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      Unmet Need for Family Planning, Contraceptive Failure, and Unintended Pregnancy among HIV-Infected and HIV-Uninfected Women in Zimbabwe

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          Abstract

          Background

          Prevention of unintended pregnancies among women living with HIV infection is a strategy recommended by the World Health Organization for prevention of mother-to-child transmission of HIV (PMTCT). We assessed pregnancy intentions and contraceptive use among HIV-positive and HIV-negative women with a recent pregnancy in Zimbabwe.

          Methods

          We analyzed baseline data from the evaluation of Zimbabwe’s Accelerated National PMTCT Program. Eligible women were randomly sampled from the catchment areas of 157 health facilities offering PMTCT services in five provinces. Eligible women were ≥16 years old and mothers of infants (alive or deceased) born 9 to 18 months prior to the interview. Participants were interviewed about their HIV status, intendedness of the birth, and contraceptive use.

          Results

          Of 8,797 women, the mean age was 26.7 years, 92.8% were married or had a regular sexual partner, and they had an average of 2.7 lifetime births. Overall, 3,090 (35.1%) reported that their births were unintended; of these women, 1,477 (47.8%) and 1,613 (52.2%) were and were not using a contraceptive method prior to learning that they were pregnant, respectively. Twelve percent of women reported that they were HIV-positive at the time of the survey; women who reported that they were HIV-infected were significantly more likely to report that their pregnancy was unintended compared to women who reported that they were HIV-uninfected (44.9% vs. 33.8%, p<0.01). After adjustment for covariates, among women with unintended births, there was no association between self-reported HIV status and lack of contraception use prior to pregnancy.

          Conclusions

          Unmet need for family planning and contraceptive failure contribute to unintended pregnancies among women in Zimbabwe. Both HIV-infected and HIV-uninfected women reported unintended pregnancies despite intending to avoid or delay pregnancy, highlighting the need for effective contraceptive methods that align with pregnancy intentions.

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          Most cited references30

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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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            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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              Alternatives for logistic regression in cross-sectional studies: an empirical comparison of models that directly estimate the prevalence ratio

              Background Cross-sectional studies with binary outcomes analyzed by logistic regression are frequent in the epidemiological literature. However, the odds ratio can importantly overestimate the prevalence ratio, the measure of choice in these studies. Also, controlling for confounding is not equivalent for the two measures. In this paper we explore alternatives for modeling data of such studies with techniques that directly estimate the prevalence ratio. Methods We compared Cox regression with constant time at risk, Poisson regression and log-binomial regression against the standard Mantel-Haenszel estimators. Models with robust variance estimators in Cox and Poisson regressions and variance corrected by the scale parameter in Poisson regression were also evaluated. Results Three outcomes, from a cross-sectional study carried out in Pelotas, Brazil, with different levels of prevalence were explored: weight-for-age deficit (4%), asthma (31%) and mother in a paid job (52%). Unadjusted Cox/Poisson regression and Poisson regression with scale parameter adjusted by deviance performed worst in terms of interval estimates. Poisson regression with scale parameter adjusted by χ2 showed variable performance depending on the outcome prevalence. Cox/Poisson regression with robust variance, and log-binomial regression performed equally well when the model was correctly specified. Conclusions Cox or Poisson regression with robust variance and log-binomial regression provide correct estimates and are a better alternative for the analysis of cross-sectional studies with binary outcomes than logistic regression, since the prevalence ratio is more interpretable and easier to communicate to non-specialists than the odds ratio. However, precautions are needed to avoid estimation problems in specific situations.
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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, USA )
                1932-6203
                2014
                21 August 2014
                : 9
                : 8
                : e105320
                Affiliations
                [1 ]University of California, Berkeley, California, United States of America
                [2 ]Ministry of Health and Child Care, Harare, Zimbabwe
                [3 ]Elizabeth Glaser Pediatric AIDS Foundation, Harare, Zimbabwe
                [4 ]Children’s Investment Fund Foundation, London, United Kingdom
                [5 ]Centre for Sexual Health and HIV Research, Harare, Zimbabwe
                [6 ]University College London, London, United Kingdom
                University of Washington, United States of America
                Author notes

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

                Conceived and designed the experiments: SM RB LR FC NP AH. Performed the experiments: SM RB LR CW JD. Analyzed the data: SM RB JD. Contributed to the writing of the manuscript: SM RB LR A. Mahomva A. Mushavi CW JD FC NP AH. Designed the parent impact evaluation: SM NP FC A. Mahomva AH. Collected data: JD CW RB.

                Article
                PONE-D-14-19504
                10.1371/journal.pone.0105320
                4140753
                25144229
                120602fa-8446-496a-95bd-781b9be80127
                Copyright @ 2014

                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
                : 30 April 2014
                : 18 July 2014
                Page count
                Pages: 8
                Funding
                The evaluation of Zimbabwe’s Accelerated National PMTCT Program was supported by the Children’s Investment Fund Foundation (CIFF, www.ciff.org) in a grant to NSP. AH (from CIFF) contributed to the study and is included as a co-author. SIM is supported by Award Number K01MH094246 from the National Institute of Mental Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Mental Health or the National Institutes of Health. The funders had no role in data collection and analysis or the decision to publish. AH (from CIFF) participated in designing the impact evaluation and preparation of this manuscript.
                Categories
                Research Article
                Medicine and health sciences
                Epidemiology
                HIV epidemiology
                Public and occupational health
                Preventive medicine
                HIV prevention
                Women's Health
                Maternal Health
                Pregnancy
                Obstetrics and Gynecology
                Contraception
                People and Places
                Geographical Locations
                Africa
                Population Groupings
                Age Groups
                Infants
                Custom metadata
                The authors confirm that all data underlying the findings are fully available without restriction. The data used for this analysis are available upon request in order to protect the confidentiality of mother-infant pairs. Data requests may be sent to Dr. Nancy Padian ( nancy.padian@ 123456gmail.com ).

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                Uncategorized

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