Background
Despite a trend of declining suicide rates in many countries over the last 30 years, suicide rates have remained stable in Australia. There is large variation in suicide rates between different subgroups of the population, indicating the need to target suicide prevention efforts towards high-risk groups. Yet there is little evidence globally on suicide rates for people with disability and no studies have examined trends over time. This study estimates trends in suicide rates for people with and without disability over a 10-year period from 2011 to 2021.

Methods
We used data from the Person Level Integrated Data Asset (PLIDA), which brings together whole-population linked data from various administrative sources. The analysis used data from the 2011 and 2016 Censuses of Population and Housing, linked to registered death records for five years after each Census. We identified people who reported requiring assistance with core activities in the Census, representing people with severe or profound disability. ICD-10 codes were used to identify suicide deaths. We calculated age-standardised suicide rates for males and females with and without disability at each time point.

Results
Suicide rates were approximately two-times higher for males and four-times higher for females with disability compared to those without disability at each time point. The relative inequality in suicide mortality was larger for females compared to males, though the absolute inequality was larger for males. There was little change in suicide rates over time.

Conclusion
The findings of this study describe, for the first time, trends in suicide rates and inequalities for people with disability. Reducing deaths by suicide among Australians with disability needs to be a public health priority. Future research should examine the causes of the large inequalities, including the contribution of the social determinants of health which are known to be important determinants of suicide.

Background
People who move through Australian prisons have markedly poorer mental and physical health outcomes, with multi-morbidity greatly elevated relative to the general population. More research using quality longitudinal data is urgently needed to improve outcomes, however resourcing constraints, social and systemic factors make following this group up difficult. Previous projects have often used either prison surveys or administrative linked data. Each have limitations, and are often underpowered, limiting the potential to investigate rare exposures and outcomes. By combining these data sources across four existing state-based cohort studies, the Health After Release From Prison (HARP-4) consortium addresses these limitations and creates a sample with superior statistical power.
Methods
We combined data from four prospective cohort studies in different Australian jurisdictions (Queensland, Western Australia, New South Wales, Victoria). All jurisdictions administered a similar baseline (pre-release) survey collecting comparable data. Participants were then followed up via linked administrative health and justice service data to provide a more complete picture of health and justice outcomes over time for people leaving prison. The resulting combined cohort (N=4,135; 21% female, 36% Indigenous) is the largest of its kind globally.
Results
Studies made possible by this unique combination of data sources include two recent investigations validating the WHO’s Alcohol, Smoking and Substance Involvement Screening Test for use during incarceration to reliably predict returning to substance use, and substance-related hospitalisation after release from prison. This evidence provides crucial evidence to correctional services to inform targeted substance use support.
Conclusion
HARP-4 utilises an innovative approach that has generated an invaluable data resource to investigate a range of health and justice outcomes for people moving through prison, a group typically difficult to follow up. HARP-4’s approach could be used to improve the health and wellbeing of other marginalised and underserved populations such as those experiencing homelessness.

Background:
Young people and families experiencing adversity, often require coordinated support across multiple government services, yet current service delivery remains fragmented, limiting the effectiveness of programs. In partnership with multiple government agencies, the Linking for Life project aims to identify opportunities, throughout the life-course, to break down service silos and to inform early intervention and prevention strategies, improving health, social and justice outcomes.
Methods:
Linking for Life utilises whole-population, genealogically-linked administrative data from 20 datasets across health, social, education and justice services in Western Australia. This linkage facilitates cross-sectoral evaluation, providing a comprehensive understanding of the circumstances of people experiencing some of the poorest outcomes in these areas. This multi-sectoral approach enables investigation at both individual and family levels, generating valuable evidence to inform agencies about client needs. Such evidence will facilitate cross-sectoral collaboration to meet those needs efficiently and effectively in order to improve or prevent negative outcomes.
Results:
Recent research within Linking for Life has shown that children exposed to maternal incarceration are at an increased risk of self-harm, especially when they also have contact with child protection services. Another study found that children exposed to family and domestic violence tend to have poorer school attendance and higher rates of suspension compared to their peers. These findings have prompted policy reviews aimed at enhancing early intervention strategies in child protection and education sectors
Conclusion:
Linking for Life represents a significant advancement in the utilisation of multi-sectoral government data to address entrenched social, health and justice issues. The project presents critical opportunities to produce high quality population-level evidence, enhancing the lives of some of the community’s most vulnerable people and families.

Background
Burden of disease describes the impact of living with and dying prematurely from different diseases or injuries. The Australian Burden of Disease Study (ABDS) 2024 estimated the health impact of 220 diseases and injuries on the Australian population.

Methods
The ABDS quantifies years of healthy life lost from living with disease and injury (non-fatal burden) or dying prematurely (fatal burden). Total burden is measured in disability-adjusted life years (DALY). Estimates for 2024 are calculated based on projections using historical trends.

Results
In 2024, 5.8 million years of healthy life were lost. Living with illness or injury caused more total disease burden than dying prematurely (54% vs. 46%). Over the period 2003 to 2024 there was a 10% decline in the rate of total disease burden. This was driven by a 26% decrease in the rate of fatal burden while the rate of non-fatal burden increased by 7%.

In 2024, the 5 disease groups causing the most burden were cancer, mental health & substance use disorders, musculoskeletal conditions, cardiovascular diseases and neurological conditions. Together, these accounted for two-thirds (64%) of total disease burden.

When considering individual diseases, coronary heart disease (CHD) was the leading cause of burden for every reference year. However, the burden from CHD showed the largest absolute reduction over time, which was mainly driven by large declines in fatal burden. Dementia was the leading cause of burden among females. For young people, mental health conditions and suicide and self-inflicted injuries were the leading contributors to disease burden.

Males and females born in 2024 could expect to live an average of 88% and 86% of their lives in full health respectively.

Conclusions
The 2024 ABDS provides the most up-to-date estimates of disease burden in Australia. It provides an important evidence base to inform health policy and service planning.

Background
Work-related injuries (WRI) occur in about 4% of the Australian working population and many injured persons end up in the hospital emergency department (ED). About a fifth of ED visits are injury-related, and about a tenth are work-related. International studies have shown increased rates of injuries among migrant workers, but this information is not available for Victoria, a multicultural society with a diverse workforce. This study aimed to compare occupational injury rates by country of birth in patients presenting to EDs in Victoria, Australia.

Methods
The Victorian Injury Surveillance Unit received Victorian Emergency Minimum Dataset (VEMD, 01/07/2019–30/06/2023) from Victoria’s Department of Health. Work-related injury presentations for persons aged 15-69 years were identified using diagnoses codes, activity when injured and workers’ compensation indicators. Injury rates were calculated using Australian Bureau of Statistics’ 2021 Labour Force data. Injury presentations and labour force data were stratified by age group, sex and country of birth.

Results
There were 111,717 ED presentations with work-related injuries, a rate of 9 per 1000 employed persons. The highest rates were Sudan-born (26 per 1000), Afghanistan-born (23 per 1000), Samoa-born (21 per 1000), Tonga-born (18 per 1000) and Cook Islands-born (17 per 1000) workers. The rates among Australia-born and New Zealand-born workers were similar, at 11 per 1000 workers, while workers born in India and China had much lower rates than Australia-born workers: 4.3 and 3.8 per 1000, respectively. The injury presentation rates were further compared by age, sex, case severity and injury type.

Conclusion
ED presentations for work-related injuries varied substantially by country of birth, calling for further explorations to decipher reasons for these discrepancies. However, it is noteworthy that not all persons with work-related injuries present to ED. Hence consideration of health-seeking behaviour patterns by migrant status is imperative.

BACKGROUND
Epidemiologists have traditionally conceived of disability as a health outcome or a component of burden of disease. However, disabled people also have poorer health for outcomes unrelated to their impairment. It is important that epidemiologists investigate the causes of poor health of people of disability and identify interventions that can improve health outcomes for the 16% of world’s population who are disabled.

METHODS
To build capacity and the evidence base we have:
1. applied rigorous epidemiological methods to demonstrate the extent and causes of disability-related health inequities
2. trained a pipeline of epidemiologists who work in disability research
3. demonstrated the value of disability epidemiology to policymakers and advocates
4. advocated for, and contributed to, new government investment in disability research and data infrastructure

RESULTS
Examples of the impact of our work include:
1. demonstrated the importance of social determinants of health and health and disability services for the health of people with disability
2. advanced the measurement of disability and identification of people with disability in surveys, bespoke data collections, and administrative data
3. attracted 15 post-doctoral and mid-career researchers to work in disability epidemiology
4. established relationships with key stakeholders to demonstrate the value of disability epidemiology who have applied findings to policy
5. contributed to substantial new investment in disability research, capacity building and data infrastructure amounting to around $45M AUS for our own research and new government investment in disability research (more than $75M) through the establishment of National Disability Research Partnership and National Disability Data Asset.

CONCLUSION
Through significant investment of time and money, our multi-pronged approach has built the case for disability epidemiology, generated new research capacity, and secured funding for research and data infrastructure that will see disability epidemiology prosper in the medium and longer-term.

Background: Vietnam faces persistent challenges in managing non-communicable diseases (NCDs), posing barriers to achieving Universal Health Coverage (UHC). This study examines national and provincial trends in NCD management, projects future coverage, and evaluates inequalities across demographic, geographic, and socioeconomic dimensions to inform evidence-based policymaking.

Methods: We analyzed 42,333 records from five nationally representative household surveys (2010–2021). Key NCD health service and risk management indicators were estimated at both national and provincial levels. Bayesian spatiotemporal analyses using the Besag-York-Mollié model were employed to assess coverage trends, project future trajectories, and estimate the probability of reaching the 80% UHC target by 2030. We conducted comprehensive inequality analyses using the Slope Index of Inequality (SII) and Relative Index of Inequality (RII) and assessed long-term changes over the study period.

Results: While NCD management coverage has improved across most indicators from 2010 to 2030, declining trends were observed in Non-Harmful Use of Alcohol (NHUA), Sufficient Physical Activity (SPA), and Non-Overweight (NOW), resulting in a low probability of meeting the 2030 UHC target. Only Sufficient Use of Fruit and Vegetables (SUFV) and Non-Use of Tobacco (NUT) showed potential for achieving the target. Although socioeconomic and demographic inequalities were widespread in 2010, they are projected to decline or stabilize for most indicators by 2030. However, disparities continue to widen across gender (SPA), ethnicity (SUFV), urban-rural areas (NOW), and wealth and education levels (NHUA, NUT). Significant provincial disparities in both coverage and inequalities were observed, particularly in the North West and Central Highlands, where low coverage and high inequalities remain despite national-level improvements.

Conclusion: Despite some progress, persistent inequalities in NCD management remain across demographic, geographic, and socioeconomic groups in Vietnam. Strengthening healthcare systems, ensuring equitable resource allocation, and implementing multi-sectoral strategies are essential to enhance NCD management, promote health equity, and accelerate progress toward UHC.

Background
Intersectionality theory posits that multiple social positions and identities – such as gender and wealth – intersect to shape life and health outcomes. Investigating these factors individually provides limited understanding of their impact. While intersectionality is gaining traction in quantitative research, methodological challenges persist, and results are often limited to specific intersections. Our goal was to develop a publicly accessible interactive tool to support quantitative intersectional analysis and interpretation in the Australian context.
Methods
We designed HELIO as a web tool that provides prevalence estimates for user-selected outcomes (e.g., smoking, affordable housing) across combinations of two intersecting characteristics (e.g., income and remoteness). We chose outcomes based on relevant thematic frameworks (e.g., Sustainable Development Goals) and characteristics that represent social structures of power in Australia. Data came from the Household, Income and Labour Dynamics in Australia Survey (2002–2022). We calculated prevalence and confidence intervals in R for the full sample, individual characteristics (e.g., Australians in major cities) and all intersections (e.g. lower-income Australians in major cities). All estimates were based on sub-samples of at least 25 people.
Results
HELIO currently includes eight characteristics, 17 outcomes, 20 years of longitudinal data, with over 75,000 pre-calculated estimates, and is expanding. With a few clicks, users access curated information: for example, while smoking in Australia decreased from 23% to 14% (2002–2022), it remained around 45% for adults (25–44 years) with lower education (Year 11 and below). To complement estimates, a responsive comment section provides context, limitations, and links to further resources. HELIO is being integrated in post-graduate teaching and will become publicly available in 2025 after further testing.
Conclusion
HELIO is a conversation starter based on intersectionality theory. It provides easy-to-access comprehensive statistics on underrepresented subgroups of the Australian population, making it a tool for public accountability, intersectionality teaching and research.

Background: Natural environment (i.e., air pollution, greenness, and temperature) is associated with gestational diabetes mellitus (GDM). However, comprehensive evidence on this link is needed in the Australian context. This study examined the association between natural environment attributes and GDM risk at the local area level in Australia.
Methods: A multistate study at the Statistical Area Level 2 (SA2), a medium-sized spatial resolution, was conducted using data from 2016 through 2022. SA2-level annual GDM cases and births/sociodemographic data were obtained from the National Diabetes Services Scheme and the Australian Bureau of Statistics. Spatiotemporal model-based satellite-driven annual greenness, air pollution, and temperature measures at the SA2 level were used. Spatiotemporal regression was employed, with an adjusted risk ratio and 95% credible interval. Effect modification by neighbourhood socioeconomic status, ethnicity, and urbanicity was examined.
Results: We included 241,264 GDM cases among 2,035,100 women across 1,977 SA2s. An increase in greenness was associated with an 11% (0.89 [0.83-0.95]) reduction in GDM risk. GDM risk decreased by 13% (0.87 [0.78-0.97]) in metropolitan residents (vs regional), 17% (0.83 [0.76-0.89]) in areas with high concentration of migrant women, and 30% (0.70 [0.59-0.83]) in most (vs least) socioeconomically advantaged areas with increase in greenness. High PM2.5 (>5µg/m3) was associated with increased GDM risk in areas with the least (vs greatest) socioeconomically advantage (1.44[1.11-1.88]) and high (vs low) concentration of migrants (1.23 [1.05-1.45]).
Conclusions: High residential greenness was associated with lower GDM risk, but the benefit was more pronounced in socioeconomically advantaged areas, for metropolitan residents', and in areas with a high concentration of migrants. PM2.5-GDM risk association was amplified in areas with socioeconomically disadvantaged and high concentrations of migrants. GDM risk associated with greenness and air pollution, notably at the intersectionality of residence, socioeconomic, and ethnic status, indicates the relevance of addressing social and natural environment health inequities