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      Multilevel negative binomial analysis of factors associated with numbers of antenatal care contacts in low and middle income countries: Findings from 59 nationally representative datasets

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          Abstract

          Background

          Antenatal care (ANC) is one of the recommended interventions to reduce stillbirth, maternal, neonatal, and child mortality through early identification and management of pregnancy complications or pre-existing conditions. Although increasing number of ANC is a key priority of the 2016 WHO recommendations, ANC uptake in Low and Middle Income Countries (LMICs) is insufficient. Therefore, this study aimed to investigate factors associated with the number of ANC contacts in LMICs.

          Methods

          Data for the study were drawn from 59 recent Demographic and Health Surveys (DHS) conducted in LMICS. We included a total sample of 520,377 mothers who gave birth in the five years preceding the survey. A multilevel negative binomial regression model was applied to identify factors that may affect number of ANC. Adjusted incidence rate ratios (AIRR) with 95% Confidence Interval (CI) were reported to show association.

          Results

          This study found that mothers and their partner with higher educational attainment, mothers aged >35 years, mothers who had decision making autonomy, mothers from female headed household, mothers from richer and richest household, mothers exposed to media, and residing in urban areas had significantly more ANC contacts. However, number of ANC contacts were significantly lower among mothers who initiated ANC after 12 weeks of gestation and perceived healthcare access to be a big problem.

          Conclusion

          Our results suggest that individual, household, and community-level factors were associated with number of ANC contacts among pregnant mothers in LMICs. Hence, local and international policymakers, and programmers should focus on improving community awareness about maternal health care services through mass media and outreach programs with especial emphasis on women’s and their partners educational attainment, rural mothers, women’s empowerment, and household socioeconomic status.

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          Global causes of maternal death: a WHO systematic analysis.

          Lale Say, Doris Chou, Alison Gemmill … (2014)
          Data for the causes of maternal deaths are needed to inform policies to improve maternal health. We developed and analysed global, regional, and subregional estimates of the causes of maternal death during 2003-09, with a novel method, updating the previous WHO systematic review. We searched specialised and general bibliographic databases for articles published between between Jan 1, 2003, and Dec 31, 2012, for research data, with no language restrictions, and the WHO mortality database for vital registration data. On the basis of prespecified inclusion criteria, we analysed causes of maternal death from datasets. We aggregated country level estimates to report estimates of causes of death by Millennium Development Goal regions and worldwide, for main and subcauses of death categories with a Bayesian hierarchical model. We identified 23 eligible studies (published 2003-12). We included 417 datasets from 115 countries comprising 60 799 deaths in the analysis. About 73% (1 771 000 of 2 443 000) of all maternal deaths between 2003 and 2009 were due to direct obstetric causes and deaths due to indirect causes accounted for 27·5% (672 000, 95% UI 19·7-37·5) of all deaths. Haemorrhage accounted for 27·1% (661 000, 19·9-36·2), hypertensive disorders 14·0% (343 000, 11·1-17·4), and sepsis 10·7% (261 000, 5·9-18·6) of maternal deaths. The rest of deaths were due to abortion (7·9% [193 000], 4·7-13·2), embolism (3·2% [78 000], 1·8-5·5), and all other direct causes of death (9·6% [235 000], 6·5-14·3). Regional estimates varied substantially. Between 2003 and 2009, haemorrhage, hypertensive disorders, and sepsis were responsible for more than half of maternal deaths worldwide. More than a quarter of deaths were attributable to indirect causes. These analyses should inform the prioritisation of health policies, programmes, and funding to reduce maternal deaths at regional and global levels. Further efforts are needed to improve the availability and quality of data related to maternal mortality. © 2014 World Health Organization; licensee Elsevier. This is an Open Access article published without any waiver of WHO's privileges and immunities under international law, convention, or agreement. This article should not be reproduced for use in association with the promotion of commercial products, services, or any legal entity. There should be no suggestion that WHO endorses any specific organisation or products. The use of the WHO logo is not permitted. This notice should be preserved along with the article's original URL.
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            National, regional, and global levels and trends in maternal mortality between 1990 and 2015 with scenario-based projections to 2030: a systematic analysis by the United Nations Maternal Mortality Estimation Inter-Agency Group

            Leontine Alkema, Doris Chou, Daniel W Hogan … (2015)
            Summary Background Millennium Development Goal (MDG) 5 calls for a reduction of 75% in the maternal mortality ratio (MMR) between 1990 and 2015. We estimated levels and trends in maternal mortality for 183 countries to assess progress made. Based on MMR estimates for 2015, we constructed scenario-based projections to highlight the accelerations needed to accomplish the Sustainable Development Goal (SDG) global target of less than 70 maternal deaths per 100,000 live births globally by 2030. Methods We updated the open access UN Maternal Mortality Estimation Inter-agency Group (MMEIG) database. Based upon nationally-representative data for 171 countries, we generated estimates of maternal mortality and related indicators with uncertainty intervals using a Bayesian model, which extends and refines the previous UN MMEIG estimation approach. The model combines the rate of change implied by a multilevel regression model with a time series model to capture data-driven changes in country-specific MMRs, and includes a data model to adjust for systematic and random errors associated with different data sources. Results The global MMR declined from 385 deaths per 100,000 live births (80% uncertainty interval ranges from 359 to 427) in 1990 to 216 (207 to 249) in 2015, corresponding to a relative decline of 43.9% (34.0 to 48.7) during the 25-year period, with 303,000 (291,000 to 349,000) maternal deaths globally in 2015. Regional progress in reducing the MMR since 1990 ranged from an annual rate of reduction of 1.8% (0 to 3.1) in the Caribbean to 5.0% (4.0 to 6.0) for Eastern Asia. Regional MMRs for 2015 range from 12 (11 to 14) for developed regions to 546 (511 to 652) for sub-Saharan Africa. Accelerated progress will be needed to achieve the SDG goal; countries will need to reduce their MMRs at an annual rate of reduction of at least 7.5%. Interpretation Despite global progress in reducing maternal mortality, immediate action is required to begin making progress towards the ambitious SDG 2030 target, and ultimately eliminating preventable maternal mortality. While the rates of reduction that are required to achieve country-specific SDG targets are ambitious for the great majority of high mortality countries, the experience and rates of change between 2000 and 2010 in selected countries–those with concerted efforts to reduce the MMR- provide inspiration as well as guidance on how to accomplish the acceleration necessary to substantially reduce preventable maternal deaths. Funding Funding from grant R-155-000-146-112 from the National University of Singapore supported the research by LA and SZ. AG is the recipient of a National Institute of Child Health and Human Development, grant # T32-HD007275. Funding also provided by USAID and HRP (the UNDP/UNFPA/UNICEF/WHO/World Bank Special Programme of Research, Development and Research Training in Human Reproduction).
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              Negative Binomial Regression

              Joseph Hilbe (2011)
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                Author and article information

                Contributors
                Adugnaw Zeleke Alem:
                ORCID: https://orcid.org/0000-0002-1928-8548
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Biresaw Ayen Tegegne: Role: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SoftwareRole: SupervisionRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Fantu Mamo Aragaw: Role: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SupervisionRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Rediet Eristu Teklu: Role: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Tsegaw Amare Baykeda:
                ORCID: https://orcid.org/0000-0002-2588-8929
                Role: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SupervisionRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Manisha Nair: 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): 18 April 2024
                Publication date Collection: 2024
                Volume: 19
                Issue: 4
                Electronic Location Identifier: e0301542
                Affiliations
                [1 ] Department of Epidemiology and Biostatistics, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia
                [2 ] Health Research Institute, Faculty of Health, University of Canberra, Bruce, Australia
                [3 ] Department of Anesthesia, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia
                [4 ] Department of Health Systems and Policy, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia
                [5 ] School of Public Health, The University of Queensland, Brisbane, Australia
                Oxford University: University of Oxford, UNITED KINGDOM
                Author notes

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

                Author information
                https://orcid.org/0000-0002-1928-8548
                https://orcid.org/0000-0002-2588-8929
                Article
                Publisher ID: PONE-D-22-24935
                DOI: 10.1371/journal.pone.0301542
                PMC ID: 11025891
                PubMed ID: 38635815
                SO-VID: ef6edc53-0558-444a-ac5d-ab3cef1e6927
                Copyright © © 2024 Alem et al
                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 : 7 September 2022
                Date accepted : 18 March 2024
                Page count
                Figures: 1, Tables: 4, Pages: 17
                Funding
                The authors received no specific funding for this work.
                Categories
                Subject: Research Article
                Subject: Medicine and Health Sciences
                Subject: Women's Health
                Subject: Maternal Health
                Subject: Antenatal Care
                Subject: Social Sciences
                Subject: Economics
                Subject: Economic Geography
                Subject: Low and Middle Income Countries
                Subject: Earth Sciences
                Subject: Geography
                Subject: Economic Geography
                Subject: Low and Middle Income Countries
                Subject: Medicine and Health Sciences
                Subject: Women's Health
                Subject: Maternal Health
                Subject: Pregnancy
                Subject: Medicine and Health Sciences
                Subject: Women's Health
                Subject: Obstetrics and Gynecology
                Subject: Pregnancy
                Subject: Biology and Life Sciences
                Subject: Neuroscience
                Subject: Cognitive Science
                Subject: Cognitive Psychology
                Subject: Decision Making
                Subject: Biology and Life Sciences
                Subject: Psychology
                Subject: Cognitive Psychology
                Subject: Decision Making
                Subject: Social Sciences
                Subject: Psychology
                Subject: Cognitive Psychology
                Subject: Decision Making
                Subject: Biology and Life Sciences
                Subject: Neuroscience
                Subject: Cognitive Science
                Subject: Cognition
                Subject: Decision Making
                Subject: Social Sciences
                Subject: Sociology
                Subject: Communications
                Subject: Mass Media
                Subject: Biology and Life Sciences
                Subject: Developmental Biology
                Subject: Neonates
                Subject: Social Sciences
                Subject: Sociology
                Subject: Education
                Subject: Educational Attainment
                Subject: Medicine and Health Sciences
                Subject: Women's Health
                Subject: Obstetrics and Gynecology
                Subject: Stillbirths
                Custom metadata
                Data Availability The data that support the findings of this study are available from the Demographic and Health Surveys (DHS) Program. Redistribution of any DHS data directly or within any tool/dashboard is not permitted without written consent from DHS. Data are available at the DHS Program website ( https://www.dhsprogram.com/data/dataset_admin/login_main.cfm).

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