table 1

Comparison of mean value of demographic factors, sleep quality, 2 h postprandial blood glucose level, insulin resistance, and daytime sleepiness of study subjects

Group 1 (n=73)Group 2 (n=87)Group 3 (n=43)P
Age (years)18.21±0.6718.90±0.6818.05±0.650.395
Sex
 Male47 (64.38%)57 (65.52%)27 (62.79%)0.9538
 Female26 (35.62%)30 (34.48%)16 (37.21%)
Weight (kg)64.49±8.5363.62±8.3561.95±8.300.293
Height (cm)167.27±8.17168.02±8.17168.21±8.570.793
BMI23.06±2.4522.50±2.1521.89±2.270.029*
Neck circumference (cm)37.41±2.4037.47±2.3637.30±2.580.933
Sleep quality
 Good7 (9.6%)19 (21.84%)26 (60.46%)<0.001**
 Poor66 (90.4%)68 (78.16%)17 (39.54%)
Sleep duration (h)
 ≥78 (10.99%)10 (11.5%)10 (23.25%)<0.001**
 6-715 (20.55%)16 (18.4%)25 (58.14%)
 <650 (68.5%)61 (70.1%)8 (18.6%)
OGTT
 2 h blood glucose (mg/dL)131.84±8.24124.61±9.23126.62±8.23<0.001**
HOMA
 Fasting glucose (mmol/L)5.63±0.485.40±0.555.21±0.58<0.001**
 Fasting insulin (µIU/L)11.50±5.4211.04±6.299.29±5.090.126
 HOMA-IR2.97±1.512.76±1.752.19±1.280.038*
ESS8.84±4.317.13±3.765.05±1.50<0.001**

Data are represented as mean±SD, n (%) and ratio. BMI=body mass index; OGTT=oral glucose tolerance test; HOMA-IR=homeostasis model of assessment for insulin resistance; ESS=Epworth Sleepiness Score; SD=standard deviation. **P<0.001; *P<0.05

Comparison of mean value of demographic factors, sleep quality, 2 h postprandial blood glucose level, insulin resistance, and daytime sleepiness of study subjects Data are represented as mean±SD, n (%) and ratio. BMI=body mass index; OGTT=oral glucose tolerance test; HOMA-IR=homeostasis model of assessment for insulin resistance; ESS=Epworth Sleepiness Score; SD=standard deviation. **P<0.001; *P<0.05 Crude OR of fasting blood glucose, 2 h postprandial blood glucose level, and HOMA-IR for poor sleep quality are shown in Table 2. Subjects who had high fasting blood glucose level showed significant association for poor sleep quality with an OR of 0.033 (0.01–0.11). Similarly, we found that subjects with high HOMA-IR values had significant association for poor sleep quality.
Table 2

Crude OR of fasting blood glucose, 2 h postprandial blood glucose level, and HOMA-IR for poor sleep quality

Poor sleep quality Frequency n (%)OR (CI)P
Blood glucose (fasting), mg/dL
 ≤10024 (22.64%)1-
 >10093 (95.88%)0.033 (0.01-0.11)<0.001**
Blood glucose (2 h postprandial), mg/dL
 ≤140105 (55.56%)1-
 >14012 (85.71%)1.601 (0.17-15.57)0.0658
HOMA-IR
 ≤2.521 (22.11%)1-
 >2.596 (88.89%)0.159 (0.06-0.42)<0.001**

OR=odds ratios; HOMA-IR=homeostasis model of assessment for insulin resistance; CI=confidence interval. **P<0.001

Crude OR of fasting blood glucose, 2 h postprandial blood glucose level, and HOMA-IR for poor sleep quality OR=odds ratios; HOMA-IR=homeostasis model of assessment for insulin resistance; CI=confidence interval. **P<0.001 On comparison of the three groups according to circadian typology, we found that the subjects of group 1 had more significant positive correlation of BMI, 2 h postprandial blood glucose level, fasting glucose level, fasting insulin level, and HOMA-IR value with poor sleep quality when compared with subjects of groups 2 and 3. Similarly, we also observed that group 2 subjects had significant positive correlation of BMI, 2 h postprandial blood glucose level, fasting insulin level, and HOMA-IR value with poor sleep quality compared with subjects of group 3. However, group 3 subjects showed significant correlation with BMI only [Table 3].
Table 3

Correlation of body mass index and metabolic parameters with poor sleep quality in subjects of groups 1, 2, and 3

Group 1 (Karl Pearson’s correlation coefficient)Group 2 (Karl Pearson’s correlation coefficient)Group 3 (Karl Pearson’s correlation coefficient)
BMI0.479**0.552**0.638**
OGTT
 Blood glucose (2 h)0.280*0.226*0.130
HOMA
 Fasting glucose (mmol/L)0.423**0.2220.214
 Fasting Insulin (µIU/L)0.518**0.279*0.205
 HOMA-IR0.514**0.301*0.222

BMI=body mass index; OGTT=oral glucose tolerance test; HOMA-IR=homeostasis model of assessment for insulin resistance. **Correlation is significant at the 0.01 level (two-tailed); *correlation is significant at the 0.05 level (two-tailed)

Correlation of body mass index and metabolic parameters with poor sleep quality in subjects of groups 1, 2, and 3 BMI=body mass index; OGTT=oral glucose tolerance test; HOMA-IR=homeostasis model of assessment for insulin resistance. **Correlation is significant at the 0.01 level (two-tailed); *correlation is significant at the 0.05 level (two-tailed)

Discussion

On comparison of the three groups according to circadian typology, we found that evening chronotype exhibited poor sleep quality and short sleep duration compared with morning chronotype individuals. These findings are corroborated by previous studies.[218] Poor sleep quality in the evening chronotype may be due to substance abuse like alcohol[19] and incongruity between intrinsic sleep–wake cycle and actual bedtime, because of social factors.[2021] Consistent with earlier findings, we found that evening chronotype was associated with a higher BMI, fasting blood glucose level, 2 h postprandial blood glucose level, and insulin resistance compared with intermediate and morning chronotype subjects, and the difference in the mean value of the above parameters was statistically significant among subjects of three groups.[2223] Few community-based,[10] clinic-based studies,[1112] and epidemiological studies[242526] also confirmed our findings that the subjects with evening chronotype have more significant positive correlation of BMI, 2 h postprandial blood glucose level (OGTT), fasting glucose level, fasting insulin level, and HOMA-IR value with poor sleep quality when compared with subjects of intermediate and morning chronotypes. Mechanisms that impair insulin sensitivity and glucose tolerance due to sleep curtailment include increase in the level of circulating cortisol,[2728] enhanced sympathetic activation,[28] and decreased leptin and increased ghrelin levels which affect appetite and food intake.[2930] Altered ratio of leptin and ghrelin leads to a change in BMI and insulin resistance. The present research highlighted that evening chronotype adolescents have unhealthy sleep habits and are at higher risk of development of insulin resistance in future. Our findings have public health importance for the subjects who are sleep-deprived. So, history regarding sleep habits should be asked in outpatient department (OPD) from the adolescents who are coming to the OPD for other than sleep disorders to decrease the chances of development of insulin resistance in high-risk adolescents. Sleep habits can be monitored in OPD by maintaining sleep diaries and by asking few questionnaires. It is also very necessary to promote awareness in the medical field, as well as in the society, regarding importance of circadian typology, sleep hygiene, and the negative cost of challenging our internal clock.

Conclusion

Study subjects have significant association of BMI with poor sleep quality. Although HOMA-IR is significantly associated with poor sleep quality among subjects of evening chronotype compared with subjects of intermediate and morning chronotypes. So it can be concluded that subjects with evening chronotype are more prone for development of metabolic syndrome compared with subjects of intermediate and morning chronotypes if the management of poor sleep quality is not there.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

Presentation at a meeting

This research work was presented in the 4th International Conference on Sleep Disorders (ICSD) organized by South East Asian Academy of Sleep Medicine at Midland Healthcare and Research Center, Lucknow, on 12th–18th October, 2018.
  28 in total

1.  Insufficient sleep undermines dietary efforts to reduce adiposity.

Authors:  Arlet V Nedeltcheva; Jennifer M Kilkus; Jacqueline Imperial; Dale A Schoeller; Plamen D Penev
Journal:  Ann Intern Med       Date:  2010-10-05       Impact factor: 25.391

2.  A self-assessment questionnaire to determine morningness-eveningness in human circadian rhythms.

Authors:  J A Horne; O Ostberg
Journal:  Int J Chronobiol       Date:  1976

Review 3.  Epidemiology of childhood type 2 diabetes and obesity.

Authors:  Jonathan Shaw
Journal:  Pediatr Diabetes       Date:  2007-12       Impact factor: 4.866

Review 4.  Epidemiology of type 2 diabetes in children and adolescents.

Authors:  Kristen Nadeau; Dana Dabelea
Journal:  Endocr Res       Date:  2008       Impact factor: 1.720

5.  Leptin levels are dependent on sleep duration: relationships with sympathovagal balance, carbohydrate regulation, cortisol, and thyrotropin.

Authors:  Karine Spiegel; Rachel Leproult; Mireille L'hermite-Balériaux; Georges Copinschi; Plamen D Penev; Eve Van Cauter
Journal:  J Clin Endocrinol Metab       Date:  2004-11       Impact factor: 5.958

Review 6.  Role of sleep and sleep loss in hormonal release and metabolism.

Authors:  Rachel Leproult; Eve Van Cauter
Journal:  Endocr Dev       Date:  2009-11-24

7.  Glucose intolerance and gestational diabetes risk in relation to sleep duration and snoring during pregnancy: a pilot study.

Authors:  Chunfang Qiu; Daniel Enquobahrie; Ihunnaya O Frederick; Dejene Abetew; Michelle A Williams
Journal:  BMC Womens Health       Date:  2010-05-14       Impact factor: 2.809

8.  A new method for measuring daytime sleepiness: the Epworth sleepiness scale.

Authors:  M W Johns
Journal:  Sleep       Date:  1991-12       Impact factor: 5.849

9.  Sleep patterns of urban school-going adolescents.

Authors:  Ravi Gupta; Manjeet Singh Bhatia; Vishal Chhabra; Sameer Sharma; Davinder Dahiya; Kapil Semalti; Rahul Sapra; Ramanpreet Singh Dua
Journal:  Indian Pediatr       Date:  2008-03       Impact factor: 1.411

10.  Meta-analysis of short sleep duration and obesity in children and adults.

Authors:  Francesco P Cappuccio; Frances M Taggart; Ngianga-Bakwin Kandala; Andrew Currie; Ed Peile; Saverio Stranges; Michelle A Miller
Journal:  Sleep       Date:  2008-05       Impact factor: 5.849

View more
  1 in total

1.  Chronotype: A Tool to Screen Eating Habits in Polycystic Ovary Syndrome?

Authors:  Luigi Barrea; Ludovica Verde; Claudia Vetrani; Silvia Savastano; Annamaria Colao; Giovanna Muscogiuri
Journal:  Nutrients       Date:  2022-02-23       Impact factor: 5.717

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.