Association of job sectors with type 2 diabetes mellitus, hypercholesterolemia and obesity: a cross-sectional study from the Malaysian Cohort (TMC) project

Int Health. 2018 Sep 1;10(5):382-390. doi: 10.1093/inthealth/ihx075.

Abstract

Background: The investigation of risk factors of cardiovascular disease (e.g., major endocrine, nutritional and metabolic diseases) across job sectors is useful for targeted public health intervention. This study examined the occurrence of type 2 diabetes mellitus (T2DM), hypercholesterolemia and obesity in 21 job sectors in the general population.

Methods: A baseline cross-sectional analysis of the Malaysian Cohort was conducted, which included 105 391 adults. Multiple logistic regression analyses were conducted for these three diseases across 20 job sectors compared with the unemployed/homemaker sector.

Results: The prevalence of T2DM, hypercholesterolemia and obesity was 16.7%, 38.8% and 33.3%, respectively. The Accommodation & Food Service Activities and Transportation & Storage sectors had significantly higher odds for T2DM (adjusted [adj.] prevalence odds ratio [POR] 1.18, p=0.007 and adj. POR 1.15, p=0.008, respectively). No job sector had significantly higher odds for hypercholesterolemia compared with the unemployed/homemaker sector. Only the Accommodation & Food Service Activities sector had significantly higher odds for obesity (adj. POR 1.17, p≤0.001).

Conclusions: Many job sectors were significantly associated with lower odds of having these three diseases when compared with the unemployed/homemaker sector. These differing associations between diverse job sectors and these diseases are important for public health intervention initiatives and prioritization.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Cross-Sectional Studies
  • Diabetes Mellitus, Type 2 / epidemiology*
  • Employment / statistics & numerical data*
  • Female
  • Humans
  • Hypercholesterolemia / epidemiology*
  • Malaysia
  • Male
  • Middle Aged
  • Obesity / epidemiology*
  • Occupational Health / statistics & numerical data*
  • Occupations / statistics & numerical data*
  • Risk Factors