The influence of sociodemographic characteristics on agreement between self-reports and expert exposure assessments.
Sembajwe-G; Quinn-M; Kriebel-D; Stoddard-A; Krieger-N; Barbeau-E
Am J Ind Med 2010 Oct; 53(10):1019-1031
BACKGROUND: Often in exposure assessment for epidemiology, there are no highly accurate exposure data and different measurement methods are considered. The objective of this study was to use various statistical techniques to explore agreement between individual reports and expert ratings of workplace exposures in several industries and investigate the sociodemographic influences on this agreement. METHODS: A cohort of 1,282 employees at 4 industries/14 worksites answered questions on workplace physical, chemical, and psychosocial exposures over the past 12 months. Occupational hygienists constructed job exposure matrices (JEMs) based on worksite walkthrough exposure evaluations. Worker self-reports were compared with the JEMs using multivariable analyses to explore discord. RESULTS: There was poor agreement between the self-reported and expert exposure assessments, but there was evidence that agreement was modified by sociodemographic characteristics. Several characteristics including gender, age, race/ethnicity, hourly wage and nativity strongly affected the degree of discord between self-reports and expert raters across a wide array of different exposures. CONCLUSIONS: Agreement between exposure assessment tools may be affected by sociodemographic characteristics. This study is cross-sectional and therefore, a snapshot of potential exposures in the workplace. Nevertheless, future studies should take into account the social contexts within which workplace exposures occur.
Epidemiology; Exposure-assessment; Statistical-analysis; Sociological-factors; Demographic-characteristics; Data-processing; Occupational-exposure; Work-environment; Health-surveys; Questionnaires; Industrial-factory-workers; Industrial-hygienists; Sex-factors; Age-factors; Racial-factors;
Author Keywords: exposure assessment; occupational epidemiology; job exposure matrix; agreement; discord; higher estimation; lower estimation
Dr. Grace Sembajwe, Department of Society, Human Development and Health, Harvard School of Public Health, Boston, MA 02115, USA
American Journal of Industrial Medicine
Dana-Farber Cancer Institute