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      An evolution of socioeconomic related inequality in teenage pregnancy and childbearing in Malawi

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          Abstract

          Background

          Teenage pregnancies and childbearing are important health concerns in low-and middle-income countries (LMICs) including Malawi. Addressing these challenges requires, among other things, an understanding of the socioeconomic determinants of and contributors to the inequalities relating to these outcomes. This study investigated the trends of the inequalities and decomposed the underlying key socioeconomic factors which accounted for the inequalities in teenage pregnancy and childbearing in Malawi.

          Methods

          The study used the 2004, 2010 and 2015–16 series of nationally representative Malawi Demographic Health Survey covering 12,719 women. We used concentration curves to examine the existence of inequalities, and then quantified the extent of inequalities in teenage pregnancies and childbearing using the Erreygers concentration index. Finally, we decomposed concentration index to find out the contribution of the determinants to socioeconomic inequality in teenage pregnancy and childbearing.

          Results

          The teenage pregnancy and childbearing rate averaged 29% ( p<0.01) between 2004 and 2015–16. Trends showed a “u-shape” in teenage pregnancy and childbearing rates, albeit a small one (34.1%; p<0.01) in 2004: (25.6%; p<0.01) in 2010, and (29%; p<0.01) in 2016. The calculated concentration indices -0.207 ( p<0.01) in 2004, -0.133 ( p<0.01) in 2010, and -0.217 ( p<0.01) in 2015–16 indicated that inequality in teenage pregnancy and childbearing worsened to the disadvantage of the poor in the country. Additionally, the decomposition exercise suggested that the primary drivers to inequality in teenage pregnancy and child bearing were, early sexual debut (15.5%), being married (50%), and wealth status (13.8%).

          Conclusion

          The findings suggest that there is a need for sustained investment in the education of young women concerning the disadvantages of early sexual debut and early marriages, and in addressing the wealth inequalities in order to reduce the incidences of teenage pregnancies and childbearing.

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          Most cited references24

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          Estimating wealth effects without expenditure data--or tears: an application to educational enrollments in states of India.

          Using data from India, we estimate the relationship between household wealth and children's school enrollment. We proxy wealth by constructing a linear index from asset ownership indicators, using principal-components analysis to derive weights. In Indian data this index is robust to the assets included, and produces internally coherent results. State-level results correspond well to independent data on per capita output and poverty. To validate the method and to show that the asset index predicts enrollments as accurately as expenditures, or more so, we use data sets from Indonesia, Pakistan, and Nepal that contain information on both expenditures and assets. The results show large, variable wealth gaps in children's enrollment across Indian states. On average a "rich" child is 31 percentage points more likely to be enrolled than a "poor" child, but this gap varies from only 4.6 percentage points in Kerala to 38.2 in Uttar Pradesh and 42.6 in Bihar.
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            Correcting the concentration index.

            In recent years attention has been drawn to several shortcomings of the Concentration Index, a frequently used indicator of the socioeconomic inequality of health. Some modifications have been suggested, but these are only partial remedies. This paper proposes a corrected version of the Concentration Index which is superior to the original Concentration Index and its variants, in the sense that it is a rank-dependent indicator which satisfies four key requirements (transfer, level independence, cardinal invariance, and mirror). The paper also shows how the corrected Concentration Index can be decomposed and generalized.
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              On correcting the concentration index for binary variables.

              This article discusses measurement of socioeconomic inequalities in the prevalence of a health condition, in response to the recent exchange between Guido Erreygers and Adam Wagstaff, in which they discuss the merits of their own corrections to the frequently used concentration index. We first reconcile their debate and discuss the value judgments implicit in their indices. Next, we provide a formal definition of the previously undefined value judgment in Wagstaff's correction. Finally, we show empirically that the choice of index matters, as illustrated by comparisons between countries using data from the European Survey of Health, Ageing and Retirement. Copyright © 2012 Elsevier B.V. All rights reserved.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: MethodologyRole: Writing – original draftRole: Writing – review & editing
                Role: SupervisionRole: Writing – review & editing
                Role: SupervisionRole: Writing – review & editing
                Role: SupervisionRole: Writing – review & editing
                Role: SupervisionRole: Writing – review & editing
                Role: SupervisionRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                20 November 2019
                2019
                : 14
                : 11
                : e0225374
                Affiliations
                [1 ] Department of Economics, University of Malawi, Chancellor College, Zomba, Malawi
                [2 ] Health Nursing and Midwifery, University of Hull, Hull, United Kingdom
                [3 ] Health Policy Unit, University of Malawi, College of Medicine, Lilongwe, Malawi
                [4 ] Department of Population Studies, University of Malawi, Chancellor College, Zomba, Malawi
                University of Cape Coast, GHANA
                Author notes

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

                [¤]

                Current address: Centre for Health Economics, University of York, York, United Kingdom

                Author information
                http://orcid.org/0000-0003-0199-779X
                http://orcid.org/0000-0001-9856-1268
                http://orcid.org/0000-0001-6125-6630
                Article
                PONE-D-19-09387
                10.1371/journal.pone.0225374
                6867649
                31747437
                8737a059-4b25-4192-b443-6734006a54c1
                © 2019 Chirwa 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
                : 2 April 2019
                : 4 November 2019
                Page count
                Figures: 8, Tables: 3, Pages: 16
                Funding
                The authors received no specific funding for this work.
                Categories
                Research Article
                Medicine and Health Sciences
                Women's Health
                Maternal Health
                Pregnancy
                Medicine and Health Sciences
                Women's Health
                Obstetrics and Gynecology
                Pregnancy
                Medicine and Health Sciences
                Health Care
                Socioeconomic Aspects of Health
                Medicine and Health Sciences
                Public and Occupational Health
                Socioeconomic Aspects of Health
                Medicine and Health Sciences
                Pediatrics
                Child Health
                Medicine and Health Sciences
                Public and Occupational Health
                Child Health
                People and Places
                Geographical Locations
                Africa
                Malawi
                People and Places
                Population Groupings
                Age Groups
                Children
                Adolescents
                People and Places
                Population Groupings
                Families
                Children
                Adolescents
                Medicine and Health Sciences
                Women's Health
                Obstetrics and Gynecology
                Contraception
                Social Sciences
                Economics
                Economic Analysis
                Medicine and Health Sciences
                Women's Health
                Obstetrics and Gynecology
                Contraception
                Female Contraception
                Custom metadata
                All data are available from https://dhsprogram.com/data/available-datasets.cfm.

                Uncategorized
                Uncategorized

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