Yanping Wang1, Xiaohong Li2, Maigeng Zhou1, Shusheng Luo3, Juan Liang4, Chelsea A Liddell5, Matthew M Coates5, Yanqiu Gao3, Linhong Wang1, Chunhua He4, Chuyun Kang3, Shiwei Liu1, Li Dai4, Austin E Schumacher5, Maya S Fraser5, Timothy M Wolock5, Amanda Pain5, Carly E Levitz5, Lavanya Singh5, Megan Coggeshall5, Margaret Lind5, Yichong Li1, Qi Li4, Kui Deng4, Yi Mu4, Changfei Deng4, Ling Yi4, Zheng Liu4, Xia Ma4, Hongtian Li6, Dezhi Mu4, Jun Zhu7, Christopher J L Murray8, Haidong Wang5. 1. National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China. 2. National Center for Birth Defect Surveillance of China, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China; Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, Sichuan, China. 3. Office for National Maternal and Child Health Statistics of China, School of Public Health, Peking University Health Science Center, Beijing, China; Department of Child, Adolescent and Women's Health, School of Public Health, Peking University Health Science Center, Beijing, China. 4. National Office for Maternal and Child Health Surveillance of China, Department of Pediatrics, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China. 5. Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA. 6. Office for National Maternal and Child Health Statistics of China, School of Public Health, Peking University Health Science Center, Beijing, China. 7. National Office for Maternal and Child Health Surveillance of China, Department of Pediatrics, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China; National Center for Birth Defect Surveillance of China, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China. Electronic address: zhujun028@163.com. 8. Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA. Electronic address: cjlm@uw.edu.
Abstract
BACKGROUND: In the past two decades, the under-5 mortality rate in China has fallen substantially, but progress with regards to the Millennium Development Goal (MDG) 4 at the subnational level has not been quantified. We aimed to estimate under-5 mortality rates in mainland China for the years 1970 to 2012. METHODS: We estimated the under-5 mortality rate for 31 provinces in mainland China between 1970 and 2013 with data from censuses, surveys, surveillance sites, and disease surveillance points. We estimated under-5 mortality rates for 2851 counties in China from 1996 to 2012 with the reported child mortality numbers from the Annual Report System on Maternal and Child Health. We used a small area mortality estimation model, spatiotemporal smoothing, and Gaussian process regression to synthesise data and generate consistent provincial and county-level estimates. We compared progress at the county level with what was expected on the basis of income and educational attainment using an econometric model. We computed Gini coefficients to study the inequality of under-5 mortality rates across counties. FINDINGS: In 2012, the lowest provincial level under-5 mortality rate in China was about five per 1000 livebirths, lower than in Canada, New Zealand, and the USA. The highest provincial level under-5 mortality rate in China was higher than that of Bangladesh. 29 provinces achieved a decrease in under-5 mortality rates twice as fast as the MDG 4 target rate; only two provinces will not achieve MDG 4 by 2015. Although some counties in China have under-5 mortality rates similar to those in the most developed nations in 2012, some have similar rates to those recorded in Burkina Faso and Cameroon. Despite wide differences, the inter-county Gini coefficient has been decreasing. Improvement in maternal education and the economic boom have contributed to the fall in child mortality; more than 60% of the counties in China had rates of decline in under-5 mortality rates significantly faster than expected. Fast reduction in under-5 mortality rates have been recorded not only in the Han population, the dominant ethnic majority in China, but also in the minority populations. All top ten minority groups in terms of population sizes have experienced annual reductions in under-5 mortality rates faster than the MDG 4 target at 4.4%. INTERPRETATION: The reduction of under-5 mortality rates in China at the country, provincial, and county level is an extraordinary success story. Reductions of under-5 mortality rates faster than 8.8% (twice MDG 4 pace) are possible. Extremely rapid declines seem to be related to public policy in addition to socioeconomic progress. Lessons from successful counties should prove valuable for China to intensify efforts for those with unacceptably high under-5 mortality rates. FUNDING: National "Twelfth Five-Year" Plan for Science and Technology Support, National Health and Family Planning Commission of The People's Republic of China, Program for Changjiang Scholars and Innovative Research Team in University, the National Institute on Aging, and the Bill & Melinda Gates Foundation.
BACKGROUND: In the past two decades, the under-5 mortality rate in China has fallen substantially, but progress with regards to the Millennium Development Goal (MDG) 4 at the subnational level has not been quantified. We aimed to estimate under-5 mortality rates in mainland China for the years 1970 to 2012. METHODS: We estimated the under-5 mortality rate for 31 provinces in mainland China between 1970 and 2013 with data from censuses, surveys, surveillance sites, and disease surveillance points. We estimated under-5 mortality rates for 2851 counties in China from 1996 to 2012 with the reported child mortality numbers from the Annual Report System on Maternal and Child Health. We used a small area mortality estimation model, spatiotemporal smoothing, and Gaussian process regression to synthesise data and generate consistent provincial and county-level estimates. We compared progress at the county level with what was expected on the basis of income and educational attainment using an econometric model. We computed Gini coefficients to study the inequality of under-5 mortality rates across counties. FINDINGS: In 2012, the lowest provincial level under-5 mortality rate in China was about five per 1000 livebirths, lower than in Canada, New Zealand, and the USA. The highest provincial level under-5 mortality rate in China was higher than that of Bangladesh. 29 provinces achieved a decrease in under-5 mortality rates twice as fast as the MDG 4 target rate; only two provinces will not achieve MDG 4 by 2015. Although some counties in China have under-5 mortality rates similar to those in the most developed nations in 2012, some have similar rates to those recorded in Burkina Faso and Cameroon. Despite wide differences, the inter-county Gini coefficient has been decreasing. Improvement in maternal education and the economic boom have contributed to the fall in child mortality; more than 60% of the counties in China had rates of decline in under-5 mortality rates significantly faster than expected. Fast reduction in under-5 mortality rates have been recorded not only in the Han population, the dominant ethnic majority in China, but also in the minority populations. All top ten minority groups in terms of population sizes have experienced annual reductions in under-5 mortality rates faster than the MDG 4 target at 4.4%. INTERPRETATION: The reduction of under-5 mortality rates in China at the country, provincial, and county level is an extraordinary success story. Reductions of under-5 mortality rates faster than 8.8% (twice MDG 4 pace) are possible. Extremely rapid declines seem to be related to public policy in addition to socioeconomic progress. Lessons from successful counties should prove valuable for China to intensify efforts for those with unacceptably high under-5 mortality rates. FUNDING: National "Twelfth Five-Year" Plan for Science and Technology Support, National Health and Family Planning Commission of The People's Republic of China, Program for Changjiang Scholars and Innovative Research Team in University, the National Institute on Aging, and the Bill & Melinda Gates Foundation.
Authors: Qun Meng; Ling Xu; Yaoguang Zhang; Juncheng Qian; Min Cai; Ying Xin; Jun Gao; Ke Xu; J Ties Boerma; Sarah L Barber Journal: Lancet Date: 2012-03-03 Impact factor: 79.321
Authors: Marie Ng; Michael K Freeman; Thomas D Fleming; Margaret Robinson; Laura Dwyer-Lindgren; Blake Thomson; Alexandra Wollum; Ella Sanman; Sarah Wulf; Alan D Lopez; Christopher J L Murray; Emmanuela Gakidou Journal: JAMA Date: 2014-01-08 Impact factor: 56.272
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