Johan Rehnberg1,2, Stefan Fors3, Johan Fritzell3. 1. Aging Research Center, Karolinska Institutet and Stockholm University, Solna, Sweden, johan.rehnberg@ki.se. 2. Centre for Health Equity Studies (CHESS), Department of Public Health Sciences, Stockholm University, Stockholm, Sweden, johan.rehnberg@ki.se. 3. Aging Research Center, Karolinska Institutet and Stockholm University, Solna, Sweden.
Abstract
BACKGROUND: Do inequalities in health by income increase or decrease with age? The empirical evidence is not conclusive and competing theories arrive at different conclusions. OBJECTIVE: This study examined inequality in mortality by income over the adult life course with longitudinal data on people aged 30-99 between the years 1990 and 2009. Each person was followed for 19 years. METHODS: We used Swedish total population data with 5,011,414 individual observations. We calculated the probability of having died for ages between 31 and 99. This approach to calculating death risk incorporates selective mortality during the follow-up period into the measure. Age and year standardized income positions were calculated for all individuals. Inequality was assessed by comparing the top 10% income group and the bottom 10% income group. Relative inequality was measured by risk ratios (RR) and absolute inequality by percentage point differences. RESULTS: The results showed that the highest relative income inequality in mortality was at age 56 for men (RR: 4.7) and at age 40 for women (RR: 4.1) with differing patterns across the younger age categories between the sexes. The highest absolute income inequality in mortality was found at age 78 for men (19% difference) and at age 89 for women (14% difference) with similar patterns for both sexes. Both measures of inequality decreased after the peak, with small or no inequalities above age 95. Income inequality in mortality remained in advanced age, with larger absolute inequalities in older ages and larger relative inequalities in younger ages. CONCLUSION: The results for absolute and relative measures of inequality differed substantially; this highlights the importance of discussing and making an active choice of inequality measure. To explain and understand the patterns of inequality in mortality over the adult life course, we conclude that the "age-as-leveler" and "cumulative disadvantage" theories are best applied to an absolute measure of inequality.
BACKGROUND: Do inequalities in health by income increase or decrease with age? The empirical evidence is not conclusive and competing theories arrive at different conclusions. OBJECTIVE: This study examined inequality in mortality by income over the adult life course with longitudinal data on people aged 30-99 between the years 1990 and 2009. Each person was followed for 19 years. METHODS: We used Swedish total population data with 5,011,414 individual observations. We calculated the probability of having died for ages between 31 and 99. This approach to calculating death risk incorporates selective mortality during the follow-up period into the measure. Age and year standardized income positions were calculated for all individuals. Inequality was assessed by comparing the top 10% income group and the bottom 10% income group. Relative inequality was measured by risk ratios (RR) and absolute inequality by percentage point differences. RESULTS: The results showed that the highest relative income inequality in mortality was at age 56 for men (RR: 4.7) and at age 40 for women (RR: 4.1) with differing patterns across the younger age categories between the sexes. The highest absolute income inequality in mortality was found at age 78 for men (19% difference) and at age 89 for women (14% difference) with similar patterns for both sexes. Both measures of inequality decreased after the peak, with small or no inequalities above age 95. Income inequality in mortality remained in advanced age, with larger absolute inequalities in older ages and larger relative inequalities in younger ages. CONCLUSION: The results for absolute and relative measures of inequality differed substantially; this highlights the importance of discussing and making an active choice of inequality measure. To explain and understand the patterns of inequality in mortality over the adult life course, we conclude that the "age-as-leveler" and "cumulative disadvantage" theories are best applied to an absolute measure of inequality.
Authors: Linda Juel Ahrenfeldt; Jacob Krabbe Pedersen; Mikael Thinggaard; Kaare Christensen; Rune Lindahl-Jacobsen Journal: J Epidemiol Community Health Date: 2019-12-16 Impact factor: 3.710