Dual role of physical workload and occupational noise in the association of the metabolic syndrome with risk of coronary heart disease: findings from the Helsinki Heart Study
- PMID: 21148595
- DOI: 10.1136/oem.2010.057075
Dual role of physical workload and occupational noise in the association of the metabolic syndrome with risk of coronary heart disease: findings from the Helsinki Heart Study
Abstract
Objectives: Previous evidence indicates that occupational exposure to physical workload or noise entails development of hypertension and risk of coronary heart disease (CHD). However, vigorous physical activity lessens the risks of the metabolic syndrome (MetS) and CHD. We explored this issue by studying the joint effect of physical workload or noise and MetS on risk of CHD.
Methods: This 18-year follow-up study comprised 1502 middle-aged men employed in industry who participated in the second screening for the Helsinki Heart Study but were not treated with gemfibrozil, the trial drug. The CHD endpoints (ICD-9 codes 410-414 and ICD-10 codes 120-125) were obtained from official Finnish registers. The Finnish job-exposure matrix FINJEM provided information on occupational exposures. The joint effect of baseline MetS levels and both occupational exposures was estimated using Cox's regression models.
Results: Workload and noise increased CHD risk due to increased blood pressure, glucose or body mass index (BMI), separately or combined: the joint effect of workload and MetS defined using these three components yielded an RR of 5.21 (95% CI 2.70 to 10.05). However, when MetS was defined using elevated BMI, high triglycerides and low high-density lipoprotein cholesterol, an RR of 2.19 (95% CI 1.11 to 4.30) among those with MetS only reduced to 1.20 (95% CI 0.61 to 2.35) if concurrently exposed to workload.
Conclusions: Occupational exposure to workload or noise modifies CHD risk differently depending on which definition of MetS is used. In the presence of physical workload or noise, hypertension and blood glucose were the best predictors.
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