Relationship of occupation to blood pressure among middle-aged Japanese men--the significance of the differences in body mass index and alcohol consumption

J Epidemiol. 1998 Oct;8(4):216-26. doi: 10.2188/jea.8.216.

Abstract

To clarify how and why blood pressure differs between occupations, the proportions of hypertensives, and the measures of blood pressure, body mass index (BMI) and alcohol consumption among the individuals not taking antihypertensive drugs were compared between the eight occupational categories using the data from a health check-up for 589 middle-aged Japanese males, mostly randomly selected from five areas in Japan. After adjusting for age, the relationships of occupation to the proportion of hypertensives and the mean systolic and diastolic blood pressure substantially differed among the five areas. However, after further adjustment for residence, these blood pressure levels (the proportion of hypertensives, and the mean systolic and diastolic blood pressure) were found to be higher for the "Personnel in transport and communications", the "Clerical personnel", the "Managerial and civil personnel" and the "Professional and technical personnel", whereas these values were consistently lowest in the "Service personnel". Age and residence-adjusted mean BMI was also higher for the four occupational categories with the increased blood pressure levels. According to a weighted multiple regression analysis across the eight occupations, the age and residence-adjusted mean BMI was a significant predictor of the age and residence-adjusted mean systolic and diastolic blood pressure (p = 0.068 and 0.018, respectively). These results suggest that the occupation-related changes in BMI may largely contribute to the occupation-related changes in blood pressure.

MeSH terms

  • Alcohol Drinking / epidemiology*
  • Blood Pressure*
  • Body Mass Index*
  • Cross-Sectional Studies
  • Health Surveys
  • Humans
  • Hypertension / epidemiology*
  • Japan / epidemiology
  • Male
  • Middle Aged
  • Occupational Health / statistics & numerical data
  • Occupations* / classification
  • Occupations* / statistics & numerical data
  • Regression Analysis
  • Risk Factors