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      Relationship between Receipt of a Social Protection Grant for a Child and Second Pregnancy Rates among South African Women: A Cohort Study

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          Abstract

          Background

          Social protection programs issuing cash grants to caregivers of young children may influence fertility. Grant-related income could foster economic independence and/or increase access to job prospects, education, and health services, resulting in lower pregnancy rates. In the other direction, these programs may motivate family expansion in order to receive larger grants. Here, we estimate the net effect of these countervailing mechanisms among rural South African women.

          Methods

          We constructed a retrospective cohort of 4845 women who first became eligible for the Child Support Grant with the birth of their first child between 1998 and 2008, with data originally collected by the Agincourt Health and Socio-Demographic Surveillance System in Mpumalanga province, South Africa. We fit Cox regression models to estimate the hazard of second pregnancy in women who reported grant receipt after birth of first child, relative to non-recipients. As a secondary analysis to explore the potential for grant loss to incentivize second pregnancy, we exploited a natural experiment created by a 2003 expansion of the program’s age eligibility criterion from age seven to nine. We compared second pregnancy rates between (i) women with children age seven or eight in 2002 (recently aged out of grant eligibility) to (ii) women with children age seven or eight in 2003 (remained grant-eligible).

          Results

          The adjusted hazard ratio for the association between grant exposure and second pregnancy was 0.66 (95% CI: 0.58, 0.75). Women with first children who aged out of grant eligibility in 2002 had similar second pregnancy rates to women with first children who remained grant-eligible in 2003 [IRR (95% CI): 0.9 (0.5, 1.4)].

          Conclusions

          Across both primary and secondary analyses, we found no evidence that the Child Support Grant incentivizes pregnancy. In harmony with South African population policy, receipt of the Child Support Grant may result in longer spacing between pregnancies.

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          Most cited references12

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          Marginal structural models to estimate the causal effect of zidovudine on the survival of HIV-positive men.

          Standard methods for survival analysis, such as the time-dependent Cox model, may produce biased effect estimates when there exist time-dependent confounders that are themselves affected by previous treatment or exposure. Marginal structural models are a new class of causal models the parameters of which are estimated through inverse-probability-of-treatment weighting; these models allow for appropriate adjustment for confounding. We describe the marginal structural Cox proportional hazards model and use it to estimate the causal effect of zidovudine on the survival of human immunodeficiency virus-positive men participating in the Multicenter AIDS Cohort Study. In this study, CD4 lymphocyte count is both a time-dependent confounder of the causal effect of zidovudine on survival and is affected by past zidovudine treatment. The crude mortality rate ratio (95% confidence interval) for zidovudine was 3.6 (3.0-4.3), which reflects the presence of confounding. After controlling for baseline CD4 count and other baseline covariates using standard methods, the mortality rate ratio decreased to 2.3 (1.9-2.8). Using a marginal structural Cox model to control further for time-dependent confounding due to CD4 count and other time-dependent covariates, the mortality rate ratio was 0.7 (95% conservative confidence interval = 0.6-1.0). We compare marginal structural models with previously proposed causal methods.
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            Research into health, population and social transitions in rural South Africa: data and methods of the Agincourt Health and Demographic Surveillance System.

            Vital registration is generally lacking in infrastructurally weak areas where health and development problems are most pressing. Health and demographic surveillance is a response to the lack of a valid information base that can provide high-quality longitudinal data on population dynamics, health, and social change to inform policy and practice. Continuous demographic monitoring of an entire geographically defined population involves a multi-round, prospective community study, with annual recording of all vital events (births, deaths, migrations). Status observations and special modules add value to particular research areas. A verbal autopsy is conducted on every death to determine its probable cause. A geographic surveillance system supports spatial analyses, and strengthens field management. Health and demographic surveillance covers the Agincourt sub-district population, sited in rural north-eastern South Africa, of some 70,000 people (nearly a third are Mozambican immigrants) in 21 villages and 11,700 households. Data enumerated are consistent or more detailed when compared with national sources; strategies to improve incomplete data, such as counts of perinatal deaths, have been introduced with positive effect. Basic characteristics: A major health and demographic transition was documented over a 12-year period with marked changes in population structure, escalating mortality, declining fertility, and high levels of temporary migration increasing particularly amongst women. A dual burden of infectious and non-communicable disease exists against a background of dramatically progressing HIV/AIDS. Health and demographic surveillance sites - fundamental to the INDEPTH Network - generate research questions and hypotheses from empirical data, highlight health, social and population priorities, provide cost-effective support for diverse study designs, and track population change and the impact of interventions over time.[image omitted].
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              Social protection to support vulnerable children and families: the potential of cash transfers to protect education, health and nutrition

              Investing in social protection in sub-Saharan Africa has taken on a new urgency as HIVand AIDS interact with other drivers of poverty to simultaneously destabilise livelihoods systems and family and community safety nets. Cash transfer programmes already reach millions of people in South Africa, and in other countries in southern and East Africa plans are underway to reach tens and eventually hundreds of thousands more. Cash transfers worldwide have demonstrated large impacts on the education, health and nutrition of children. While the strongest evidence is from conditional cash transfer evaluations in Latin America and Asia, important results are emerging in the newer African programmes. Cash transfers can be implemented in conjunction with other services involving education, health, nutrition, social welfare and others, including those related to HIV and AIDS. HIV/ AIDS-affected families are diverse with respect to household structure, ability to work and access to assets, arguing for a mix of approaches, including food assistance and income-generation programmes. However, cash transfers appear to offer the best strategy for scaling up to a national system of social protection, by reaching families who are the most capacity constrained, in large numbers, relatively quickly. These are important considerations for communities hard-hit by HIV and AIDS, given the extent and nature of deprivation, the long-term risk to human capital and the current political willingness to act.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                23 September 2015
                2015
                : 10
                : 9
                : e0137352
                Affiliations
                [1 ]Center for Population and Development Studies, Harvard University, Cambridge, United States of America
                [2 ]Department of Epidemiology, University of North Carolina-Chapel Hill, Chapel Hill, United States of America
                [3 ]MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
                [4 ]Carolina Population Center, University of North Carolina-Chapel Hill, Chapel Hill, United States of America
                [5 ]Department of Global Health, Boston University, Boston, United States of America
                [6 ]Department of Global Health and Population, Harvard School of Public Health, Harvard University, Boston, United States of America
                [7 ]Wellcome Trust Africa Centre for Health and Population Studies, Mtubatuba, KwaZulu-Natal, South Africa
                [8 ]Department of Global Health and Development, Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, United Kingdom
                [9 ]Umeå Centre for Global Health Research, Division of Epidemiology and Global Health, Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
                [10 ]INDEPTH Network, Accra, Ghana
                University Hospital Basel, SWITZERLAND
                Author notes

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

                Conceived and designed the experiments: MR AP NN DW JB TB PM RT ST KK. Performed the experiments: MR. Analyzed the data: MR. Wrote the paper: MR AP NN DW JB TB PM RT ST KK. Conceptualized and designed the study: MR. Drafted the manuscript: MR. Contributed to the conception and design of the study: AP NN DW JB TB PM RT ST KK. Designed and/or were involved with the collection, storage, and analysis of data from the parent studies: TB PM RT ST KK. Contributed to the interpretation of the findings, contributed to the manuscript, and approved the final version as submitted: MR AP NN DW JB TB PM RT ST KK.

                Article
                PONE-D-15-19920
                10.1371/journal.pone.0137352
                4580643
                26398678
                1c3d578d-2be7-4f43-8a80-c0d62522d969
                Copyright @ 2015

                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
                : 12 May 2015
                : 14 August 2015
                Page count
                Figures: 3, Tables: 3, Pages: 12
                Funding
                This work was supported by the National Institutes of Health through Grant Numbers T32 HD007168 and R24 HD050924 to the Carolina Population Center and through Grant Number 1R01-HD058482-01. The Agincourt HDSS is funded by the Wellcome Trust, UK (grants 058893/Z/99/A; 069683/Z/02/Z; 085477/Z/08/Z; 085477/B/08/Z), with important contributions from the University of the Witwatersrand and the Medical Research Council, South Africa; and the National Institute on Aging (NIA) of the NIH, USA. The Wellcome Trust, UK, provides core funding to the Africa Centre, including for the surveillance on which this work is based (grant 082384/Z/07/Z). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Custom metadata
                The data analyzed in this paper are available upon request because they were obtained from a third party and contain sensitive health and personal information. The Agincourt data are available upon request as described on their data overview website ( http://www.agincourt.co.za/index.php/data/) and by contacting their data manager ( DataManager@ 123456agincourt.co.za ). The Africa Centre data are available upon request as described on their data overview website ( http://www.africacentre.ac.za/Default.aspx?tabid=69) and by contacting key personnel who can appropriately direct their request ( info@ 123456africacentre.ac.za ).

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