• Lancet · Jan 2019

    Maternal mortality ratios in 2852 Chinese counties, 1996-2015, and achievement of Millennium Development Goal 5 in China: a subnational analysis of the Global Burden of Disease Study 2016.

    • Juan Liang, Xiaohong Li, Chuyun Kang, Yanping Wang, Xie Rachel Kulikoff, Matthew M Coates, Marie Ng, Shusheng Luo, Yi Mu, Xiaodong Wang, Rong Zhou, Xinghui Liu, Yali Zhang, Yubo Zhou, Maigeng Zhou, Qi Li, Zheng Liu, Li Dai, Mingrong Li, Yiyi Zhang, Kui Deng, Xinying Zeng, Changfei Deng, Ling Yi, Jun Zhu, MurrayChristopher J LCJLInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA. Electronic address: cjlm@uw.edu., and Haidong Wang.
    • National Office for Maternal and Child Health Surveillance of China, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China; Department of Obstetrics, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China.
    • Lancet. 2019 Jan 19; 393 (10168): 241252241-252.

    BackgroundAs one of only a handful of countries that have achieved both Millennium Development Goals (MDGs) 4 and 5, China has substantially lowered maternal mortality in the past two decades. Little is known, however, about the levels and trends of maternal mortality at the county level in China.MethodsUsing a national registration system of maternal mortality at the county level, we estimated the maternal mortality ratios for 2852 counties in China between 1996 and 2015. We used a state-of-the-art Bayesian small-area estimation hierarchical model with latent Gaussian layers to account for space and time correlations among neighbouring counties. Estimates at the county level were then scaled to be consistent with country-level estimates of maternal mortality for China, which were separately estimated from multiple data sources. We also assessed maternal mortality ratios among ethnic minorities in China and computed Gini coefficients of inequality of maternal mortality ratios at the country and provincial levels.FindingsChina as a country has experienced fast decline in maternal mortality ratios, from 108·7 per 100 000 livebirths in 1996 to 21·8 per 100 000 livebirths in 2015, with an annualised rate of decline of 8·5% per year, which is much faster than the target pace in MDG 5. However, we found substantial heterogeneity in levels and trends at the county level. In 1996, the range of maternal mortality ratios by county was 16·8 per 100 000 livebirths in Shantou, Guangdong, to 3510·3 per 100 000 livebirths in Zanda County, Tibet. Almost all counties showed remarkable decline in maternal mortality ratios in the two decades regardless of those in 1996. The annualised rate of decline across counties from 1996 to 2015 ranges from 4·4% to 12·9%, and 2838 (99·5%) of the 2852 counties had achieved the MDG 5 pace of decline. Decline accelerated between 2005 and 2015 compared with between 1996 and 2005. In 2015, the lowest county-level maternal mortality ratio was 3·4 per 100 000 livebirths in Nanhu District, Zhejiang Province. The highest was still in Zanda County, Tibet, but the fall to 830·5 per 100 000 livebirths was only 76·3%. 26 ethnic groups had population majorities in at least one county in China, and all had achieved declines in maternal mortality ratios in line with the pace of MDG 5. Intercounty Gini coefficients for maternal mortality ratio have declined at the national level in China, indicating improved equality, whereas trends in inequality at the provincial level varied.InterpretationIn the past two decades, maternal mortality ratios have reduced rapidly and universally across China at the county level. Fast improvement in maternal mortality ratios is possible even in less economically developed places with resource constraints. This finding has important implications for improving maternal mortality ratios in developing countries in the Sustainable Development Goal era.FundingNational Health and Family Planning Commission of the People's Republic of China, China Medical Board, WHO, University of Washington Center for Demography and Economics of Aging, Bill & Melinda Gates Foundation.Copyright © 2019 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.

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