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Predicting Iran's Achievement to Sustainable Development Goal 3.2: A Systematic Analysis of Neonatal Mortality With Scenario-Based Projections to 2030 Publisher Pubmed



Ebrahimi N1 ; Shahin S1 ; Koolaji S1 ; Ghanbari A1 ; Mehdipour P1, 2 ; Masinaei M1, 3 ; Moghaddam SS1 ; Rezaei N1, 4 ; Ghamari A1 ; Malekpour MR1 ; Rezaei N1, 4 ; Jamshidi H5 ; Larijani B4 ; Khosravi A6 Show All Authors
Authors
  1. Ebrahimi N1
  2. Shahin S1
  3. Koolaji S1
  4. Ghanbari A1
  5. Mehdipour P1, 2
  6. Masinaei M1, 3
  7. Moghaddam SS1
  8. Rezaei N1, 4
  9. Ghamari A1
  10. Malekpour MR1
  11. Rezaei N1, 4
  12. Jamshidi H5
  13. Larijani B4
  14. Khosravi A6
  15. Farzadfar F1, 4
Show Affiliations
Authors Affiliations
  1. 1. Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
  2. 2. Melbourne School of Population and Global Health, University of Melbourne, Parkville, Australia
  3. 3. Department of Epidemiology and Biostatistics, Tehran University of Medical Sciences, Tehran, Iran
  4. 4. Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
  5. 5. Department of Pharmacology, Research Institute for Endocrine Sciences, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
  6. 6. Deputy for Public Health, Ministry of Health and Medical Education, Tehran, Iran

Source: PLoS ONE Published:2023


Abstract

Background Sustainable Development Goal 3.2 (SDG 3.2) is to reduce Under-5 and neonatal mortality rates (U5MR and NMR), two major health systems' performance indicators, globally by 2030. We aimed to report Iran's U5MR and NMR status during 2010-2017 and its achievement of SDG 3.2 by 2030, using scenario-based projection. Study design To estimate the national and subnational levels of U5MR and NMR, we applied an Ensemble Bayesian Model Averaging (EBMA) with Gaussian Process Regression (GPR) and Spatio_-temporal models. We used all available data sources including: 12-year data from the Death Registration System (DRS), two censuses, and a demographic and health surveys (DHS). This study employed two approaches, Maternal Age Cohort (MAC) and Maternal Age Period (MAP), to analyze summary birth history data obtained from censuses and DHS. In addition, we calculated the child mortality rate directly from DHS using the complete birth history method. National and subnational NMR was projected up to 2030 with a scenario-based method using average Annual Rate of Reduction (ARR) introduced by UN-IGME. Results In 2017, national U5MR and NMR were 15-2 (12-4-18-0) and 11-8 (10-4-13-2), with an average ARR of 5-1% (2-1-8-9) and 3-1% (0-9-5-8) during 2010-2017, respectively. According to our projection scenarios, 17 provinces have not fulfilled SDG 3.2 for NMR yet, and the current trend (the current trend of NMR improvement in Iran) will not result in reaching SDG for some provinces by 2030; However, if each province has the same neonatal mortality annual reduction rate as the best-performing province in the same region, besides achieving SDG, the national NMR will be reduced to 5-2, and almost 92,000 newborn lives will be saved. Conclusions Iran has achieved SDG3.2 regarding U5MR and NMR; however, there are provincial inequalities. For all provinces to reach SDG3.2, health policies should focus on reducing provincial inequalities by precise planning for neonatal health care. Copyright: © 2023 Ebrahimi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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