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Widening inequalities in multimorbidity? Time trends among the working population between 2005 and 2015 based on German health insurance data.
International Journal for Equity in Health 2018 July 17
BACKGROUND: Previous research has produced evidence for social inequalities in multimorbidity, but little is known on how these disparities change over time. Our study investigates the development of social inequalities in multimorbidity among the middle-aged and older working population. Special attention is paid to whether differing time trends between socio-economic status (SES) groups have taken place, increasing or decreasing inequalities in multimorbidity.
METHODS: The analyses are based on claims data of a German statutory health insurance company covering an observation period from 2005 to 2015. Multimorbidity prevalence risks are estimated using logistic generalized estimation equations (GEE) models. Predicted probabilities of multimorbidity prevalence are used to assess time trends in absolute social inequalities in terms of educational level, income, and occupational group.
RESULTS: The prevalence risks of multimorbidity rose among all SES groups and social gradients persist throughout the observation period, indicating significantly higher multimorbidity prevalence risks for individuals with lower SES. Widening absolute inequalities are found among men in terms of educational level and among women in terms of occupational groups.
CONCLUSIONS: The increases in multimorbidity prevalence among the working population are accompanied by widening social inequalities, pointing towards a growing disadvantage for men and women in lower SES groups. The rising burden and the increasing inequalities among the working population stress the importance of multimorbidity as a major public health concern.
METHODS: The analyses are based on claims data of a German statutory health insurance company covering an observation period from 2005 to 2015. Multimorbidity prevalence risks are estimated using logistic generalized estimation equations (GEE) models. Predicted probabilities of multimorbidity prevalence are used to assess time trends in absolute social inequalities in terms of educational level, income, and occupational group.
RESULTS: The prevalence risks of multimorbidity rose among all SES groups and social gradients persist throughout the observation period, indicating significantly higher multimorbidity prevalence risks for individuals with lower SES. Widening absolute inequalities are found among men in terms of educational level and among women in terms of occupational groups.
CONCLUSIONS: The increases in multimorbidity prevalence among the working population are accompanied by widening social inequalities, pointing towards a growing disadvantage for men and women in lower SES groups. The rising burden and the increasing inequalities among the working population stress the importance of multimorbidity as a major public health concern.
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