Inclusion of mobile telephone numbers into an ongoing population health survey in New South Wales, Australia, using an overlapping dual-frame design: impact on the time series

Moving towards a single-frame cell phone design in random digit dialing surveys: considerations from a French general population health survey

Background

Over the last two decades, telephone surveys based on random digit dialing have developed considerably. At the same time, however, the proportion of the population with a cell phone has increased, whereas landline frame coverage has declined, thus raising the possibility of discontinuing landline phone surveys. This paper aims to assess the impact of using a single-frame (SF) cell phone design instead of a dual-frame (DF) design with landlines and cell phones in the context of repeated health surveillance surveys in the general population. We analyze data from a random digit dialing health survey of the French population and assess differences between the DF and the counterfactual SF design that excludes the landline phone sample from the DF design. We evaluate the quality of the two survey designs in terms of survey productivity, response rates, representativeness, balancing of external covariates, and prevalence estimates of key health behavior indicators.

Results

Our results show that a SF cell phone survey has several advantages over a combined DF landline and cell phone survey. Cell numbers require fewer call attempts to complete an interview, leading to a substantial reduction in the mean data collection duration and weight dispersion. The global representativeness of the SF design was slightly better than its DF counterpart, although the elderly were underrepresented. After calibration, differences in health behavior estimates were small for the seven health indicators analyzed.

Conclusions

Switching from a DF random telephone survey to a SF cell phone design has a number of practical advantages and would have a minimal impact on general population health surveys for monitoring health behavior at the population level. However, the different aspects of the survey quality had to be studied to make a decision. Further studies are needed to explore the scope of possibilities.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-022-01573-1.

Examining the municipal-level representativeness of the Canadian Longitudinal Study on Aging (CLSA) cohort: an analysis using Calgary participant baseline data

INTRODUCTION

The Canadian Longitudinal Study on Aging (CLSA) is a rich, nationally representative population-based resource that can be used for multiple purposes. Although municipalities may wish to use CLSA data to address local policy needs, how well localized CLSA cohorts reflect municipal populations is unknown. Because Calgary, Alberta, is home to one of 11 CLSA data collection sites, our objective was to explore how well the Calgary CLSA sample represented the general Calgary population on select sociodemographic variables.

METHODS

Baseline characteristics (i.e. sex, marital status, ethnicity, education, retirement status, income, immigration, internal migration) of CLSA participants who visited the Calgary data collection site between 2011 and 2015 were compared to analogous profiles derived from the 2011 National Household Survey (NHS) and 2016 Census datasets, which spanned the years when data were collected on the CLSA participants.

RESULTS

Calgary CLSA participants were representative of the Calgary population for age, sex and Indigenous identity. Discrepancies of over 5% with the NHS and/or 2016 Census were found for marital status, measures of ethnic diversity (i.e. immigrant status, place of birth, non-official language spoken at home), internal migration, income, retirement status and education.

CONCLUSION

Voluntary studies face challenges in recruiting fully representative cohorts. Communities opting to use CLSA data at a municipal level, including the 10 other CLSA data collection sites, should exercise caution when interpreting the results of these analyses, as CLSA participants may not be fully representative of the local population on select characteristics of interest.

Long-term follow-up of pediatric head trauma patients treated at Mulago National Referral Hospital in Uganda

In Brief: This study used telephone surveys as a novel method of measuring health outcomes and tracking healthcare utilization in pediatric head trauma patients at the national referral hospital in Uganda. As the first-ever long-term follow-up of this patient population in Uganda, this work establishes a baseline of pediatric head trauma outcomes and lays the groundwork for tracking and improving outcomes for similar patients in low-resource settings.

Taking the pressure off the spring: the case of rebounding smoking rates when antitobacco campaigns ceased

OBJECTIVE

Smoking rates have been compared with a spring, requiring continuous downward pressure against protobacco forces, rather than a screw, which once driven down stays down. Quality antitobacco mass media campaigns put downward pressure on smoking rates. The suspension of a major Australian state campaign provided a natural experiment to assess effects on smoking. Furthermore, we document the positive influence of robust monitoring and mature advocacy on the political decision to reinstate funding. We also document the misuse by industry of South Australian smoking data from the period between Australia's implementation and subsequent evaluation of plain packaging.

METHODS

A time series analysis was used to examine monthly smoking prevalence trends at each of four intervention points: (A) commencement of high-intensity mass media campaign (August 2010); (B) introduction of plain packaging (December 2012), (C) defunding of campaign (July 2013); and (D) reinstatement of moderate-intensity campaign (July 2014).

FINDINGS

The suspension of the antitobacco campaign was disruptive to achieving smoking prevalence targets. There was an absence of a downward monthly smoking prevalence trajectory during the non-campaign period. Moreover, there was a significant decline in smoking prevalence during the period of high-intensity advertising, which continued after the introduction of plain packaging laws, and at the recommencement of campaign activity.

CONCLUSIONS

While the observed declines in smoking prevalence are likely due to a combination of interventions and cannot be attributed exclusively to antitobacco advertising, the results reinforce the political decision to reinstate the campaign and demonstrate the need for maintained investment to keep downward pressure on smoking rates.

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

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.

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There is a rapidly growing proportion of adults who are contactable via mobile-only.

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Exclusion of mobile-only group leads to biases in health prevalence estimates.

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Weighting and controlling for age differences does not correct for these biases.

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A list-based survey yields representative statistics for public health policy.

The impact of the mode of survey administration on estimates of daily smoking for mobile phone only users

Background

Over the past decade, there have been substantial changes in landline and mobile phone ownership, with a substantial increase in the proportion of mobile-only households. Estimates of daily smoking rates for the mobile phone only (MPO) population have been found to be substantially higher than the rest of the population and telephone surveys that use a dual sampling frame (landline and mobile phones) are now considered best practice. Smoking is seen as an undesirable behaviour; measuring such behaviours using an interviewer may lead to lower estimates when using telephone based surveys compared to self-administered approaches. This study aims to assess whether higher daily smoking estimates observed for the mobile phone only population can be explained by administrative features of surveys, after accounting for differences in the phone ownership population groups.

Methods

Data on New South Wales (NSW) residents aged 18 years or older from the NSW Population Health Survey (PHS), a telephone survey, and the National Drug Strategy Household Survey (NDSHS), a self-administered survey, were combined, with weights adjusted to match the 2013 population. Design-adjusted prevalence estimates and odds ratios were calculated using survey analysis procedures available in SAS 9.4.

Results

Both the PHS and NDSHS gave the same estimates for daily smoking (12%) and similar estimates for MPO users (20% and 18% respectively). Pooled data showed that daily smoking was 19% for MPO users, compared to 10% for dual phone owners, and 12% for landline phone only users. Prevalence estimates for MPO users across both surveys were consistently higher than other phone ownership groups. Differences in estimates for the MPO population compared to other phone ownership groups persisted even after adjustment for the mode of collection and demographic factors.

Conclusions

Daily smoking rates were consistently higher for the mobile phone only population and this was not driven by the mode of survey collection. This supports the assertion that the use of a dual sampling frame addresses coverage issues that would otherwise be present in telephone surveys that only made use of a landline sampling frame.

Electronic supplementary material

The online version of this article (doi:10.1186/s12874-017-0342-4) contains supplementary material, which is available to authorized users.

Australia's plain tobacco packs: anticipated and actual responses among adolescents and young adults 2010-2013

BACKGROUND

In December 2012, Australia introduced world-first legislation mandating plain packaging for all tobacco products. To date, there is very little evidence on youth responses to the changed packs.

AIM

To assess attitudes towards, and responses to, tobacco plain packs preimplementation and postimplementation.

METHODS

The Tobacco Promotion Impact Study (TPIS) was a yearly cross-sectional telephone survey of adolescents and young adults (12-24 years) from the states of New South Wales (NSW) and Queensland, conducted at three time points preimplementation (June 2010; June 2011; June 2012) and one time point postimplementation (June 2013; total n=8820).

RESULTS

There were significant increases in support for plain packaging from preimplementation to postimplementation for: never smokers (56% in 2012 vs 63% in 2013; OR=0.77, 95% CI 0.65 to 0.90, p=0.001), experimenters/ex-smokers (55% in 2012 vs 72% in 2013; OR=0.51, 95% CI 0.38 to 0.68, p<0.001) and current smokers (35% in 2012 vs 55% in 2013; OR=0.49, 95% CI 0.32 to 0.75, p=0.001). At postimplementation, 16% of never smokers reported that plain packaging made them less likely to try smoking and 18% of experimenters/ex-smokers reported that plain packaging made them less likely to smoke again. Youth were significantly less likely to have anticipated these responses preimplementation (never smokers: 8% in 2011; OR=0.43, 95% CI 0.28 to 0.65, p<0.00; experimenters/ex-smokers: 11%; OR=0.65, 95% CI 0.52 to 0.82, p<0.001). At postimplementation, 34% of smokers reported a quitting-related response to plain packaging (tried to quit or thought about quitting); the proportion who anticipated such a response preimplementation was significantly less (14% in 2011; OR=0.33, 95% CI 0.20 to 0.53, p<0.001). 28% of smokers reported a social denormalisation response at postimplementation (hid their pack from view, used a case to cover their pack, felt embarrassed); the proportion who anticipated such a response preimplementation was significantly less (9% in 2011; OR=0.24, 95% CI 0.14 to 0.42, p<0.001).

CONCLUSIONS

The actual response of youth to plain packaging was greater than anticipated prior to their introduction, and support for plain packaging increased from preimplementation to postimplementation among all groups of youth. Jurisdictions planning to implement plain tobacco packaging should be encouraged by these findings.

Exposure to Internet-Based Tobacco Advertising and Branding: Results From Population Surveys of Australian Youth 2010-2013

Background

Since legislation prohibiting tobacco advertising in traditional media, online communication platforms and social media have become one of the few avenues for the tobacco industry to promote its products to Australians. Little is currently known about the exposure of young people to these new media promotions.

Objective

To measure exposure to Internet-based tobacco advertising and branding among Australian youth, identify common formats of branding encountered, and examine the association between exposure and smoking susceptibility.

Methods

The Tobacco Promotion Impact Study is a repeat cross-sectional telephone survey of young people (12-24 years) in 2 Australian states, conducted yearly from 2010 to 2013 (total n=8820). The survey included questions about past-month exposure to Internet-based tobacco advertising and tobacco company branding. Changes in levels of exposure, characteristics of exposed youth, and the association between exposure and smoking susceptibility were explored.

Results

Past-month exposure to Internet-based tobacco advertising and branding among young people increased over the years of the survey (advertising: 21% in 2010 to 29% in 2013; branding: 20% in 2010 to 26% in 2013). The participants who were younger, female, from lower socioeconomic status, and never-smokers were more likely to report exposure. Facebook was the most commonly cited platform for encountering tobacco branding in 2013 (22% of all branding). Compared with young people interviewed in 2013, participants in 2010 were significantly less likely to report exposure to tobacco branding on social media (odds ratio [OR] 0.26, 95% CI 0.20-0.33, P<.001) or 2011 (OR 0.46, 95% CI 0.37-0.57, P<.001). Among never-smokers aged 12-17 years, exposure to online advertising and branding (OR 1.32, 95% CI 1.11-1.57, P=.002) or branding alone (OR 1.39, 95% CI 1.10-1.77, P=.007) were significant predictors of smoking susceptibility.

Conclusions

Ensuring tobacco advertising bans are inclusive of Internet-based media is essential. Given the global nature of Internet-based content, cooperation among signatory nations to the World Health Organization Framework Convention Alliance on Tobacco Control will be necessary.

Has the incidence of brain cancer risen in Australia since the introduction of mobile phones 29 years ago?

BACKGROUND

Mobile phone use in Australia has increased rapidly since its introduction in 1987 with whole population usage being 94% by 2014. We explored the popularly hypothesised association between brain cancer incidence and mobile phone use.

STUDY METHODS

Using national cancer registration data, we examined age and gender specific incidence rates of 19,858 male and 14,222 females diagnosed with brain cancer in Australia between 1982 and 2012, and mobile phone usage data from 1987 to 2012. We modelled expected age specific rates (20-39, 40-59, 60-69, 70-84 years), based on published reports of relative risks (RR) of 1.5 in ever-users of mobile phones, and RR of 2.5 in a proportion of 'heavy users' (19% of all users), assuming a 10-year lag period between use and incidence.

SUMMARY ANSWERS

Age adjusted brain cancer incidence rates (20-84 years, per 100,000) have risen slightly in males (p<0.05) but were stable over 30 years in females (p>0.05) and are higher in males 8.7 (CI=8.1-9.3) than in females, 5.8 (CI=5.3-6.3). Assuming a causal RR of 1.5 and 10-year lag period, the expected incidence rate in males in 2012 would be 11.7 (11-12.4) and in females 7.7 (CI=7.2-8.3), both p<0.01; 1434 cases observed in 2012, vs. 1867 expected. Significant increases in brain cancer incidence were observed (in keeping with modelled rates) only in those aged ≥70 years (both sexes), but the increase in incidence in this age group began from 1982, before the introduction of mobile phones. Modelled expected incidence rates were higher in all age groups in comparison to what was observed. Assuming a causal RR of 2.5 among 'heavy users' gave 2038 expected cases in all age groups.

LIMITATIONS

This is an ecological trends analysis, with no data on individual mobile phone use and outcome.

WHAT THIS STUDY ADDS

The observed stability of brain cancer incidence in Australia between 1982 and 2012 in all age groups except in those over 70 years compared to increasing modelled expected estimates, suggests that the observed increases in brain cancer incidence in the older age group are unlikely to be related to mobile phone use. Rather, we hypothesize that the observed increases in brain cancer incidence in Australia are related to the advent of improved diagnostic procedures when computed tomography and related imaging technologies were introduced in the early 1980s.

Bias of health estimates obtained from chronic disease and risk factor surveillance systems using telephone population surveys in Australia: results from a representative face-to-face survey in Australia from 2010 to 2013

BACKGROUND

Emerging communication technologies have had an impact on population-based telephone surveys worldwide. Our objective was to examine the potential biases of health estimates in South Australia, a state of Australia, obtained via current landline telephone survey methodologies and to report on the impact of mobile-only household on household surveys.

METHODS

Data from an annual multi-stage, systematic, clustered area, face-to-face population survey, Health Omnibus Survey (approximately 3000 interviews annually), included questions about telephone ownership to assess the population that were non-contactable by current telephone sampling methods (2006 to 2013). Univariable analyses (2010 to 2013) and trend analyses were conducted for sociodemographic and health indicator variables in relation to telephone status. Relative coverage biases (RCB) of two hypothetical telephone samples was undertaken by examining the prevalence estimates of health status and health risk behaviours (2010 to 2013): directory-listed numbers, consisting mainly of landline telephone numbers and a small proportion of mobile telephone numbers; and a random digit dialling (RDD) sample of landline telephone numbers which excludes mobile-only households.

RESULTS

Telephone (landline and mobile) coverage in South Australia is very high (97%). Mobile telephone ownership increased slightly (7.4%), rising from 89.7% in 2006 to 96.3% in 2013; mobile-only households increased by 431% over the eight year period from 5.2% in 2006 to 27.6% in 2013. Only half of the households have either a mobile or landline number listed in the telephone directory. There were small differences in the prevalence estimates for current asthma, arthritis, diabetes and obesity between the hypothetical telephone samples and the overall sample. However, prevalence estimate for diabetes was slightly underestimated (RCB value of -0.077) in 2013. Mixed RCB results were found for having a mental health condition for both telephone samples. Current smoking prevalence was lower for both hypothetical telephone samples in absolute differences and RCB values: -0.136 to -0.191 for RDD landline samples and -0.129 to -0.313 for directory-listed samples.

CONCLUSION

These findings suggest landline-based sampling frames used in Australia, when appropriately weighted, produce reliable representative estimates for some health indicators but not for all. Researchers need to be aware of their limitations and potential biased estimates.

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

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.