Relationship Between Shift Work and Clustering of the Metabolic Syndrome Diagnostic Components
Relationship Between Shift Work and Clustering of the Metabolic Syndrome Diagnostic Components
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DOI：
10.5551/jat.19380
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发表时间：
2014-01-01
影响因子：
4.4
通讯作者：
Ueshima, Hirotsugu
中科院分区：
文献类型：
--
作者：
Kawabe, Yuri;Nakamura, Yasuyuki;Ueshima, Hirotsugu
目的：为了研究日本工人的工作类型和代谢综合征诊断成分（MetS-DC）的数量之间的关系，以及MetS的风险，调整生活习惯，我们检查了4,427名参与者（81.4%男性）的基线数据，年龄在19岁至69岁之间。根据国际体力活动问卷（IPAQ）对每位参与者的体力活动进行分类。我们在本研究中将四种MetS-DC定义如下：1）高血压（BP）：收缩压>= 130 mmHg，或舒张压>= 85 mmHg，或使用降压药物; 2）血脂异常：高密度脂蛋白胆固醇浓度< 40 mg/dl或甘油三酯浓度>= 150 mg/dl，或使用血脂异常药物; 3）血脂异常：空腹血糖水平>= 110 mg/dl，或餐后8小时内>= 140 mg/dl，或正在服用糖尿病药物; 4）超重：体重指数>= 25 kg/m（2）。我们将MetS定义为超重加上两个或更多的MetS-DC.Results：有3,094名受试者在白天工作组，73名在固定的夜间工作组，1,017名在轮班工作组和243名在白天到夜间工作组。Poisson回归分析显示，与白天工作相比，固定夜间工作（回归系数[B] =-0.233，P=0.028）和轮班工作（B=0.098，P=0.034）独立地对MetS-DC的数量做出贡献。不包括睡眠时间的多因素Logistic回归分析显示，倒班工作与代谢综合征呈正相关（OR = 1.47，P
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 >= 140 mg/dl, or on medication for diabetes mellitus; 4) overweight: a body mass index >= 25 kg/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