Identifying risk factors for developing obesity: a record linkage longitudinal study in metropolitan Sydney using the 45 and Up Study.

BACKGROUND: Primary care clinicians have key responsibilities in obesity prevention and weight management. AIMS: We aimed to identify risk factors for developing obesity among people aged ≥45 years. METHODS: We conducted a record linkage longitudinal study of residents of metropolitan Sydney, Australia using data from the: (1) 45 and Up Study at baseline (2005-2009) and first follow-up (2012-2015); (2) Medicare claims; (3) Pharmaceutical Benefits Scheme; and (4) deaths registry. We examined risk factors for developing obesity (body mass index [BMI]: 30-40) at follow-up, separately for people within the: (1) healthy weight range (BMI 18.5-<25) and (2) overweight range (BMI 25-<30) at baseline. Covariates included demographics, modifiable behaviours, health status, allied health use, and medication use. Crude and adjusted relative risks were estimated using Poisson regression modelling. RESULTS: At follow-up, 1.1% (180/16,205) of those in the healthy weight range group, and 12.7% (1,939/15,266) of those in the overweight range group developed obesity. In both groups, the following were associated with developing obesity: current smoking at baseline, physical functioning limitations, and allied health service use through team care planning, while any alcohol consumption and adequate physical activity were found to be associated with a lower risk of developing obesity. In the healthy weight group, high psychological distress and the use of antiepileptics were associated with developing obesity. In the overweight group, female sex and full-time work were associated with developing obesity, while older age was found to be associated with a lower risk of developing obesity. CONCLUSIONS: These findings may inform the targeting of preventive interventions for obesity in clinical practice and broader public health programs.

Early intervention to prevent weight gain requires a targeted multidisciplinary team-based approach to improve diet, increase physical activity, and change behaviour. However, the capacity to provide this within primary care is limited and there is little funding for consultations with allied health professionals. There is a need to identify priority at-risk groups to help primary care clinicians target interventions to those in most need. We have identified, using a longitudinal study of residents of metropolitan Sydney, key characteristics of older adults who are at risk of gaining weight and developing obesity, including risk behaviours (smoking and physical inactivity), and chronic conditions or their treatment (physical function, psychological distress, and use of anti-epileptic medications). These findings may help alert clinicians to the need for preventive interventions in selected cases, as well as informing the targeting of public health programs.

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.

BACKGROUND: In 2012 mobile phone numbers were included into the ongoing New South Wales Population Health Survey (NSWPHS) using an overlapping dual-frame design. Previously in the NSWPHS the sample was selected using random digit dialing (RDD) of landline phone numbers. The survey was undertaken using computer assisted telephone interviewing (CATI). The weighting strategy needed to be significantly expanded to manage the differing probabilities of selection by frame, including that of children of mobile-only phone users, and to adjust for the increased chance of selection of dual-phone users. This paper describes the development of the final weighting strategy to properly combine the data from two overlapping sample frames accounting for the fact that population benchmarks for the different sampling frames were not available at the state or regional level. METHODS: Estimates of the number of phone numbers for the landline and mobile phone frames used to calculate the differing probabilities of selection by frame, for New South Wales (NSW) and by stratum, were obtained by apportioning Australian estimates as none were available for NSW. The weighting strategy was then developed by calculating person selection probabilities, selection weights, applying a constant composite factor to the dual-phone users sample weights, and benchmarking to the latest NSW population by age group, sex and stratum. RESULTS: Data from the NSWPHS for the first quarter of 2012 was used to test the weighting strategy. This consisted of data on 3395 respondents with 2171 (64%) from the landline frame and 1224 (36%) from the mobile frame. However, in order to calculate the weights, data needed to be available for all core weighting variables and so 3378 respondents, 2933 adults and 445 children, had sufficient data to be included. Average person weights were 3.3 times higher for the mobile-only respondents, 1.3 times higher for the landline-only respondents and 1.7 times higher for dual-phone users in the mobile frame compared to the dual-phone users in the landline frame. The overall weight effect for the first quarter of 2012 was 1.93 and the coefficient of variation of the weights was 0.96. The weight effects for 2012 were similar to, and in many cases less than, the effects found in the corresponding quarter of the 2011 NSWPHS when only a landline based sample was used. CONCLUSIONS: The inclusion of mobile phone numbers, through an overlapping dual-frame design, improved the coverage of the survey and an appropriate weighing procedure is feasible, although it added substantially to the complexity of the weighting strategy. Access to accurate Australian, State and Territory estimates of the number of landline and mobile phone numbers and type of phone use by at least age group and sex would greatly assist in the weighting of dual-frame surveys in Australia.

Impact of Fruit and Fruit Juice on Death and Disease Incidence: A Sex-Specific Longitudinal Analysis of 18 603 Adults.

BACKGROUND: The health benefits of fruits are well established, but fruit juice has been more controversial. Fruit and juice are often ingested with other foods, which prompted our investigation to determine whether fruit consumed as juice may negate the beneficial effects of consuming whole fruit in people with cardiovascular disease. METHODS AND RESULTS: We retrospectively analyzed data from a population-based study in Australia (the 45 and Up Study) linked with hospitalization and mortality data up to September 2018. Kaplan-Meier survival estimates and Cox proportional hazards models were used to examine effects of fruit, fruit juice, and the combination of fruit and fruit juice in relation to death and disease incidence among men and women living with cardiovascular disease. A total of 7308 deaths occurred among 18 603 participants diagnosed with cardiovascular disease over a 13-year follow-up. After multivariable adjustment, inadequate fruit intake (hazard ratio [HR], 1.12 [95% CI, 1.01-1.24]) and high fruit juice intake (HR, 1.26 [95% CI, 1.12-1.41]) predicted all-cause mortality in women. Also, high fruit juice intake plus either adequate fruit intake (HR, 1.18 [95% CI, 1.02-1.37]) or inadequate fruit intake (HR, 1.43 [95% CI, 1.21-1.69]) predicted mortality in women. No relationships were found in men after multivariable adjustments. Also, we found no prognostic value for fruit and fruit juice intake on disease incidence. CONCLUSIONS: In adults with cardiovascular disease, we found that fruit juice (in combination with adequate or inadequate fruit intake) predicted mortality in women but not in men. These effects became less clear when focusing on disease incidence.

Inclusion of mobile phone numbers into an ongoing population health survey in New South Wales, Australia: design, methods, call outcomes, costs and sample representativeness.

BACKGROUND: In Australia telephone surveys have been the method of choice for ongoing jurisdictional population health surveys. Although it was estimated in 2011 that nearly 20% of the Australian population were mobile-only phone users, the inclusion of mobile phone numbers into these existing landline population health surveys has not occurred. This paper describes the methods used for the inclusion of mobile phone numbers into an existing ongoing landline random digit dialling (RDD) health survey in an Australian state, the New South Wales Population Health Survey (NSWPHS). This paper also compares the call outcomes, costs and the representativeness of the resultant sample to that of the previous landline sample. METHODS: After examining several mobile phone pilot studies conducted in Australia and possible sample designs (screening dual-frame and overlapping dual-frame), mobile phone numbers were included into the NSWPHS using an overlapping dual-frame design. Data collection was consistent, where possible, with the previous years' landline RDD phone surveys and between frames. Survey operational data for the frames were compared and combined. Demographic information from the interview data for mobile-only phone users, both, and total were compared to the landline frame using χ2 tests. Demographic information for each frame, landline and the mobile-only (equivalent to a screening dual frame design), and the frames combined (with appropriate overlap adjustment) were compared to the NSW demographic profile from the 2011 census using χ2 tests. RESULTS: In the first quarter of 2012, 3395 interviews were completed with 2171 respondents (63.9%) from the landline frame (17.6% landline only) and 1224 (36.1%) from the mobile frame (25.8% mobile only). Overall combined response, contact and cooperation rates were 33.1%, 65.1% and 72.2% respectively. As expected from previous research, the demographic profile of the mobile-only phone respondents differed most (more that were young, males, Aboriginal and Torres Strait Islanders, overseas born and single) compared to the landline frame responders. The profile of respondents from the two frames combined, with overlap adjustment, was most similar to the latest New South Wales (NSW) population profile. CONCLUSIONS: The inclusion of the mobile phone numbers, through an overlapping dual-frame design, did not impact negatively on response rates or data collection, and although costing more the design was still cost-effective because of the additional interviews that were conducted with young people, Aboriginal and Torres Strait Islanders and people who were born overseas resulting in a more representative overall sample.

Different Types of Long-Term Milk Consumption and Mortality in Adults with Cardiovascular Disease: A Population-Based Study in 7236 Australian Adults over 8.4 Years.

Most studies disregard long-term dairy consumption behaviour and how it relates to mortality. We examined four different types of long-term milk consumption, namely whole milk, reduced fat milk, skim milk and soy milk, in relation to mortality among adults diagnosed with cardiovascular disease (CVD). A retrospective population-based study was conducted in Australia (the 45 and Up Study) linking baseline (2006-2009) and follow-up data (2012-2015) to hospitalisation and mortality data up to 30 September 2018. A total of 1,101 deaths occurred among 7236 participants with CVD over a mean follow-up of 8.4 years. Males (Hazard Ratio, HR = 0.69, 95% CI (0.54; 0.89)) and females (HR = 0.59 (0.38; 0.91)) with long-term reduced fat milk consumption had the lowest risk of mortality compared to counterparts with long-term whole milk consumption. Among participants with ischemic heart disease, males with a long-term reduced fat milk consumption had the lowest risk of mortality (HR = 0.63, 95% CI: 0.43; 0.92). We conclude that among males and females with CVD, those who often consume reduced fat milk over the long-term present with a 31-41% lower risk of mortality than those who often consume whole milk, supporting dairy advice from the Heart Foundation of replacing whole milk with reduced fat milk to achieve better health.

A population-based survey of knowledge of first aid for burns in New South Wales.

OBJECTIVE: To determine the current level of knowledge of first aid for a burn injury and sources of this knowledge among the general population of New South Wales. DESIGN, SETTING AND PARTICIPANTS: People aged 16 years or older were interviewed as part of the 2007 NSW Population Health Survey, a continuous telephone survey of NSW residents. MAIN OUTCOME MEASURE: Weighted proportion of the population with optimal first aid knowledge for burns. RESULTS: In total, 7320 respondents were asked questions related to burn injuries and first aid. Of the surveyed population, 82% reported that they would cool a burn with water, and 9% reported that they would cool the burn for the recommended 20 minutes. Few respondents reported that they would remove the patient's clothing and keep the injured person warm. The most common sources of first aid information were a first aid book (42%) and the internet (33%). Speaking a language other than English at home, and being over 65 years of age were associated with a lack of first aid knowledge. CONCLUSIONS: A minority of people living in NSW know the optimal time for cooling a burn injury and other appropriate first aid steps for burns. This study demonstrates a gap in the public's knowledge, especially among non-English speaking people and older people, and highlights the need for a clear, consistent first aid message.

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.

BACKGROUND: Since 1997, the NSW Population Health Survey (NSWPHS) had selected the sample using random digit dialing of landline telephone numbers. When the survey began coverage of the population by landline phone frames was high (96%). As landline coverage in Australia has declined and continues to do so, in 2012, a sample of mobile telephone numbers was added to the survey using an overlapping dual-frame design. Details of the methodology are published elsewhere. This paper discusses the impacts of the sampling frame change on the time series, and provides possible approaches to handling these impacts. METHODS: Prevalence estimates were calculated for type of phone-use, and a range of health indicators. Prevalence ratios (PR) for each of the health indicators were also calculated using Poisson regression analysis with robust variance estimation by type of phone-use. Health estimates for 2012 were compared to 2011. The full time series was examined for selected health indicators. RESULTS: It was estimated from the 2012 NSWPHS that 20.0% of the NSW population were mobile-only phone users. Looking at the full time series for overweight or obese and current smoking if the NSWPHS had continued to be undertaken only using a landline frame, overweight or obese would have been shown to continue to increase and current smoking would have been shown to continue to decrease. However, with the introduction of the overlapping dual-frame design in 2012, overweight or obese increased until 2011 and then decreased in 2012, and current smoking decreased until 2011, and then increased in 2012. Our examination of these time series showed that the changes were a consequence of the sampling frame change and were not real changes. Both the backcasting method and the minimal coverage method could adequately adjust for the design change and allow for the continuation of the time series. CONCLUSIONS: The inclusion of the mobile telephone numbers, through an overlapping dual-frame design, did impact on the time series for some of the health indicators collected through the NSWPHS, but only in that it corrected the estimates that were being calculated from a sample frame that was progressively covering less of the population.