A multi-country comparison between mobile phone surveys and face-to-face household surveys to estimate the prevalence of non-communicable diseases behavioural risk factors in low- and middle-income settings
Background Although mobile phone surveys (MPS) are routinely used to collect health information in high-income countries, concerns remain about the impact of bias on population-level estimates in low-income settings and validation studies are lacking. This study aims to compare non-communicable dise...
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BMJ Publishing Group
2025-06-01
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| Series: | BMJ Global Health |
| Online Access: | https://gh.bmj.com/content/10/6/e017785.full |
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| author | Gulam Muhammed Al Kibria Saifuddin Ahmed Dustin G Gibson Kennedy Lishimpi Jones K Masiye Daksha Shah Melanie Cowan Wilbroad Mutale Namasiku Siyumbwa Julián A Fernández-Niño Champika Wickramasinghe Leanne Riley Stacy Davlin Rachael Phadnis Romina Costa Beltrán Juan Carlos Zevallos Lopez Juan Vásconez Hicham El Berri Samir Mounach Mangla Gomare Gulnar Khan Niraj Dave Udara Perera |
| author_facet | Gulam Muhammed Al Kibria Saifuddin Ahmed Dustin G Gibson Kennedy Lishimpi Jones K Masiye Daksha Shah Melanie Cowan Wilbroad Mutale Namasiku Siyumbwa Julián A Fernández-Niño Champika Wickramasinghe Leanne Riley Stacy Davlin Rachael Phadnis Romina Costa Beltrán Juan Carlos Zevallos Lopez Juan Vásconez Hicham El Berri Samir Mounach Mangla Gomare Gulnar Khan Niraj Dave Udara Perera |
| author_sort | Gulam Muhammed Al Kibria |
| collection | DOAJ |
| description | Background Although mobile phone surveys (MPS) are routinely used to collect health information in high-income countries, concerns remain about the impact of bias on population-level estimates in low-income settings and validation studies are lacking. This study aims to compare non-communicable diseases (NCDs) risk factor estimates obtained from MPS and nationally representative face-to-face household surveys in six low- and middle-income settings.Methods The MPS contained core questions from the standard STEPwise approach to NCD risk factor surveillance questionnaire. MPS sampling frames were generated by random digit dialling, while data collection was done by interactive voice response and SMS. At the same time, a nationally representative household survey (WHO STEPS) was conducted using multi-stage sampling. Participants aged 18 and older were included. Absolute differences and prevalence ratios, with 95% CIs, were analysed. The distribution of the differences between estimates by sex, age and education was also explored.Results MPS and STEPS surveys were conducted in Ecuador, Malawi, Morocco, Zambia, Mumbai (India) and Sri Lanka between 2017 and 2022. Overall, MPS estimates of NCDs were most similar to STEPS estimates in Ecuador and Sri Lanka, and most dissimilar in Mumbai and Malawi. Broadly, smoking tobacco, fruit and vegetable consumption, and current drinking questions performed similarly across settings, whereas questions on smokeless tobacco, salt intake and hypertension yielded dissimilar results.Conclusions MPS estimates were most similar to household estimates in settings with high levels of mobile phone ownership. MPS have the potential to serve as a valuable tool to monitor and address NCD risk factors, in addition to traditional face-to-face household surveys. However, producing nationally representative MPS estimates requires careful adjustments to sampling strategies, addressing coverage biases and overcoming technological limitations. Currently, face-to-face household surveys reach a more representative sample of the population, including those in remote and lower educational demographics. |
| format | Article |
| id | doaj-art-6c7961e4a2194cfd9d283407b1881a4e |
| institution | Kabale University |
| issn | 2059-7908 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | BMJ Publishing Group |
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| spelling | doaj-art-6c7961e4a2194cfd9d283407b1881a4e2025-08-20T03:30:36ZengBMJ Publishing GroupBMJ Global Health2059-79082025-06-0110610.1136/bmjgh-2024-017785A multi-country comparison between mobile phone surveys and face-to-face household surveys to estimate the prevalence of non-communicable diseases behavioural risk factors in low- and middle-income settingsGulam Muhammed Al Kibria0Saifuddin Ahmed1Dustin G Gibson2Kennedy Lishimpi3Jones K Masiye4Daksha Shah5Melanie Cowan6Wilbroad Mutale7Namasiku Siyumbwa8Julián A Fernández-Niño9Champika Wickramasinghe10Leanne Riley11Stacy Davlin12Rachael Phadnis13Romina Costa Beltrán14Juan Carlos Zevallos Lopez15Juan Vásconez16Hicham El Berri17Samir Mounach18Mangla Gomare19Gulnar Khan20Niraj Dave21Udara Perera221 Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA2 Population, Family And Reproductive Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA12 Center for Global Digital Health Innovation, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA11 Zambia Ministry of Health, Lusaka, Zambia6 Government of Malawi Ministry of Health, Lilongwe, Malawi8 Brihanmumbai Municipal Corporation, Mumbai, Maharashtra, India4 World Health Organization, Geneva, Switzerland11 Zambia Ministry of Health, Lusaka, Zambia11 Zambia Ministry of Health, Lusaka, Zambia1 Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA10 Government of Sri Lanka Ministry of Health Sri Lanka, Colombo, Sri Lanka4 World Health Organization, Geneva, Switzerland3 CDC Foundation Inc, Atlanta, Georgia, USA3 CDC Foundation Inc, Atlanta, Georgia, USA5 Ministry of Public Health of Ecuador, Quito, Ecuador5 Ministry of Public Health of Ecuador, Quito, Ecuador5 Ministry of Public Health of Ecuador, Quito, Ecuador7 Government of the Kingdom of Morocco Ministry of Public Health, Rabat, Morocco7 Government of the Kingdom of Morocco Ministry of Public Health, Rabat, Morocco8 Brihanmumbai Municipal Corporation, Mumbai, Maharashtra, India8 Brihanmumbai Municipal Corporation, Mumbai, Maharashtra, India9 Nielsen India, Mumbai, Maharashtra, India10 Government of Sri Lanka Ministry of Health Sri Lanka, Colombo, Sri LankaBackground Although mobile phone surveys (MPS) are routinely used to collect health information in high-income countries, concerns remain about the impact of bias on population-level estimates in low-income settings and validation studies are lacking. This study aims to compare non-communicable diseases (NCDs) risk factor estimates obtained from MPS and nationally representative face-to-face household surveys in six low- and middle-income settings.Methods The MPS contained core questions from the standard STEPwise approach to NCD risk factor surveillance questionnaire. MPS sampling frames were generated by random digit dialling, while data collection was done by interactive voice response and SMS. At the same time, a nationally representative household survey (WHO STEPS) was conducted using multi-stage sampling. Participants aged 18 and older were included. Absolute differences and prevalence ratios, with 95% CIs, were analysed. The distribution of the differences between estimates by sex, age and education was also explored.Results MPS and STEPS surveys were conducted in Ecuador, Malawi, Morocco, Zambia, Mumbai (India) and Sri Lanka between 2017 and 2022. Overall, MPS estimates of NCDs were most similar to STEPS estimates in Ecuador and Sri Lanka, and most dissimilar in Mumbai and Malawi. Broadly, smoking tobacco, fruit and vegetable consumption, and current drinking questions performed similarly across settings, whereas questions on smokeless tobacco, salt intake and hypertension yielded dissimilar results.Conclusions MPS estimates were most similar to household estimates in settings with high levels of mobile phone ownership. MPS have the potential to serve as a valuable tool to monitor and address NCD risk factors, in addition to traditional face-to-face household surveys. However, producing nationally representative MPS estimates requires careful adjustments to sampling strategies, addressing coverage biases and overcoming technological limitations. Currently, face-to-face household surveys reach a more representative sample of the population, including those in remote and lower educational demographics.https://gh.bmj.com/content/10/6/e017785.full |
| spellingShingle | Gulam Muhammed Al Kibria Saifuddin Ahmed Dustin G Gibson Kennedy Lishimpi Jones K Masiye Daksha Shah Melanie Cowan Wilbroad Mutale Namasiku Siyumbwa Julián A Fernández-Niño Champika Wickramasinghe Leanne Riley Stacy Davlin Rachael Phadnis Romina Costa Beltrán Juan Carlos Zevallos Lopez Juan Vásconez Hicham El Berri Samir Mounach Mangla Gomare Gulnar Khan Niraj Dave Udara Perera A multi-country comparison between mobile phone surveys and face-to-face household surveys to estimate the prevalence of non-communicable diseases behavioural risk factors in low- and middle-income settings BMJ Global Health |
| title | A multi-country comparison between mobile phone surveys and face-to-face household surveys to estimate the prevalence of non-communicable diseases behavioural risk factors in low- and middle-income settings |
| title_full | A multi-country comparison between mobile phone surveys and face-to-face household surveys to estimate the prevalence of non-communicable diseases behavioural risk factors in low- and middle-income settings |
| title_fullStr | A multi-country comparison between mobile phone surveys and face-to-face household surveys to estimate the prevalence of non-communicable diseases behavioural risk factors in low- and middle-income settings |
| title_full_unstemmed | A multi-country comparison between mobile phone surveys and face-to-face household surveys to estimate the prevalence of non-communicable diseases behavioural risk factors in low- and middle-income settings |
| title_short | A multi-country comparison between mobile phone surveys and face-to-face household surveys to estimate the prevalence of non-communicable diseases behavioural risk factors in low- and middle-income settings |
| title_sort | multi country comparison between mobile phone surveys and face to face household surveys to estimate the prevalence of non communicable diseases behavioural risk factors in low and middle income settings |
| url | https://gh.bmj.com/content/10/6/e017785.full |
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