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Summary of the Impact of the Inclusion of Mobile Phone Numbers into the NSW Population Health Survey in 2012

1 Centre for Epidemiology and Evidence, NSW Ministry of Health, 73 Miller Street, North Sydney, NSW 2060, Australia;
2 National Institute for Applied Statistics Research, University of Wollongong, NSW 2522, Australia

Background: Although it was estimated that 20% of the population in Australia were mobile-only phone users in 2010, the inclusion of mobile numbers into computer-assisted telephone interviews (CATI) behavioural risk factor surveys did not occur until 2012. Methods: Three papers have been published describing the methods, weighting strategy and the impact in detail of including mobile numbers into the NSW Population Health Survey (NSWPHS). This paper identifies the important components of those papers and summarises them for a broader audience. Results: In the 2012 NSWPHS, 15,214 (15,149 with weights) interviews were completed (64% landline frame; 36% mobile frame). Response, cooperation and contact rates were 37%, 65% and 69% respectively. The inclusion of mobile phone numbers resulted in a sample that was closer to the NSW population profile and impacted on the time series of estimates for alcohol drinking, recommended fruit consumption, current smoking, and overweight or obesity. Conclusions: The papers found that including mobile phone numbers into NSWPHS did not impact negatively on response rates or data collection, but it did cost more and affect the time series for some behavioural risk factors, in that it corrected the estimates that had been produced from a sample frame that was progressively getting less representative of the population.
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Keywords CATI survey; mobile phone; overlapping dual-frame

Citation: Margo Barr, Raymond Ferguson, Jason van Ritten, Phil Hughes, David Steel. Summary of the Impact of the Inclusion of Mobile Phone Numbers into the NSW Population Health Survey in 2012. AIMS Public Health , 2015, 2(2): 210-217. doi: 10.3934/publichealth.2015.2.210


  • 1. NSW Population Health Surveys. Available from: http://www.health.nsw.gov.au/publichealth/surveys/index.
  • 2. SA Monitoring and Surveillance System. Available from: http://www.health.adelaide.edu.
  • 3. Victorian Population Health Survey. Available from: http://www.health.vic.gov.
  • 4. WA Health and Wellbeing Surveillance System. Available from: http://www.health.wa.gov.
  • 5. Queensland Health Omnibus Survey. Available from: http://www.health.qld.gov.
  • 6. ACT General Health Survey. Available from: http://www.health.act.gov.au.
  • 7. Barr ML, van Ritten JJ, Steel DG, et al. (2012) Inclusion of mobile phone numbers into an ongoing population health survey in New South Wales, Australia: design, methods, call outcomes, costs and sample representativeness. BMC Med Res Methodol 12: 177.    
  • 8. Barr ML, Ferguson RA, Hughes PJ, et al. (2014) Developing a weighting strategy to include mobile phone numbers into an ongoing population health survey using an overlapping dual-frame design with limited benchmark information. BMC Med Res Methodol 14: 102
  • 9. Barr ML, Ferguson RA, Steel DG (2014) Inclusion of mobile phone numbers into an ongoing population health survey in New South Wales, Australia: impact on the time series. BMC Res Notes 7: 517.    
  • 10. SAS Institute (2009) The SAS System for Windows version 9.2. Cary, NC: SAS Institute Inc. Available from: http://www.sas.com
  • 11. Altman DG, Bland JM (2003) Interaction revisited: the differences between two estimates. BMJ 326: 219.
  • 12. American Association for Public Opinion Research (AAPOR) Availabe from: http://www.aapor.
  • 13. Pennay D, Bishop N (2009) Profiling the ‘mobile phone only’ population: A study of Australians with a mobile phone and no landline telephone. Melbourne: The Social Research Centre Pty Ltd.
  • 14. Livingston M, Dietze P, Ferris J, et al. (2013) Surveying alcohol and other drug use through telephone sampling: a comparison of landline and mobile phone samples. BMC Med Res Methodol 13: 41.    
  • 15. Mohorko A, de Leeuw E, Hox J (2013) Coverage bias in European Telephone Surveys: Development of landline and mobile phone coverage across countries and over time. Survey Methods. Insights from the Field. Available from: http://surveyinsights.org/?p=828


This article has been cited by

  • 1. Bernard Baffour, Tim Roselli, Michele Haynes, Joshua J. Bon, Mark Western, Susan Clemens, Including mobile-only telephone users in a statewide preventive health survey—Differences in the prevalence of health risk factors and impact on trends, Preventive Medicine Reports, 2017, 10.1016/j.pmedr.2017.05.009
  • 2. Josephine Chau, Tien Chey, Sarah Burks-Young, Lina Engelen, Adrian Bauman, Authors' response to Letter to the Editor: ANZJPH-2017-248, Australian and New Zealand Journal of Public Health, 2017, 10.1111/1753-6405.12768

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Copyright Info: 2015, Margo Barr, et al., licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution Licese (http://creativecommons.org/licenses/by/4.0)

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