Predicting Iran’s achievement to Sustainable Development Goal 3.2: A systematic analysis of neonatal mortality with scenario-based projections to 2030

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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.

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Most cited references 41

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Global, regional, and national causes of under-5 mortality in 2000–15: an updated systematic analysis with implications for the Sustainable Development Goals

Li Liu, Shefali Oza, Dan Hogan … (2016)

Summary Background Despite remarkable progress in the improvement of child survival between 1990 and 2015, the Millennium Development Goal (MDG) 4 target of a two-thirds reduction of under-5 mortality rate (U5MR) was not achieved globally. In this paper, we updated our annual estimates of child mortality by cause to 2000–15 to reflect on progress toward the MDG 4 and consider implications for the Sustainable Development Goals (SDG) target for child survival. Methods We increased the estimation input data for causes of deaths by 43% among neonates and 23% among 1–59-month-olds, respectively. We used adequate vital registration (VR) data where available, and modelled cause-specific mortality fractions applying multinomial logistic regressions using adequate VR for low U5MR countries and verbal autopsy data for high U5MR countries. We updated the estimation to use Plasmodium falciparum parasite rate in place of malaria index in the modelling of malaria deaths; to use adjusted empirical estimates instead of modelled estimates for China; and to consider the effects of pneumococcal conjugate vaccine and rotavirus vaccine in the estimation. Findings In 2015, among the 5·9 million under-5 deaths, 2·7 million occurred in the neonatal period. The leading under-5 causes were preterm birth complications (1·055 million [95% uncertainty range (UR) 0·935–1·179]), pneumonia (0·921 million [0·812 −1·117]), and intrapartum-related events (0·691 million [0·598 −0·778]). In the two MDG regions with the most under-5 deaths, the leading cause was pneumonia in sub-Saharan Africa and preterm birth complications in southern Asia. Reductions in mortality rates for pneumonia, diarrhoea, neonatal intrapartum-related events, malaria, and measles were responsible for 61% of the total reduction of 35 per 1000 livebirths in U5MR in 2000–15. Stratified by U5MR, pneumonia was the leading cause in countries with very high U5MR. Preterm birth complications and pneumonia were both important in high, medium high, and medium child mortality countries; whereas congenital abnormalities was the most important cause in countries with low and very low U5MR. Interpretation In the SDG era, countries are advised to prioritise child survival policy and programmes based on their child cause-of-death composition. Continued and enhanced efforts to scale up proven life-saving interventions are needed to achieve the SDG child survival target. Funding Bill & Melinda Gates Foundation, WHO.

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How can I deal with missing data in my study?

D A Bennett (2001)

Missing data in medical research is a common problem that has long been recognised by statisticians and medical researchers alike. In general, if the effect of missing data is not taken into account the results of the statistical analyses will be biased and the amount of variability in the data will not be correctly estimated. There are three main types of missing data pattern: Missing Completely At Random (MCAR), Missing At Random (MAR) and Not Missing At Random (NMAR). The type of missing data that a researcher has in their dataset determines the appropriate method to use in handling the missing data before a formal statistical analysis begins. The aim of this practice note is to describe these patterns of missing data and how they can occur, as well describing the methods of handling them. Simple and more complex methods are described, including the advantages and disadvantages of each method as well as their availability in routine software. It is good practice to perform a sensitivity analysis employing different missing data techniques in order to assess the robustness of the conclusions drawn from each approach.

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Can available interventions end preventable deaths in mothers, newborn babies, and stillbirths, and at what cost?

Zulfiqar Bhutta, Jai K Das, Rajiv Bahl … (2014)

Progress in newborn survival has been slow, and even more so for reductions in stillbirths. To meet Every Newborn targets of ten or fewer neonatal deaths and ten or fewer stillbirths per 1000 births in every country by 2035 will necessitate accelerated scale-up of the most effective care targeting major causes of newborn deaths. We have systematically reviewed interventions across the continuum of care and various delivery platforms, and then modelled the effect and cost of scale-up in the 75 high-burden Countdown countries. Closure of the quality gap through the provision of effective care for all women and newborn babies delivering in facilities could prevent an estimated 113,000 maternal deaths, 531,000 stillbirths, and 1·325 million neonatal deaths annually by 2020 at an estimated running cost of US$4·5 billion per year (US$0·9 per person). Increased coverage and quality of preconception, antenatal, intrapartum, and postnatal interventions by 2025 could avert 71% of neonatal deaths (1·9 million [range 1·6-2·1 million]), 33% of stillbirths (0·82 million [0·60-0·93 million]), and 54% of maternal deaths (0·16 million [0·14-0·17 million]) per year. These reductions can be achieved at an annual incremental running cost of US$5·65 billion (US$1·15 per person), which amounts to US$1928 for each life saved, including stillbirths, neonatal, and maternal deaths. Most (82%) of this effect is attributable to facility-based care which, although more expensive than community-based strategies, improves the likelihood of survival. Most of the running costs are also for facility-based care (US$3·66 billion or 64%), even without the cost of new hospitals and country-specific capital inputs being factored in. The maximum effect on neonatal deaths is through interventions delivered during labour and birth, including for obstetric complications (41%), followed by care of small and ill newborn babies (30%). To meet the unmet need for family planning with modern contraceptives would be synergistic, and would contribute to around a halving of births and therefore deaths. Our analysis also indicates that available interventions can reduce the three most common cause of neonatal mortality--preterm, intrapartum, and infection-related deaths--by 58%, 79%, and 84%, respectively. Copyright © 2014 Elsevier Ltd. All rights reserved.

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Author and article information

Contributors

Narges Ebrahimi: Role: ConceptualizationRole: Writing – original draft

Sarvenaz Shahin: Role: InvestigationRole: Writing – original draft

Sogol Koolaji: Role: InvestigationRole: Writing – original draft

Ali Ghanbari: Role: MethodologyRole: VisualizationRole: Writing – review & editing

Parinaz Mehdipour: Role: Data curationRole: SoftwareRole: Writing – review & editing

Masoud Masinaei: Role: MethodologyRole: Writing – review & editing

Sahar Saeedi Moghaddam: Role: MethodologyRole: Writing – review & editing

Negar Rezaei: Role: Writing – review & editing

Azin Ghamari: Role: InvestigationRole: Writing – review & editing

Mohammad-Reza Malekpour:

ORCID: https://orcid.org/0000-0002-8648-5402

Role: Data curationRole: Writing – review & editing

Nazila Rezaei: Role: Project administrationRole: Writing – review & editing

Hamidreza Jamshidi: Role: Writing – review & editing

Bagher Larijani:

ORCID: https://orcid.org/0000-0001-5386-7597

Role: Writing – review & editing

Ardeshir Khosravi: Role: Writing – review & editing

Farshad Farzadfar:

ORCID: https://orcid.org/0000-0001-8288-4046

Role: ConceptualizationRole: Writing – review & editing

Xiaohong Li: Role: Editor

Journal

Journal ID (nlm-ta): PLoS One

Journal ID (iso-abbrev): PLoS One

Journal ID (publisher-id): plos

Title: PLOS ONE

Publisher: Public Library of Science (San Francisco, CA USA )

ISSN (Electronic): 1932-6203

Publication date (Electronic): 6 April 2023

Publication date Collection: 2023

Volume: 18

Issue: 4

Electronic Location Identifier: e0283784

Affiliations

[1 ] Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran

[2 ] Melbourne School of Population and Global Health, University of Melbourne, Parkville, Australia

[3 ] Department of Epidemiology and Biostatistics, Tehran University of Medical Sciences, Tehran, Iran

[4 ] Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran

[5 ] Department of Pharmacology, Research Institute for Endocrine Sciences, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran

[6 ] Deputy for Public Health, Ministry of Health and Medical Education, Tehran, Iran

West China Second University Hospital of Sichuan University, CHINA

Author notes

Competing Interests: The authors have declared that no competing interests exist.

‡ NE and SS contributed equally to this work as Co-first authors.

* E-mail: f–farzadfar@ 123456tums.ac.ir

Author information

Mohammad-Reza Malekpour https://orcid.org/0000-0002-8648-5402

Bagher Larijani https://orcid.org/0000-0001-5386-7597

Farshad Farzadfar https://orcid.org/0000-0001-8288-4046

Article

Publisher ID: PONE-D-22-18310

DOI: 10.1371/journal.pone.0283784

PMC ID: 10079046

SO-VID: 003a5308-b800-438a-b199-86fb9e079326

License:

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.

History

Date received : 28 June 2022

Date accepted : 16 March 2023

Page count

Figures: 7, Tables: 1, Pages: 19

Funding

Funded by: Iran’s Ministry of Health and Education.

This study was funded by Iran’s Ministry of Health and Education. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Data Availability All data used for this study is available and is uploaded as an excel file.

Predicting Iran’s achievement to Sustainable Development Goal 3.2: A systematic analysis of neonatal mortality with scenario-based projections to 2030

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Study design

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Conclusions

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UN Sustainable Development Goals

Most cited references 41

Global, regional, and national causes of under-5 mortality in 2000–15: an updated systematic analysis with implications for the Sustainable Development Goals

How can I deal with missing data in my study?

Can available interventions end preventable deaths in mothers, newborn babies, and stillbirths, and at what cost?

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