Airflow obstruction attributable to work in industry and occupation among U.S. race/ethnic groups: a study of NHANES III data

Am J Ind Med. 2004 Aug;46(2):126-35. doi: 10.1002/ajim.20042.

Abstract

Objectives: To estimate the fraction of airflow obstruction attributable to workplace exposure by U.S. race/ethnic group.

Methods: U.S. population-based third National Health and Nutrition Examination Survey (NHANES III) data on 4,086 Caucasians, 2,774 African-Americans, and 2,568 Mexican-Americans, aged 30-75, were studied. Airflow obstruction was defined as FEV1/FVC<75% and FEV1<80% predicted. Weighted prevalence, and prevalence odds ratios (OR) adjusted for the effect of age, smoking status, pack-years, body mass index, education, and socio-economic status were estimated using SUDAAN software.

Results: Industries with the most cases of airflow obstruction attributable to workplace exposure include: armed forces; rubber, plastics, and leather manufacturing; utilities; textile mill manufacturing; health care; food products manufacturing; sales; construction; and agriculture. The fraction of cases with airflow obstruction associated with work in industry varied by race/ethnic group and was estimated as 22.2% (95% CI 9.1-33.4) among Caucasians, 23.4% (95% CI 2.2-40.0) among African-Americans, and 49.6% (32.1-62.6) among Mexican-Americans.

Conclusions: This study found differences in the fraction of airflow obstruction cases associated with employment pattern among major U.S. race/ethnic population groups.

Publication types

  • Comparative Study

MeSH terms

  • Adult
  • Aged
  • Black or African American / statistics & numerical data*
  • Humans
  • Mexican Americans / statistics & numerical data*
  • Middle Aged
  • Occupational Diseases / ethnology*
  • Occupational Exposure / statistics & numerical data*
  • Occupations / statistics & numerical data
  • Prevalence
  • Pulmonary Disease, Chronic Obstructive / ethnology*
  • Spectrophotometry, Atomic
  • United States / epidemiology
  • White People / statistics & numerical data*