ABSTRACT
Communications through mobile phones and mass media have shown to be useful for health promotion activities in developing nations. This study explored the potential association of mothers’ mobile phone ownership and mass media exposure on maternal health care services in a developing nation setting: urban Bangladesh. The Urban Health Survey 2013 was examined for antenatal care, delivery assistance, and postnatal care of both mothers and children through multiple regression models, adjusting for sociodemographic factors. Among 8987 ever-married female respondents, 64.1% owned mobile phones and 88% were exposed to mass media (TV, radio or newspaper) at least once a week. Mobile phone ownership was associated with a 48% greater likelihood of access to antenatal care, 34% greater delivery assistance and 31% greater postnatal care of the mother, but no differences were found for postnatal care of children. Similarly, frequent media exposure was associated with increased access to antenatal care (38%) and delivery assistance (46%), but not associated with postnatal care of mothers or children. The results suggested that mobile phones and mass media could be valid avenues for promoting access to maternal health services, and thus, support for mobile phone access and investment in awareness campaigns targeting relevant communities are worthwhile.
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No potential conflict of interest was reported by the author(s).
Additional information
Notes on contributors
Raaj Kishore Biswas
Raaj Kishore Biswas, statistician by training, is a PhD scholar at the Transport and Road Safety (TARS) Research Centre in University of New South Wales, Sydney. His research focuses on the risk associated with everyday driving in Australia and big data analytics in road safety. His area of expertise includes biostatistics and public health, particularly focusing on health policy evaluation, health care system and health care accessibility in developing countries. Environmental statistics, behavioral analysis and spatial techniques are also part of his area of interest.
Nusma Rahman
Nusma Rahman is working as a Lecturer in Department of Statistics, Jagannath University, Dhaka, Bangladesh. Her research areas include application of biostatistics in developing randomized clinical design, public health and epidemiology.
Humayera Islam
Humayera Islam is currently a PhD student at Institute for Data Science and Informatics at University of Missouri-Columbia, Missouri, USA. She also serves as Lecturer (currently on study leave) of Applied Statistics at Institute of Statistical Research and Training, University of Dhaka, Bangladesh. Her research interests include application of artificial intelligence in areas of healthcare, mining massive unstructured data, clinical data and electronic health record data for predictive analytics, telemedicine applications in healthcare and applications of mhealth consumer health and public health informatics.
Teresa Senserrick
Teresa Senserrick PhD is a Professor at Queensland University of Technology (QUT) in the Centre for Accident Research and Road Safety – Queensland (CARRS-Q). She has over 20 years of research expertise in public health and injury prevention in Australia and internationally. Broadly, her research centres on policy and practice relevant research to improve health and safety outcomes, with a focus on disadvantaged and vulnerable communities.
Jahar Bhowmik
Dr Jahar Bhowmik is an Associate Professor and postgraduate applied statistics course director at the Department of Statistics, Data Science and Epidemiology at Swinburne University of Technology. His research interests are biostatistics, public health and wellbeing, research design, experimental design, applied epidemiology, applied statistics and econometrics. He has co-authored on around 70 peer reviewed publications including two book chapters in the area of public health, biostatistics, research design, experimental design, applied epidemiology and econometrics. Jahar supervises PhD and Masters students in many areas including applied epidemiology, biostatistics, experimental design and heath related data modeling.