Relationship between sleep duration and clustering of metabolic syndrome diagnostic components

Sayuri Katano1, Yasuyuki Nakamura1,2, Aki Nakamura1, Yoshitaka Murakami3, Taichiro Tanaka4, Toru Takebayashi5, Akira Okayama6, Katsuyuki Miura2, Tomonori Okamura7, Hirotsugu Ueshima2, for HIPOP-OHP Research Group1Cardiovascular Epidemiology, Kyoto Women's University, Kyoto, Japan; 2Department of Health Science, Shiga University of Medical Science, Otsu, Japan; 3Department of Medical Statistics, Shiga University of Medical Science, Otsu, Japan; 4Department of Health Sciences, Interdisciplinary Graduate School of Medicine and Engineering, University of Yamanashi, Chuo, Japan; 5Department of Preventive Medicine and Public Health, School of Medicine, Keio University, Tokyo, Japan; 6The First Institute of Health Service, Japan Anti-Tuberculosis Association, Tokyo, Japan; 7Department of Preventive Cardiology, National Cardiovascular Center, Suita, JapanObjective: 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.Keyword: short sleep duration, MetS diagnostic components, obesit

Relationship between Dietary and Other Lifestyle Habits and Cardiometabolic Risk Factors in Men

<p>Abstract</p> <p>Background</p> <p>Prevalence of men with cardiometabolic risk factors (CMRF) is increasing in Japan. Few studies have comprehensively examined the relation between lifestyles and CMRF.</p> <p>Methods</p> <p>We examined the baseline data from 3,498 male workers ages 19 to 69 years who participated in the high-risk and population strategy for occupational health promotion (HIPOP-OHP) study at 12 large-scale companies throughout Japan. The physical activity of each participant was classified according to the International Physical Activity Questionnaire (IPAQ). Dietary intake was surveyed by a semi-quantitative Food Frequency Questionnaire. We defined four CMRF in this study as follows: 1) high blood pressure (BP): systolic BP ≥ 130 mmHg, or diastolic BP ≥ 85 mmHg, or the use of antihypertensive drugs; 2) dyslipidemia: high-density lipoprotein-cholesterol concentration < 40 mg/dl, or triglycerides concentration ≥ 150 mg/dl, or on medication for dyslipidemia; 3) impaired glucose tolerance: fasting blood sugar concentration ≥110 mg/dl; 4) obese: a body mass index ≥ 25 kg/m².</p> <p>Results</p> <p>Those who had 0 to 4 CMRF accounted for 1,597 (45.7%), 1,032 (29.5%), 587 (16.8%), 236 (6.7%), and 44 (1.3%) participants, respectively, in the Poisson distribution. Poisson regression analysis revealed that independent factors that contributed to the number of CMRF were age (b = 0.020, P < 0.01), IPAQ (b = -0.091, P < 0.01), alcohol intake (ml/day) (b = 0.001, P = 0.03), percentage of protein intake (b = 0.059, P = 0.01), and total energy intake (kcal)(b = 0.0001, P < 0.01). Furthermore, alcohol intake and its frequency had differential effects.</p> <p>Conclusions</p> <p>Alcohol intake, percent protein and total energy intake were positively associated, whereas drinking frequency and IPAQ were inversely associated, with the number of CMRF.</p