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      Effect of unintended pregnancy on skilled antenatal care uptake in Bangladesh: analysis of national survey data

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          Abstract

          Background

          Around 48% of all pregnancies in low- and middle-income countries are unintended. Unintended pregnancy may contribute to lower use of antenatal care (ANC); however, current research in the area is largely inconclusive due to the methodological approaches applied.

          Methods

          Responses from 4493 women extracted from the 2014 Bangladesh Demographic and Health Survey (BDHS) were used to assess the association between unintended pregnancy and subsequent uptake of at least one and at least four skilled ANC visits. For this, Bayesian multilevel logistic regression models with informative priors (representing a range of values within which the researcher is certain the true effect of the parameters included lies) were used, adjusting for other factors that affect ANC uptake. Informative priors were selected from the BDHS data collected in 2004, 2007, and 2011.

          Results

          Around 64% of women in Bangladesh who had at least one pregnancy within 3 years prior to the survey (that ended in a live birth) received ANC at least once, and of these around 32% used ANC at least four times. Mistimed (aOR, 0.73, 95% Cred I, 0.66–0.81) and unwanted (aOR, 0.69, 95% Cred I, 0.64–0.75) pregnancy were associated with reduced odds of attending the recommended minimum of four skilled ANC visits compared with wanted pregnancy. These likelihoods were even lower for at least one skilled ANC visit among women with a mistimed (aOR, 0.59, 95% Cred I, 0.53–0.65) or an unwanted pregnancy (aOR, 0.67, 95% Cred I, 0.61–0.74) than women with a wanted pregnancy.

          Conclusions

          In Bangladesh, more than one-quarter of women who report an unintended pregnancy at conception and do not terminate the pregnancy are at high risk of not using ANC. It is important for policies to include women with unintended pregnancy in mainstream healthcare services. This will increase the use of ANC and reduce associated adverse consequences.

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          Most cited references36

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          A Gentle Introduction to Bayesian Analysis: Applications to Developmental Research

          Bayesian statistical methods are becoming ever more popular in applied and fundamental research. In this study a gentle introduction to Bayesian analysis is provided. It is shown under what circumstances it is attractive to use Bayesian estimation, and how to interpret properly the results. First, the ingredients underlying Bayesian methods are introduced using a simplified example. Thereafter, the advantages and pitfalls of the specification of prior knowledge are discussed. To illustrate Bayesian methods explained in this study, in a second example a series of studies that examine the theoretical framework of dynamic interactionism are considered. In the Discussion the advantages and disadvantages of using Bayesian statistics are reviewed, and guidelines on how to report on Bayesian statistics are provided.
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            Early antenatal care visit: a systematic analysis of regional and global levels and trends of coverage from 1990 to 2013

            Summary Background The timing of the first antenatal care visit is paramount for ensuring optimal health outcomes for women and children, and it is recommended that all pregnant women initiate antenatal care in the first trimester of pregnancy (early antenatal care visit). Systematic global analysis of early antenatal care visits has not been done previously. This study reports on regional and global estimates of the coverage of early antenatal care visits from 1990 to 2013. Methods Data were obtained from nationally representative surveys and national health information systems. Estimates of coverage of early antenatal care visits were generated with linear regression analysis and based on 516 logit-transformed observations from 132 countries. The model accounted for differences by data sources in reporting the cutoff for the early antenatal care visit. Findings The estimated worldwide coverage of early antenatal care visits increased from 40·9% (95% uncertainty interval [UI] 34·6–46·7) in 1990 to 58·6% (52·1–64·3) in 2013, corresponding to a 43·3% increase. Overall coverage in the developing regions was 48·1% (95% UI 43·4–52·4) in 2013 compared with 84·8% (81·6–87·7) in the developed regions. In 2013, the estimated coverage of early antenatal care visits was 24·0% (95% UI 21·7–26·5) in low-income countries compared with 81·9% (76·5–87·1) in high-income countries. Interpretation Progress in the coverage of early antenatal care visits has been achieved but coverage is still far from universal. Substantial inequity exists in coverage both within regions and between income groups. The absence of data in many countries is of concern and efforts should be made to collect and report coverage of early antenatal care visits to enable better monitoring and evaluation. Funding Department of Reproductive Health and Research, WHO and UNDP/UNFPA/UNICEF/WHO/World Bank Special Programme of Research, Development and Research Training in Human Reproduction.
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              Antenatal care services and its implications for vital and health outcomes of children: evidence from 193 surveys in 69 low-income and middle-income countries

              Objectives Antenatal care (ANC) is an essential part of primary healthcare and its provision has expanded worldwide. There is limited evidence of large-scale cross-country studies on the impact of ANC offered to pregnant women on child health outcomes. We investigate the association of ANC in low-income and middle-income countries with short- and long-term mortality and nutritional child outcomes. Setting We used nationally representative health and welfare data from 193 Demographic and Health Surveys conducted between 1990 and 2013 from 69 low-income and middle-income countries for women of reproductive age (15–49 years), their children and their respective household. Participants The analytical sample consisted of 752 635 observations for neonatal mortality, 574 675 observations for infant mortality, 400 426 observations for low birth weight, 501 484 observations for stunting and 512 424 observations for underweight. Main outcomes and measures Outcome variables are neonatal and infant mortality, low birth weight, stunting and underweight. Results At least one ANC visit was associated with a 1.04% points reduced probability of neonatal mortality and a 1.07% points lower probability of infant mortality. Having at least four ANC visits and having at least once seen a skilled provider reduced the probability by an additional 0.56% and 0.42% points, respectively. At least one ANC visit is associated with a 3.82% points reduced probability of giving birth to a low birth weight baby and a 4.11 and 3.26% points reduced stunting and underweight probability. Having at least four ANC visits and at least once seen a skilled provider reduced the probability by an additional 2.83%, 1.41% and 1.90% points, respectively. Conclusions The currently existing and accessed ANC services in low-income and middle-income countries are directly associated with improved birth outcomes and longer-term reductions of child mortality and malnourishment.
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                Author and article information

                Contributors
                sumonrupop@gmail.com , mdnuruzzaman.khan@uon.edu.au
                Journal
                Arch Public Health
                Arch Public Health
                Archives of Public Health
                BioMed Central (London )
                0778-7367
                2049-3258
                16 September 2020
                16 September 2020
                2020
                : 78
                : 81
                Affiliations
                [1 ]GRID grid.443076.2, ISNI 0000 0004 4684 062X, Department of Population Sciences, , Jatiya Kabi Kazi Nazrul Islam University, ; Mymensingh, Bangladesh
                [2 ]GRID grid.266842.c, ISNI 0000 0000 8831 109X, Priority Research Centre for Generational Health and Ageing, Faculty of Health and Medicine, School of Medicine and Public Health, , University of Newcastle, ; Newcastle, Australia
                [3 ]GRID grid.266842.c, ISNI 0000 0000 8831 109X, Faculty of Health and Medicine, School of Medicine and Public Health, , University of Newcastle, ; Newcastle, Australia
                Author information
                http://orcid.org/0000-0002-4550-4363
                Article
                468
                10.1186/s13690-020-00468-1
                7493902
                31908777
                ee816d10-d9b3-4d2e-b0e8-4675b9c8d646
                © The Author(s) 2020

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 26 February 2020
                : 8 September 2020
                Categories
                Research
                Custom metadata
                © The Author(s) 2020

                Public health
                unintended pregnancy,antenatal care uptake,informative bayesian approach,multilevel logistic regression model,bangladesh

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