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Journal of Huazhong University of Science and Technology (Medical Sciences) ; (6): 606-614, 2015.
Article Dans Anglais | WPRIM | ID: wpr-250370

Résumé

Health disparities between the western, central and eastern regions of rural China, and the impact of national health improvement policies and programming were assessed. A total of 400 counties were randomly sampled. ANOVA and Logistic regression modeling were employed to estimate differences in health outcomes and determinants. Significant differences were found between the western, central and eastern rural regions in community infrastructure and health outcomes. From 2000 to 2010, health indicators in rural China were improved significantly, and the infant mortality rate (IMR), maternal mortality rate (MMR) and under 5 mortality rate (U5MR) had fallen by 62.79%, 71.74% and 61.92%, respectively. Central rural China had the greatest decrease in IMR (65.05%); whereas, western rural China had the greatest reduction in MMR (72.99%) but smallest reduction in U5MR (57.36%). Despite these improvements, Logistic regression analysis showed regional differences in key health outcome indicators (odds ratios): IMR (central: 2.13; western: 5.31), U5MR (central: 2.25; western: 5.69), MMR (central: 1.94; western: 3.31), and prevalence of infectious diseases (central: 1.62; western: 3.58). The community infrastructure and health outcomes of the western and central rural regions of China have been improved markedly during the first decade of the 21st century. However, health disparities still exist across the three regions. National efforts to increase per capita income, community empowerment and mobilization, community infrastructure, capacity of rural health facilities, and health literacy would be effective policy options to attain health equity.


Sujets)
Femelle , Humains , Nourrisson , Chine , Épidémiologie , Études transversales , Promotion de la santé , Économie , Disparités d'accès aux soins , Économie , Mortalité infantile , Mortalité maternelle , Mortalité , Analyse de régression , Population rurale , Facteurs socioéconomiques
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