Relationship between sleep duration and clustering of metabolic syndrome diagnostic components

Abstract

Objective

To examine the relation between sleep duration and metabolic syndrome (MetS).

Methods

We examined the baseline data from 4356 healthy workers (3556 men and 800 women) aged 19–69 years. The physical activity of each participant was classified according to the International Physical Activity Questionnaire (IPAQ). We defined four components of MetS diagnostic components in this study as follows: 1) high blood pressure (BP) systolic BP [SBP] ≥ 130 mmHg, or diastolic BP [DBP] ≥ 85 mmHg, or on medication; 2) dyslipidemia (high-density lipoprotein-cholesterol concentration <40 mg/dL, or triglycerides concentration ≥150 mg/dL, or on medication; 3) impaired glucose tolerance (fasting blood sugar concentration ≥ 110 mg/dL, or if less than 8 hours after meals ≥ 140 mg/dL), or on medication; and 4) overweight (body mass index [BMI] ≥ 25 kg/m²), or obesity (BMI ≥ 30 kg/m²). There were 680 participants in the group, with sleep duration <6 hours (15.6%).

Results

Those who had 0–4 MetS diagnostic components, including overweight, accounted for 2159, 1222, 674, 255, and 46 participants, respectively, in the Poisson distribution. Poisson regression analysis revealed that independent factors that contributed to the number of MetS diagnostic components were being male (regression coefficient b = 0.752, P < 0.001), age (b = 0.026, P < 0.001), IPAQ classification (b = −0.238, P = 0.034), and alcohol intake (mL/day) (b = 0.018, P < 0.001). Short sleep duration (<6 hours) was also related to the number of MetS (b = 0.162, P < 0.001). The results of analyses with obesity component showed a similar association.

Conclusion

Short sleep duration was positively associated with the number of MetS diagnostic components independent of other lifestyle habits.

Keywords:

• short sleep duration
• MetS diagnostic components
• obesity

Acknowledgments

This study was funded by research grants from the Ministry of Health and Welfare of Japan (H10-12, No. 063, Research on Health Services, Health Sciences Research Grants and H13, No. 010, Medical Frontier Strategy Research, Health Sciences Research Grants), the Ministry of Health, Labor, and Welfare of Japan (H14-15, No. 010, Clinical Research for Evidence-Based Medicine, Health, and Labor Sciences Research Grants), and the Japan Arteriosclerosis Prevention Fund 2004.

We thank Toshimi Yoshida of the Department of Health Science, Shiga University of Medical Science, for her excellent clerical support during this research.

Investigators and members of the research group are listed in the appendix of Okamura et al.¹¹

Disclosure

None of the authors have any conflicts of interest related to this manuscript.