TY - JOUR
T1 - Socio-economic inequalities in bodily pain over the life cycle
T2 - Longitudinal evidence from Australia, Britain and Germany
AU - Schurer, Stefanie
AU - Shields, Michael A
AU - Jones, Andrew Michael
PY - 2014
Y1 - 2014
N2 - We document the extent of socio-economic status (SES) inequalities in bodily pain in Australia, Britain and Germany, with a particular focus on whether such inequalities widen over the life course. Random-effects logistic and kernel regressions are used to estimate odds ratios of experiencing severe pain by income, educational qualification and occupational status, and to graph age-pain profiles, while accounting for individual heterogeneity. Cohort level regression analysis is used to control for cohort effects. Low SES is consistently related to higher levels of bodily pain in each country and inequalities widen with increasing age. The odds of experiencing severe bodily pain for individuals in the lowest, relative to the highest, household income quartile is up to two times higher, whereas the odds for those with minimum relative to university education are up to three times higher. For each country, the odds of experiencing severe pain by machine operators are around three times higher than for professionals. Maximum levels, and maximum SES differences in pain, are both reached at around age 60 years, with the differentials ranging between 0.2 and 0.7 of sample standard deviations. No convergence of pain profiles is observed by age 70 years. Controlling for cohort effects in the Australian data confirms the results from the age group analysis. Taken together these results suggest that low SES and manual work have cumulative health effects over the life cycle.
AB - We document the extent of socio-economic status (SES) inequalities in bodily pain in Australia, Britain and Germany, with a particular focus on whether such inequalities widen over the life course. Random-effects logistic and kernel regressions are used to estimate odds ratios of experiencing severe pain by income, educational qualification and occupational status, and to graph age-pain profiles, while accounting for individual heterogeneity. Cohort level regression analysis is used to control for cohort effects. Low SES is consistently related to higher levels of bodily pain in each country and inequalities widen with increasing age. The odds of experiencing severe bodily pain for individuals in the lowest, relative to the highest, household income quartile is up to two times higher, whereas the odds for those with minimum relative to university education are up to three times higher. For each country, the odds of experiencing severe pain by machine operators are around three times higher than for professionals. Maximum levels, and maximum SES differences in pain, are both reached at around age 60 years, with the differentials ranging between 0.2 and 0.7 of sample standard deviations. No convergence of pain profiles is observed by age 70 years. Controlling for cohort effects in the Australian data confirms the results from the age group analysis. Taken together these results suggest that low SES and manual work have cumulative health effects over the life cycle.
KW - Bodily pain
KW - Life cycle analysis
KW - Longitudinal data
KW - Socio-economic status
UR - http://www.scopus.com/inward/record.url?scp=84908071042&partnerID=8YFLogxK
U2 - 10.1111/rssa.12058
DO - 10.1111/rssa.12058
M3 - Article
VL - 177
SP - 783
EP - 806
JO - Journal of the Royal Statistical Society Series A-Statistics in Society
JF - Journal of the Royal Statistical Society Series A-Statistics in Society
SN - 0964-1998
IS - 4
ER -