ArticleBMJ open2023
Measuring under-5 mortality and fertility through mobile phone surveys: an assessment of selection bias in 34 low-income and middle-income countries.
Article in BMJ open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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11 citing papers in PubMed.
- Do Mobile Phone Surveys Supplement Other Mortality Surveillance Methods? Results From a National Study in Bangladesh.Tropical medicine & international health : TM & IH · 2026Article
- Under-Five Mortality in Humanitarian Emergencies: A Comparison of Face-to-Face and Mobile Phone Survey Estimates From Burkina Faso.Tropical medicine & international health : TM & IH · 2026Article
- Feasibility and Validity of Mobile Phone-Based Proxy Full Pregnancy History (mPFPH) for Estimating Perinatal Mortality in Rural Northwest Bangladesh.Tropical medicine & international health : TM & IH · 2026Article
- Estimates of Under-Five Mortality From a Mobile Phone Survey During the COVID-19 Outbreak: An Observational Study Comparing Three Instruments in Malawi.Demography · 2026Observational
- Can mobile phone surveys accurately measure the coverage of maternal healthcare services? Results from the Rapid Mortality Mobile Phone Survey (RaMMPS) study in Mozambique.Oxford open digital health · 2026Article
- 2022-'23 Malawi rapid mortality mobile phone survey (RaMMPS) dataset.Data in brief · 2025Article
- Measuring adult mortality from mobile phone surveys in Burkina Faso, Malawi and the Democratic Republic of the Congo.BMJ global health · 2025Article
- Measuring childhood mortality through mobile phone interviews in Mozambique.Tropical medicine & international health : TM & IH · 2025Article
- Interactive voice response surveys as a method for increasing the representativeness of rural respondents in a mortality mobile phone survey: Findings from Malawi.Tropical medicine & international health : TM & IH · 2025Article
- Mobile phone survey estimates of perinatal mortality in Malawi: A comparison of data from truncated and full pregnancy histories.Tropical medicine & international health : TM & IH · 2025Article
- Mobile phone ownership among young adults in seven Southern African countries.Journal of global health · 2025Article
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Authors and funding
5 authors.
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No grant is acknowledged in the PubMed record.
Abstract
objectivesThis study aims to assess sample selection bias in mobile phone survey estimates of fertility and under-5 mortality.
designWith data from the Demographic and Health Surveys, we use logistic regressions to identify sociodemographic correlates of mobile phone ownership and access, and Poisson regressions to estimate the association between mobile phone ownership (or access) and fertility and under-5 mortality estimates. We evaluate the potential reasons why estimates by mobile phone ownership differ using a set of behavioural characteristics.
setting34 low-income and middle-income countries, mostly in sub-Saharan Africa.
participants534 536 women between the ages of 15 and 49. OUTCOME MEASURES: Under-5 mortality rate (U5MR) and total fertility rate (TFR).
resultsMobile phone ownership ranges from 23.6% in Burundi to 96.7% in Armenia. The median TFR ratio and U5MR ratio between the non-owners and the owners of a mobile phone are 1.48 and 1.29, respectively. Fertility and mortality rates would be biased downwards if estimates are only based on women who own or have access to mobile phones. Estimates of U5MR can be adjusted through poststratification using age, educational level, area of residence, wealth and marital status as weights. However, estimates of TFR remain biased even after adjusting for these covariates. This difference is associated with behavioural factors (eg, contraceptive use) that are not captured by the poststratification variables, but for which there are also differences between mobile phone owners and non-owners.
conclusionsMobile phone surveys need to collect data on sociodemographic background characteristics to be able to weight and adjust mortality estimates ex post facto. Fertility estimates from mobile phone surveys will be biased unless further research uncovers the mechanisms driving the bias.
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