S Jackson1, A C Sleigh, G J Wang, X L Liu. 1. School of Economics, The University of Queensland, St Lucia, Brisbane, Queensland 4072, Australia. s.jackson@economics.uq.edu.au
Abstract
OBJECTIVE: To investigate the economic effects of illness on individual tuberculosis (TB) cases in rural China and to use a case-control study to show a strong TB-poverty link. SETTING: In 2002-2004 we studied 160 new smear-positive pulmonary tuberculosis (PTB) cases and 320 age- and sex-matched controls living in neighbouring houses in four rural counties of Henan Province. DESIGN: Cases and controls were interviewed 1-3 months after patients were diagnosed. We used matched multivariate logistic regression to compare cases with controls for poverty status using household income, household assets and relative wealth within the village. We conducted follow-up interviews of patients 10-12 months later to assess economic effects by collecting data on treatment costs, income losses, coping strategies and treatment completion. RESULTS: Poverty is strongly associated with TB incidence even after controlling for smoking and other risk factors. Excluding income losses, direct out-of-pocket treatment costs (medical and non-medical) accounted for 55.5% of average annual household income, and most TB cases fell into heavy debt. The DOTS cure rate was 91%. When DOTS was incomplete or not done, mortality was high. CONCLUSIONS: Poverty is both a cause and a devastating outcome of TB. Ongoing poverty reduction schemes in China must also include reducing TB.
OBJECTIVE: To investigate the economic effects of illness on individual tuberculosis (TB) cases in rural China and to use a case-control study to show a strong TB-poverty link. SETTING: In 2002-2004 we studied 160 new smear-positive pulmonary tuberculosis (PTB) cases and 320 age- and sex-matched controls living in neighbouring houses in four rural counties of Henan Province. DESIGN: Cases and controls were interviewed 1-3 months after patients were diagnosed. We used matched multivariate logistic regression to compare cases with controls for poverty status using household income, household assets and relative wealth within the village. We conducted follow-up interviews of patients 10-12 months later to assess economic effects by collecting data on treatment costs, income losses, coping strategies and treatment completion. RESULTS: Poverty is strongly associated with TB incidence even after controlling for smoking and other risk factors. Excluding income losses, direct out-of-pocket treatment costs (medical and non-medical) accounted for 55.5% of average annual household income, and most TB cases fell into heavy debt. The DOTS cure rate was 91%. When DOTS was incomplete or not done, mortality was high. CONCLUSIONS: Poverty is both a cause and a devastating outcome of TB. Ongoing poverty reduction schemes in China must also include reducing TB.
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