Global burden of maternal disorders attributable to malnutrition from 1990 to 2019 and predictions to 2035: worsening or improving?
Background and aimsMaternal malnutrition is a major global public health problem that can lead to serious maternal diseases. This study aimed to analyze and predict the spatio-temporal trends in the burden of maternal disorders attributable to malnutrition, and to provide a basis for scientific impr...
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Frontiers Media S.A.
2024-02-01
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| Series: | Frontiers in Nutrition |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fnut.2024.1343772/full |
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| author | Tongtong Xu Chenxian Dong Jianjiang Shao Chaojing Huo Zuhai Chen Zhengyang Shi Teng Yao Chenyang Gu Wanting Wei Dongsheng Rui Dongsheng Rui Dongsheng Rui Dongsheng Rui Xiaoju Li Xiaoju Li Xiaoju Li Xiaoju Li Yunhua Hu Yunhua Hu Yunhua Hu Yunhua Hu Jiaolong Ma Jiaolong Ma Jiaolong Ma Jiaolong Ma Qiang Niu Qiang Niu Qiang Niu Qiang Niu Yizhong Yan Yizhong Yan Yizhong Yan Yizhong Yan |
| author_facet | Tongtong Xu Chenxian Dong Jianjiang Shao Chaojing Huo Zuhai Chen Zhengyang Shi Teng Yao Chenyang Gu Wanting Wei Dongsheng Rui Dongsheng Rui Dongsheng Rui Dongsheng Rui Xiaoju Li Xiaoju Li Xiaoju Li Xiaoju Li Yunhua Hu Yunhua Hu Yunhua Hu Yunhua Hu Jiaolong Ma Jiaolong Ma Jiaolong Ma Jiaolong Ma Qiang Niu Qiang Niu Qiang Niu Qiang Niu Yizhong Yan Yizhong Yan Yizhong Yan Yizhong Yan |
| author_sort | Tongtong Xu |
| collection | DOAJ |
| description | Background and aimsMaternal malnutrition is a major global public health problem that can lead to serious maternal diseases. This study aimed to analyze and predict the spatio-temporal trends in the burden of maternal disorders attributable to malnutrition, and to provide a basis for scientific improvement of maternal malnutrition and targeted prevention of maternal disorders.MethodsData on maternal disorders attributable to malnutrition, including number of deaths, disability-adjusted life years (DALYs), population attributable fractions (PAFs), age-standardized mortality rates (ASMRs), and age-standardized DALY rates (ASDRs) were obtained from the Global Burden of Disease Study 2019 to describe their epidemiological characteristics by age, region, year, and type of disease. A log-linear regression model was used to calculate the annual percentage change (AAPC) of ASMR or ASDR to reflect their temporal trends. Bayesian age-period-cohort model was used to predict the number of deaths and mortality rates to 2035.ResultsGlobal number of deaths and DALYs for maternal disorders attributable to malnutrition declined by 42.35 and 41.61% from 1990 to 2019, with an AAPC of –3.09 (95% CI: −3.31, −2.88) and –2.98 (95% CI: −3.20, −2.77) for ASMR and ASDR, respectively. The burden was higher among younger pregnant women (20–29 years) in low and low-middle socio-demographic index (SDI) regions, whereas it was higher among older pregnant women (30–39 years) in high SDI region. Both ASMR and ASDR showed a significant decreasing trend with increasing SDI. Maternal hemorrhage had the highest burden of all diseases. Global deaths are predicted to decline from 42,350 in 2019 to 38,461 in 2035, with the ASMR declining from 1.08 (95% UI: 0.38, 1.79) to 0.89 (95% UI: 0.47, 1.31).ConclusionMaternal malnutrition is improving globally, but in the context of the global food crisis, attention needs to be paid to malnutrition in low SDI regions, especially among young pregnant women, and corresponding measures need to be taken to effectively reduce the burden of disease. |
| first_indexed | 2024-03-08T00:50:47Z |
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| language | English |
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| publishDate | 2024-02-01 |
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| series | Frontiers in Nutrition |
| spelling | doaj.art-3858d4ddc9e845de8f73cb32903bce6d2024-02-15T04:30:55ZengFrontiers Media S.A.Frontiers in Nutrition2296-861X2024-02-011110.3389/fnut.2024.13437721343772Global burden of maternal disorders attributable to malnutrition from 1990 to 2019 and predictions to 2035: worsening or improving?Tongtong Xu0Chenxian Dong1Jianjiang Shao2Chaojing Huo3Zuhai Chen4Zhengyang Shi5Teng Yao6Chenyang Gu7Wanting Wei8Dongsheng Rui9Dongsheng Rui10Dongsheng Rui11Dongsheng Rui12Xiaoju Li13Xiaoju Li14Xiaoju Li15Xiaoju Li16Yunhua Hu17Yunhua Hu18Yunhua Hu19Yunhua Hu20Jiaolong Ma21Jiaolong Ma22Jiaolong Ma23Jiaolong Ma24Qiang Niu25Qiang Niu26Qiang Niu27Qiang Niu28Yizhong Yan29Yizhong Yan30Yizhong Yan31Yizhong Yan32Department of Preventive Medicine, School of Medicine, Shihezi University, Shihezi, Xinjiang, ChinaDepartment of Preventive Medicine, School of Medicine, Shihezi University, Shihezi, Xinjiang, ChinaDepartment of Preventive Medicine, School of Medicine, Shihezi University, Shihezi, Xinjiang, ChinaDepartment of Preventive Medicine, School of Medicine, Shihezi University, Shihezi, Xinjiang, ChinaDepartment of Preventive Medicine, School of Medicine, Shihezi University, Shihezi, Xinjiang, ChinaDepartment of Preventive Medicine, School of Medicine, Shihezi University, Shihezi, Xinjiang, ChinaDepartment of Preventive Medicine, School of Medicine, Shihezi University, Shihezi, Xinjiang, ChinaDepartment of Preventive Medicine, School of Medicine, Shihezi University, Shihezi, Xinjiang, ChinaDepartment of Preventive Medicine, School of Medicine, Shihezi University, Shihezi, Xinjiang, ChinaDepartment of Preventive Medicine, School of Medicine, Shihezi University, Shihezi, Xinjiang, ChinaKey Laboratory for Prevention and Control of Emerging Infectious Diseases and Public Health Security, The Xinjiang Production and Construction Corps, Shihezi, Xinjiang, ChinaKey Laboratory of Preventive Medicine, Shihezi University, Shihezi, Xinjiang, ChinaKey Laboratory of Xinjiang Endemic and Ethnic Diseases (Ministry of Education), School of Medicine, Shihezi University, Xinjiang, Shihezi, ChinaDepartment of Preventive Medicine, School of Medicine, Shihezi University, Shihezi, Xinjiang, ChinaKey Laboratory for Prevention and Control of Emerging Infectious Diseases and Public Health Security, The Xinjiang Production and Construction Corps, Shihezi, Xinjiang, ChinaKey Laboratory of Preventive Medicine, Shihezi University, Shihezi, Xinjiang, ChinaKey Laboratory of Xinjiang Endemic and Ethnic Diseases (Ministry of Education), School of Medicine, Shihezi University, Xinjiang, Shihezi, ChinaDepartment of Preventive Medicine, School of Medicine, Shihezi University, Shihezi, Xinjiang, ChinaKey Laboratory for Prevention and Control of Emerging Infectious Diseases and Public Health Security, The Xinjiang Production and Construction Corps, Shihezi, Xinjiang, ChinaKey Laboratory of Preventive Medicine, Shihezi University, Shihezi, Xinjiang, ChinaKey Laboratory of Xinjiang Endemic and Ethnic Diseases (Ministry of Education), School of Medicine, Shihezi University, Xinjiang, Shihezi, ChinaDepartment of Preventive Medicine, School of Medicine, Shihezi University, Shihezi, Xinjiang, ChinaKey Laboratory for Prevention and Control of Emerging Infectious Diseases and Public Health Security, The Xinjiang Production and Construction Corps, Shihezi, Xinjiang, ChinaKey Laboratory of Preventive Medicine, Shihezi University, Shihezi, Xinjiang, ChinaKey Laboratory of Xinjiang Endemic and Ethnic Diseases (Ministry of Education), School of Medicine, Shihezi University, Xinjiang, Shihezi, ChinaDepartment of Preventive Medicine, School of Medicine, Shihezi University, Shihezi, Xinjiang, ChinaKey Laboratory for Prevention and Control of Emerging Infectious Diseases and Public Health Security, The Xinjiang Production and Construction Corps, Shihezi, Xinjiang, ChinaKey Laboratory of Preventive Medicine, Shihezi University, Shihezi, Xinjiang, ChinaKey Laboratory of Xinjiang Endemic and Ethnic Diseases (Ministry of Education), School of Medicine, Shihezi University, Xinjiang, Shihezi, ChinaDepartment of Preventive Medicine, School of Medicine, Shihezi University, Shihezi, Xinjiang, ChinaKey Laboratory for Prevention and Control of Emerging Infectious Diseases and Public Health Security, The Xinjiang Production and Construction Corps, Shihezi, Xinjiang, ChinaKey Laboratory of Preventive Medicine, Shihezi University, Shihezi, Xinjiang, ChinaKey Laboratory of Xinjiang Endemic and Ethnic Diseases (Ministry of Education), School of Medicine, Shihezi University, Xinjiang, Shihezi, ChinaBackground and aimsMaternal malnutrition is a major global public health problem that can lead to serious maternal diseases. This study aimed to analyze and predict the spatio-temporal trends in the burden of maternal disorders attributable to malnutrition, and to provide a basis for scientific improvement of maternal malnutrition and targeted prevention of maternal disorders.MethodsData on maternal disorders attributable to malnutrition, including number of deaths, disability-adjusted life years (DALYs), population attributable fractions (PAFs), age-standardized mortality rates (ASMRs), and age-standardized DALY rates (ASDRs) were obtained from the Global Burden of Disease Study 2019 to describe their epidemiological characteristics by age, region, year, and type of disease. A log-linear regression model was used to calculate the annual percentage change (AAPC) of ASMR or ASDR to reflect their temporal trends. Bayesian age-period-cohort model was used to predict the number of deaths and mortality rates to 2035.ResultsGlobal number of deaths and DALYs for maternal disorders attributable to malnutrition declined by 42.35 and 41.61% from 1990 to 2019, with an AAPC of –3.09 (95% CI: −3.31, −2.88) and –2.98 (95% CI: −3.20, −2.77) for ASMR and ASDR, respectively. The burden was higher among younger pregnant women (20–29 years) in low and low-middle socio-demographic index (SDI) regions, whereas it was higher among older pregnant women (30–39 years) in high SDI region. Both ASMR and ASDR showed a significant decreasing trend with increasing SDI. Maternal hemorrhage had the highest burden of all diseases. Global deaths are predicted to decline from 42,350 in 2019 to 38,461 in 2035, with the ASMR declining from 1.08 (95% UI: 0.38, 1.79) to 0.89 (95% UI: 0.47, 1.31).ConclusionMaternal malnutrition is improving globally, but in the context of the global food crisis, attention needs to be paid to malnutrition in low SDI regions, especially among young pregnant women, and corresponding measures need to be taken to effectively reduce the burden of disease.https://www.frontiersin.org/articles/10.3389/fnut.2024.1343772/fullglobal burdenmalnutritionmaternal disorderspredictionepidemiology |
| spellingShingle | Tongtong Xu Chenxian Dong Jianjiang Shao Chaojing Huo Zuhai Chen Zhengyang Shi Teng Yao Chenyang Gu Wanting Wei Dongsheng Rui Dongsheng Rui Dongsheng Rui Dongsheng Rui Xiaoju Li Xiaoju Li Xiaoju Li Xiaoju Li Yunhua Hu Yunhua Hu Yunhua Hu Yunhua Hu Jiaolong Ma Jiaolong Ma Jiaolong Ma Jiaolong Ma Qiang Niu Qiang Niu Qiang Niu Qiang Niu Yizhong Yan Yizhong Yan Yizhong Yan Yizhong Yan Global burden of maternal disorders attributable to malnutrition from 1990 to 2019 and predictions to 2035: worsening or improving? Frontiers in Nutrition global burden malnutrition maternal disorders prediction epidemiology |
| title | Global burden of maternal disorders attributable to malnutrition from 1990 to 2019 and predictions to 2035: worsening or improving? |
| title_full | Global burden of maternal disorders attributable to malnutrition from 1990 to 2019 and predictions to 2035: worsening or improving? |
| title_fullStr | Global burden of maternal disorders attributable to malnutrition from 1990 to 2019 and predictions to 2035: worsening or improving? |
| title_full_unstemmed | Global burden of maternal disorders attributable to malnutrition from 1990 to 2019 and predictions to 2035: worsening or improving? |
| title_short | Global burden of maternal disorders attributable to malnutrition from 1990 to 2019 and predictions to 2035: worsening or improving? |
| title_sort | global burden of maternal disorders attributable to malnutrition from 1990 to 2019 and predictions to 2035 worsening or improving |
| topic | global burden malnutrition maternal disorders prediction epidemiology |
| url | https://www.frontiersin.org/articles/10.3389/fnut.2024.1343772/full |
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