WEALTH AND HEALTH IN EUROPE AND THE UNITED STATES: A COMPARATIVE ANALYSIS Authors:

Background and objectives: There are large differences among European countries and the United States in social and health expenditures, welfare policies and wealth inequality. This study assess whether these differences translate into variations in the magnitude of wealth disparities in physical health across countries, and examines the contribution of risk factors and healthcare utilization patterns to these disparities. Data and methods: Data from the SHARE and HRS studies were used. SHARE comprised data from 21,596 men and women age 50 years and over in 10 European countries who participated in the baseline survey in 2004. Data from HRS comprised 14,303 non-Hispanic white participants aged 50 years and over with information available from the 2004 interview wave. Data on physical health included: Self-perceived health, cardiovascular (heart or stroke) disease (CVD), cancer, ADL limitations (0 vs. 1 or more), maximum grip strength (kg) and walking speed (m/s). Data on wealth comprised total net worth, net financial assets and real assets. Additionally, data were used on household income, education, indicators of healthrelated behaviour (smoking, alcohol consumption, body mass index and physical activity), depression and health care utilization (doctor visits, hospital visits and outpatient surgery). Analyses were conducted using linear or logistic regression, entering interaction terms to allow estimates of the effect of wealth quintiles to differ according to country or region, and adjusting for confounders (US region, age and sex). Subsequently, risk factors and health care utilization variable were entered into the models to assess their contribution to wealth gradients in physical health outcomes. Results: Total net worth, financial and real assets were negatively associated with most health outcomes both in Europe (SHARE) and the United States (HRS). Europeans in the lowest quintile of total net worth had consistently higher odds of cardiovascular disease (OR=1.56, 95%CI 1.38, 1.78) and ADL limitations (OR=2.40, 95%CI 2.06. 2.81). Higher odds ratios were observed for the United States and were 2.42 (95%CI 2.14, 2.73) for CVD and 3.39 (95%CI 2.86, 4.01) for ADL limitations. Mean grip strength and walking speed were also negatively associated with wealth, and associations were of similar magnitude for most European countries and the United States. These associations were largely independent from income and education. In contrast, cancer prevalence was not negatively associated with wealth. Financial and real assets showed similar associations with most health outcomes. However, real assets were more strongly associated than financial assets with disability indicators as reflected by ADL limitations and walking speed. Individual risk factors such as physical activity and alcohol consumption marginally contributed to wealth disparities in health outcomes, whereas the contribution of depression was more substantial. Health care utilization patterns also contributed to wealth disparities in both Europe and the United States. Overall, however, behavioural risk factors, depression and health care utilization explained only about half of the wealth gradient in physical health. Conclusions: Total net worth, financial and real assets are independently associated with physical health in Europe and the United States. The association between wealth and physical health was stronger in the United States than in Europe for self-reported measures, but was of similar magnitude for objective health measures. More egalitarian health and wealth distribution policies may have contributed to smaller wealth disparities in some health outcomes in Europe as compared to the United States.