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      Do mothers who delivered at health facilities return to health facilities for postnatal care follow-up? A multilevel analysis of the 2016 Ethiopian Demographic and Health Survey

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          Abstract

          Introduction

          Returning to health facility for postnatal care (PNC) use after giving birth at health facility could reflect the health seeking behavior of mothers. However, such studies are rare though they are critically important to develop vigorous strategies to improve PNC service utilization. Therefore, this study aimed to determine the magnitude and factors associated with returning to health facilities for PNC among mothers who delivered in Ethiopian health facilities after they were discharged.

          Methods

          This cross-sectional study used 2016 Ethiopian Demographic and Health Survey data. A total of 2405mothers who gave birth in a health facility were included in this study. Multilevel mixed-effect logistic regression model was fitted to estimate both independent (fixed) effects of the explanatory variables and community-level (random) effects on return for PNC utilization. Variable with p-value of ≤ 0.25 from unadjusted multilevel logistic regression were selected to develop three models and p-value of ≤0.05 was used to declare significance of the explanatory variables on the outcome variable in the final (adjusted) model. Analysis was done using IBM SPSS statistics version 21.

          Result

          In this analysis, from the total 2405 participants, 14.3% ((95%CI: 12.1–16.8), (n = 344)) of them returned to health facilities for PNC use after they gave birth at a health facility. From the multilevel logistic regression analysis, being employed (AOR = 1.51, 95%CI: 1.04–2.19), receiving eight and above antenatal care visits (AOR = 2.90, 95%CI: 1.05–8.00), caesarean section delivery (AOR = 2.53, 95%CI: 1.40–4.58) and rural residence (AOR = 0.56, 95%CI: 0.36–0.88) were found significantly associated with return to health facilities for PNC use among women who gave birth at health facility.

          Conclusion

          Facility-based PNC utilization among mothers who delivered at health facilities is low in Ethiopia. Both individual and community level variables were determined women to return to health facilities for PNC use. Thus, adopting context-specific strategies/policies could improve PNC utilization and should be paid a due focus.

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          4 million neonatal deaths: when? Where? Why?

          The proportion of child deaths that occurs in the neonatal period (38% in 2000) is increasing, and the Millennium Development Goal for child survival cannot be met without substantial reductions in neonatal mortality. Every year an estimated 4 million babies die in the first 4 weeks of life (the neonatal period). A similar number are stillborn, and 0.5 million mothers die from pregnancy-related causes. Three-quarters of neonatal deaths happen in the first week--the highest risk of death is on the first day of life. Almost all (99%) neonatal deaths arise in low-income and middle-income countries, yet most epidemiological and other research focuses on the 1% of deaths in rich countries. The highest numbers of neonatal deaths are in south-central Asian countries and the highest rates are generally in sub-Saharan Africa. The countries in these regions (with some exceptions) have made little progress in reducing such deaths in the past 10-15 years. Globally, the main direct causes of neonatal death are estimated to be preterm birth (28%), severe infections (26%), and asphyxia (23%). Neonatal tetanus accounts for a smaller proportion of deaths (7%), but is easily preventable. Low birthweight is an important indirect cause of death. Maternal complications in labour carry a high risk of neonatal death, and poverty is strongly associated with an increased risk. Preventing deaths in newborn babies has not been a focus of child survival or safe motherhood programmes. While we neglect these challenges, 450 newborn children die every hour, mainly from preventable causes, which is unconscionable in the 21st century.
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            A brief conceptual tutorial of multilevel analysis in social epidemiology: using measures of clustering in multilevel logistic regression to investigate contextual phenomena.

            In social epidemiology, it is easy to compute and interpret measures of variation in multilevel linear regression, but technical difficulties exist in the case of logistic regression. The aim of this study was to present measures of variation appropriate for the logistic case in a didactic rather than a mathematical way. Data were used from the health survey conducted in 2000 in the county of Scania, Sweden, that comprised 10 723 persons aged 18-80 years living in 60 areas. Conducting multilevel logistic regression different techniques were applied to investigate whether the individual propensity to consult private physicians was statistically dependent on the area of residence (that is, intraclass correlation (ICC), median odds ratio (MOR)), the 80% interval odds ratio (IOR-80), and the sorting out index). The MOR provided more interpretable information than the ICC on the relevance of the residential area for understanding the individual propensity of consulting private physicians. The MOR showed that the unexplained heterogeneity between areas was of greater relevance than the individual variables considered in the analysis (age, sex, and education) for understanding the individual propensity of visiting private physicians. Residing in a high education area increased the probability of visiting a private physician. However, the IOR showed that the unexplained variability between areas did not allow to clearly distinguishing low from high propensity areas with the area educational level. The sorting out index was equal to 82%. Measures of variation in logistic regression should be promoted in social epidemiological and public health research as efficient means of quantifying the importance of the context of residence for understanding disparities in health and health related behaviour.
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              Variance Inflation Factor: As a Condition for the Inclusion of Suppressor Variable(s) in Regression Analysis

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: MethodologyRole: Writing – review & editing
                Role: ConceptualizationRole: MethodologyRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: Writing – review & editing
                Role: Writing – review & editing
                Role: Writing – review & editing
                Role: Writing – review & editing
                Role: Writing – review & editing
                Role: VisualizationRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                7 April 2021
                2021
                : 16
                : 4
                : e0249793
                Affiliations
                [1 ] Tigray Health Research Institute, Mekelle, Tigray, Ethiopia
                [2 ] College of Health Sciences, Mekelle University, Mekelle, Ethiopia
                [3 ] Fenot, a Project of the Harvard T.H. Chan School of Public Health, Addis Ababa, Ethiopia
                Addis Ababa University, ETHIOPIA
                Author notes

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

                Author information
                https://orcid.org/0000-0003-4749-4629
                Article
                PONE-D-20-18442
                10.1371/journal.pone.0249793
                8026072
                33826670
                f4755618-a0c7-4c40-903f-eff58706ed04
                © 2021 Ayele 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.

                History
                : 16 June 2020
                : 24 March 2021
                Page count
                Figures: 0, Tables: 4, Pages: 14
                Funding
                The authors received no specific funding for this work.
                Categories
                Research Article
                Medicine and Health Sciences
                Health Care
                Health Care Facilities
                Medicine and Health Sciences
                Health Care
                Postpartum Care
                Postnatal Care
                Medicine and Health Sciences
                Women's Health
                Maternal Health
                Antenatal Care
                Medicine and Health Sciences
                Women's Health
                Maternal Health
                Birth
                Labor and Delivery
                Medicine and Health Sciences
                Women's Health
                Obstetrics and Gynecology
                Birth
                Labor and Delivery
                Medicine and Health Sciences
                Epidemiology
                Medical Risk Factors
                Traumatic Injury Risk Factors
                Violent Crime
                Domestic Violence
                Medicine and Health Sciences
                Public and Occupational Health
                Traumatic Injury Risk Factors
                Violent Crime
                Domestic Violence
                Social Sciences
                Sociology
                Criminology
                Crime
                Violent Crime
                Domestic Violence
                Medicine and Health Sciences
                Public and Occupational Health
                Behavioral and Social Aspects of Health
                Medicine and Health Sciences
                Women's Health
                Maternal Health
                Pregnancy
                Medicine and Health Sciences
                Women's Health
                Obstetrics and Gynecology
                Pregnancy
                Research and Analysis Methods
                Research Design
                Survey Research
                Surveys
                Health Surveys
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

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