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The trends of maternal mortality ratios and cause pattern in 34 Chinese provinces, 1990–2017
Background Understanding the trends and causes to the burden of maternal deaths is a key requirement to further reduce the maternal mortality ratio (MMR), and devise targeted intervention policy. We aimed to evaluate the spatiotemporal trends of MMRs and cause patterns across the 34 provinces of Chi...
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description | Background Understanding the trends and causes to the burden of maternal deaths is a key requirement to further reduce the maternal mortality ratio (MMR), and devise targeted intervention policy. We aimed to evaluate the spatiotemporal trends of MMRs and cause patterns across the 34 provinces of China during 1990-2017. Methods Using data from the Global Burden of Disease Study 2017, we calculated the levels and trends of total maternal deaths and MMR due to ten different causes through Bayesian multivariable regression model for pregnancies aged 10-54 years, and assessed the age and regional distribution over time. Results China has experienced fast decline in MMR, dropped from 95.2 (87.8-102.3) in 1990 to 13.6 (12.5-15.0) in 2017, with an annualised rate of decline of 7.0%. In 1990, the range of MMRs in mainland China was 31.1 in Shanghai, to 323.4 in Tibet. Almost all provinces showed remarkable decline in the last two decades. However, spatial heterogeneity in levels and trends still existed. The annualised rate of decline across provinces from 1990 to 2017 ranged from 0.54% to 10.14%. Decline accelerated between 2005 and 2017 compared with between 1990 and 2005. In 2017, the lowest MMR was 4.2 in Zhejiang; the highest was still in Tibet, but had fallen to 82.7, dropped by 74.4%. MMR was highest in the 40-49 years age group in both 1990 and 2017. In 2017, haemorrhage and hypertensive disorders were the leading two specific causes for maternal deaths. Conclusions MMRs have declined rapidly and universally across the provinces of China. Setting of associated interventions in the future will need careful consideration of provinces that still have MMR significantly higher than the national mean level. Keywords: Maternal mortality ratios, Cause pattern, Spatiotemporal trends, China |
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We aimed to evaluate the spatiotemporal trends of MMRs and cause patterns across the 34 provinces of China during 1990-2017. Methods Using data from the Global Burden of Disease Study 2017, we calculated the levels and trends of total maternal deaths and MMR due to ten different causes through Bayesian multivariable regression model for pregnancies aged 10-54 years, and assessed the age and regional distribution over time. Results China has experienced fast decline in MMR, dropped from 95.2 (87.8-102.3) in 1990 to 13.6 (12.5-15.0) in 2017, with an annualised rate of decline of 7.0%. In 1990, the range of MMRs in mainland China was 31.1 in Shanghai, to 323.4 in Tibet. Almost all provinces showed remarkable decline in the last two decades. However, spatial heterogeneity in levels and trends still existed. The annualised rate of decline across provinces from 1990 to 2017 ranged from 0.54% to 10.14%. Decline accelerated between 2005 and 2017 compared with between 1990 and 2005. In 2017, the lowest MMR was 4.2 in Zhejiang; the highest was still in Tibet, but had fallen to 82.7, dropped by 74.4%. MMR was highest in the 40-49 years age group in both 1990 and 2017. In 2017, haemorrhage and hypertensive disorders were the leading two specific causes for maternal deaths. Conclusions MMRs have declined rapidly and universally across the provinces of China. Setting of associated interventions in the future will need careful consideration of provinces that still have MMR significantly higher than the national mean level. Keywords: Maternal mortality ratios, Cause pattern, Spatiotemporal trends, China</description><identifier>ISSN: 1471-2458</identifier><identifier>EISSN: 1471-2458</identifier><identifier>DOI: 10.1186/s12889-022-13770-0</identifier><identifier>PMID: 35842611</identifier><language>eng</language><publisher>London: BioMed Central Ltd</publisher><subject>Age composition ; Age groups ; Bayesian analysis ; Cause pattern ; China ; Expected values ; Fatalities ; Fertility ; Hemorrhage ; Heterogeneity ; Maternal & child health ; Maternal mortality ; Maternal mortality ratios ; Methods ; Mortality ; Mothers ; Patient outcomes ; Pregnancy ; Provinces ; Public health ; Regression models ; Spatial analysis (Statistics) ; Spatial heterogeneity ; Spatiotemporal trends ; Trends ; Womens health</subject><ispartof>BMC public health, 2022-07, Vol.22 (1), p.1-1369, Article 1369</ispartof><rights>COPYRIGHT 2022 BioMed Central Ltd.</rights><rights>2022. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>The Author(s) 2022</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c540t-c1549fcd343f376129af48a660cb1c7ee7b3b28788b3f3bfbaebc376d3dc711a3</citedby><cites>FETCH-LOGICAL-c540t-c1549fcd343f376129af48a660cb1c7ee7b3b28788b3f3bfbaebc376d3dc711a3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9288211/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2691575001?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25753,27924,27925,37012,37013,44590,53791,53793</link.rule.ids></links><search><creatorcontrib>Li, Chang-li</creatorcontrib><creatorcontrib>Jiang, Meng</creatorcontrib><creatorcontrib>Huang, Ke-cheng</creatorcontrib><creatorcontrib>Li, Jian</creatorcontrib><creatorcontrib>Xu, Li-gang</creatorcontrib><title>The trends of maternal mortality ratios and cause pattern in 34 Chinese provinces, 1990–2017</title><title>BMC public health</title><description>Background Understanding the trends and causes to the burden of maternal deaths is a key requirement to further reduce the maternal mortality ratio (MMR), and devise targeted intervention policy. We aimed to evaluate the spatiotemporal trends of MMRs and cause patterns across the 34 provinces of China during 1990-2017. Methods Using data from the Global Burden of Disease Study 2017, we calculated the levels and trends of total maternal deaths and MMR due to ten different causes through Bayesian multivariable regression model for pregnancies aged 10-54 years, and assessed the age and regional distribution over time. Results China has experienced fast decline in MMR, dropped from 95.2 (87.8-102.3) in 1990 to 13.6 (12.5-15.0) in 2017, with an annualised rate of decline of 7.0%. In 1990, the range of MMRs in mainland China was 31.1 in Shanghai, to 323.4 in Tibet. Almost all provinces showed remarkable decline in the last two decades. However, spatial heterogeneity in levels and trends still existed. The annualised rate of decline across provinces from 1990 to 2017 ranged from 0.54% to 10.14%. Decline accelerated between 2005 and 2017 compared with between 1990 and 2005. In 2017, the lowest MMR was 4.2 in Zhejiang; the highest was still in Tibet, but had fallen to 82.7, dropped by 74.4%. MMR was highest in the 40-49 years age group in both 1990 and 2017. In 2017, haemorrhage and hypertensive disorders were the leading two specific causes for maternal deaths. Conclusions MMRs have declined rapidly and universally across the provinces of China. Setting of associated interventions in the future will need careful consideration of provinces that still have MMR significantly higher than the national mean level. Keywords: Maternal mortality ratios, Cause pattern, Spatiotemporal trends, China</description><subject>Age composition</subject><subject>Age groups</subject><subject>Bayesian analysis</subject><subject>Cause pattern</subject><subject>China</subject><subject>Expected values</subject><subject>Fatalities</subject><subject>Fertility</subject><subject>Hemorrhage</subject><subject>Heterogeneity</subject><subject>Maternal & child health</subject><subject>Maternal mortality</subject><subject>Maternal mortality ratios</subject><subject>Methods</subject><subject>Mortality</subject><subject>Mothers</subject><subject>Patient outcomes</subject><subject>Pregnancy</subject><subject>Provinces</subject><subject>Public health</subject><subject>Regression models</subject><subject>Spatial analysis (Statistics)</subject><subject>Spatial heterogeneity</subject><subject>Spatiotemporal trends</subject><subject>Trends</subject><subject>Womens health</subject><issn>1471-2458</issn><issn>1471-2458</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNptkstu1DAUhiMEoqXwAqwssWFBii-JLxukasSlUiU2ZYt1YjszHiX2YCeVuuMdeMM-SZ2mAgYhL2wdf-c_Ovr_qnpN8Dkhkr_PhEqpakxpTZgQuMZPqlPSCFLTppVP_3qfVC9y3mNMhGzp8-qEtbKhnJDT6vv1zqEpuWAzij0aYXIpwIDGmCYY_HSLEkw-ZgTBIgNzdugA0wIhHxBr0Gbng1uqKd74YFx-h4hS-O7nL1rGvaye9TBk9-rxPqu-ffp4vflSX339fLm5uKpN2-CpNqRtVG8sa1jPBCdUQd9I4BybjhjhnOhYR6WQsitA13fgOlNAy6wRhAA7qy5XXRthrw_Jj5BudQSvHwoxbTWkyZvBaWZaAVIKpYA3ljolOGe46TprmTCUFK0Pq9Zh7kZnjQtTguFI9Pgn-J3exhutih2ULAJvHwVS_DG7POnRZ-OGAYKLc9aUK4JbTDgu6Jt_0H2cFwNWqhVtMe0PtYWygA99LHPNIqovRJEqVipeqPP_UOVYN3oTg-t9qR810LXBpJhzcv3vHQnWS8L0mjBdEqYfEqYxuwfTiMAG</recordid><startdate>20220716</startdate><enddate>20220716</enddate><creator>Li, Chang-li</creator><creator>Jiang, Meng</creator><creator>Huang, Ke-cheng</creator><creator>Li, Jian</creator><creator>Xu, Li-gang</creator><general>BioMed Central Ltd</general><general>BioMed Central</general><general>BMC</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7T2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8C1</scope><scope>8FE</scope><scope>8FG</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AN0</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>L6V</scope><scope>M0S</scope><scope>M1P</scope><scope>M7S</scope><scope>PATMY</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20220716</creationdate><title>The trends of maternal mortality ratios and cause pattern in 34 Chinese provinces, 1990–2017</title><author>Li, Chang-li ; Jiang, Meng ; Huang, Ke-cheng ; Li, Jian ; Xu, Li-gang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c540t-c1549fcd343f376129af48a660cb1c7ee7b3b28788b3f3bfbaebc376d3dc711a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Age composition</topic><topic>Age groups</topic><topic>Bayesian analysis</topic><topic>Cause pattern</topic><topic>China</topic><topic>Expected values</topic><topic>Fatalities</topic><topic>Fertility</topic><topic>Hemorrhage</topic><topic>Heterogeneity</topic><topic>Maternal & child health</topic><topic>Maternal mortality</topic><topic>Maternal mortality ratios</topic><topic>Methods</topic><topic>Mortality</topic><topic>Mothers</topic><topic>Patient outcomes</topic><topic>Pregnancy</topic><topic>Provinces</topic><topic>Public health</topic><topic>Regression models</topic><topic>Spatial analysis (Statistics)</topic><topic>Spatial heterogeneity</topic><topic>Spatiotemporal trends</topic><topic>Trends</topic><topic>Womens health</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, Chang-li</creatorcontrib><creatorcontrib>Jiang, Meng</creatorcontrib><creatorcontrib>Huang, Ke-cheng</creatorcontrib><creatorcontrib>Li, Jian</creatorcontrib><creatorcontrib>Xu, Li-gang</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health and Safety Science Abstracts (Full archive)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Public Health Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>British Nursing Database</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Engineering Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Engineering Database</collection><collection>Environmental Science Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering collection</collection><collection>Environmental Science Collection</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>BMC public health</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, Chang-li</au><au>Jiang, Meng</au><au>Huang, Ke-cheng</au><au>Li, Jian</au><au>Xu, Li-gang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The trends of maternal mortality ratios and cause pattern in 34 Chinese provinces, 1990–2017</atitle><jtitle>BMC public health</jtitle><date>2022-07-16</date><risdate>2022</risdate><volume>22</volume><issue>1</issue><spage>1</spage><epage>1369</epage><pages>1-1369</pages><artnum>1369</artnum><issn>1471-2458</issn><eissn>1471-2458</eissn><abstract>Background Understanding the trends and causes to the burden of maternal deaths is a key requirement to further reduce the maternal mortality ratio (MMR), and devise targeted intervention policy. We aimed to evaluate the spatiotemporal trends of MMRs and cause patterns across the 34 provinces of China during 1990-2017. Methods Using data from the Global Burden of Disease Study 2017, we calculated the levels and trends of total maternal deaths and MMR due to ten different causes through Bayesian multivariable regression model for pregnancies aged 10-54 years, and assessed the age and regional distribution over time. Results China has experienced fast decline in MMR, dropped from 95.2 (87.8-102.3) in 1990 to 13.6 (12.5-15.0) in 2017, with an annualised rate of decline of 7.0%. In 1990, the range of MMRs in mainland China was 31.1 in Shanghai, to 323.4 in Tibet. Almost all provinces showed remarkable decline in the last two decades. However, spatial heterogeneity in levels and trends still existed. The annualised rate of decline across provinces from 1990 to 2017 ranged from 0.54% to 10.14%. Decline accelerated between 2005 and 2017 compared with between 1990 and 2005. In 2017, the lowest MMR was 4.2 in Zhejiang; the highest was still in Tibet, but had fallen to 82.7, dropped by 74.4%. MMR was highest in the 40-49 years age group in both 1990 and 2017. In 2017, haemorrhage and hypertensive disorders were the leading two specific causes for maternal deaths. Conclusions MMRs have declined rapidly and universally across the provinces of China. Setting of associated interventions in the future will need careful consideration of provinces that still have MMR significantly higher than the national mean level. Keywords: Maternal mortality ratios, Cause pattern, Spatiotemporal trends, China</abstract><cop>London</cop><pub>BioMed Central Ltd</pub><pmid>35842611</pmid><doi>10.1186/s12889-022-13770-0</doi><oa>free_for_read</oa></addata></record> |
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subjects | Age composition Age groups Bayesian analysis Cause pattern China Expected values Fatalities Fertility Hemorrhage Heterogeneity Maternal & child health Maternal mortality Maternal mortality ratios Methods Mortality Mothers Patient outcomes Pregnancy Provinces Public health Regression models Spatial analysis (Statistics) Spatial heterogeneity Spatiotemporal trends Trends Womens health |
title | The trends of maternal mortality ratios and cause pattern in 34 Chinese provinces, 1990–2017 |
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