Measuring the effect of health on the income of people living in extreme poverty: A comparative cross-sectional analysis

Int J Health Plann Manage. 2019 Apr;34(2):714-726. doi: 10.1002/hpm.2730. Epub 2019 Feb 1.

Abstract

Background: Through a review of the literature, we have observed that existing studies primarily focus on defining and measuring poverty, identifying the factors that affect poverty, and proposing anti-poverty strategies. The impact of health on income in the context of extreme poverty has not been adequately studied. In China, 30 million people live below the poverty line, and poverty caused by illness accounts for nearly 44% of the total number of recorded incidents. Health impaired by disease has become the largest obstacle to escaping extreme poverty.

Objective: To determine whether health has a greater effect on the incomes of individuals in the extreme poverty group compared with the nonimpoverished group.

Methods: The poverty threshold of China in 2010 was adopted for the definition of extreme poverty. The China Health and Nutrition Survey (CHNS) Database 2014 was selected as the data source. Ordinary least squares (OLS) test was conducted to estimate the model, and the endogeneity of the variables was analyzed by the random effects model. Waist-to-hip ratio (WHR) was used instead of body mass index (BMI) to perform the robustness test.

Results: We found that the influence of individual health conditions on income was augmented in the case of extreme poverty, which indicates that health indeed influences income more strongly for individuals in the extreme poverty group.

Conclusions: In addition to education, investment, and social security projects, further public policy attention should be given to the improvement of the health status of the extremely impoverished population.

Keywords: extreme poverty; health; income effect; poverty.

Publication types

  • Comparative Study

MeSH terms

  • China / epidemiology
  • Cross-Sectional Studies
  • Educational Status
  • Health Status*
  • Humans
  • Income* / statistics & numerical data
  • Poverty* / statistics & numerical data