2023 Australian guideline for assessing and managing cardiovascular disease risk.

INTRODUCTION: The 2023 Australian guideline for assessing and managing cardiovascular disease risk provides updated evidence-based recommendations for the clinical assessment and management of cardiovascular disease (CVD) risk for primary prevention. It includes the new Australian CVD risk calculator (Aus CVD Risk Calculator), based on an equation developed from a large New Zealand cohort study, customised and recalibrated for the Australian population. The new guideline replaces the 2012 guideline that recommended CVD risk assessment using the Framingham risk equation. MAIN RECOMMENDATIONS: The new guideline recommends CVD risk assessment in people without known CVD: all people aged 45-79 years, people with diabetes from 35 years, and First Nations people from 30 years. The new Aus CVD Risk Calculator should be used to estimate and categorise CVD risk into low (< 5% risk over five years), intermediate (5% to < 10% risk over five years) or high risk (≥ 10% over five years). The following reclassification factors may be applied to recategorise calculated risk to improve accuracy of risk prediction, particularly in individuals close to a risk threshold: Indigenous status/ethnicity, estimated glomerular filtration rate, urine albumin to creatinine ratio measurements, severe mental illness, coronary artery calcium score and family history of premature CVD. A variety of communication formats is available to communicate CVD risk to help enable shared decision making. Healthy lifestyle modification, including smoking cessation, nutrition, physical activity and limiting alcohol, is encouraged for all individuals. Blood pressure-lowering and lipid-modifying pharmacotherapies should be prescribed for high risk and considered for intermediate risk individuals, unless contraindicated or clinically inappropriate. Reassessment of CVD risk should be considered within five years for individuals at low risk and within two years for those with intermediate risk. Reassessment of CVD risk is not recommended for individuals at high risk. CHANGES IN ASSESSMENT AND MANAGEMENT AS A RESULT OF THE GUIDELINE: The updated guideline recommends assessment over a broader age range and uses the Aus CVD Risk Calculator, which replaces the previous Framingham-based equation. It incorporates new variables: social disadvantage, diabetes-specific risk markers, diagnosis of atrial fibrillation and use of blood pressure-lowering and lipid-modifying therapies. Reclassification factors are also a new addition. Updated risk categories and thresholds are based on the new Aus CVD Risk Calculator. The proportion of the population in the high risk category (≥ 10% over five years) is likely to be broadly comparable to more than 15% risk from the Framingham-based equation. The full guideline and Aus CVD Risk Calculator can be accessed at www.cvdcheck.org.au.

Mental health-related service and medicine use among a cohort of urban Aboriginal children and young people: Data linkage study.

OBJECTIVE: The objective was to describe mental health service and psychotropic medicine use among a cohort of Aboriginal young people and quantify their relation to sociodemographic, family and health factors. METHODS: In a prospective cohort study with data linkage, 892 Aboriginal children aged 0-17 years living in urban and regional areas of New South Wales, Australia, were included. We assessed mental health-related service use, paediatric service use and psychotropic medicine dispensing claims covered by the Australian Government Medicare Benefits Schedule and the Pharmaceutical Benefits Scheme from July 2012 to June 2017. RESULTS: Most children (71%) did not have a record of mental health service or psychotropic medication use. 18.7% had ⩾1 mental health-related service claim; 26.7% had ⩾1 paediatric service claim; and 20.3% had ⩾1 psychotropic medicine dispensing claim. General practitioner services were the most accessed mental health-related service (17.4%) and 12.7% had been dispensed attention-deficit hyperactivity disorder medicines. Child characteristics associated with treatment included emotional and behavioural problems (prevalence ratio: 1.97, 95% confidence interval = [1.46, 2.64] for mental health services; prevalence ratio: 2.87, 95% confidence interval = [2.07, 3.96] for medicines) and risky behaviour (prevalence ratio: 1.56, 95% confidence interval = [1.12, 2.16] for mental health services; prevalence ratio: 2.28, 95% confidence interval = [1.54, 3.37] for medicines). Parent-related factors included chronic illness (prevalence ratio: 1.42, 95% confidence interval = [1.03, 1.95] for mental health services; prevalence ratio: 2.00, 95% confidence interval = [1.49, 2.69] for medicines) and functional limitations (prevalence ratio: 1.61, 95% confidence interval = [1.16, 2.24] for mental health services; prevalence ratio: 1.86, 95% confidence interval = [1.34, 2.59] for medicines). CONCLUSIONS: Most Aboriginal children and young people did not have claims for mental health services or medicines. Aboriginal children with emotional and behavioural problems, or parents with health problems were more likely to have mental health service or medicine claims.

Electronic cigarette social norms among adolescents in New South Wales, Australia.

The use of electronic cigarettes (e-cigarettes) is common and increasing, especially among youth. In 2022/2023, 30% of 12- to 17-year-olds reported ever using e-cigarettes in Australia-a >50% increase from 2017 (14%). Several adverse e-cigarette health effects have been identified and most effects remain unknown. Social norms, rules that govern social behaviours, are associated with current and future adolescent e-cigarette use. Understanding social norms in Australian adolescents is critical to the development of targeted and effective e-cigarette prevention activities. This study aims to explore e-cigarette social norms among adolescents living in New South Wales, Australia. A total of 32 online single or paired semi-structured qualitative interviews were conducted involving 46 participants aged 14-17 years, as part of the Generation Vape project. Reflexive thematic analysis was applied within a constructivist perceptive. Adolescents perceived e-cigarettes use as prolific among their peers, with use considered common, acceptable and normal. Fuelled by social exposure to e-cigarettes, 'everyone' was generally thought to be using them (descriptive norms). E-cigarette use was considered so entrenched that it was part of adolescent identity, with abstinence regarded as atypical. Use was driven by an internalised desire to fit it (injunctive norm), rather than being attributed to overt/external 'peer-pressure'. Positive e-cigarette norms exist among Australian adolescents with norm formation strongly influenced by social exposure, including e-cigarette promotion. Prevention efforts should include limiting adolescent exposure to e-cigarette marketing to help redefine existing pro-e-cigarette social norms and protect health.

The future burden of oesophageal and stomach cancers attributable to modifiable behaviours in Australia: a pooled cohort study.

BACKGROUND: We quantified the individual and joint contribution of contemporaneous causal behavioural exposures on the future burden of oesophageal and stomach cancers and their subtypes and assessed whether these burdens differ between population groups in Australia, as such estimates are currently lacking. METHODS: We combined hazard ratios from seven pooled Australian cohorts (N = 367,058) linked to national cancer and death registries with exposure prevalence from the 2017-2018 National Health Survey to estimate Population Attributable Fractions (PAFs) with 95% confidence intervals (CIs), accounting for competing risk of death. RESULTS: Current and past smoking explain 35.2% (95% CI = 11.7-52.4%), current alcohol consumption exceeding three drinks/day 15.7% (95% CI = 0.9-28.4%), and these exposures jointly 41.4% (95% CI = 19.8-57.3%) of oesophageal squamous cell carcinomas in Australia. Current and past smoking contribute 38.2% (95% CI = 9.4-57.9%), obesity 27.0% (95% CI = 0.6-46.4%), and these exposures jointly 54.4% (95% CI = 25.3-72.1%) of oesophageal adenocarcinomas. Overweight and obesity explain 36.1% (95% CI = 9.1-55.1%), current and past smoking 24.2% (95% CI = 4.2-40.0%), and these exposures jointly 51.2% (95% CI = 26.3-67.8%) of stomach cardia cancers. Several population groups had a significantly higher smoking-attributable oesophageal cancer burden, including men and those consuming excessive alcohol. CONCLUSIONS: Smoking is the leading preventable behavioural cause of oesophageal cancers and overweight/obesity of stomach cancers.

Population-level contribution of interpersonal discrimination to psychological distress among Australian Aboriginal and Torres Strait Islander adults, and to Indigenous-non-Indigenous inequities: cross-sectional analysis of a community-controlled First Nations cohort study.

BACKGROUND: International and population-specific evidence identifies elevated psychological distress prevalence among those experiencing interpersonal discrimination. We aim to quantify the potential whole-of-population contribution of interpersonal discrimination to psychological distress prevalence and Indigenous-non-Indigenous gaps in Australia. METHODS: We did a cross-sectional analysis of data from Mayi Kuwayu: the National Study of Aboriginal and Torres Strait Islander Wellbeing. Baseline surveys were completed between June 8, 2018, and Sept 28, 2022. We analysed responses from participants who were aged 18 years or older at survey completion, whose surveys were processed between Oct 1, 2018, and May 1, 2021. Sample weights were developed on the basis of national population benchmarks. We measured everyday discrimination using an eight-item measure modified from the Everyday Discrimination Scale and classified experiences as racial discrimination if participants attributed these experiences to their Indigeneity. Psychological distress was measured using a validated, modified Kessler-5 scale. Applying logistic regression, we calculated unadjusted odds ratios (ORs), to approximate incident rate ratios (IRRs), for high or very high psychological distress in relation to everyday discrimination and everyday racial discrimination across age-gender strata. Population attributable fractions (PAFs), under the hypothetical assumption that ORs represent causal relationships, were calculated using these ORs and population-level exposure prevalence. These PAFs were used to quantify the contribution of everyday racial discrimination to psychological distress gaps between Indigenous and non-Indigenous adults. FINDINGS: 9963 survey responses were eligible for inclusion in our study, of which we analysed 9951 (99·9%); 12 were excluded due to responders identifying as a gender other than man or woman (there were too few responses from this demographic to be included as a category in stratified tables or adjusted analyses). The overall prevalence of psychological distress was 48·3% (95% CI 47·0-49·6) in those experiencing everyday discrimination compared with 25·2% (23·8-26·6) in those experiencing no everyday discrimination (OR 2·77 [95% CI 2·52-3·04]) and psychological distress prevalence was 49·0% (95% CI 47·3-50·6) in those experiencing everyday racial discrimination and 31·8% (30·6-33·1) in those experiencing no everyday racial discrimination (OR 2·06 [95% CI 1·88-2·25]. Overall, 49·3% of the total psychological distress burden among Aboriginal and Torres Strait Islander adults could be attributable to everyday discrimination (39·4-58·8% across strata) and 27·1% to everyday racial discrimination. Everyday racial discrimination could explain 47·4% of the overall gap in psychological distress between Indigenous and non-Indigenous people (40·0-60·3% across strata). INTERPRETATION: Our findings show that interpersonal discrimination might contribute substantially to psychological distress among Aboriginal and Torres Strait Islander adults, and to inequities compared with non-Indigenous adults. Estimated PAFs include contributions from social and health disadvantage, reflecting contributions from structural racism. Although not providing strictly conclusive evidence of causality, this evidence is sufficient to indicate the psychological harm of interpersonal discrimination. Findings add weight to imperatives to combat discrimination and structural racism at its core. Urgent individual and policy action is required of non-Indigenous people and colonial structures, directed by Aboriginal and Torres Strait Islander peoples. FUNDING: National Health and Medical Research Council of Australia, Ian Potter Foundation, Australian Research Council, US National Institutes of Health, and Sierra Foundation.

Analysis of Multiple Causes of Death: A Review of Methods and Practices.

BACKGROUND: Research and reporting of mortality indicators typically focus on a single underlying cause of death selected from multiple causes recorded on a death certificate. The need to incorporate the multiple causes in mortality statistics-reflecting increasing multimorbidity and complex causation patterns-is recognized internationally. This review aims to identify and appraise relevant analytical methods and practices related to multiple causes. METHODS: We searched Medline, PubMed, Scopus, and Web of Science from their incept ion to December 2020 without language restrictions, supplemented by consultation with international experts. Eligible articles analyzed multiple causes of death from death certificates. The process identified 4,080 items of which we reviewed 434 full-text articles. RESULTS: Most articles we reviewed (76%, n = 332) were published since 2001. The majority of articles examined mortality by "any- mention" of the cause of death (87%, n = 377) and assessed pairwise combinations of causes (57%, n = 245). Since 2001, applications of methods emerged to group deaths based on common cause patterns using, for example, cluster analysis (2%, n = 9), and application of multiple-cause weights to re-evaluate mortality burden (1%, n = 5). We describe multiple-cause methods applied to specific research objectives for approaches emerging recently. CONCLUSION: This review confirms rapidly increasing international interest in the analysis of multiple causes of death and provides the most comprehensive overview, to our knowledge, of methods and practices to date. Available multiple-cause methods are diverse but suit a range of research objectives. With greater availability of data and technology, these could be further developed and applied across a range of settings.

Pain and its interference with daily living in relation to cancer: a comparative population-based study of 16,053 cancer survivors and 106,345 people without cancer.

BACKGROUND: Pain is a common, debilitating, and feared symptom, including among cancer survivors. However, large-scale population-based evidence on pain and its impact in cancer survivors is limited. We quantified the prevalence of pain in community-dwelling people with and without cancer, and its relation to physical functioning, psychological distress, and quality of life (QoL). METHODS: Questionnaire data from participants in the 45 and Up Study (Wave 2, n = 122,398, 2012-2015, mean age = 60.8 years), an Australian population-based cohort study, were linked to cancer registration data to ascertain prior cancer diagnoses. Modified Poisson regression estimated age- and sex-adjusted prevalence ratios (PRs) for bodily pain and pain sufficient to interfere with daily activities (high-impact pain) in people with versus without cancer, for 13 cancer types, overall and according to clinical, personal, and health characteristics. The relation of high-impact pain to physical and mental health outcomes was quantified in people with and without cancer. RESULTS: Overall, 34.9% (5,436/15,570) of cancer survivors and 31.3% (32,471/103,604) of participants without cancer reported bodily pain (PR = 1.07 [95% CI = 1.05-1.10]), and 15.9% (2,468/15,550) versus 13.1% (13,573/103,623), respectively, reported high-impact pain (PR = 1.13 [1.09-1.18]). Pain was greater with more recent cancer diagnosis, more advanced disease, and recent cancer treatment. High-impact pain varied by cancer type; compared to cancer-free participants, PRs were: 2.23 (1.71-2.90) for multiple myeloma; 1.87 (1.53-2.29) for lung cancer; 1.06 (0.98-1.16) for breast cancer; 1.05 (0.94-1.17) for colorectal cancer; 1.04 (0.96-1.13) for prostate cancer; and 1.02 (0.92-1.12) for melanoma. Regardless of cancer diagnosis, high-impact pain was strongly related to impaired physical functioning, psychological distress, and reduced QoL. CONCLUSIONS: Pain is common, interfering with daily life in around one-in-eight older community-dwelling participants. Pain was elevated overall in cancer survivors, particularly for certain cancer types, around diagnosis and treatment, and with advanced disease. However, pain was comparable to population levels for many common cancers, including breast, prostate and colorectal cancer, and melanoma.

Health behaviours associated with healthy body composition among Aboriginal adolescents in Australia in the 'Next Generation: Youth Well-being study'.

This study described the distribution of healthy body composition among Aboriginal adolescents in Australia aged 10-24 years and examined associations with health behaviours and self-rated health. Data were cross-sectional from the 'Next Generation: Youth Well-being study' baseline (N = 1294). We used robust Poisson regression to quantify associations of self-reported health behaviours (physical activity, screen time, sleep, consumption of vegetables, fruit, soft drinks and fast food, and tobacco smoking and alcohol) and self-rated health to healthy body mass index (BMI) and waist/height ratio (WHtR). Overall, 48% of participants had healthy BMI and 64% healthy WHtR, with healthy body composition more common among younger adolescents. Higher physical activity was associated with healthy body composition (5-7 days last week vs none; adjusted prevalence ratio (aPR) healthy BMI 1.31 [95% CI 1.05-1.64], and healthy WHtR 1.30 [1.10-1.54]), as was recommended sleep duration (vs not; aPR healthy BMI 1.56 [1.19-2.05], and healthy WHtR 1.37 [1.13-1.67]). There was a trend for higher proportion of healthy body composition with more frequent fast food consumption. Healthy body composition was also associated with higher self-rated health ('very good/excellent' vs 'poor/fair'; aPR healthy BMI 1.87 [1.45-2.42], and healthy WHtR 1.71 [1.40-2.10]). Culturally appropriate community health interventions with a focus on physical activity and sleep may hold promise for improving body composition among Aboriginal adolescents.

Evidence supporting the choice of a new cardiovascular risk equation for Australia.

This article reviews the risk equations recommended for use in international cardiovascular disease (CVD) primary prevention guidelines and assesses their suitability for use in Australia against a set of a priori defined selection criteria. The review and assessment were commissioned by the National Heart Foundation of Australia on behalf of the Australian Chronic Disease Prevention Alliance to inform recommendations on CVD risk estimation as part of the 2023 update of the Australian CVD risk assessment and management guidelines. Selected international risk equations were assessed against eight selection criteria: development using contemporary data; inclusion of established cardiovascular risk factors; inclusion of ethnicity and deprivation measures; prediction of a broad selection of fatal and non-fatal CVD outcomes; population representativeness; model performance; external validation in an Australian dataset; and the ability to be recalibrated or modified. Of the ten risk prediction equations reviewed, the New Zealand PREDICT equation met seven of the eight selection criteria, and met additional usability criteria aimed at assessing the ability to apply the risk equation in practice in Australia.

Electronic cigarettes and health outcomes: umbrella and systematic review of the global evidence.

OBJECTIVE: To review and synthesise the global evidence regarding the health effects of electronic cigarettes (e-cigarettes, vapes). STUDY DESIGN: Umbrella review (based on major independent reviews, including the 2018 United States National Academies of Sciences, Engineering, and Medicine [NASEM] report) and top-up systematic review of published, peer-reviewed studies in humans examining the relationship of e-cigarette use to health outcomes published since the NASEM report. DATA SOURCES: Umbrella review: eight major independent reviews published 2017-2021. Systematic review: PubMed, MEDLINE, Scopus, Web of Science, the Cochrane Library, and PsycINFO (articles published July 2017 - July 2020 and not included in NASEM review). DATA SYNTHESIS: Four hundred eligible publications were included in our synthesis: 112 from the NASEM review, 189 from our top-up review search, and 99 further publications cited by other reviews. There is conclusive evidence linking e-cigarette use with poisoning, immediate inhalation toxicity (including seizures), and e-cigarette or vaping product use-associated lung injury (EVALI; largely but not exclusively for e-liquids containing tetrahydrocannabinol and vitamin E acetate), as well as for malfunctioning devices causing injuries and burns. Environmental effects include waste, fires, and generation of indoor airborne particulate matter (substantial to conclusive evidence). There is substantial evidence that nicotine e-cigarettes can cause dependence or addiction in non-smokers, and strong evidence that young non-smokers who use e-cigarettes are more likely than non-users to initiate smoking and to become regular smokers. There is limited evidence that freebase nicotine e-cigarettes used with clinical support are efficacious aids for smoking cessation. Evidence regarding effects on other clinical outcomes, including cardiovascular disease, cancer, development, and mental and reproductive health, is insufficient or unavailable. CONCLUSION: E-cigarettes can be harmful to health, particularly for non-smokers and children, adolescents, and young adults. Their effects on many important health outcomes are uncertain. E-cigarettes may be beneficial for smokers who use them to completely and promptly quit smoking, but they are not currently approved smoking cessation aids. Better quality evidence is needed regarding the health impact of e-cigarette use, their safety and efficacy for smoking cessation, and effective regulation. REGISTRATION: Systematic review: PROSPERO, CRD42020200673 (prospective).

Fifty-year forecasts of daily smoking prevalence: can Australia reach 5% by 2030?

OBJECTIVE: To compare 50-year forecasts of Australian tobacco smoking rates in relation to trends in smoking initiation and cessation and in relation to a national target of ≤5% adult daily prevalence by 2030. METHODS: A compartmental model of Australian population daily smoking, calibrated to the observed smoking status of 229 523 participants aged 20-99 years in 26 surveys (1962-2016) by age, sex and birth year (1910-1996), estimated smoking prevalence to 2066 using Australian Bureau of Statistics 50-year population predictions. Prevalence forecasts were compared across scenarios in which smoking initiation and cessation trends from 2017 were continued, kept constant or reversed. RESULTS: At the end of the observation period in 2016, model-estimated daily smoking prevalence was 13.7% (90% equal-tailed interval (EI) 13.4%-14.0%). When smoking initiation and cessation rates were held constant, daily smoking prevalence reached 5.2% (90% EI 4.9%-5.5%) after 50 years, in 2066. When initiation and cessation rates continued their trajectory downwards and upwards, respectively, daily smoking prevalence reached 5% by 2039 (90% EI 2037-2041). The greatest progress towards the 5% goal came from eliminating initiation among younger cohorts, with the target met by 2037 (90% EI 2036-2038) in the most optimistic scenario. Conversely, if initiation and cessation rates reversed to 2007 levels, estimated prevalence was 9.1% (90% EI 8.8%-9.4%) in 2066. CONCLUSION: A 5% adult daily smoking prevalence target cannot be achieved by the year 2030 based on current trends. Urgent investment in concerted strategies that prevent smoking initiation and facilitate cessation is necessary to achieve 5% prevalence by 2030.

Output-orientated policy engagement: a model for advancing the use of epidemiological evidence in health policy.

BACKGROUND: Use of epidemiological research in policy and practice is suboptimal, contributing to significant preventable morbidity and mortality. Barriers to the use of research evidence in policy include lack of research-policy engagement, lack of policy-relevant research, differences in policymaker and researcher practice norms, time constraints, difficulties in coordination, and divergent languages and reward systems. APPROACH AND OUTCOMES: In order to increase policy-relevant research and research uptake, we developed the output-orientated policy engagement (OOPE) model, in Australia. It integrates a foundational approach to engagement with cycles of specific activity focused around selected research outputs. Foundational elements include measures to increase recognition and valuing of policymaker expertise, emphasis on policy uptake, policy awareness of the research group's work, regular policy engagement and policy-relevant capacity-building. Specific activities include (i) identification of an "output"-usually at draft stage-and program of work which are likely to be of interest to policymakers; (ii) initial engagement focusing on sharing "preview" evidence from this output, with an invitation to provide input into this and to advise on the broader program of work; and (iii) if there is sufficient interest, formation of a researcher-policy-maker partnership to shape and release the output, as well as inform the program of work. This cycle is repeated as the relationship continues and is deepened. As well as supporting policy-informed evidence generation and research-aware policymakers, the output-orientated model has been found to be beneficial in fostering the following: a pragmatic starting place for researchers, in often large and complex policy environments; purposeful and specific engagement, encouraging shared expectations; non-transactional engagement around common evidence needs, whereby researchers are not meeting with policymakers with the expectation of receiving funding; built-in translation; time and resource efficiency; relationship-building; mutual learning; policy-invested researchers and research-invested policy-makers; and tangible policy impacts. A case study outlines how the output-orientated approach supported researcher-policymaker collaboration to generate new evidence regarding Aboriginal and Torres Strait Islander cardiovascular disease risk and to apply this to national guidelines. CONCLUSION: Output-orientated policy engagement provides a potentially useful pragmatic model to catalyse and support partnerships between researchers and policymakers, to increase the policy-relevance and application of epidemiological evidence.

Thyroid cancers potentially preventable by reducing overweight and obesity in Australia: A pooled cohort study.

Thyroid cancer incidence and the prevalence of overweight and obesity are increasing, but the future thyroid cancer burden attributable to contemporary levels of overweight and obesity has not been evaluated before. We quantified this burden in Australia, and assessed whether the overweight/obesity-attributable burden differed by sex or other population subgroupings. We estimated the strength of the associations of overweight and obesity with thyroid cancer with adjusted proportional hazards models using pooled data from seven Australian cohorts (N = 367 058) with 431 thyroid cancer cases ascertained from linked national cancer registry data during a maximum 22-year follow-up. We combined these estimates with nationally representative 2017 to 2018 estimates of overweight and obesity prevalence to estimate population attributable fractions (PAFs) of future thyroid cancers attributable to overweight and obesity, accounting for competing risk of death, and compared PAFs for population subgroups. Contemporary levels of overweight and obesity explain 18.6% (95% confidence interval [CI] = 5.2%-30.2%), and obesity alone 13.7% (95% CI: 5.2%-21.4%), of the future thyroid cancer burden. The obesity-attributable thyroid cancer burden is 21.4% (95% CI: 2.8%-36.5%) for men and 10.1% (95% CI: 0.8%-18.6%) for women. Were the currently obese overweight instead, 9.9% (95% CI: 1.0%-18.1%) of thyroid cancers could be avoided. The relative overweight/obesity-attributable burden is higher for those consuming on average more than two alcoholic drinks per day (63.4%) and for those who are not married/co-habiting (33.2%). In conclusion, avoiding excess weight, especially obesity, should be a priority for thyroid cancer prevention. Further studies, with findings stratified by tumour size, may reveal the potential role of overdiagnosis in our results.

Family history, obesity, urological factors and diabetic medications and their associations with risk of prostate cancer diagnosis in a large prospective study.

BACKGROUND: Prostate cancer (PC) aetiology is unclear. PC risk was examined in relation to several factors in a large population-based prospective study. METHODS: Male participants were from Sax Institute's 45 and Up Study (Australia) recruited between 2006 and 2009. Questionnaire and linked administrative health data from the Centre for Health Record Linkage and Services Australia were used to identify incident PC, healthcare utilisations, Prostate Specific Antigen (PSA) testing reimbursements and dispensing of metformin and benign prostatic hyperplasia (BPH) prescriptions. Multivariable Cox and Joint Cox regression analyses were used to examine associations by cancer spread, adjusting for various confounders. RESULTS: Of 107,706 eligible men, 4257 developed incident PC up to end 2013. Risk of PC diagnosis increased with: PC family history (versus no family history of cancer; HRadjusted = 1.36; 95% CI:1.21-1.52); father and brother(s) diagnosed with PC (versus cancer-free family history; HRadjusted = 2.20; 95% CI:1.61-2.99); severe lower-urinary-tract symptoms (versus mild; HRadjusted = 1.77; 95% CI:1.53-2.04) and vasectomy (versus none; HRadjusted = 1.08; 95% CI:1.00-1.16). PC risk decreased with dispensed prescriptions (versus none) for BPH (HRadjusted = 0.76; 95% CI:0.69-0.85) and metformin (HRadjusted = 0.57; 95% CI:0.48-0.68). Advanced PC risk increased with vasectomy (HRadjusted = 1.28; 95% CI:1.06-1.55) and being obese (versus normal weight; HRadjusted = 1.31; 95% CI:1.01-1.69). CONCLUSION: Vasectomy and obesity are associated with an increased risk of advanced PC. The reduced risk of localised and advanced PC associated with BPH, and diabetes prescriptions warrants investigation.

Observed and predicted premature mortality in Australia due to non-communicable diseases: a population-based study examining progress towards the WHO 25X25 goal.

BACKGROUND: The World Health Organization's (WHO) 25X25 goal aims for a 25% relative reduction in premature death due to four non-communicable diseases (NCD4)-cancer, cardiovascular disease, chronic respiratory diseases and diabetes-by 2025 compared to 2010. This study aimed to quantify the premature mortality in the Australian population due to NCD4, quantify the variation in mortality rates by age and sex, predict the premature mortality due to NCD4 in 2025 and evaluate the progress towards the WHO 25X25 goal. METHODS: A population-based study using cause-specific mortality data of all deaths which occurred in Australia from 2010 to 2016 and registered up to 2017, for adults aged 30-69 years, was conducted. Age-specific and age-standardised mortality rates (ASMR) and probability of death for NCD4 were calculated for each year. ASMRs in 2016 were calculated for men and women. Deaths and the probability of death in 2025 were predicted using Poisson regression based on data from 2006 to 2016. To assess the progress against the WHO 25X25 goal, the relative reduction in the probability of death from NCD4 conditions in 2025 compared to 2010 was calculated. RESULTS: ASMRs for NCD4 decreased from 2010 to 2016, except for diabetes which increased on average by 2.5% per year. Across sociodemographic factors, ASMRs were highest in males and increased with age. The projected probability of premature death in 2025 was 7.36%, equivalent to a relative reduction of 25.16% compared to 2010 levels. CONCLUSIONS: Premature mortality due to cancer, cardiovascular disease, respiratory diseases and diabetes declined in Australia from 2010 to 2016. This trend is consistent across age groups and by sex, and higher mortality rates were observed in males and at older ages. Nationally, if the current trends continue, we estimate that Australia will achieve a 25.16% relative reduction in premature deaths due to NCD4 in 2025 compared to 2010, signifying substantial progress towards the WHO 25X25 goal. Concerted efforts will need to continue to meet the 25X25 goal, especially in the context of the COVID-19 pandemic.

Opening up safely: public health system requirements for ongoing COVID-19 management based on evaluation of Australia's surveillance system performance.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) community transmission was eliminated in Australia from 1/11/2020 to 30/6/2021, allowing evaluation of surveillance system performance in detecting novel outbreaks, including against variants of concern (VoCs). This paper aims to define system requirements for coronavirus disease 2019 (COVID-19) surveillance under future transmission and response scenarios, based on surveillance system performance to date. METHODS: This study described and evaluated surveillance systems and epidemiological characteristics of novel outbreaks based on publicly available data, and assessed surveillance system sensitivity and timeliness in outbreak detection. These findings were integrated with analysis of other critical COVID-19 public health measures to establish future COVID-19 management requirements. RESULTS: Twenty-five epidemiologically distinct outbreaks and five distinct clusters were identified in the study period, all linked through genomic sequencing to novel introductions from international travellers. Seventy percent (21/30) were detected through community testing of people with acute respiratory illness, and 30% (9/30) through quarantine screening. On average, 2.07% of the State population was tested in the week preceding detection for those identified through community surveillance. From 17/30 with publicly available data, the average time from seeding to detection was 4.9 days. One outbreak was preceded by unexpected positive wastewater results. Twenty of the 24 outbreaks in 2021 had publicly available sequencing data, all of which identified VoCs. A surveillance strategy for future VoCs similar to that used for detecting SARS-CoV-2 would require a 100-1000-fold increase in genomic sequencing capacity compared to the study period. Other essential requirements are maintaining outbreak response capacity and developing capacity to rapidly engineer, manufacture, and distribute variant vaccines at scale. CONCLUSIONS: Australia's surveillance systems performed well in detecting novel introduction of SARS-CoV-2 while community transmission was eliminated; introductions were infrequent and case numbers were low. Detection relied on quarantine screening and community surveillance in symptomatic members of the general population, supported by comprehensive genomic sequencing. Once vaccine coverage is maximised, future COVID-19 control should shift to detection of SARS-CoV-2 VoCs, requiring maintenance of surveillance systems and testing all international arrivals, alongside greatly increased genomic sequencing capacity. Effective government support of localised public health response mechanisms and engagement of all sectors of the community is crucial to current and future COVID-19 management.

The relationship of socioeconomic factors to the use of preventative cardiovascular disease medications: A prospective Australian cohort study.

Cardiovascular disease (CVD) events are highly preventable through appropriate treatment and disproportionally affect socioeconomically disadvantaged individuals. This study quantified the relationship of socioeconomic factors to dispensing and persistent use of lipid- and blood pressure-lowering medication following hospital admission for a major CVD event (myocardial infarction, ischaemic stroke/transient ischaemic attack). Data from 8285 people with such events aged ≥45 years from the Australian 45 and Up Study with linked medication data were used to estimate relative risks (RRs) for combined lipid- and blood pressure-lowering dispensing at three-months following hospital discharge and for 12-month persistent use, in relation to education, income, and level of medication subsidisation. Overall, 56% were dispensed guideline-recommended medications at three months and 37% persistently used them across 12 months. After adjusting for demographic factors, type of CVD and history of CVD hospitalisation, RRs for lowest (no educational qualifications) compared to highest education level (university degree) were 1.14 (95% CI: 1.06, 1.22) for medication dispensing and 1.15 (1.02, 1.29) for persistent medication use; 1.14 (1.06, 1.22) and 1.17 (1.04, 1.32) respectively for lowest (<$20,000) versus highest (≥$70,000) household pre-tax income; and 1.25 (1.17, 1.33) and 1.28 (1.15, 1.43) respectively for those receiving highest versus lowest subsidisation. There was little to no evidence of a relationship of income and education to medication use after adjustment for medication subsidisation. While preventive medication use is sub-optimal, subsidisation is substantially associated with increased use and accounts for most of the relationship with socioeconomic position, suggesting subsidy schemes are working in the intended direction.

Large-Scale Population-Based Surveys Linked to Administrative Health Databases as a Source of Data on Health Utilities in Australia.

OBJECTIVES: Large-scale health surveys that contain quality-of-life instruments are a rich source of health utility data for health economic evaluations, especially when linked to routinely collected, administrative health databases. We derived health utility values for a wide range of health conditions using a large Australian cohort study linked to population-wide health databases. METHODS: Short-Form 6-Dimension utility values were calculated for 56 094 adults, aged 47+ years, in the New South Wales 45 and Up Study who completed the Social, Economic, and Environmental Factors survey (2010-2011). Mean utilities were summarized for major health conditions identified through self-report, hospital records, primary cancer notifications, and claims for government-subsidized prescription medicines and medical services. To identify unique associations between health conditions and utilities, beta regression was performed. Utility values were analyzed by time to death using linked death records. RESULTS: Mean Short-Form 6-Dimension utility was 0.810 (95% confidence interval [CI] 0.809-0.811), was age dependent, and was higher in men than women. Utilities for serious health conditions ranged from 0.685 (95% CI 0.652-0.718) for lung cancer to 0.800 (95% CI 0.787-0.812) for melanoma whereas disease-free respondents had a mean of 0.859 (95% CI 0.858-0.861). Most health conditions were independently associated with poorer quality of life. Utility values also declined by proximity to death where participants sampled 6 months before death had a mean score of 0.637 (95% CI 0.613-0.662). CONCLUSIONS: Our data offer a snapshot of the health status of an older Australian population and show that record linkage can enable comprehensive ascertainment of utility values for use in health economic modeling.

Clearing the air: underestimation of youth smoking prevalence associated with proxy-reporting compared to youth self-report.

BACKGROUND: Smoking remains a leading cause of disease burden globally. Declining youth smoking prevalence is an essential feature of effective tobacco control; however, accurate data are required to assess progress. This study investigates bias in youth smoking prevalence estimates by respondent type (proxy-reported, self-report with parent present, or self-report independently) for Aboriginal and Torres Strait Islander and total populations of Australia. METHODS: Repeated cross-sectional analysis of representative Aboriginal and Torres Strait Islander Health and National Health Surveys, 2007-2019. Data were restricted to participants aged 15-17 years. Prevalence ratios (PR) and 95% Confidence Intervals (CI) for ever-smoking by respondent type were calculated using Poisson regression with robust standard errors. National youth current-smoking prevalence was estimated if all data were collected by youth self-report; estimates and trends were compared to observed estimates. RESULTS: Over 75% of all smoking status data were reported by proxy or with parent present. Ever-smoking prevalence among youth self-reporting independently versus proxy-reported was 1.29 (95% CI:0.96-1.73) to 1.99 (95% CI:1.39-2.85) times as high for Aboriginal and Torres Strait Islander youth, and 1.83 (95% CI:0.92-3.63) to 2.72 (95% CI:1.68-4.41) times as high for total population youth. Across surveys, predicted national current-smoking prevalence if all youth self-reported independently was generally higher than observed estimate. CONCLUSIONS: Estimates of youth smoking prevalence are likely inaccurate and underestimated if data are collected by proxy or with parent present. Increased reliance on data reported by youth independently is crucial to improve data accuracy, including to enable accurate assessment of national prevalence.

Raking of data from a large Australian cohort study improves generalisability of estimates of prevalence of health and behaviour characteristics and cancer incidence.

BACKGROUND: Health surveys are commonly somewhat non-representative of their target population, potentially limiting the generalisability of prevalence estimates for health/behaviour characteristics and disease to the population. To reduce bias, weighting methods have been developed, though few studies have validated weighted survey estimates against generally accepted high-quality independent population benchmark estimates. METHODS: We applied post-stratification and raking methods to the Australian 45 and Up Study using Census data and compared the resulting prevalence of characteristics to accepted population benchmark estimates and separately, the incidence rates of lung, colorectal, breast and prostate cancer to whole-of-population estimates using Standardised Incidence Ratios (SIRs). RESULTS: The differences between 45 and Up Study and population benchmark estimates narrowed following sufficiently-informed raking, e.g. 13.6% unweighted prevalence of self-reported fair/poor overall health, compared to 17.0% after raking and 17.9% from a population benchmark estimate. Raking also improved generalisability of cancer incidence estimates. For example, unweighted 45 and Up Study versus whole-of-population SIRs were 0.700 (95%CI:0.574-0.848) for male lung cancer and 1.098 (95%CI:1.002-1.204) for prostate cancer, while estimated SIRs after sufficiently-informed raking were 0.828 (95%CI:0.684-0.998) and 1.019 (95%CI:0.926-1.121), respectively. CONCLUSION: Raking may be a useful tool for improving the generalisability of exposure prevalence and disease incidence from surveys to the population.