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Aim: To examine the relationship between the type of work and the number of metabolic syndrome diagnostic components(MetS-DC), as well as the risk of MetS, with adjustment for lifestyle habits in Japanese workers., Methods: We examined the baseline data from 4,427 participants(81.4% male) aged 19 to 69 years old. The physical activity of each participant was classified according to the International Physical Activity Questionnaire(IPAQ). We defined the four MetS-DC 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 triglyceride concentration ≥150 mg/dl, or on medication for dyslipidemia; 3) dysglycemia: fasting blood sugar level ≥110 mg/dl, or if less than eight hours after meals ≥140mg/dl, or on medication for diabetes mellitus; 4) overweight: a body mass index ≥25kg/m(2). We defined MetS as overweight plus two or more of the MetS-DC., Results: There were 3,094 subjects in the daytime work group, 73 in the fixed nighttime work group, 1,017 in the shift work group and 243 in the day-to-night work group. The Poisson regression analysis revealed that fixed nighttime (regression coefficient [b]=-0.233, P=0.028) and shift work (b=0.098, P=0.034) independently contributed to the number of MetS-DC, compared to daytime work. The multivariate logistic analysis not including sleep hours in the model showed that shift work was positively related to MetS (odd ratio=1.47, P＜0.01)., Conclusion: Shift work were significantly associated with the number of MetS-DC, and was related to risk of MetS compared to daytime work.

Purpose: To examine the association of the number of metabolic syndrome diagnostic components (MetS-DC) with health-related quality of life (HR-QOL)., Methods: We examined the baseline data from 4,480 healthy workers in Japan (3,668 men and 812 women) aged 19-69 years. We assessed HR-QOL based on scores for five scales of the SF-36. We defined four components for MetS in this study as follows: (1) high blood pressure (BP); (2) dyslipidemia; (3) impaired glucose tolerance; and (4) overweight: a body mass index ≥25 kg/m(2). Logistic regression analysis adjusted for lifestyle factors was used to examine the association of the number of MetS-DC with the HR-QOL sub-scales., Results: Those who had 0-4 MetS-DC accounted for 2,287, 1,135, 722, 282, and 54 participants. The number of MetS-DC inversely contributed significantly to General Health (norm-based scoring >50) (odd ratios [OR] 0.59-0.82, P < 0.05) and positively associated with Mental Health (OR 1.37, P < 0.05)., Conclusion: When adjusted for lifestyle factors, the number of MetS-DC was inversely associated with General Health and positively with Mental Health in men and women.

Aim: To examine the relation between lifestyle and the number of metabolic syndrome (MetS) diagnostic components in a general population, and to find a means of preventing the development of MetS components., Methods: We examined baseline data from 3,365 participants (2,714 men and 651 women) aged 19 to 69 years who underwent a physical examination, lifestyle survey, and blood chemical examination. The physical activity of each participant was classified according to the International Physical Activity Questionnaire (IPAQ). We defined four components for MetS in this study as follows: 1) high BP: systolic BP > or = 130 mmHg or diastolic BP > or = 85 mmHg, or the use of antihypertensive drugs; 2) dyslipidemia: high-density lipoprotein-cholesterol concentration < 40 mg/dL, triglycerides concentration > or = 150 mg/dL, or on medication for dyslipidemia; 3) Impaired glucose tolerance: fasting blood sugar level > or = 110 mg/d, or if less than 8 hours after meals > or = 140 mg/dL), or on medication for diabetes mellitus; 4) obesity: body mass index > or = 25 kg/m(2)., Results: Those who had 0 to 4 MetS diagnostic components accounted for 1,726, 949, 484, 190, and 16 participants, respectively, in the Poisson distribution. Poisson regression analysis revealed that independent factors contributing to the number of MetS diagnostic components were being male (regression coefficient b=0.600, p < 0.01), age (b=0.027, p < 0.01), IPAQ class (b=-0.272, p= 0.03), and alcohol consumption (b=0.020, p=0.01). The contribution of current smoking was not statistically significant (b=-0.067, p=0.76)., Conclusion: Moderate physical activity was inversely associated with the number of MetS diagnostic components, whereas smoking was not associated.

Abstract Background Prevalence of men with cardiometabolic risk factors (CMRF) is increasing in Japan. Few studies have comprehensively examined the relation between lifestyles and CMRF. Methods 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. Results 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. Conclusions Alcohol intake, percent protein and total energy intake were positively associated, whereas drinking frequency and IPAQ were inversely associated, with the number of CMRF.