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.

Primary Prevention of Cardiovascular Disease and Type 2 Diabetes Mellitus Using Mobile Health Technology: Systematic Review of the Literature.

BACKGROUND: Digital technology is an opportunity for public health interventions to reach a large part of the population. OBJECTIVE: This systematic literature review aimed to assess the effectiveness of mobile health-based interventions in reducing the risk of cardiovascular disease and type 2 diabetes mellitus. METHODS: We conducted the systematic search in 7 electronic databases using a predefined search strategy. We included articles published between inception of the databases and March 2019 if they reported on the effectiveness of an intervention for prevention of cardiovascular disease or type 2 diabetes via mobile technology. One researcher performed the search, study selection, data extraction, and methodological quality assessment. The steps were validated by the other members of the research team. RESULTS: The search yielded 941 articles for cardiovascular disease, of which 3 met the inclusion criteria, and 732 for type 2 diabetes, of which 6 met the inclusion criteria. The methodological quality of the studies was low, with the main issue being nonblinding of participants. Of the selected studies, 4 used SMS text messaging, 1 used WhatsApp, and the remaining ones used specific smartphone apps. Weight loss and reduction in BMI were the most reported successful outcomes (reported in 4 studies). CONCLUSIONS: Evidence on the effectiveness of mobile health-based interventions in reducing the risk for cardiovascular disease and type 2 diabetes is low due to the quality of the studies and the small effects that were measured. This highlights the need for further high-quality research to investigate the potential of mobile health interventions. TRIAL REGISTRATION: International Prospective Register of Systematic Reviews (PROSPERO) CRD42019135405; https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=135405.

End-of-life priorities of older adults with terminal illness and caregivers: A qualitative consultation.

BACKGROUND: As older adults approach the end-of-life (EOL), many are faced with complex decisions including whether to use medical advances to prolong life. Limited information exists on the priorities of older adults at the EOL. OBJECTIVE: This study aimed to explore patient and family experiences and identify factors deemed important to quality EOL care. METHOD: A descriptive qualitative study involving three focus group discussions (n = 18) and six in-depth interviews with older adults suffering from either a terminal condition and/or caregivers were conducted in NSW, Australia. Data were analysed thematically. RESULTS: Seven major themes were identified as follows: quality as a priority, sense of control, life on hold, need for health system support, being at home, talking about death and competent and caring health professionals. An underpinning priority throughout the seven themes was knowing and adhering to patient's wishes. CONCLUSION: Our study highlights that to better adhere to EOL patient's wishes a reorganization of care needs is required. The readiness of the health system to cater for this expectation is questionable as real choices may not be available in acute hospital settings. With an ageing population, a reorganization of care which influences the way we manage terminal patients is required.

Do general practice management and/or team care arrangements reduce avoidable hospitalisations in Central and Eastern Sydney, Australia?

BACKGROUND: The number of people living with chronic health conditions is increasing in Australia. The Chronic Disease Management program was introduced to Medicare Benefits Schedule (MBS) to provide a more structured approach to managing patients with chronic conditions and complex care needs. The program supports General Practitioners (GP)s claiming for up to one general practice management plan (GPMP) and one team care arrangement (TCA) every year and the patient claiming for up to five private allied health visits. We describe the profile of participants who claimed for GPMPs and/or TCAs in Central and Eastern Sydney (CES) and explore if GPMPs and/or TCAs are associated with fewer emergency hospitalisations (EH)s or potentially preventable hospitalisations (PPH)s over the following 5 years. METHODS: This research used the CES Primary and Community Health Cohort/Linkage Resource (CES-P&CH) based on the 45 and Up Study to identify a community-dwelling population in the CES region. There were 30,645 participants recruited within the CES area at baseline. The CES-P&CH includes 45 and Up Study questionnaire data linked to MBS data for the period 2006-2014. It also includes data from the Admitted Patient Data Collection, Emergency Department Data Collection and Deaths Registry linked by the NSW Centre for Health Record Linkage. RESULTS: Within a two-year health service utilisation baseline period 22% (5771) of CES participants had at least one claim for a GPMP and/or TCA. Having at least one claim for a GPMP and/or TCA was closely related to the socio-demographic and health needs of participants with higher EHs and PPHs in the 5 years that followed. However, after controlling for confounding factors such as socio-demographic need, health risk, health status and health care utilization no significant difference was found between having claimed for a GPMP and/or TCA during the two-year health service utilisation baseline period and EHs or PPHs in the subsequent 5 years. CONCLUSIONS: The use of GPMPs and/or TCAs in the CES area appears well-targeted towards those with chronic and complex care needs. There was no evidence to suggest that the use of GPMPs and /or TCAs has prevented hospitalisations in the CES region.

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 multimorbidity and complex multimorbidity on healthcare utilisation in older Australian adults aged 45 years or more: a large population-based cross-sectional data linkage study.

OBJECTIVES: As life expectancy increases, older people are living longer with multimorbidity (MM, co-occurrence of ≥2 chronic health conditions) and complex multimorbidity (CMM, ≥3 chronic conditions affecting ≥3 different body systems). We assessed the impacts of MM and CMM on healthcare service use in Australia, as little was known about this. DESIGN: Population-based cross-sectional data linkage study. SETTING: New South Wales, Australia. PARTICIPANTS: 248 496 people aged ≥45 years who completed the Sax Institute's 45 and Up Study baseline questionnaire. PRIMARY OUTCOME: High average annual healthcare service use (≥2 hospital admissions, ≥11 general practice visits and ≥2 emergency department (ED) visits) during the 3-year baseline period (year before, year of and year after recruitment). METHODS: Baseline questionnaire data were linked with hospital, Medicare claims and ED datasets. Poisson regression models were used to estimate adjusted and unadjusted prevalence ratios for high service use with 95% CIs. Using a count of chronic conditions (disease count) as an alternative morbidity metric was requested during peer review. RESULTS: Prevalence of MM and CMM was 43.8% and 15.5%, respectively, and prevalence increased with age. Across three healthcare settings, MM was associated with a 2.02-fold to 2.26-fold, and CMM was associated with a 1.83-fold to 2.08-fold, increased risk of high service use. The association was higher in the youngest group (45-59 years) versus the oldest group (≥75 years), which was confirmed when disease count was used as the morbidity metric in sensitivity analysis.When comparing impact using three categories with no overlap (no MM/CMM, MM with no CMM, and CMM), CMM had greater impact than MM across all settings. CONCLUSION: Increased healthcare service use among older adults with MM and CMM impacts on the demand for primary care and hospital services. Which of MM or CMM has greater impact on risk of high healthcare service use depends on the analytic method used. Ageing populations living longer with increasing burdens of MM and CMM will require increased Medicare funding and provision of integrated care across the healthcare system to meet their complex needs.

Correction: Mobile App Intervention of a Randomized Controlled Trial for Patients With Obesity and Those Who Are Overweight in General Practice: User Engagement Analysis Quantitative Study.

[This corrects the article DOI: 10.2196/45942.].

Mobile App Intervention of a Randomized Controlled Trial for Patients With Obesity and Those Who Are Overweight in General Practice: User Engagement Analysis Quantitative Study.

BACKGROUND: The Health eLiteracy for Prevention in General Practice trial is a primary health care-based behavior change intervention for weight loss in Australians who are overweight and those with obesity from lower socioeconomic areas. Individuals from these areas are known to have low levels of health literacy and are particularly at risk for chronic conditions, including diabetes and cardiovascular disease. The intervention comprised health check visits with a practice nurse, a purpose-built patient-facing mobile app (mysnapp), and a referral to telephone coaching. OBJECTIVE: This study aimed to assess mysnapp app use, its user profiles, the duration and frequency of use within the Health eLiteracy for Prevention in General Practice trial, its association with other intervention components, and its association with study outcomes (health literacy and diet) to determine whether they have significantly improved at 6 months. METHODS: In 2018, a total of 22 general practices from 2 Australian states were recruited and randomized by cluster to the intervention or usual care. Patients who met the main eligibility criteria (ie, BMI>28 in the previous 12 months and aged 40-74 years) were identified through the clinical software. The practice staff then provided the patients with details about this study. The intervention consisted of a health check with a practice nurse and a lifestyle app, a telephone coaching program, or both depending on the participants' choice. Data were collected directly through the app and combined with data from the 6-week health check with the practice nurses, the telephone coaching, and the participants' questionnaires at baseline and 6-month follow-up. The analyses comprised descriptive and inferential statistics. RESULTS: Of the 120 participants who received the intervention, 62 (52%) chose to use the app. The app and nonapp user groups did not differ significantly in demographics or prior recent hospital admissions. The median time between first and last app use was 52 (IQR 4-95) days, with a median of 5 (IQR 2-10) active days. App users were significantly more likely to attend the 6-week health check (2-sided Fisher exact test; P<.001) and participate in the telephone coaching (2-sided Fisher exact test; P=.007) than nonapp users. There was no association between app use and study outcomes shown to have significantly improved (health literacy and diet) at 6 months. CONCLUSIONS: Recruitment and engagement were difficult for this study in disadvantaged populations with low health literacy. However, app users were more likely to attend the 6-week health check and participate in telephone coaching, suggesting that participants who opted for several intervention components felt more committed to this study. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ACTRN12617001508369; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=373505. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2018-023239.

Community health navigator-assisted transition of care from hospital to community: protocol for a randomised controlled trial.

INTRODUCTION: The objective of this parallel group, randomised controlled trial is to evaluate a community health navigator (CHN) intervention provided to patients aged over 40 years and living with chronic health conditions to transition from hospital inpatient care to their homes. Unplanned hospital readmissions are costly for the health system and negatively impact patients. METHODS AND ANALYSIS: Patients are randomised post hospital discharge to the CHN intervention or usual care. A comparison of outcomes between intervention and control groups will use multivariate regression techniques that adjust for age, sex and any independent variables that are significantly different between the two groups, using multiple imputation for missing values. Time-to-event analysis will examine the relationship between seeing a CHN following discharge from the index hospitalisation and reduced rehospitalisations in the subsequent 60 days and 6 months. Secondary outcomes include medication adherence, health literacy, quality of life, experience of healthcare and health service use (including the cost of care). We will also conduct a qualitative assessment of the implementation of the navigator role from the viewpoint of stakeholders including patients, health professionals and the navigators themselves. ETHICS APPROVAL: Ethics approval was obtained from the Research Ethics and Governance Office, Sydney Local Health District, on 21 January 2022 (Protocol no. X21-0438 and 2021/ETH12171). The findings of the trial will be disseminated through peer-reviewed journals and national and international conference presentations. Data will be deposited in an institutional data repository at the end of the trial. This is subject to Ethics Committee approval, and the metadata will be made available on request. TRIAL REGISTRATION NUMBER: Australian New Zealand Clinical Trials Registry (ACTRN 12622000659707). ARTICLE SUMMARY: The objective of this trial is to evaluate a CHN intervention provided to patients aged over 40 years and living with chronic health conditions to transition from hospital inpatient care to their homes.

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.

Perceived coping & concern predict terrorism preparedness in Australia.

BACKGROUND: In the aftermath of major terrorist incidents research shows population shifts towards protective behaviours, including specific preparedness and avoidance responses. Less is known about individual preparedness in populations with high assumed threat but limited direct exposure, such as Australia. In this study we aimed to determine whether individuals with high perceived coping and higher concern would show greater preparedness to respond to terrorism threats. METHODS: Adults in New South Wales (NSW) completed terrorism perception and response questions as part of computer assisted telephone interviews (CATI) in 2010 (N=2038). Responses were weighted against the NSW population. Multiple logistic regression analyses were conducted to evaluate the relationship between personal coping/concern factors and terrorism-related preparedness and avoidance behaviours, and to control for potential confounders such as socio-demographic and threat perception factors. RESULTS: Increased vigilance for suspicious behaviours was the most commonly reported behavioural response to perceived terrorism threat. Multivariate analyses showed that the factor combination of high perceived coping and higher concern was the most consistent predictor of terrorism preparedness behaviours and evacuation intentions, including increased vigilance (Adjusted Odd Ratios (AOR)=2.07, p=0.001) learning evacuation plans (AOR=1.61, p=0.05), establishing emergency contact plans (AOR=2.73, p<0.001), willingness to evacuate homes (AOR=2.20, p=0.039), and willingness to evacuate workplaces or public facilities (AOR=6.19, p=0.015) during potential future incidents. CONCLUSION: The findings of this study suggest that terrorism preparedness behaviours are strongly associated with perceived high coping but that this relationship is also mediated by personal concerns relating to this threat. Cognitive variables such as coping self-efficacy are increasingly targeted as part of natural hazard preparedness and are a viable intervention target for terrorism preparedness initiatives. Raising individual coping perceptions may promote greater general and incident-specific preparedness and could form an integral element of community resilience strategies regarding this threat.

A Mobile App for Prevention of Cardiovascular Disease and Type 2 Diabetes Mellitus: Development and Usability Study.

BACKGROUND: Cardiovascular disease (CVD) and type 2 diabetes mellitus (T2DM) are posing a huge burden on health care systems worldwide. Mobile apps can deliver behavior change interventions for chronic disease prevention on a large scale, but current evidence for their effectiveness is limited. OBJECTIVE: This paper reported on the development and user testing of a mobile app that aims at increasing risk awareness and engaging users in behavior change. It would form part of an intervention for primary prevention of CVD and T2DM. METHODS: The theoretical framework of the app design was based on the Behaviour Change Wheel, combined with the capability, opportunity, and motivation for behavior change system and the behavior change techniques from the Behavior Change Technique Taxonomy (version 1). In addition, evidence from scientific literature has guided the development process. The prototype was tested for user-friendliness via an iterative approach. We conducted semistructured interviews with individuals in the target populations, which included the System Usability Scale. We transcribed and analyzed the interviews using descriptive statistics for the System Usability Scale and thematic analysis to identify app features that improved utility and usability. RESULTS: The target population was Australians aged ≥45 years. The app included 4 core modules (risk score, goal setting, health measures, and education). In these modules, users learned about their risk for CVD and T2DM; set goals for smoking, alcohol consumption, diet, and physical activity; and tracked them. In total, we included 12 behavior change techniques. We conducted 2 rounds of usability testing, each involving 5 participants. The average age of the participants was 58 (SD 8) years. Totally, 60% (6/10) of the participants owned iPhone Operating System phones, and 40% (4/10) of them owned Android phones. In the first round, we identified a technical issue that prevented 30% (3/10) of the participants from completing the registration process. Among the 70% (7/10) of participants who were able to complete the registration process, 71% (5/7) rated the app above average, based on the System Usability Scale. During the interviews, we identified some issues related to functionality, content, and language and clarity. We used the participants' feedback to improve these aspects. CONCLUSIONS: We developed the app using behavior change theory and scientific evidence. The user testing allowed us to identify and remove technical errors and integrate additional functions into the app, which the participants had requested. Next, we will evaluate the feasibility of the revised version of the app developed through this design process and usability testing.

Remotely Conducted App-Based Intervention for Cardiovascular Disease and Diabetes Risk Awareness and Prevention: Single-Group Feasibility Trial.

BACKGROUND: Cardiovascular disease and type 2 diabetes mellitus are two of the most prevalent chronic conditions worldwide. An unhealthy lifestyle greatly contributes to someone's risk of developing these conditions. Mobile health is an emerging technology that can help deliver health promotion interventions to the population, for example, in the form of health apps. OBJECTIVE: The aim of this study was to test the feasibility of an app-based intervention for cardiovascular and diabetes risk awareness and prevention by measuring nonusage, dropout, adherence to app use, and usability of the app over 3 months. METHODS: Participants were eligible if they were aged 45 years or older, resided in Australia, were free of cardiovascular disease and diabetes, were fluent in English, and owned a smartphone. In the beginning, participants received an email with instructions on how to install the app and a user guide. After 3 months, they received an email with an invitation to an end-of-study survey. The survey included questions about general smartphone use and the user version of the Mobile Application Rating Scale. We analyzed app-generated and survey data by using descriptive and inferential statistics as well as thematic analysis for open-text comments. RESULTS: Recruitment took place between September and October 2021. Of the 46 participants who consented to the study, 20 (44%) never used the app and 15 (33%) dropped out. The median age of the app users at baseline was 62 (IQR 56-67) years. Adherence to app use, that is, using the app at least once a week over 3 months, was 17% (8/46) of the total sample and 31% (8/26) of all app users. The mean app quality rating on the user version of the Mobile Application Rating Scale was 3.5 (SD 0.6) of 5 points. The app scored the highest for the information section and the lowest for the engagement section of the scale. CONCLUSIONS: Nonusage and dropouts were too high, and the adherence was too low to consider the intervention in its current form feasible. Potential barriers that we identified include the research team not actively engaging with participants early in the study to verify that all participants could install the app, the intervention did not involve direct contact with health care professionals, and the app did not have enough interactive features.

Mobile Health Use by Older Individuals at Risk of Cardiovascular Disease and Type 2 Diabetes Mellitus in an Australian Cohort: Cross-sectional Survey Study.

BACKGROUND: The digital transformation has the potential to change health care toward more consumers' involvement, for example, in the form of health-related apps which are already widely available through app stores. These could be useful in helping people understand their risk of chronic conditions and helping them to live more healthily. OBJECTIVE: With this study, we assessed mobile health app use among older Australians in general and among those who were at risk of cardiovascular disease or type 2 diabetes mellitus. METHODS: In this cross-sectional analysis, we used data from the second follow-up wave of the 45 and Up Study. It is a cohort study from New South Wales, Australia, with 267,153 participants aged 45 years and older that is based on a random sample from the Services Australia (formerly the Australian Government Department of Human Services) Medicare enrollment database. The 2019 follow-up questionnaire contained questions about technology and mobile health use. We further used data on prescribed drugs and hospitalizations to identify participants who already had cardiovascular disease or diabetes or who were at risk of these conditions. Our primary outcome measure was mobile health use, defined as having used a mobile health app before. We used descriptive statistics and multivariate logistic regression to answer the research questions. RESULTS: Overall, 31,946 individuals with a median age of 69 (IQR 63-76) years had completed the follow-up questionnaire in 2019. We classified half (16,422/31,946, 51.41%) of these as being at risk of cardiovascular disease or type 2 diabetes mellitus and 38.04% (12,152/31,946) as having cardiovascular disease or type 1 or type 2 diabetes mellitus. The proportion of mobile health app users among the at-risk group was 31.46% (5166/16,422) compared to 29.16% (9314/31,946) in the total sample. Those who used mobile health apps were more likely to be female, younger, without physical disability, and with a higher income. People at risk of cardiovascular disease or type 2 diabetes mellitus were not statistically significantly more likely to use mobile health than were people without risk (odds ratio 1.06, 95% CI 0.97-1.16; P=.18; adjusted for age, sex, income, and physical disability). CONCLUSIONS: People at risk of cardiovascular disease or type 2 diabetes mellitus were not more likely to use mobile health apps than were people without risk. Those who used mobile health apps were less likely to be male, older, with a physical disability, and with a lower income. From the results, we concluded that aspects of equity must be considered when implementing a mobile health intervention to reach all those that can potentially benefit from it.

Impact of multimorbidity and complex multimorbidity on mortality among older Australians aged 45 years and over: a large population-based record linkage study.

OBJECTIVES: Multimorbidity (MM, co-occurrence of two or more chronic conditions) and complex multimorbidity (CMM, three or more chronic conditions affecting three or more different body systems) are used in the assessment of complex healthcare needs and their impact on health outcomes. However, little is known about the impacts of MM and CMM on mortality in Australia. DESIGN: Community-based prospective cohort study. SETTING: New South Wales, Australia. PARTICIPANTS: People aged 45 years and over who completed the baseline survey of the 45 and Up Study. MEASURES: Baseline survey data from the 45 and Up Study were linked with deaths registry data. Deaths that occurred within 8 years from the baseline survey date were the study outcome. Eleven self-reported chronic conditions (cancer, heart disease, diabetes, stroke, Parkinson's disease, depression/anxiety, asthma, allergic rhinitis, hypertension, thrombosis and musculoskeletal conditions) from the baseline survey were included in the MM and CMM classifications. Cox proportional hazard models were used to estimate adjusted and unadjusted 8-year mortality hazard ratios (HRs). RESULTS: Of 251 689 people (53% female and 54% aged ≥60 years) in the cohort, 111 084 (44.1%) were classified as having MM and 39 478 (15.7%) as having CMM. During the 8-year follow-up, there were 25 891 deaths. Cancer (34.7%) was the most prevalent chronic condition and the cardiovascular system (50.9%) was the body system most affected by a chronic condition. MM and CMM were associated with a 37% (adjusted HR 1.36, 95% CI 1.32 to 1.40) and a 22% (adjusted HR 1.22, 95% CI 1.18 to 1.25) increased risk of death, respectively. The relative impact of MM and CMM on mortality decreased as age increased. CONCLUSION: MM and CMM were common in older Australian adults; and MM was a better predictor of all-cause mortality risk than CMM. Higher mortality risk in those aged 45-59 years indicates tailored, person-centred integrated care interventions and better access to holistic healthcare are needed for this age group.

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.

Qualitative Case Study: A Pilot Program to Improve the Integration of Care in a Vulnerable Inner-City Community.

Introduction: There is a strong correlation between vulnerable populations and poor health outcomes. Growing evidence suggests that person-centred interventions using 'link workers' can support communities to navigate and engage with health and community services, leading to improved health service access. We describe the initial phase and qualitative evaluation of a Healthy Living Program, supported by a link worker role. The Program aimed to improve health service access for residents of an Australian inner-city suburb. Methods: To inform future program development, semi-structured interviews were conducted with clients and stakeholders (n = 21). The interviews were analysed thematically to understand program impact, success factors, constraints and potential improvements. Results: Key themes relating to impacts were a new model of working with community, improved access to services, and responsiveness to community need. Key factors for success included being a trusted, consistent presence, having knowledge of the community and health system, and successful engagement with the community and stakeholders. The constraints included difficulty influencing health system change and lack of community input. Suggested improvements were expanding the service, enhancing health system change and increasing community involvement. Conclusion: Knowledge gained from this study will inform future integrated approaches in health districts to address health inequities in areas of need.

Frequent users of health services among community-based older Australians: Characteristics and association with mortality.

OBJECTIVES: To investigate characteristics of frequent users of general practice (GP; ≥21 visits in a year), medical specialist (≥10 visits), emergency department (ED; ≥2 presentations) and hospital services (≥2 overnight hospitalisations) and the association with mortality for people aged over 75 years. METHODS: The study included residents from Central and Eastern Sydney, Australia, aged over 75 years who participated in a large community-dwelling cohort study. Demographic, social and health characteristics data were extracted from the 45 and Up Study survey. Health service (GP, medical specialist, ED and hospitalisations) use and mortality data were extracted from linked administrative data. We calculated adjusted prevalence ratios to identify independent characteristics associated with frequent users of services at baseline (approx. 2008) and adjusted hazard ratios to assess the association between frequent users of services and mortality. RESULTS: Frequent users of services (GPs, medical specialists, EDs and hospitals) were more likely to be associated with ever having had heart disease and less likely to be associated with reporting good quality of life. Characteristics varied by service type. Frequent users of services were 1.5-2.0 times more likely to die within 7 years compared to those who were less frequent service users after controlling for all significant factors. CONCLUSIONS: Our analysis found that frequent service users aged over 75 years had poorer quality of life, more complex health conditions and higher mortality and so their health service use was not inappropriate. However, better management of these frequent service users may lead to better health outcomes.