Hanna Rinne1,2, Mikko Laaksonen3. 1. Rehabilitation Foundation, Finland. 2. Social Insurance Institution of Finland. 3. Finnish Centre for Pensions, Helsinki, Finland.
Abstract
AIMS: Most high mortality-risk occupations are manual occupations. We examined to what extent high mortality of such occupations could be explained by education, income, unemployment or industry and whether there were differences in these effects among different manual occupations. METHODS: We used longitudinal individual-level register-based data, the study population consisting of employees aged 30-64 at the end of the year 2000 with the follow-up period 2001-2015. We used Cox proportional hazard regression models in 31 male and 11 female occupations with high mortality. RESULTS: There were considerable differences between manual occupations in how much adjusting for education, income, unemployment and industry explained the excess mortality. The variation was especially large among men: controlling for these variables explained over 50% of the excess mortality in 23 occupations. However, in some occupations the excess mortality even increased in relation to unadjusted mortality. Among women, these variables explained a varying proportion of the excess mortality in every occupation. After adjustment of all variables, mortality was no more statistically significantly higher than average in 14 occupations among men and 2 occupations among women. The high mortality in manual occupations was mainly explained by education, income, unemployment and industry. However, the degree of explanation varied widely between occupations, and considerable variation in mortality existed between manual occupations after controlling for these variables. More research is needed on other determinants of mortality in specific high-risk occupations.
AIMS: Most high mortality-risk occupations are manual occupations. We examined to what extent high mortality of such occupations could be explained by education, income, unemployment or industry and whether there were differences in these effects among different manual occupations. METHODS: We used longitudinal individual-level register-based data, the study population consisting of employees aged 30-64 at the end of the year 2000 with the follow-up period 2001-2015. We used Cox proportional hazard regression models in 31 male and 11 female occupations with high mortality. RESULTS: There were considerable differences between manual occupations in how much adjusting for education, income, unemployment and industry explained the excess mortality. The variation was especially large among men: controlling for these variables explained over 50% of the excess mortality in 23 occupations. However, in some occupations the excess mortality even increased in relation to unadjusted mortality. Among women, these variables explained a varying proportion of the excess mortality in every occupation. After adjustment of all variables, mortality was no more statistically significantly higher than average in 14 occupations among men and 2 occupations among women. The high mortality in manual occupations was mainly explained by education, income, unemployment and industry. However, the degree of explanation varied widely between occupations, and considerable variation in mortality existed between manual occupations after controlling for these variables. More research is needed on other determinants of mortality in specific high-risk occupations.