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      Factors associated with mobile phone usage to access maternal and child healthcare among women of urban slums in Dhaka, Bangladesh: a cross-sectional study

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          Abstract

          Introduction

          With the acute shortage of human resources and infrastructure, mobile phones can be a critical tool for accessing health services and strengthening health systems in Bangladesh. Yet, there is a scarcity of evidence on the use of mobile phones in this context for accessing health services. In this study, we sought to explore the current use of mobile phones for accessing maternal and child healthcare and its determinants among recently delivered women in urban slums of Bangladesh.

          Methods

          The data were collected through interviewing 800 recently delivered women from eight slums of Dhaka city of Bangladesh during May and June 2018. The study followed a cross-sectional design and a two-stage cluster random sampling procedure was followed. A pretested structured questionnaire was employed to collect information. Chi square tests were performed for descriptive analyses and a multilevel binary logistic regression model was executed to explore the determinants of mobile phone usage for accessing maternal and childcare among the participants.

          Results

          Overall, 73.8% of study participants used mobile phones for accessing maternal and child healthcare. After adjusting for potential confounders, participants’ age, husband’s occupation, sex of household head, women’s ownership of mobile phones and household wealth status were found to be significantly associated with higher odds of using mobile phones to access maternal and child healthcare.

          Conclusion

          The study highlighted the possibility of implementing large-scale mobile health (mHealth) interventions in slum settlements for accessing maternal and child healthcare and is a sustainable mitigation strategy for the acute health worker crisis in Bangladesh. The findings of this study are particularly crucial for policymakers and practitioners while they revise the health policy to incorporate mHealth interventions as highlighted in the recently initiated Digital Health Strategy of Bangladesh.

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          Most cited references49

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          Longitudinal data analysis using generalized linear models

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            Statistical analysis of correlated data using generalized estimating equations: an orientation.

            J Hanley (2003)
            The method of generalized estimating equations (GEE) is often used to analyze longitudinal and other correlated response data, particularly if responses are binary. However, few descriptions of the method are accessible to epidemiologists. In this paper, the authors use small worked examples and one real data set, involving both binary and quantitative response data, to help end-users appreciate the essence of the method. The examples are simple enough to see the behind-the-scenes calculations and the essential role of weighted observations, and they allow nonstatisticians to imagine the calculations involved when the GEE method is applied to more complex multivariate data.
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              Stillbirths: ending preventable deaths by 2030.

              Efforts to achieve the new worldwide goals for maternal and child survival will also prevent stillbirth and improve health and developmental outcomes. However, the number of annual stillbirths remains unchanged since 2011 and is unacceptably high: an estimated 2.6 million in 2015. Failure to consistently include global targets or indicators for stillbirth in post-2015 initiatives shows that stillbirths are hidden in the worldwide agenda. This Series paper summarises findings from previous papers in this Series, presents new analyses, and proposes specific criteria for successful integration of stillbirths into post-2015 initiatives for women's and children's health. Five priority areas to change the stillbirth trend include intentional leadership; increased voice, especially of women; implementation of integrated interventions with commensurate investment; indicators to measure effect of interventions and especially to monitor progress; and investigation into crucial knowledge gaps. The post-2015 agenda represents opportunities for all stakeholders to act together to end all preventable deaths, including stillbirths.
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                Author and article information

                Journal
                BMJ Open
                BMJ Open
                bmjopen
                bmjopen
                BMJ Open
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2044-6055
                2021
                9 April 2021
                : 11
                : 4
                : e043933
                Affiliations
                [1 ]departmentBRAC James P Grant School of Public Health , BRAC University , Dhaka, Bangladesh
                [2 ]departmentCentre for Primary Health Care and Equity , University of New South Wales , Sydney, New South Wales, Australia
                [3 ]Center for Research Policy and Implementation , Biratnagar, Nepal
                [4 ]departmentSchool of Population and Public Health , University of British Columbia , Vancouver, British Columbia, Canada
                [5 ]Cambridge Science Park , Cambridge, UK
                [6 ]departmentDepartment of International Health , Johns Hopkins University Bloomberg School of Public Health , Baltimore, Maryland, USA
                [7 ]departmentLaboratory of Viral Zoonotics , University of Cambridge , Cambridge, UK
                Author notes
                [Correspondence to ] Mr Sabuj Kanti Mistry; smitra411@ 123456gmail.com
                Author information
                http://orcid.org/0000-0001-6100-6076
                http://orcid.org/0000-0002-6626-1604
                http://orcid.org/0000-0003-4603-863X
                Article
                bmjopen-2020-043933
                10.1136/bmjopen-2020-043933
                8043001
                33837099
                17621117-3157-430e-9f85-eab493f96ba5
                © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

                This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:  http://creativecommons.org/licenses/by-nc/4.0/.

                History
                : 20 August 2020
                : 20 March 2021
                : 22 March 2021
                Funding
                Funded by: UKaid;
                Award ID: UKAD-INN-083
                Categories
                Epidemiology
                1506
                1692
                Original research
                Custom metadata
                unlocked

                Medicine
                telemedicine,epidemiology,health policy
                Medicine
                telemedicine, epidemiology, health policy

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