Global landscape of neonatal disorders attributed to environmental and maternal risks over three decades
Neonatal disorders persist as a leading contributor to global child mortality. While particulate matter (PM2.5), low birth weight (LBW), and short gestation (SG) are well-documented risk factors, comprehensive assessments of their population-attributable burdens remain critically lacking. We analyze...
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Elsevier
2025-07-01
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| Series: | Ecotoxicology and Environmental Safety |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S014765132500747X |
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| author | Xue-Er Cheng Jian Tang Man Ge Yi-Sheng He Xiao-Xiao Li Yi-Qing Xu Hai-Fen Wei Dan-Ni Zhu Peng Wang Hai-Feng Pan |
| author_facet | Xue-Er Cheng Jian Tang Man Ge Yi-Sheng He Xiao-Xiao Li Yi-Qing Xu Hai-Fen Wei Dan-Ni Zhu Peng Wang Hai-Feng Pan |
| author_sort | Xue-Er Cheng |
| collection | DOAJ |
| description | Neonatal disorders persist as a leading contributor to global child mortality. While particulate matter (PM2.5), low birth weight (LBW), and short gestation (SG) are well-documented risk factors, comprehensive assessments of their population-attributable burdens remain critically lacking. We analyzed data from the Global Burden of Disease Study 2021 to assess the global, regional, and national burden of neonatal disorders attributable to PM2.5 exposure, LBW and SG from 1990 to 2021, situating these risk factors within a comprehensive framework to enable direct comparison across domains. Outcomes included deaths and disability-adjusted life years (DALYs), disaggregated by sex, disease subtype, and Socio-demographic Index (SDI). In 2021, 81.01 % of the global neonatal deaths were linked to LBW and SG (1.48 million deaths), with an Estimated Annual Percentage Change (EAPC) in age-standardized rate (ASR) of −1.48 (95 % CI: −1.56 to −1.40) since 1990. PM2.5 exposure was responsible for 27.18 % of neonatal deaths (496,966 deaths), with an EAPC in ASR of −1.53 (95 % CI: −1.63 to −1.43) since 1990. Preterm birth represented the highest burden of disease subtype. Males consistently experienced a higher burden across both risk factors. Regional disparities were observed, with South Asia bearing the highest burden and high-SDI regions such as Australasia reporting the lowest. Strong inverse correlations were observed between SDI and PM2.5, LBW and SG-related neonatal mortality and DALYs. A temporary increase in ambient PM2.5-attributable burden was noted between 2010 and 2014. Despite progress in reducing household PM2.5 and improving neonatal care, ambient PM2.5 continues to pose a significant threat, particularly in low-SDI regions. The high burden of LBW and SG underscores the need for targeted maternal health interventions. Comprehensive, region-specific strategies that address both environmental and maternal factors are essential to reducing neonatal mortality and achieving global health goals. |
| format | Article |
| id | doaj-art-eaf7ab2db62e408c9df9ef6dc74f7775 |
| institution | OA Journals |
| issn | 0147-6513 |
| language | English |
| publishDate | 2025-07-01 |
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| series | Ecotoxicology and Environmental Safety |
| spelling | doaj-art-eaf7ab2db62e408c9df9ef6dc74f77752025-08-20T02:32:26ZengElsevierEcotoxicology and Environmental Safety0147-65132025-07-0129911841110.1016/j.ecoenv.2025.118411Global landscape of neonatal disorders attributed to environmental and maternal risks over three decadesXue-Er Cheng0Jian Tang1Man Ge2Yi-Sheng He3Xiao-Xiao Li4Yi-Qing Xu5Hai-Fen Wei6Dan-Ni Zhu7Peng Wang8Hai-Feng Pan9Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China; Center for Big Data and Population Health of IHM, Anhui Medical University, Hefei, Anhui, ChinaDepartment of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China; Center for Big Data and Population Health of IHM, Anhui Medical University, Hefei, Anhui, ChinaDepartment of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China; Center for Big Data and Population Health of IHM, Anhui Medical University, Hefei, Anhui, ChinaDepartment of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China; Center for Big Data and Population Health of IHM, Anhui Medical University, Hefei, Anhui, ChinaDepartment of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China; Center for Big Data and Population Health of IHM, Anhui Medical University, Hefei, Anhui, ChinaDepartment of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China; Center for Big Data and Population Health of IHM, Anhui Medical University, Hefei, Anhui, ChinaDepartment of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China; Center for Big Data and Population Health of IHM, Anhui Medical University, Hefei, Anhui, ChinaDepartment of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, ChinaDepartment of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Department of Health Promotion and Behavioral Sciences, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, China; Correspondence to: Department of Health Promotion and Behavioral Sciences, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui 230032, ChinaDepartment of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China; Center for Big Data and Population Health of IHM, Anhui Medical University, Hefei, Anhui, China; Correspondence to: Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei 230032, ChinaNeonatal disorders persist as a leading contributor to global child mortality. While particulate matter (PM2.5), low birth weight (LBW), and short gestation (SG) are well-documented risk factors, comprehensive assessments of their population-attributable burdens remain critically lacking. We analyzed data from the Global Burden of Disease Study 2021 to assess the global, regional, and national burden of neonatal disorders attributable to PM2.5 exposure, LBW and SG from 1990 to 2021, situating these risk factors within a comprehensive framework to enable direct comparison across domains. Outcomes included deaths and disability-adjusted life years (DALYs), disaggregated by sex, disease subtype, and Socio-demographic Index (SDI). In 2021, 81.01 % of the global neonatal deaths were linked to LBW and SG (1.48 million deaths), with an Estimated Annual Percentage Change (EAPC) in age-standardized rate (ASR) of −1.48 (95 % CI: −1.56 to −1.40) since 1990. PM2.5 exposure was responsible for 27.18 % of neonatal deaths (496,966 deaths), with an EAPC in ASR of −1.53 (95 % CI: −1.63 to −1.43) since 1990. Preterm birth represented the highest burden of disease subtype. Males consistently experienced a higher burden across both risk factors. Regional disparities were observed, with South Asia bearing the highest burden and high-SDI regions such as Australasia reporting the lowest. Strong inverse correlations were observed between SDI and PM2.5, LBW and SG-related neonatal mortality and DALYs. A temporary increase in ambient PM2.5-attributable burden was noted between 2010 and 2014. Despite progress in reducing household PM2.5 and improving neonatal care, ambient PM2.5 continues to pose a significant threat, particularly in low-SDI regions. The high burden of LBW and SG underscores the need for targeted maternal health interventions. Comprehensive, region-specific strategies that address both environmental and maternal factors are essential to reducing neonatal mortality and achieving global health goals.http://www.sciencedirect.com/science/article/pii/S014765132500747XNeonatal disordersPM2.5Low birth weightShort gestationGlobal burdenEpidemiology |
| spellingShingle | Xue-Er Cheng Jian Tang Man Ge Yi-Sheng He Xiao-Xiao Li Yi-Qing Xu Hai-Fen Wei Dan-Ni Zhu Peng Wang Hai-Feng Pan Global landscape of neonatal disorders attributed to environmental and maternal risks over three decades Ecotoxicology and Environmental Safety Neonatal disorders PM2.5 Low birth weight Short gestation Global burden Epidemiology |
| title | Global landscape of neonatal disorders attributed to environmental and maternal risks over three decades |
| title_full | Global landscape of neonatal disorders attributed to environmental and maternal risks over three decades |
| title_fullStr | Global landscape of neonatal disorders attributed to environmental and maternal risks over three decades |
| title_full_unstemmed | Global landscape of neonatal disorders attributed to environmental and maternal risks over three decades |
| title_short | Global landscape of neonatal disorders attributed to environmental and maternal risks over three decades |
| title_sort | global landscape of neonatal disorders attributed to environmental and maternal risks over three decades |
| topic | Neonatal disorders PM2.5 Low birth weight Short gestation Global burden Epidemiology |
| url | http://www.sciencedirect.com/science/article/pii/S014765132500747X |
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