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. 2017 May 18:7:91-98.
doi: 10.1016/j.pmedr.2017.05.009. eCollection 2017 Sep.

Including mobile-only telephone users in a statewide preventive health survey-Differences in the prevalence of health risk factors and impact on trends

Bernard Baffour  1 , Tim Roselli  2 , Michele Haynes  1 , Joshua J Bon  1 , Mark Western  1 , Susan Clemens  2
Affiliations

Including mobile-only telephone users in a statewide preventive health survey-Differences in the prevalence of health risk factors and impact on trends

Bernard Baffour et al. Prev Med Rep. .

Abstract

The Queensland preventive health survey is conducted annually to monitor the prevalence of behavioural risk factors in the north-east Australian state. Prompted by domestic and international trends in mobile telephone usage, the 2015 survey incorporated both mobile and landline telephone numbers from a list-based sampling frame. Estimates for landline-accessible and mobile-only respondents are compared to assess potential bias in landline-only surveys in the context of public health surveillance. Significant differences were found in subcategories of all health prevalence estimates considered (alcohol consumption, body mass index, smoking, and physical activity) from 2015 survey results. Results from Australian and international studies that have considered mobile telephone non-coverage bias are also summarised and discussed. We find that adjusting for sampling biases of telephone surveys by weighting does not fully compensate for the differences in prevalence estimates. However, predicted trends from previous years' surveys only differ significantly for the 2015 prevalence estimates of alcohol consumption. We conclude that the inclusion of mobile telephones into standard telephones surveys is important for obtaining valid, reliable and representative data to reduce bias in health prevalence estimates. Importantly, unlike some international experiences, the addition of mobiles telephones into the Queensland preventive health survey occurred before population trends were significantly affected.

Keywords: Dual-frame survey; Health prevalence estimates; Non-coverage bias; Public health surveillance; Telephone surveys.

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Figures

Fig. 1:
Fig. 1
Prevalence and 95% confidence intervals for landline respondents (to 2014) and for landline-accessible and total respondents (in 2015) for Queensland.
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