Accepted for/Published in: JMIR Public Health and Surveillance
Date Submitted: Mar 22, 2021
Date Accepted: Sep 8, 2021
Population health surveillance using mobile telephone surveys in low- and middle-income countries: methodology and sample representativeness of a behavioural risk factor survey of live poultry exposure in Bangladesh
ABSTRACT
Background:
In low- and middle-income countries (LMICs), population-based health surveys are typically conducted using face-to-face household interviews. However, telephone-based surveys are cheaper, faster, and can provide greater access to hard to reach or remote populations. The rapid growth in mobile telephone ownership in LMICs provides a unique opportunity to implement novel data collection methods for population health surveys.
Objective:
This study aims to describe the development and population representativeness of a mobile telephone survey measuring live poultry exposure in urban Bangladesh.
Methods:
A population-based cross-sectional mobile telephone survey was conducted between September and November 2019 in North and South Dhaka City Corporations (DCC), Bangladesh to measure live poultry exposure using a stratified probability sampling design. Data were collected using a computer-assisted telephone interview (CATI) platform. Call operational data were summarized, and participant data were weighted by age, sex, and education to the 2011 census. Demographic distributions of the weighted sample were compared with external sources to assess population representativeness.
Results:
A total of 5486 unique mobile telephone numbers were dialed, with 1047 respondents completing the survey. The survey had an overall response rate of 52.2% and a cooperation rate of 89.0%. Initial results comparing the socio-demographic profile of the survey sample to the census population showed that mobile telephone sampling slightly underrepresented older individuals and overrepresented those with higher secondary education. After weighting, the demographic profile of the sample population was well matched to the latest DCC census population profile.
Conclusions:
Probability-based mobile telephone survey sampling and data collection methods produced a population-representative sample with minimal adjustment in DCC, Bangladesh. Mobile telephone-based surveys can offer an efficient, economic, and robust way to conduct surveillance for population health outcomes, which has important implications for improving population health surveillance in LMICs.
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