Income, financial barriers to health care and public health expenditure: A multilevel analysis of 28 countries

Soc Sci Med. 2017 Mar:176:158-165. doi: 10.1016/j.socscimed.2017.01.044. Epub 2017 Jan 24.

Abstract

International studies have repeatedly shown that people with lower income are more likely to experience difficulties to access medical services. Less is known on why these relations vary across countries. This study investigates whether the association between income and financial barriers to health care is influenced by national public health expenditures (PHE, in % of total health expenditure). Data from the International Social Survey Programme (2011) was used (28 countries, 23,669 respondents). Financial barriers were assessed by the individual experience of forgone care due to financial reasons. Monthly equivalent household income was included as the main predictor. Other individual-level control variables were age, gender, education, subjective health, insurance coverage and place of living. PHE was considered as a macro-level predictor, adjusted for total health expenditure. Statistically significant associations between income and forgone care were found in 21 of 28 examined countries. Multilevel analyses across countries revealed that people with lower income have a higher likelihood to forgo needed medical care (OR: 3.94, 95%-CI: 2.96-5.24). After adjustments for individual-level covariates, this association slightly decreased (OR: 2.94, 95%-CI: 2.16-3.99). PHE did not moderate the relation between income and forgone care. The linkage between health system financing and inequalities in access to health care seems to be more complex than initially assumed, pointing towards further research to explore how PHE affects the redistribution of health resources in different health care systems.

Keywords: Access to health care; Income-related inequalities; Public health expenditure.

MeSH terms

  • Developed Countries / statistics & numerical data
  • Developing Countries / statistics & numerical data*
  • Health Expenditures / statistics & numerical data*
  • Health Services Accessibility / standards*
  • Humans
  • Income / statistics & numerical data
  • Internationality
  • Logistic Models
  • Multilevel Analysis
  • Poverty / statistics & numerical data
  • Public Health / economics*
  • Public Health / statistics & numerical data