Large urban-rural disparity in the severity of two-week illness: updated results based on the first health service survey of Hunan Province, China

Int J Equity Health. 2016 Feb 29:15:37. doi: 10.1186/s12939-016-0330-z.

Abstract

Background: To examine urban-rural differences in the severity of non-fatal disease and injury using the latest household interview survey data of Hunan Province, China.

Methods: Two-week illness data were from the first provincial health household interview survey of Hunan in 2013. The proportion of patients being bedridden, the average days of being bedridden and the average off-work days were calculated to measure the severity of two-week illness. Rao-Scott-adjusted chi-square test was performed to examine the significance of two-week illness severity differences from demographic variables. Multiple logistic regression and linear regression were used to control for sex, age and household income.

Results: The two-week illness prevalence was 22.8 % in Hunan province. Despite similar two-week ill prevalence rates between urban areas and rural areas (23.0 % vs. 22.8 %), rural residents had higher proportions of being bedridden and of being off work than urban residents after controlling for sex, age and household income, with adjusted odds ratios of 3.4 and 6.9, respectively. Similarly, the average days of being bedridden and of being off work in rural residents were 0.45 days and 1.61 days longer than in urban residents after controlling for demographic variables, respectively.

Conclusion: The recent data shows that two-week illness in rural residents is more serious than urban residents in Hunan Province, China in spite of very similar two-week prevalence rates. The neglected urban-rural disparities in the severity of two-week illness deserve the attention of health policy-makers and researchers.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • China / epidemiology
  • Female
  • Health Surveys*
  • Humans
  • Male
  • Middle Aged
  • Patient Acuity*
  • Prevalence
  • Rural Population / statistics & numerical data*
  • Urban Population / statistics & numerical data*