Use of pudendal nerve blocks in rubber band ligation of haemorrhoids: an Australia-wide cross-sectional analysis

BACKGROUND

Surgeons vary in their approach to preventing pain post rubber band ligation (RBL) of haemorrhoids, with pudendal nerve blocks (PNB) being one analgesic strategy. No data exists on how commonly PNBs are used in RBL in Australia, and whether use varies by year and patient and hospital characteristics.

METHODS

Aggregate data from the National Hospital Morbidity Database was obtained for all admissions for RBL in Australia from 2012 to 2021, with and without a PNB, overall and in relation to sex, age group, hospital remoteness, hospital sector, and year of procedure. Adjusted relative risks (adj. RR) of PNB were estimated using Poisson regression, mutually adjusting for all variables.

RESULTS

Of the 346 542 admissions for RBL, 14013 (4.04%) involved a PNB. The proportion of patients receiving a PNB increased between 2012-2013 and 2020-2021, from 1.62% to 6.63% (adj. RR 3.99, CI 3.64-4.36). Patients most likely to receive a PNB were female (adj. RR 1.10; CI 1.07-1.14) aged 25-34 years (adj. RR 1.13; CI 1.01-1.26); in major-city (adj. RR 1.25 CI 1.20-1.30) and private hospitals (adj. RR 3.28 CI 3.13-3.45).

CONCLUSION

This is the first published analysis of the use of PNB in RBL. Pudendal nerve block use has increased over time, with substantial variation in practice. Blocks were more than three times as likely to be used in private compared to public hospitals. If evidence supporting PNB use is established, equitable access to the procedure should be pursued.

Long COVID in a highly vaccinated but largely unexposed Australian population following the 2022 SARS-CoV-2 Omicron wave: a cross-sectional survey

OBJECTIVE

To estimate the prevalence of long COVID among Western Australian adults, a highly vaccinated population whose first major exposure to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was during the 2022 Omicron wave, and to assess its impact on health service use and return to work or study.

STUDY DESIGN

Follow-up survey (completed online or by telephone).

SETTING, PARTICIPANTS

Adult Western Australians surveyed 90 days after positive SARS-CoV-2 test results (polymerase chain reaction or rapid antigen testing) during 16 July - 3 August 2022 who had consented to follow-up contact for research purposes.

MAIN OUTCOME MEASURES

Proportion of respondents with long COVID (ie, reporting new or ongoing symptoms or health problems, 90 days after positive SARS-CoV-2 test result); proportion with long COVID who sought health care for long COVID-related symptoms two to three months after infection; proportion who reported not fully returning to previous work or study because of long COVID-related symptoms.

RESULTS

Of the 70 876 adults with reported SARS-CoV-2 infections, 24 024 consented to contact (33.9%); after exclusions, 22 744 people were invited to complete the survey, of whom 11 697 (51.4%) provided complete responses. Our case definition for long COVID was satisfied by 2130 respondents (18.2%). The risk of long COVID was greater for women (v men: adjusted risk ratio [aRR], 1.5; 95% confidence interval [CI], 1.4-1.6) and for people aged 50-69 years (v 18-29 years: aRR, 1.6; 95% CI, 1.4-1.9) or with pre-existing health conditions (aRR, 1.5; 95% CI, 1.4-1.7), as well as for people who had received two or fewer COVID-19 vaccine doses (v four or more: aRR, 1.4; 95% CI, 1.2-1.8) or three doses (aRR, 1.3; 95% CI, 1.1-1.5). The symptoms most frequently reported by people with long COVID were fatigue (1504, 70.6%) and concentration difficulties (1267, 59.5%). In the month preceding the survey, 814 people had consulted general practitioners (38.2%) and 34 reported being hospitalised (1.6%) with long COVID. Of 1779 respondents with long COVID who had worked or studied before the infection, 318 reported reducing or discontinuing this activity (17.8%).

CONCLUSION

Ninety days after infection with the Omicron SARS-CoV-2 variant, 18.2% of survey respondents reported symptoms consistent with long COVID, of whom 38.7% (7.1% of all survey respondents) sought health care for related health concerns two to three months after the acute infection.

Relative risks of childhood developmental vulnerabilities in three Australian communities with exposure to per- and polyfluoroalkyl substances: data linkage study

Background

Aqueous film forming foams (AFFF) containing per- and polyfluoroalkyl substances (PFAS) caused local environmental contamination in three Australian residential areas: Katherine in the Northern Territory (NT), Oakey in Queensland (Qld) and Williamtown in New South Wales (NSW). We examined whether children who lived in these areas had higher risks of developmental vulnerabilities than children who lived in comparison areas without known contamination.

Methods

All children identified in the Medicare Enrolment File-a consumer directory for Australia's universal healthcare insurance scheme-who ever lived in exposure areas, and a sample of children who ever lived in selected comparison areas, were linked to the Australian Early Development Census (AEDC). The AEDC data were available from four cycles: 2009, 2012, 2015 and 2018. For each exposure area, we estimated relative risks (RRs) of developmental vulnerability on each of five AEDC domains and a summary measure, adjusting for sociodemographic characteristics and other potential confounders.

Findings

We included 2,429 children from the NT, 2,592 from Qld and 510 from NSW. We observed lower risk of developmental vulnerability in the Communication skills and general knowledge domain in Katherine (RR = 0.74, 95% confidence interval (CI) 0.57 to 0.97), and higher risks of developmental vulnerability in the same domain (RR = 1.49, 95% CI 1.18 to 1.87) and in the Physical health and wellbeing domain in Oakey (RR = 1.31, 95% CI 1.06 to 1.61). Risks of developmental vulnerabilities on other domains were not different from those in the relevant comparison areas or were uncertain due to small numbers of events.

Conclusion

There was inadequate evidence for increased risks of developmental vulnerabilities in children who ever lived in three PFAS-affected areas in Australia.

Does use of GP and specialist services vary across areas and according to individual socioeconomic position? A multilevel analysis using linked data in Australia

OBJECTIVE

Timely access to primary care and supporting specialist care relative to need is essential for health equity. However, use of services can vary according to an individual's socioeconomic circumstances or where they live. This study aimed to quantify individual socioeconomic variation in general practitioner (GP) and specialist use in New South Wales (NSW), accounting for area-level variation in use.

DESIGN

Outcomes were GP use and quality-of-care and specialist use. Multilevel logistic regression was used to estimate: (1) median ORs (MORs) to quantify small area variation in outcomes, which gives the median increased risk of moving to an area of higher risk of an outcome, and (2) ORs to quantify associations between outcomes and individual education level, our main exposure variable. Analyses were adjusted for individual sociodemographic and health characteristics and performed separately by remoteness categories.

SETTING

Baseline data (2006-2009) from the 45 and Up Study, NSW, Australia, linked to Medicare Benefits Schedule and death data (to December 2012).

PARTICIPANTS

267 153 adults aged 45 years and older.

RESULTS

GP (MOR=1.32-1.35) and specialist use (1.16-1.18) varied between areas, accounting for individual characteristics. For a given level of need and accounting for area variation, low education-level individuals were more likely to be frequent users of GP services (no school certificate vs university, OR=1.63-1.91, depending on remoteness category) and have continuity of care (OR=1.14-1.24), but were less likely to see a specialist (OR=0.85-0.95).

CONCLUSION

GP and specialist use varied across small areas in NSW, independent of individual characteristics. Use of GP care was equitable, but specialist care was not. Failure to address inequitable specialist use may undermine equity gains within the primary care system. Policies should also focus on local variation.

Discretion in decision to receive COVID-19 vaccines and associated socio-economic inequalities in rates of uptake: a whole-of-population data linkage study from Australia

OBJECTIVE

In Australia, first and second compared to third dose of a COVID-19 vaccine were implemented under different policies and contexts, resulting in greater discretion in decisions to receive a third compared to first and second dose. We quantified socio-economic inequalities in first and third dose to understand how discretion is associated with differences in uptake.

STUDY DESIGN

Whole-of-population cohort study.

METHODS

Linked immunisation, census, death and migration data were used to estimate weekly proportions who received first and third doses of a COVID-19 vaccine until 31 August 2022 for those with low (no formal qualification) compared to high (university degree) education, stratified by 10-year age group (from 30 to 89 years). We estimated relative rates using Cox regression, including adjustment for sociodemographic factors.

RESULTS

Among 13.1 million people in our study population, 94% had received a first and 80% a third dose by 31 August 2022. Rates of uptake of first and third dose were around 50% lower for people with low compared to high education. Gaps were small in absolute terms for first dose, and at the end of the study period ranged from 1 to 11 percentage points across age groups. However, gaps were substantial for third dose, particularly at younger ages where the socio-economic gap was as wide as 32 percentage-points.

CONCLUSION

Education-related inequalities in uptake were larger where discretion in decisions was larger. Policies that limited discretion in decisions to receive vaccines may have contributed to achieving the dual aims of maximising uptake and minimising inequalities.

Relative Risks of Adverse Perinatal Outcomes in Three Australian Communities Exposed to Per- and Polyfluoroalkyl Substances: Data Linkage Study

INTRODUCTION

Firefighting foams containing per- and polyfluoroalkyl substances (PFAS) have caused environmental contamination in several Australian residential areas, including Katherine in the Northern Territory (NT), Oakey in Queensland (Qld), and Williamtown in New South Wales (NSW). We examined whether the risks of adverse perinatal outcomes were higher in mothers living in these exposure areas than in selected comparison areas without known contamination.

METHODS

We linked residential addresses in exposure areas to addresses collected in the jurisdictional Perinatal Data Collections of the NT (1986-2017), Qld (2007-2018), and NSW (1994-2018) to select all pregnancies from mothers who gave birth while living in these areas. We also identified one comparison group for each exposure area by selecting pregnancies where the maternal address was in selected comparison areas. We examined 12 binary perinatal outcomes and three growth measurements. For each exposure area, we estimated relative risks (RRs) of adverse outcomes and differences in means of growth measures, adjusting for sociodemographic characteristics and other potential confounders.

RESULTS

We included 16,970 pregnancies from the NT, 4654 from Qld, and 7475 from NSW. We observed elevated risks of stillbirth in Oakey (RR = 2.59, 95% confidence interval (CI) 1.25 to 5.39) and of postpartum haemorrhage (RR = 1.94, 95% CI 1.13 to 3.33) and pregnancy-induced hypertension (RR = 1.88, 95% CI 1.30 to 2.73) in Williamtown. The risks of other perinatal outcomes were not materially different from those in the relevant comparison areas or were uncertain due to small numbers of events.

CONCLUSIONS

There was limited evidence for increased risks of adverse perinatal outcomes in mothers living in areas with PFAS contamination from firefighting foams. We found higher risks of some outcomes in individual areas, but these were not consistent across all areas under study and could have been due to chance, bias, or confounding.

Association of individual-socioeconomic variation in quality-of-primary care with area-level service organisation: A multilevel analysis using linked data

RATIONALE, AIMS AND OBJECTIVES

Ensuring equitable access to primary care (PC) contributes to reducing differences in health related to people's socioeconomic circumstances. However, there is limited data on system-level factors associated with equitable access to high-quality PC. We examine whether individual-level socioeconomic variation in general practitioner (GP) quality-of-care varies by area-level organisation of PC services.

METHODS

Baseline data (2006-2009) from the Sax Institute's 45 and Up Study, involving 267,153 adults in New South Wales, Australia, were linked to Medicare Benefits Schedule claims and death data (to December 2012). Small area-level measures of PC service organisation were GPs per capita, bulk-billing (i.e., no copayment) rates, out-of-pocket costs (OPCs), rates of after-hours and chronic disease care planning/coordination services. Using multilevel logistic regression with cross-level interaction terms we quantified the relationship between area-level PC service characteristics and individual-level socioeconomic variation in need-adjusted quality-of-care (continuity-of-care, long-consultations, and care planning), separately by remoteness.

RESULTS

In major cities, more bulk-billing and chronic disease services and fewer OPCs within areas were associated with an increased odds of continuity-of-care-more so among people of high- than low education (e.g., bulk-billing interaction with university vs. no school certificate 1.006 [1.000, 1.011]). While more bulk-billing, after-hours services and fewer OPCs were associated with long consultations and care planning across all education levels, in regional locations alone, more after-hours services were associated with larger increases in the odds of long consultations among people with low- than high education (0.970 [0.951, 0.989]). Area GP availability was not associated with outcomes.

CONCLUSIONS

In major cities, PC initiatives at the local level, such as bulk-billing and after-hours access, were not associated with a relative benefit for low- compared with high-education individuals. In regional locations, policies supporting after-hours access may improve access to long consultations, more so for people with low- compared with high-education.

National estimates of occupation-related inequalities in all-cause mortality using linked Census-mortality data

OBJECTIVE

This report aims to provide national estimates of occupation-related inequalities in all-cause mortality for Australian residents aged 25-64 years.

METHOD

Data came from the 2016 Census linked to Deaths Registrations, available via the Multi-Agency Data Integration Project. Using negative binomial regression, we estimated age-adjusted relative and absolute inequalities in all-cause mortality rates in the 13 months following Census according to occupation, defined using the Australian and New Zealand Standard Classification of Occupations (eight major groups), using managers as the reference group.

RESULTS

Among 10.8M people, there were 20,987 deaths. Age-adjusted mortality rates were lowest among managers and professionals and were generally highest for manual occupations, for example, among men, relative risks (RR) for labourers ranged across age groups from 1.44 (95% CI 1.19-1.75, age 54-64) to 2.99 (1.93-4.65, age 25-34); among women, the RR for machine operators and drivers were 3.95 (1.39-11.21 in age 25-24 and 2.73 (1.66-4.49) in age 45-54, but there was relatively little variation by occupation in women aged 35-44 and 55-64. Around one in five deaths (23% for men, 17% for women) were associated with being in an occupation other than manager.

CONCLUSION

These findings highlight that there is benefit in documenting national mortality inequalities according to occupation in addition to other measures of socioeconomic position. They provide further insights into socioeconomic inequalities in mortality.

IMPLICATIONS FOR PUBLIC HEALTH

Methods that aim to reduce mortality for those in manual occupations, particularly among young men, will reduce inequalities and improve population health.

Liver and cardiometabolic markers and conditions in a cross-sectional study of three Australian communities living with environmental per- and polyfluoroalkyl substances contamination

BACKGROUND

Per- and polyfluoroalkyl substances (PFAS) have been associated with higher cholesterol and liver function markers in some studies, but the evidence for specific cardiometabolic conditions has been inconclusive.

OBJECTIVES

We quantified the associations of single and combined PFAS with cardiometabolic markers and conditions in a cross-sectional study of three Australian communities with PFAS-contaminated water from the historical use of aqueous film-forming foam in firefighting activities, and three comparison communities.

METHODS

Participants gave blood samples for measurement of nine PFAS, four lipids, six liver function markers, and completed a survey on sociodemographic characteristics and eight cardiometabolic conditions. We estimated differences in mean biomarker concentrations per doubling in single PFAS concentrations (linear regression) and per interquartile range increase in the PFAS mixture (Bayesian kernel machine regression). We estimated prevalence ratios of biomarker concentrations outside reference limits and self-reported cardiometabolic conditions (Poisson regression).

RESULTS

We recruited 881 adults in exposed communities and 801 in comparison communities. We observed higher mean total cholesterol with higher single and mixture PFAS concentrations in blood serum (e.g., 0.18 mmol/L, 95% credible interval -0.06 to 0.42, higher total cholesterol concentrations with an interquartile range increase in all PFAS concentrations in Williamtown, New South Wales), with varying certainty across communities and PFAS. There was less consistency in direction of associations for liver function markers. Serum perfluorooctanoic acid (PFOA) concentrations were positively associated with the prevalence of self-reported hypercholesterolemia in one of three communities, but PFAS concentrations were not associated with self-reported type II diabetes, liver disease, or cardiovascular disease.

DISCUSSION

Our study is one of few that has simultaneously quantified the associations of blood PFAS concentrations with multiple biomarkers and cardiometabolic conditions in multiple communities. Our findings for total cholesterol were consistent with previous studies; however, substantial uncertainty in our estimates and the cross-sectional design limit causal inference.

Psychological distress in three Australian communities living with environmental per- and polyfluoroalkyl substances contamination

BACKGROUND

Environmental chemical contamination is a recognised risk factor for psychological distress, but has been seldom studied in the context of per- and polyfluoroalkyl substances (PFAS) contamination. We examined psychological distress in a cross-sectional study of three Australian communities exposed to PFAS from the historical use of aqueous film-forming foam in firefighting activities, and three comparison communities without environmental contamination.

METHODS

Participation was voluntary following recruitment from a PFAS blood-testing program (exposed) or random selection (comparison). Participants provided blood samples and completed a survey on their exposure history, sociodemographic characteristics, and four measures of psychological distress (Kessler-6, Distress Questionnaire-5, Patient Health Questionnaire-15, and Generalised Anxiety Disorder-7). We estimated prevalence ratios (PR) of clinically-significant psychological distress scores, and differences in mean scores: (1) between exposed and comparison communities; (2) per doubling in PFAS serum concentrations in exposed communities; (3) for factors that affect the perceived risk of living in a community exposed to PFAS; and (4) in relation to self-reported health concerns.

RESULTS

We recruited 881 adults in exposed communities and 801 in comparison communities. We observed higher levels of self-reported psychological distress in exposed communities than in comparison communities (e.g., Katherine compared to Alice Springs, Northern Territory: clinically-significant anxiety scores, adjusted PR = 2.82, 95 % CI 1.16-6.89). We found little evidence to suggest that psychological distress was associated with PFAS serum concentrations (e.g., Katherine, PFOS and anxiety, adjusted PR = 0.85, 95 % CI 0.65-1.10). Psychological distress was higher among exposed participants who were occupationally exposed to firefighting foam, used bore water on their properties, or were concerned about their health.

CONCLUSION

Psychological distress was substantially more prevalent in exposed communities than in comparison communities. Our findings suggest that the perception of risks to health, rather than PFAS exposure, contribute to psychological distress in communities with PFAS contamination.

Quantifying cause-related mortality in Australia, incorporating multiple causes: observed patterns, trends and practical considerations

BACKGROUND

Mortality statistics using a single underlying cause of death (UC) are key health indicators. Rising multimorbidity and chronic disease mean that deaths increasingly involve multiple conditions. However, additional causes reported on death certificates are rarely integrated into mortality indicators, partly due to complexities in data and methods. This study aimed to assess trends and patterns in cause-related mortality in Australia, integrating multiple causes (MC) of death.

METHODS

Deaths (n = 1 773 399) in Australia (2006-17) were mapped to 136 ICD-10-based groups and MC indicators applied. Age-standardized cause-related rates (deaths/100 000) based on the UC (ASRUC) were compared with rates based on any mention of the cause (ASRAM) using rate ratios (RR = ASRAM/ASRUC) and to rates based on weighting multiple contributing causes (ASRW).

RESULTS

Deaths involved on average 3.4 causes in 2017; the percentage with >4 causes increased from 20.9 (2006) to 24.4 (2017). Ischaemic heart disease (ASRUC = 73.3, ASRAM = 135.8, ASRW = 63.5), dementia (ASRUC = 51.1, ASRAM = 98.1, ASRW = 52.1) and cerebrovascular diseases (ASRUC = 39.9, ASRAM = 76.7, ASRW = 33.5) ranked as leading causes by all methods. Causes with high RR included hypertension (ASRUC = 2.2, RR = 35.5), atrial fibrillation (ASRUC = 8.0, RR = 6.5) and diabetes (ASRUC = 18.5, RR = 3.5); the corresponding ASRW were 12.5, 12.6 and 24.0, respectively. Renal failure, atrial fibrillation and hypertension ranked among the 10 leading causes by ASRAM and ASRW but not by ASRUC. Practical considerations in working with MC data are discussed.

CONCLUSIONS

Despite the similarities in leading causes under the three methods, with integration of MC several preventable diseases emerged as leading causes. MC analyses offer a richer additional perspective for population health monitoring and policy development.

Factors related to under-treatment of secondary cardiovascular risk, including primary healthcare: Australian National Health Survey linked data analysis

OBJECTIVE

To inform national evidence gaps on cardiovascular disease (CVD) preventive medication use and factors relating to under-treatment - including primary healthcare engagement - among CVD survivors in Australia.

METHODS

Data from 884 participants with self-reported CVD from the 2014-15 National Health Survey were linked to primary care and pharmaceutical dispensing data for 2016 through the Multi-Agency Data Integration Project. Logistic regression quantified the relation of combined blood pressure- and lipid-lowering medication use to participant characteristics.

RESULTS

Overall, 94.8% had visited a general practitioner (GP) and 40.0% were on both blood pressure- and lipid-lowering medications. Medication use was least likely in: women versus men (OR=0.49[95%CI:0.37-0.65]), younger participants (e.g. 45-64y versus 65-85y: OR=0.58[0.42-0.79])and current versus never-smokers (OR=0.73[0.44-1.20]). Treatment was more likely in those with ≥9 versus ≤4 conditions (OR=2.15[1.39-3.31]), with ≥11 versus 0-2 GP visits/year (OR=2.62[1.53-4.48]) and with individual CVD risk factors (e.g. high blood pressure OR=3.13 [2.34-4.19]) versus without); the latter even accounting for GP service-use frequency.

CONCLUSIONS

Younger people, smokers, those with infrequent GP visits or without CVD risk factors were the least likely to be on medication.

IMPLICATIONS FOR PUBLIC HEALTH

Substantial under-treatment, even among those using GP services, indicates opportunities to prevent further CVD events in primary care.

Aboriginal and Torres Strait Islander health checks: sociodemographic characteristics and cardiovascular risk factors

OBJECTIVE

To quantify Aboriginal and Torres Strait Islander health check claims in Australian adults in relation to sociodemographic and health characteristics, including prior cardiovascular disease (CVD) and CVD risk factors.

METHODS

The study involved analysis of baseline data (2006-2009) from the Sax Institute's 45 and Up Study, involving 1753 Aboriginal and Torres Strait Islander adults in New South Wales, Australia, linked to Medicare Benefits Schedule (MBS) hospital and death data (to December 2015). The outcome was a claim for receiving a Medicare-funded Health Assessment for Aboriginal and Torres Strait Islander People (MBS item 715) in the 2 years before December 2015. Logistic regression was used to estimate odds ratios (ORs) for receiving a health check in relation to sociodemographic and health characteristics.

RESULTS

One-third (32%) of participants received at least one Medicare-funded health check in the 2-year period. The probability of receiving a health check was higher for women than men (adjusted OR 1.47; 95% CI 1.18, 1.84), for those with lowest education than for those with highest education (OR 1.58; CI 1.11, 2.24), for those in a regional area (OR 1.56; CI 1.22, 2.01) or remote area (OR 2.38; CI 1.8, 3.16) than for those in major cities, for those with prior CVD than for those without (OR 1.80; CI 1.42, 2.27), for those with CVD risk factors than for those without (adjusted OR between 1.28 and 2.28, depending on risk factor), for those with poor self-rated health than for those with excellent self-rated health (OR 3.15; CI 1.76, 6.65) and for those with more than 10 visits to a general practitioner (GP) per year than for those with 0-2 visits (OR 33.62; CI 13.45, 84.02). Additional adjustment for number of GP visits or self-rated health substantially attenuated ORs for prior CVD and most CVD risk factors. When mutually adjusted, use of GP services and poorer self-rated health remained strongly associated with receiving a health check.

CONCLUSIONS

Aboriginal and Torres Strait Islander people with the greatest healthcare need and at highest risk of CVD were more likely to receive a health check; however, a significant proportion of those who were eligible had not received this preventive care intervention. Findings indicate that there is greater potential for the use of health checks (MBS item 715) in improving identification and management of Aboriginal and Torres Strait Islander people at high risk of CVD, potentially preventing future CVD events.

Education-related inequalities in cause-specific mortality: first estimates for Australia using individual-level linked census and mortality data

BACKGROUND

Socioeconomic inequalities in mortality are evident in all high-income countries, and ongoing monitoring is recommended using linked census-mortality data. Using such data, we provide the first estimates of education-related inequalities in cause-specific mortality in Australia, suitable for international comparisons.

METHODS

We used Australian Census (2016) linked to 13 months of Death Registrations (2016-17). We estimated relative rates (RR) and rate differences (RD, per 100 000 person-years), comparing rates in low (no qualifications) and intermediate (secondary school) with high (tertiary) education for individual causes of death (among those aged 25-84 years) and grouped according to preventability (25-74 years), separately by sex and age group, adjusting for age, using negative binomial regression.

RESULTS

Among 13.9 M people contributing 14 452 732 person-years, 84 743 deaths occurred. All-cause mortality rates among men and women aged 25-84 years with low education were 2.76 [95% confidence interval (CI): 2.61-2.91] and 2.13 (2.01-2.26) times the rates of those with high education, respectively. We observed inequalities in most causes of death in each age-sex group. Among men aged 25-44 years, relative and absolute inequalities were largest for injuries, e.g. transport accidents [RR = 10.1 (5.4-18.7), RD = 21.2 (14.5-27.9)]). Among those aged 45-64 years, inequalities were greatest for chronic diseases, e.g. lung cancer [men RR = 6.6 (4.9-8.9), RD = 57.7 (49.7-65.8)] and ischaemic heart disease [women RR = 5.8 (3.7-9.1), RD = 20.2 (15.8-24.6)], with similar patterns for people aged 65-84 years. When grouped according to preventability, inequalities were large for causes amenable to behaviour change and medical intervention for all ages and causes amenable to injury prevention among young men.

CONCLUSIONS

Australian education-related inequalities in mortality are substantial, generally higher than international estimates, and related to preventability. Findings highlight opportunities to reduce them and the potential to improve the health of the population.

Use of health and aged care services in Australia following hospital admission for myocardial infarction, stroke or heart failure

BACKGROUND

Cardiovascular diseases (CVD), including myocardial infarction (MI), stroke and heart failure (HF) are the leading cause of death amongst the older population worldwide. The aim of this study is to investigate trajectories of use of health and aged care services after hospital admission for MI, stroke or HF among community-dwelling people not previously receiving aged care services.

METHODS

The study population comprised people aged 65+ years from the 45 and Up Study with linked records for hospital stays, aged care services and deaths for the period 2006-14. Among those with an index hospital admission for MI, stroke or HF, we developed Sankey plots to describe and visualize sequences and trajectories of service use (none, re-hospitalization, community care, residential care, death) in the 12 months following discharge. We used Cox proportional hazards models to estimate hazard ratios (HRs), for commencing community care and entering residential care (and the other outcomes) within 3, 6 and 12 months, compared to a matched group without MI, stroke or HF.

RESULTS

Two thousand six hundred thirty-nine, two thousand five hundred and two thousand eight hundred seventy-three people had an index hospitalization for MI, stroke and HF, respectively. Within 3 months of hospital discharge, 16, 32 and 29%, respectively, commenced community care (multivariable-adjusted HRs: 1.26 (95%CI:1.18-1.35), 1.53 (95%CI:1.44-1.64) and 1.39 (95%CI:1.32-1.48)); and 7, 18 and 14%, respectively, entered residential care (HRs: 1.25 (95%CI:1.12-1.41), 2.65 (95%CI:2.42-2.91) and 1.50 (95%CI:1.37-1.65)). Likewise, 26, 15 and 28%, respectively, were rehospitalized within 3 months following discharge (multivariable-adjusted HRs: 4.78 (95%CI:4.31-5.32), 3.26 (95%CI:2.91-3.65) and 4.94 (95%CI:4.47-5.46)).

CONCLUSIONS

Older people hospitalized for major CVD may be vulnerable to transition-related risks and have poor health trajectories, thus emphasizing the value of preventing such events and care strategies targeted towards this at-risk group.

The ATHENA COVID-19 Study: Cohort profile and first findings for people diagnosed with COVID-19 in Queensland, 1 January to 31 December 2020

Background

To date, there are limited Australian data on characteristics of people diagnosed with COVID-19 and on how these characteristics relate to outcomes. The ATHENA COVID-19 Study was established to describe health outcomes and investigate predictors of outcomes for all people diagnosed with COVID-19 in Queensland by linking COVID-19 notification, hospital, general practice and death registry data. This paper reports on the establishment and first findings for the ATHENA COVID-19 Study.

Methods

Part 1 of the ATHENA COVID-19 Study used Notifiable Conditions System data from 1 January 2020 to 31 December 2020, linked to: Emergency Department Collection data for the same period; Queensland Health Admitted Patient Data Collections (from 1 January 2010 to 30 January 2021); and Deaths Registrations data (from 1 January 2020 to 17 January 2021).

Results

To 31 December 2020, a total of 1,254 people had been diagnosed with SARS-CoV-2 infection in Queensland: half were female (49.8%); two-thirds (67.7%) were aged 20-59 years; and there was an over-representation of people living in less-disadvantaged areas. More than half of people diagnosed (57.6%) presented to an ED; 21.2% were admitted to hospital as an inpatient (median length of stay 11 days); 1.4% were admitted to an intensive care unit (82.4% of these required ventilation); and there were six deaths. Analysis of factors associated with these outcomes was limited due to small case numbers: people living in less-disadvantaged areas had a lower risk of being admitted to hospital (test for trend, p < 0.001), while those living in more remote areas were less likely than people living in major cities to present to an ED (test for trend: p=0.007), which may reflect differential health care access rather than health outcomes per se. Increasing age (test for trend, p < 0.001) and being a current/recent smoker (age-sex-adjusted relative risk: 1.61; 95% confidence interval: 1.00, 2.61) were associated with a higher risk of being admitted to hospital.

Conclusion

Despite uncertainty in our estimates due to small numbers, our findings are consistent with what is known about COVID-19. Our findings reinforce the value of linking multiple data sources to enhance reporting of outcomes for people diagnosed with COVID-19 and provide a platform for longer term follow-up.

Inequalities in life expectancy in Australia according to education level: a whole-of-population record linkage study

Background

Life expectancy in Australia is amongst the highest globally, but national estimates mask within-country inequalities. To monitor socioeconomic inequalities in health, many high-income countries routinely report life expectancy by education level. However in Australia, education-related gaps in life expectancy are not routinely reported because, until recently, the data required to produce these estimates have not been available. Using newly linked, whole-of-population data, we estimated education-related inequalities in adult life expectancy in Australia.

Methods

Using data from 2016 Australian Census linked to 2016-17 Death Registrations, we estimated age-sex-education-specific mortality rates and used standard life table methodology to calculate life expectancy. For men and women separately, we estimated absolute (in years) and relative (ratios) differences in life expectancy at ages 25, 45, 65 and 85 years according to education level (measured in five categories, from university qualification [highest] to no formal qualifications [lowest]).

Results

Data came from 14,565,910 Australian residents aged 25 years and older. At each age, those with lower levels of education had lower life expectancies. For men, the gap (highest vs. lowest level of education) was 9.1 (95 %CI: 8.8, 9.4) years at age 25, 7.3 (7.1, 7.5) years at age 45, 4.9 (4.7, 5.1) years at age 65 and 1.9 (1.8, 2.1) years at age 85. For women, the gap was 5.5 (5.1, 5.9) years at age 25, 4.7 (4.4, 5.0) years at age 45, 3.3 (3.1, 3.5) years at 65 and 1.6 (1.4, 1.8) years at age 85. Relative differences (comparing highest education level with each of the other levels) were larger for men than women and increased with age, but overall, revealed a 10–25 % reduction in life expectancy for those with the lowest compared to the highest education level.

Conclusions

Education-related inequalities in life expectancy from age 25 years in Australia are substantial, particularly for men. Those with the lowest education level have a life expectancy equivalent to the national average 15–20 years ago. These vast gaps indicate large potential for further gains in life expectancy at the national level and continuing opportunities to improve health equity.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12939-021-01513-3.

Reflection on modern methods: statistical, policy and ethical implications of using age-standardized health indicators to quantify inequities

Methods for calculating health indicators profoundly influence understanding of and action on population health and inequities. Age-standardization can be useful and is commonly applied to account for differences in age structures when comparing health indicators across groups. Age-standardized rates have well-acknowledged limitations, including that they are relative indices for comparison, and not accurate measures of actual rates where the age structures of groups diverge. This paper explores these limitations, and demonstrates alternative approaches through a case study quantifying mortality rates within the Aboriginal and Torres Strait Islander (Indigenous) population of Australia and inequities compared with the non-Indigenous population, over 2001–16. Applying the Australian Standard Population, the Aboriginal and Torres Strait Islander age-standardized mortality rate was more than double the crude mortality rate in 2001 and 2016, inflated through high weighting of older age groups. Despite divergent population age structures, age-standardized mortality rates remain a key policy metric for measuring progress in reducing Indigenous-non-Indigenous inequities in Australia. Focusing on outcomes age-standardized to the total population can obscure inequities, and denies Aboriginal and Torres Strait Islander peoples and communities valid, actionable information about their health and well-being. Age-specific statistics convey the true magnitude of health risks and highlight high-risk subgroups. When requiring standardization, standardizing to a population-specific standard (here, an Indigenous standard) generates metrics centred around and reflective of reality for the population of focus, supporting communities’ self-determination to identify priorities and informing resource allocation and service delivery. The principles outlined here apply across populations, including Indigenous and other populations internationally.

Education inequalities in adult all-cause mortality: first national data for Australia using linked census and mortality data

Background

National linked mortality and census data have not previously been available for Australia. We estimated education-based mortality inequalities from linked census and mortality data that are suitable for international comparisons.

Methods

We used the Australian Bureau of Statistics Death Registrations to Census file, with data on deaths (2011–2012) linked probabilistically to census data (linkage rate 81%). To assess validity, we compared mortality rates by age group (25–44, 45–64, 65–84 years), sex and area-inequality measures to those based on complete death registration data. We used negative binomial regression to quantify inequalities in all-cause mortality in relation to five levels of education [‘Bachelor degree or higher’ (highest) to ‘no Year 12 and no post-secondary qualification’ (lowest)], separately by sex and age group, adjusting for single year of age and correcting for linkage bias and missing education data.

Results

Mortality rates and area-based inequality estimates were comparable to published national estimates. Men aged 25–84 years with the lowest education had age-adjusted mortality rates 2.20 [95% confidence interval (CI): 2.08‒2.33] times those of men with the highest education. Among women, the rate ratio was 1.64 (1.55‒1.74). Rate ratios were 3.87 (3.38‒4.44) in men and 2.57 (2.15‒3.07) in women aged 25–44 years, decreasing to 1.68 (1.60‒1.76) in men and 1.44 (1.36‒1.53) in women aged 65–84 years. Absolute education inequalities increased with age. One in three to four deaths (31%) was associated with less than Bachelor level education.

Conclusions

These linked national data enabled valid estimates of education inequality in mortality suitable for international comparisons. The magnitude of relative inequality is substantial and similar to that reported for other high-income countries.

Differences between men and women in the use of preventive medications following a major cardiovascular event: Australian prospective cohort study

Most cardiovascular disease (CVD) events can be prevented with appropriate risk management. Existing evidence suggests women are less likely than men to receive guideline-recommended medications, however data on sex-differences in preventive medication use following a CVD event are lacking. Relative risks (RRs) comparing use of blood pressure- and lipid-lowering medications in men and women at 3-, 6-, 9- and 12-months following hospitalisation for myocardial infarction (MI) or stroke from 2012 to 2017 were quantified using linked data from 8,278 participants enrolled in the Australian 45 and Up Study. Overall, 51% of women and 58% of men were using both blood-pressure- and lipid-lowering medications three months after a MI or stroke event, decreasing to 48% and 53%, respectively, at 12 months after an event. Adjusting for potential confounders, women were 9% less likely than men (RR = 0.91 [95% CI: 0.87, 0.95]) to be using both medications and 19% more likely (RR = 1.19 [95% CI: 1.07, 1.32]) to use neither medication three months after a MI or stroke event. At the 12-month mark, women were 8% less likely (RR = 0.92 [95% CI: 0.88, 0.97]) to be using both medications and 14% more likely (RR = 1.14 [95% CI: 1.03, 1.26]) to use neither medication. Women were consistently less likely to use both preventive medications and more likely to use neither medication at each follow-up time point. Overall, there were major shortfalls in basic preventive medication use post-CVD event and sex disparities are likely to further jeopardise efforts to reduce CVD events in the community.

Does psychological distress directly increase risk of incident cardiovascular disease? Evidence from a prospective cohort study using a longer-term measure of distress

OBJECTIVE

Cardiovascular disease (CVD) incidence is elevated among people with psychological distress. However, whether the relationship is causal is unclear, partly due to methodological limitations, including limited evidence relating to longer-term rather than single time-point measures of distress. We compared CVD relative risks for psychological distress using single time-point and multi-time-point assessments using data from a large-scale cohort study.

DESIGN

We used questionnaire data, with data collection at two time-points (time 1: between 2006 and 2009; time 2: between 2010 and 2015), from CVD-free and cancer-free 45 and Up Study participants, linked to hospitalisation and death records. The follow-up period began at time 2 and ended on 30 November 2017. Psychological distress was measured at both time-points using Kessler 10 (K10), allowing assessment of single time-point (at time 2: high (K10 score: 22-50) vs low (K10 score: <12)) and multi-time-point (high distress (K10 score: 22-50) at both time-points vs low distress (K10 score: <12) at both time-points) measures of distress. Cox regression quantified the association between distress and major CVD, with and without adjustment for sociodemographic and health-related characteristics, including functional limitations.

RESULTS

Among 83 906 respondents, 7350 CVD events occurred over 410 719 follow-up person-years (rate: 17.9 per 1000 person-years). Age-adjusted and sex-adjusted rates of major CVD were elevated by 50%-60% among those with high versus low distress for both the multi-time-point (HR=1.63, 95% CI 1.40 to 1.90) and single time-point (HR=1.53, 95% CI 1.39 to 1.69) assessments. HRs for both measures of distress attenuated with adjustment for sociodemographic and health-related characteristics, and there was little evidence of an association when functional limitations were taken into account (multi-time-point HR=1.09, 95% CI 0.93 to 1.27; single time-point HR=1.14, 95% CI 1.02 to 1.26).

CONCLUSION

Irrespective of whether a single time-point or multi-time-point measure is used, the distress-CVD relationship is substantively explained by sociodemographic characteristics and pre-existing physical health-related factors.

Comparison of cardiovascular disease risk factors, assessment and management in men and women, including consideration of absolute risk: a nationally representative cross-sectional study

OBJECTIVES

Cardiovascular disease (CVD) is highly preventable and optimal treatments based on absolute risk can halve risk of future events. Compared with women, men have higher risks of developing CVD. However, women can experience suboptimal treatment. We aimed to quantify sex differences in CVD risk, assessment and treatment in Australian adults.

DESIGN, PARTICIPANTS, SETTING

Cross-sectional analysis of nationally representative data from interview, physical measures, medication review and blood and urine samples, from 2011 to 2012 Australian Health Survey participants aged 45-74 (n=11 518).

OUTCOME MEASURES

CVD risk factors, absolute 5-year risk of a primary CVD event, blood pressure and cholesterol assessment in the previous 2 and 5 years and use of recommended CVD preventive medications were compared using Poisson regression to estimate age-adjusted male versus female prevalence ratios (PRs).

RESULTS

Women had a generally more favourable CVD risk factor profile than men, including lower: current smoking prevalence (women=14.5%; men=18.4%, PR=0.78, 95% CI=0.70 to 0.88); body mass index (women (mean)=28.3 kg/m²; men (mean)=28.8 kg/m², p<0.01); systolic and diastolic blood pressure (systolic: women (mean)=127.1 mm Hg; men (mean)=130.5 mm Hg, p<0.001); blood glucose (women (mean)=5.2 mmol/L; men (mean)=5.5 mmol/L); diabetes prevalence (women=6.8%; men=12.5%, PR=0.55, 95% CI=0.44 to 0.67); prior CVD (women=7.9%; men=11.3%) and absolute primary CVD risk (absolute 5-year CVD risk >15%: women=6.6%, 95% CI=5.4 to 7.8; men=15.4%, 95% CI=13.9% to 16.9%). Compared with men, women had higher low-density lipoprotein, high-density lipoprotein and total cholesterol and sedentary behaviour and lower physical activity. Blood pressure and cholesterol assessment were common in both sexes. Among those at high absolute risk, age-adjusted proportions receiving recommended CVD medications were low, without sex differences (women=21.3%; men=23.8%, PR=0.93, 95% CI=0.49 to 1.78). Fewer women than men with prior atherosclerotic CVD were receiving recommended treatment (women=21.8%, men=41.4%, PR=0.55, 95% CI=0.31 to 0.96).

CONCLUSION

Women have a more favourable CVD risk factor profile than men. Preventive treatment is uncommon and women with prior atherosclerotic CVD are around half as likely as men to be receiving recommended treatment.

Using Newly Linked Data to Assess Equity of Out-Of-Pocket Healthcare Costs in Australia

IntroductionDescribing out-of-pocket (OOP) healthcare costs in relation to ability to pay requires multiple linked data sources not previously available. Current estimates of the progressivity of OOP healthcare costs in Australia are based on self-report surveys. Using newly linked Census to administrative income and medical claims data, we aimed to quantify, for the first time, the progressivity of OOP costs for government-subsidised out-of-hospital healthcare in Australia. Objectives and ApproachWe used Australian Census 2011 linked to Personal Income Tax (PIT), Medicare Benefits Schedule (MBS) and Pharmaceutical Benefits Scheme (PBS) data compiled through the Multi-Agency Data Integration Project (MADIP). Personal disposable income was estimated using a combination of PIT data and Census self-reported income, and aggregated across the household to estimate equivalised household income. We estimated annual MBS (out-of-hospital only) and PBS OOP costs as a proportion of equivalised household income, and assessed progressivity by reporting this for each income decile and computing a Kakwani Index. ResultsWe will present findings on progressivity overall, and separately by age, sex and location (incomplete at time of abstract submission). Conclusion / ImplicationsOur study will present one measure regarding the equity of healthcare costs, and help to identify vulnerable or at-risk groups. These findings may inform policy changes on equity in the financing of healthcare. Newly linked data from the MADIP can be used to relate healthcare costs to ability to pay.

Demonstrating the Utility of New Linked National Health Survey and Administrative Data: Secondary CVD Prevention in The Community

IntroductionCardiovascular events are largely preventable though access to timely quality primary health care and use of guideline-recommended medication. However, around half of Australians with cardiovascular disease (CVD) are not receiving best practice treatment. This study aims to identify factors associated with under treatment, using National Health Survey (NHS) linked for the first time to administrative health data. Objectives and ApproachParticipants with self-reported CVD in the NHS 2014-15 were included in the study, with data linked to Medicare (MBS) and pharmaceutical (PBS) data by the Australian Bureau of Statistics through the Multi-Agency Data Integration Project (MADIP). Use of primary and specialist ambulatory care and blood pressure- and lipid-lowering medications and their relation to sociodemographic and health characteristics were quantified using logistic and Poisson regression analyses. Results1100 participants with self-reported CVD were available for analysis, with linkage rates for NHS data to a Person Linkage Spine of 95%. We will present our findings from adjusted regression models (incomplete at time of abstract submission). Conclusion / ImplicationsThe nationally representative linked data developed under this project provides a unique opportunity to quantify and identify points to improve access to best practice CVD care, with the ultimate aim of preventing secondary CVD events in the population. Findings will also inform optimal use of MADIP data by the research community in order to answer questions of national importance and provide robust evidence to drive improvement in health and health care.

Using Linked Whole-Of-Population Data to Estimate Education-Related Inequalities in Cause-Specific Mortality in Australia

IntroductionOfficial Australian estimates of socioeconomic inequalities in cause-specific mortality have been based on area-level socioeconomic measures. Using area-level measures is known to underestimate inequalities. Objectives and ApproachUsing recently released census linked to mortality data, we estimate education-related inequalities in cause-specific mortality for Australia. We used 2016 Australian Census and Death Registration data (2016-17) linked via a Person Linkage Spine (linkage rates: 92% and 97%, respectively) from the Multi-Agency Data Integration Project (MADIP). Education, from the Census, was categorised as low (no secondary school graduation or other qualification), intermediate (secondary graduation with/without other non-tertiary qualifications) and high (tertiary qualification). Cause of death was coded according to the underlying cause of death using the ICD-10. We used negative binomial regression to estimate relative rates (RR) for cause-specific mortality at ages 25-84 years, in the 12-months following Census, comparing low vs high education, separately by sex and 20-year age group, adjusting for age. Results80,317 deaths occurred among 13,856,202 people. For those aged 25-44 years, relative inequalities were large for causes related to injury and smaller for lesspreventable deaths (e.g. for men, suicide RR=5.6, 95%CI: 4.1-7.5 and brain cancer RR=1.3, 0.6-3.1). For those aged 45-64, inequalities were large for causes related to health behaviours and amenable to medical intervention, e.g. lung cancer (men RR= 6.4, 4.7-8.8) and ischaemic heart disease (women RR=5.0, 3.2-7.7), and were small for less preventable causes e.g. brain cancer (women RR=0.9, 0.6-1.3). Patterns among those aged 65-84years were similar to those aged 45-64 years. Conclusion / ImplicationsIn Australia, inequalities in mortality are substantial. Our findings highlight the health burden from inequalities, opportunities for prevention and provide insights on targets to effectively reduce them.

Education-related variation in coronary procedure rates and the contribution of private health care in Australia: a prospective cohort study

Background

Contemporary Australian evidence on socioeconomic variation in secondary cardiovascular disease (CVD) care, a possible contributor to inequalities in cardiovascular disease outcomes, is lacking. This study examined the relationship between education, an individual-level indicator of socioeconomic position, and receipt of angiography and revascularisation procedures following incident hospitalisation for acute myocardial infarction (AMI) or angina, and the role of private care in this relationship.

Methods

Participants aged ≥45 from the New South Wales population-based 45 and Up Study with no history of prior ischaemic heart disease hospitalised for AMI or angina were followed for receipt of angiography or revascularisation within 30 days of hospital admission, ascertained through linked hospital records. Education attainment, measured on baseline survey, was categorised as low (no school certificate/qualifications), intermediate (school certificate/trade/apprenticeship/diploma) and high (university degree). Cox regression estimated the association (hazard ratios [HRs]) between education and coronary procedure receipt, adjusting for demographic and health-related factors, and testing for linear trend. Private health insurance was investigated as a mediating variable.

Results

Among 4454 patients with AMI, 68.3% received angiography within 30 days of admission (crude rate: 25.8/person-year) and 48.8% received revascularisation (rate: 11.7/person-year); corresponding figures among 4348 angina patients were 59.7% (rate: 17.4/person-year) and 30.8% (rate: 5.3/person-year). Procedure rates decreased with decreasing levels of education. Comparing low to high education, angiography rates were 29% lower among AMI patients (adjusted HR = 0.71, 95% CI: 0.56–0.90) and 40% lower among angina patients (0.60, 0.47–0.76). Patterns were similar for revascularisation among those with angina (0.78, 0.61–0.99) but not AMI (0.93, 0.69–1.25). After adjustment for private health insurance status, the HRs were attenuated and there was little evidence of an association between education and angiography among those admitted for AMI.

Conclusions

There is a socioeconomic gradient in coronary procedures with the most disadvantaged patients being less likely to receive angiography following hospital admission for AMI or angina, and revascularisation procedures for angina. Unequal access to private health care contributes to these differences. The extent to which the remaining variation is clinically appropriate, or whether angiography is being underused among people with low socioeconomic position or overused among those with higher socioeconomic position, is unclear.

Identifying long-term psychological distress from single measures: evidence from a nationally representative longitudinal survey of the Australian population

BACKGROUND

Single time-point assessments of psychological distress are often used to indicate chronic mental health problems, but the validity of this approach is unclear. The aims of this study were to investigate how a single assessment of distress relates to longer-term assessment and quantify misclassification from using single measures to indicate chronic distress.

METHODS

Data came from the Household, Income and Labour Dynamics in Australia Survey, a nationally representative study of Australian adults. Psychological distress, measured with the Kessler10 and categorised into low (scores:10- < 12), mild (12- < 16), moderate (16- < 22) and high (22-50), has been assessed in the Survey biennially since wave 7. Among respondents who were aged ≥25 years and participated in all waves in which distress was measured, we describe agreement in distress categories, and using a mixed linear model adjusting for age and sex we estimate change in scores, over a two-, four-, six- and eight-year follow-up period. We applied weights, benchmarked to the Australian population, to all analyses.

RESULTS

Two-years following initial assessment, proportions within identical categories of distress were 66.0% for low, 54.5% for mild, 44.0% for moderate and 50.3% for high, while 94.1% of those with low distress initially had low/mild distress and 81.4% with high distress initially had moderate/high distress. These patterns did not change materially as follow-up time increased. Over the full eight-year period, 77.3% of individuals with high distress initially reported high distress on ≥1 follow-up occasion. Age-and sex- adjusted change in K10 scores over a two-year period was 1.1, 0.5, - 0.7 and - 4.9 for low, mild, moderate and high distress, respectively, and also did not change materially as follow-up time increased.

CONCLUSION

In the absence of repeated measures, single assessments are useful proxies for chronic distress. Our estimates could be used in bias analyses to quantify the magnitude of the bias resulting from use of single assessments to indicate chronic distress.

Variation in coronary angiography and revascularisation procedures in relation to psychological distress among patients admitted to hospital with myocardial infarction or angina

OBJECTIVE

Cardiac patients with psychological distress have a poorer prognosis than patients without distress; which may in part reflect differences in treatment. We quantified variation in coronary angiography and revascularisation procedures according to psychological distress among patients admitted with incident acute myocardial infarction (AMI) or angina.

METHODS

Questionnaire data (collected 2006-09) from 45 and Up Study participants were linked to hospitalisation and mortality data, to 30 June 2016. Among patients free from ischaemic heart disease at baseline and subsequently hospitalised with AMI or angina, Cox regression was used to model the association between distress (Kessler-10 scores: low [10-<12], mild [12-<16], moderate [16-<22] and high [22-50]) - assessed on the questionnaire - and coronary angiography and revascularisation procedures (percutaneous coronary intervention [PCI] or coronary artery bypass grafting [CABG]) within 30 days of admission, adjusting for personal characteristics, including physical functioning.

RESULTS

Proportions receiving angiography and PCI/CABG were 71.4% and 51.7% following AMI (n = 3749), and 61.3% and 31.3% for angina patients (n = 3772), respectively. Following AMI, age-sex-adjusted rates of PCI/CABG were lower with higher levels of distress (test for trend: p = .037), as were rates of angiography and PCI/CABG (p < .01) following admission with angina. After additional adjustment for personal characteristics, associations between distress and procedure rates attenuated substantively and were no longer significant, except that PCI/CABG rates remained lower among angina patients with high versus low distress (HR = 0.76, 95%CI: 0.59-0.99).

CONCLUSION

Distress-related variation in coronary procedures largely reflects differences in personal characteristics. Whether lower revascularisation rates among angina patients with high compared to low distress are clinically appropriate or represent under-treatment remains unclear.

Psychological distress and medication use for secondary prevention of cardiovascular events: Evidence from a large-scale population-based cohort study

OBJECTIVE

Cardiac patients with psychological distress have a poorer prognosis than patients without distress, potentially reflecting differences in preventive care. We aimed to examine distress-related variation in guideline-recommended medication use for secondary prevention of cardiovascular disease (CVD).

METHODS

Baseline questionnaire data from the 45 and Up Study (collected 2006-2009) were linked to hospitalisation, pharmaceutical dispensing and death records (to exclude those who died). Among participants hospitalised with myocardial infarction, angina, stroke/transient ischaemic attack in the six years before the questionnaire, Modified Poisson regression was used to estimate relative risks (RR) for distress (Kessler 10 scores: low[10- < 12], mild[12- < 16], moderate[16- < 22] and high[22-50]) and use of both blood pressure- and lipid-lowering medications, and use of neither medication in the three months following the questionnaire, adjusting for sociodemographic and health characteristics.

RESULTS

Among 7598 participants, 34.0% had low, 35.4% mild, 18.3% moderate and 12.3% high psychological distress. Around two-thirds (63.4%) were using both medications and the proportion declined with increasing levels of distress: RRs were 1.01(95%CI:0.97-1.05), 0.95(0.90-1.00) and 0.91(0.86-0.97) for mild, moderate and high compared to low distress, respectively (p(trend) = 0.001). The proportion using neither medication was 9.1% and increased with increasing distress: RRs for mild, moderate and high compared to low distress were 0.99(0.82-1.19), 1.30(1.06-1.59) and 1.60(1.28-1.98), respectively (p(trend) < 0.001).

CONCLUSION

Patients with psychological distress may need more support to optimise their use of secondary CVD prevention medications. Increasing the use of these medications for distressed patients may improve prognosis for patients with distress and improve population-level secondary prevention of CVD more broadly.

Variation in cardiovascular disease care: an Australian cohort study on sex differences in receipt of coronary procedures

OBJECTIVES

The aim of this study was to quantify sex differences in diagnostic and revascularisation coronary procedures within 1 year of hospitalisation for acute myocardial infarction (AMI) or angina.

DESIGN

This is a prospective cohort study. Baseline questionnaire (January 2006-April 2009) data from the Sax Institute's 45 and Up Study were linked to hospitalisation and mortality data (to 30 June 2016) in a time-to-event analysis, treating death as a censoring event.

SETTING

This was conducted in New South Wales, Australia.

PARTICIPANTS

The study included participants aged ≥45 years with no history of ischaemic heart disease (IHD) who were admitted to hospital with a primary diagnosis of AMI (n=4580) or a primary diagnosis of angina or chronic IHD with secondary diagnosis of angina (n=4457).

OUTCOME MEASURES

The outcome of this study was coronary angiography and coronary revascularisation with percutaneous coronary intervention or coronary artery bypass graft (PCI/CABG) within 1 year of index admission. Cox regression models compared coronary procedure rates in men and women, adjusting sequentially for age, sociodemographic variables and health characteristics.

RESULTS

Among patients with AMI, 71.6% of men (crude rate 3.45/person-year) and 64.7% of women (2.62/person-year) received angiography; 57.8% of men (1.73/person-year) and 37.4% of women (0.77/person-year) received PCI/CABG. Adjusted HRs for men versus women were 1.00 (0.92-1.08) for angiography and 1.51 (1.38-1.67) for PCI/CABG. In the angina group, 67.3% of men (crude rate 2.36/person-year) and 54.9% of women (1.32/person-year) received angiography; 44.6% of men (0.90/person-year) and 19.5% of women (0.26/person-year) received PCI/CABG. Adjusted HRs were 1.24 (1.14-1.34) and 2.44 (2.16-2.75), respectively.

CONCLUSIONS

Men are more likely than women to receive coronary procedures, particularly revascularisation. This difference is most evident among people with angina, where clinical guidelines are less prescriptive than for AMI.

Tobacco smoking and risk of 36 cardiovascular disease subtypes: fatal and non-fatal outcomes in a large prospective Australian study

BACKGROUND

Tobacco smoking is a leading cause of cardiovascular disease (CVD) morbidity and mortality. Evidence on the relation of smoking to different subtypes of CVD, across fatal and non-fatal outcomes, is limited.

METHODS

A prospective study of 188,167 CVD- and cancer-free individuals aged ≥ 45 years from the Australian general population joining the 45 and Up Study from 2006 to 2009, with linked questionnaire, hospitalisation and death data up to the end of 2015. Hazard ratios (HRs) for hospitalisation with or mortality from CVD among current and past versus never smokers were estimated, including according to intensity and recency of smoking, using Cox regression, adjusting for age, sex, urban/rural residence, alcohol consumption, income and education. Population-attributable fractions were estimated.

RESULTS

During a mean 7.2 years follow-up (1.35 million person-years), 27,511 (crude rate 20.4/1000 person-years) incident fatal and non-fatal major CVD events occurred, including 4548 (3.2) acute myocardial infarction (AMI), 3991 (2.8) cerebrovascular disease, 3874 (2.7) heart failure and 2311 (1.6) peripheral arterial disease (PAD) events. At baseline, 8% of participants were current and 34% were past smokers. Of the 36 most common specific CVD subtypes, event rates for 29 were increased significantly in current smokers. Adjusted HRs in current versus never smokers were as follows: 1.63 (95%CI 1.56-1.71) for any major CVD, 2.45 (2.22-2.70) for AMI, 2.16 (1.93-2.42) for cerebrovascular disease, 2.23 (1.96-2.53) for heart failure, 5.06 (4.47-5.74) for PAD, 1.50 (1.24-1.80) for paroxysmal tachycardia, 1.31 (1.20-1.44) for atrial fibrillation/flutter, 1.41 (1.17-1.70) for pulmonary embolism, 2.79 (2.04-3.80) for AMI mortality, 2.26 (1.65-3.10) for cerebrovascular disease mortality and 2.75 (2.37-3.19) for total CVD mortality. CVD risks were elevated at almost all levels of current smoking intensity examined and increased with smoking intensity, with HRs for total CVD mortality in current versus never smokers of 1.92 (1.11-3.32) and 4.90 (3.79-6.34) for 4-6 and ≥ 25 cigarettes/day, respectively. Risks diminished with quitting, with excess risks largely avoided by quitting before age 45. Over one third of CVD deaths and one quarter of acute coronary syndrome hospitalisations in Australia aged < 65 can be attributed to smoking.

CONCLUSIONS

Current smoking increases the risk of virtually all CVD subtypes, at least doubling the risk of many, including AMI, cerebrovascular disease and heart failure. Paroxysmal tachycardia is a newly identified smoking-related risk. Where comparisons are possible, smoking-associated relative risks for fatal and non-fatal outcomes are similar. Quitting reduces the risk substantially. In an established smoking epidemic, with declining and low current smoking prevalence, smoking accounts for a substantial proportion of premature CVD events.

Primary Absolute Cardiovascular Disease Risk and Prevention in Relation to Psychological Distress in the Australian Population: A Nationally Representative Cross-Sectional Study

People who experience psychological distress have an elevated risk of incident cardiovascular disease (CVD). However, the extent to which traditional CVD prevention strategies could be used to reduce the CVD burden in this group is unclear because population-level data on CVD risk profiles and appropriate management of risk in relation to distress are currently not available. The aim of this study was to use nationally representative data to quantify variation in CVD risk and appropriate management of risk according to level of psychological distress in the Australian population. Data were from 2,618 participants aged 45-74 years without prior CVD who participated in the 2011-12 Australian Health Survey, a cross-sectional and nationally representative study of Australian adults. Age-and sex-adjusted prevalence of 5-year absolute risk of primary CVD (low <10%, moderate 10-15%, or high >15%), CVD risk factors, blood-pressure, and cholesterol assessments, and appropriate treatment (combined blood pressure- and lipid-lowering medication) if at high primary risk, were estimated. Prevalence ratios (PR) quantified variation in these outcomes in relation to low (Kessler-10 score: 10-<12), mild (12-<16), moderate (16-<22) and high (22-50) psychological distress, after adjusting for sociodemographic characteristics. The prevalence of high absolute risk of primary CVD for low, mild, moderate and high distress was 10.9, 12.3, 11.4, and 18.6%, respectively, and was significantly higher among participants with high compared to low distress (adjusted PR:1.62, 95%CI:1.04-2.52). The prevalence of CVD risk factors was generally higher in those with higher psychological distress. Blood pressure and cholesterol assessments were reported by the majority of participants (>85%) but treatment of high absolute risk was low (<30%), and neither were related to psychological distress. Our findings confirm the importance of recognizing people who experience psychological distress as a high risk group and suggest that at least part of the excess burden of primary CVD events among people with high psychological distress could be reduced with an absolute risk approach to assessment and improved management of high primary CVD risk.

General practitioners' perspectives on the prevention of cardiovascular disease: systematic review and thematic synthesis of qualitative studies

OBJECTIVE

Cardiovascular disease (CVD) is a leading cause of morbidity and mortality globally, and prevention of CVD is a public health priority. This paper aims to describe the perspectives of general practitioners (GPs) on the prevention of CVD across different contexts.

DESIGN

Systematic review and thematic synthesis of qualitative studies using the Enhancing Transparency of Reporting the Synthesis of Qualitative research (ENTREQ) framework.

DATA SOURCES

MEDLINE, Embase, PsycINFO and CINAHL from database inception to April 2018.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

We included qualitative studies on the perspectives of GPs on CVD prevention.

DATA EXTRACTION AND SYNTHESIS

We used HyperRESEARCH to code the primary papers and identified themes.

RESULTS

We selected 34 studies involving 1223 participants across nine countries. We identified six themes: defining own primary role (duty to prescribe medication, refraining from risking patients' lives, mediating between patients and specialists, delegating responsibility to patients, providing holistic care); trusting external expertise (depending on credible evidence and opinion, entrusting care to other health professionals, integrating into patient context); motivating behavioural change for prevention (highlighting tangible improvements, negotiating patient acceptance, enabling autonomy and empowerment, harnessing the power of fear, disappointment with futility of advice); recognising and accepting patient capacities (ascertaining patient's drive for lifestyle change, conceding to ingrained habits, prioritising urgent comorbidities, tailoring to patient environment and literacy); avoiding overmedicalisation (averting long-term dependence on medications, preventing a false sense of security, minimising stress of sickness) and minimising economic burdens (avoiding unjustified costs to patients, delivering practice within budget, alleviating healthcare expenses).

CONCLUSIONS

GPs sought to empower patients to prevent CVD, but consideration of patients' individual factors was challenging. Community-based strategies for assessing CVD risk involving other health professionals, and decision aids that address the individuality of the patient's health and environment, may support GPs in their decisions regarding CVD prevention.

Socioeconomic variation in absolute cardiovascular disease risk and treatment in the Australian population

Cardiovascular disease (CVD), preventable through appropriate management of absolute CVD risk, disproportionately affects socioeconomically disadvantaged individuals. The aim of this study was to estimate absolute and relative socioeconomic inequalities in absolute CVD risk and treatment in the Australian population using cross-sectional representative data on 4751 people aged 45-74 from the 2011-12 Australian Health Survey. Poisson regression was used to calculate prevalence differences (PD) and ratios (PR) for prior CVD, high 5-year absolute risk of a primary CVD event and guideline-recommended medication use, in relation to socioeconomic position (SEP, measured by education). After adjusting for age and sex, the prevalence of high absolute risk of a primary CVD event among those of low, intermediate and high SEP was 12.6%, 10.9% and 7.7% (PD, low vs. high = 5.0 [95% CI: 2.3, 7.7], PR = 1.6 [1.2, 2.2]) and for prior CVD was 10.7%, 9.1% and 6.7% (PD = 4.0 [1.4, 6.6], PR = 1.6 [1.1, 2.2]). The proportions using preventive medication use among those with high primary risk were 21.3%, 19.5% and 29.4% for low, intermediate and high SEP and for prior CVD, were 37.8%, 35.7% and 17.7% (PD = 20.1 [9.7, 30.5], PR = 2.1 [1.3, 3.5]). Proportions at high primary risk and not using medications among those of low, intermediate and high SEP were 10.6%, 8.8% and 4.7% and with prior CVD and not using medications were 8.5%, 6.3% and 4.1%. Findings indicate substantial potential to prevent CVD and reduce inequalities through appropriate management of high absolute risk in the population.

Psychological distress and ischaemic heart disease: cause or consequence? Evidence from a large prospective cohort study

BACKGROUND

Ischaemic heart disease (IHD) incidence is elevated in people reporting psychological distress. The extent to which this relationship is causal or related to reverse causality-that is, undiagnosed disease causing distress-is unclear. We quantified the relationship between psychological distress and IHD, with consideration of confounding and undiagnosed disease.

METHODS

Questionnaire data (2006-2009) from 151 811 cardiovascular disease-free and cancer-free Australian general population members aged ≥45years (45 and Up Study) were linked to hospitalisation and mortality data, to December 2013. A two-stage approach estimated HRs for incident IHD (IHD-related hospitalisation or death) for low (Kessler-10 scores: 10-<12), mild (12-<16), moderate (16-<22) and high (22-50) psychological distress, adjusting for demographic and behavioural characteristics, and then restricting to those with no/minor functioning limitations (likely free from undiagnosed disease).

RESULTS

Over 859 396 person-years, 5230 incident IHD events occurred (rate: 6.09/1000person-years). IHD risk was increased for mild (age-adjusted and sex-adjusted HR: 1.18, 95% CI 1.11 to 1.26), moderate (1.36, 1.25 to 1.47), and high (1.69, 1.52 to 1.88) versus low distress. HRs attenuated to 1.15 (1.08 to 1.22), 1.26 (1.16 to 1.37) and 1.41 (1.26 to 1.57) after adjustment for demographic and behavioural characteristics and were further attenuated by 35%-41% in those with no/minor limitations, leaving a significant but relatively weak dose-response relationship: 1.11 (1.02 to 1.20), 1.21 (1.08 to 1.37) and 1.24 (1.02 to 1.51) for mild, moderate and high versus low distress, respectively. The observed adjustment-related attenuation suggests measurement error/residual confounding likely contribute to the remaining association.

CONCLUSION

A substantial part of the distress-IHD association is explained by confounding and functional limitations, an indicator of undiagnosed disease. Emphasis should be on psychological distress as a marker of healthcare need and IHD risk, rather than a causative factor.

Burden of Clostridium difficile infection: Associated hospitalization in a cohort of middle-aged and older adults

BACKGROUND

Clostridium difficile is the principal cause of infectious diarrhea in hospitalized patients. The aim of this study was to describe and compare length of stay (LOS), costs, and in-hospital deaths for C difficile infection (CDI) and non-CDI hospitalizations, in a cohort of middle-aged and older Australians.

METHODS

We used survey data from the 45 and Up Study, linked to hospitalization and death data. We calculated the average LOS and costs per hospitalization, and the proportion of in-hospital deaths for CDI and non-CDI hospitalizations. We then compared hospitalizations with CDI as a secondary diagnosis to non-CDI hospitalizations by stratifying hospitalizations based on principal diagnosis and then using generalized linear models to compare LOS and in-hospital costs, and logistic regression for in-hospital deaths, adjusting for age and sex.

RESULTS

There were 641 CDI hospitalizations during 2006-2012. The average LOS was 17 days; the average cost per hospitalization was AUD 12,704; and in 7.3% of admissions (47 out of 641) the patient died. After adjusting for age and sex, hospitalizations with CDI were associated with longer LOS, higher costs, and a greater proportion of in-hospital deaths compared with hospitalizations with similar principal diagnosis but without CDI.

CONCLUSIONS

CDI places additional burden on the Australian hospital system, with CDI patients having relatively lengthy hospital stays and high costs.

Variation in readmission and mortality following hospitalisation with a diagnosis of heart failure: prospective cohort study using linked data

Background

Hospitalisation for heart failure is common and post-discharge outcomes, including readmission and mortality, are often poor and are poorly understood. The purpose of this study was to examine patient- and hospital-level variation in the risk of 30-day unplanned readmission and mortality following discharge from hospital with a diagnosis of heart failure.

Methods

Prospective cohort study using data from the Sax Institute’s 45 and Up Study, linking baseline survey (Jan 2006-April 2009) to hospital and mortality data (to Dec 2011). Primary outcomes in those admitted to hospital with heart failure included unplanned readmission, mortality and combined unplanned readmission/mortality, within 30 days of discharge. Multilevel models quantified the variation in outcomes between hospitals and examined associations with patient- and hospital-level characteristics.

Results

There were 5074 participants with a heart failure admission discharged from 251 hospitals; 1052 (21%) had unplanned readmissions, 186 (3.7%) died, and 1146 (23%) had either/both outcomes within 30 days of discharge. Crude outcomes varied across hospitals, but between-hospital variation explained little of the total variation in outcomes (intraclass correlation coefficients (ICC) after inclusion of patient factors: 30-day unplanned readmission ICC = 0.0125 (p = 0.24); death ICC = 0.0000 (p > 0.99); unplanned readmission/death ICC = 0.0266 (p = 0.07)). Patient characteristics associated with a higher risk of unplanned readmission included: being male (male vs female, adjusted odds ratio (aOR) = 1.18, 95% CI: 1.00–1.37); prior hospitalisation for cardiovascular disease (aOR = 1.44, 1.08–1.91) and for anemia (aOR = 1.36, 1.14–1.63); comorbidities at admission (severe vs none: aOR = 1.26, 1.03–1.54); lower body-mass-index (obese vs normal weight: aOR = 0.77, 0.63–0.94); and lower social interaction scores. Similarly, risk of 30-day mortality was associated with patient- rather than hospital-level factors, in particular age (≥85y vs 45–< 75y: aOR = 3.23, 1.93–5.41) and comorbidity (severe vs none: aOR = 2.68, 1.82–3.94).

Conclusions

The issue of high readmission and mortality rates in people with heart failure appear to be system-wide, with the variation in these outcomes essentially attributable to variation between patients rather than hospitals. The findings suggest that there are limitations in using these outcomes as hospital performance measures in this patient population and support the need for patient-centred strategies to optimise heart failure management and outcomes.

Electronic supplementary material

The online version of this article (doi:10.1186/s12913-017-2152-0) contains supplementary material, which is available to authorized users.

Factors related to receipt of non-cancer-related transurethral prostatectomy: findings from a large prospective study of 106 769 middle-aged and older Australian men

BACKGROUND

Transurethral prostatectomy (TURP) is a common surgical intervention for chronic lower urinary tract symptoms (LUTS). Little large-scale evidence exists on factors related to receipt of non-cancer-related TURP.

METHODS

A prospective study of men aged ≥45 years participating in the 45 and Up Study, a large Australian cohort study, without prior prostatectomy and/or bowel/genital/urinary-tract cancer; questionnaire data were linked to hospitalisations and deaths. HRs for TURP were estimated in relation to multiple factors, adjusting for confounders.

RESULTS

There were 3416 incident TURPs among 106 769 men (median follow-up 5.8 years), with rates of 1.8, 5.3, 9.1 and 11.4/1000 person-years for ages 45-54, 55-64, 65-74 and ≥75 years, respectively. Age-adjusted rates of TURP varied markedly according to baseline LUTS from 2.2/1000 person-years with no/mild symptoms to 30.7/1000 person-years with severe symptoms. Annual household income ≥$70 000 versus <$20 000, having private health insurance and living in major cities were associated with higher TURP rates; there were no significant differences according to baseline diabetes, stroke, high blood pressure or cardiovascular disease. Men reporting severe versus no physical functioning limitation, high versus low psychological distress or poor versus excellent self-rated health were 36-51% more likely to undergo procedures overall, but were 24-37% less likely to undergo procedures following additional adjustment for need (baseline LUTS).

CONCLUSIONS

TURP rates were most strongly related to baseline LUTS and age, consistent with appropriate health services targeting. Lower TURP rates in men experiencing socioeconomic disadvantage and with poor health/disability, after accounting for baseline LUTS, suggest inequity and factors such as frailty and risks related to surgery.

Socioeconomic variation in incidence of primary and secondary major cardiovascular disease events: an Australian population-based prospective cohort study

BACKGROUND

Cardiovascular disease (CVD) disproportionately affects disadvantaged people, but reliable quantitative evidence on socioeconomic variation in CVD incidence in Australia is lacking. This study aimed to quantify socioeconomic variation in rates of primary and secondary CVD events in mid-age and older Australians.

METHODS

Baseline data (2006-2009) from the 45 and Up Study, an Australian cohort involving 267,153 men and women aged ≥ 45, were linked to hospital and death data (to December 2013). Outcomes comprised first event - death or hospital admission - for major CVD combined, as well as myocardial infarction and stroke, in those with and without prior CVD (secondary and primary events, respectively). Cox regression estimated hazard ratios (HRs) for each outcome in relation to education (and income and area-level disadvantage), separately by age group (45-64, 65-79, and ≥ 80 years), adjusting for age and sex, and additional sociodemographic factors.

RESULTS

There were 18,207 primary major CVD events over 1,144,845 years of follow-up (15.9/1000 person-years), and 20,048 secondary events over 260,357 years (77.0/1000 person-years). For both primary and secondary events, incidence increased with decreasing education, with the absolute difference between education groups largest for secondary events. Age-sex adjusted hazard ratios were highest in the 45-64 years group: for major CVDs, HR (no qualifications vs university degree) = 1.62 (95% CI: 1.49-1.77) for primary events, and HR = 1.49 (1.34-1.65) for secondary events; myocardial infarction HR = 2.31 (1.87-2.85) and HR = 2.57 (1.90-3.47) respectively; stroke HR = 1.48 (1.16-1.87) and HR = 1.97 (1.42-2.74) respectively. Similar but attenuated results were seen in older age groups, and with income. For area-level disadvantage, CVD gradients were weak and non-significant in older people (> 64 years).

CONCLUSIONS

Individual-level data are important for quantifying socioeconomic variation in CVD incidence, which is shown to be substantial among both those with and without prior CVD. Findings reinforce the opportunity for, and importance of, primary and secondary prevention and treatment in reducing socioeconomic variation in CVD and consequently the overall burden of CVD morbidity and mortality in Australia.

Is poor oral health a risk marker for incident cardiovascular disease hospitalisation and all-cause mortality? Findings from 172 630 participants from the prospective 45 and Up Study

OBJECTIVE

To investigate the relationship between oral health and incident hospitalisation for ischaemic heart disease (IHD), heart failure (HF), ischaemic stroke and peripheral vascular disease (PVD) and all-cause mortality.

DESIGN

Prospective population-based study of Australian men and women aged 45 years or older, who were recruited to the 45 and Up Study between January 2006 and April 2009; baseline questionnaire data were linked to hospitalisations and deaths up to December 2011. Study exposures include tooth loss and self-rated health of teeth and gums at baseline.

SETTING

New South Wales, Australia.

PARTICIPANTS

Individuals aged 45-75 years, excluding those with a history of cancer/cardiovascular disease (CVD) at baseline; n=172 630.

PRIMARY OUTCOMES

Incident hospitalisation for IHD, HF, ischaemic stroke and PVD and all-cause mortality.

RESULTS

During a median follow-up of 3.9 years, 3239 incident hospitalisations for IHD, 212 for HF, 283 for ischaemic stroke and 359 for PVD, and 1908 deaths, were observed. Cox proportional hazards models examined the relationship between oral health indicators and incident hospitalisation for CVD and all-cause mortality, adjusting for potential confounding factors. All-cause mortality and incident CVD hospitalisation risk increased significantly with increasing tooth loss for all outcomes except ischaemic stroke (ptrend<0.05). In those reporting no teeth versus ≥20 teeth left, risks were increased for HF (HR, 95% CI 1.97, 1.27 to 3.07), PVD (2.53, 1.81 to 3.52) and all-cause mortality (1.60, 1.37 to 1.87). The risk of IHD, PVD and all-cause mortality (but not HF or ischaemic stroke) increased significantly with worsening self-rated health of teeth and gums (ptrend<0.05). In those reporting poor versus very good health of teeth and gums, risks were increased for IHD (1.19, 1.03 to 1.38), PVD (1.66, 1.13 to 2.43) and all-cause mortality (1.76, 1.50 to 2.08).

CONCLUSIONS

Tooth loss and, to a lesser extent, self-rated health of teeth and gums, are markers for increased risk of IHD, PVD and all-cause mortality. Tooth loss is also a marker for increased risk of HF.

Categorising major cardiovascular disease hospitalisations from routinely collected data

Objectives and importance of the study: Routine hospital administrative data provide an important source of information about cardiovascular disease (CVD) for health statistics reporting, health services and research. How such conditions are classified and grouped has implications for the use and interpretation of these data. International Classification of Diseases (ICD) diagnosis codes from hospital data collections are often used to classify CVD, but there is little published evidence on the most appropriate ways to use these codes to categorise CVD in a way that maximises the usefulness of hospital data for reporting and research. In particular, ICD codes under 'Diseases of the circulatory system' (I00-I99) are often grouped together into a general CVD category. However, this category is heterogeneous and combines common severe atherosclerotic and thrombotic CVDs (such as myocardial infarction and pulmonary embolism) with common, less severe and pathologically dissimilar conditions (such as varicose veins and haemorrhoids). In addition, hospital data collections contain a range of data fields, including those relating to primary and additional diagnoses and those relating to procedures. All of these have the potential to contribute valuable information on CVD. This paper proposes a pragmatic approach to using ICD diagnosis codes and procedure codes to capture major atherosclerotic and arteriovenous thromboembolic and related CVD.

METHODS

We reviewed the ICD diagnosis codes and procedure codes and developed an algorithm for classifying and categorising major CVD diagnoses. This approach was then applied to linked hospitalisation data from individuals participating in the 45 and Up Study, a cohort study of 267 153 New South Wales residents aged 45 and over, to investigate the implications of the proposed approach for quantifying CVD.

RESULTS

Large differences were observed in the numbers of events in grouped CVD outcomes, depending on the methods used.

CONCLUSIONS

In cases where the reporting and research interest relates to incident disease, it may be appropriate to prioritise specific disease categories and pathological homogeneity.

Characteristics of antidepressant medication users in a cohort of mid-age and older Australians

OBJECTIVES

We aimed to investigate antidepressant use, including the class of antidepressant, in mid-age and older Australians according to sociodemographic, lifestyle and physical and mental health-related factors.

METHODS

Baseline questionnaire data on 111,705 concession card holders aged ⩾45 years from the 45 and Up Study-a population-based cohort study from New South Wales, Australia-were linked to administrative pharmaceutical data. Current- and any-antidepressant users were those dispensed medications with Anatomical Therapeutic Chemical classification codes beginning N06A, within ⩽6 months and ⩽19 months before baseline, respectively; non-users had no antidepressants dispensed ⩽19 months before baseline. Multinomial logistic regression was used to calculate adjusted relative risk ratios (aRRRs) for predominantly self-reported factors in relation to antidepressant use.

RESULTS

Some 19% of the study population (15% of males and 23% of females) were dispensed at least one antidepressant during the study period; 40% of participants used selective serotonin reuptake inhibitors (SSRIs) only and 32% used tricyclic antidepressants (TCAs) only. Current antidepressant use was markedly higher in those reporting: severe versus no physical impairment (aRRR 3.86(95%CI 3.67-4.06)); fair/poor versus excellent/very good self-rated health (4.04(3.83-4.25)); high/very high versus low psychological distress (7.22(6.81-7.66)); ever- versus never-diagnosis of depression by a doctor (18.85(17.95-19.79)); low-dose antipsychotic use versus no antipsychotic use (12.26(9.85-15.27)); and dispensing of ⩾10 versus <5 other medications (5.97(5.62-6.34)). Sociodemographic and lifestyle factors were also associated with use, although to a lesser extent. Females, older people, those with lower education and those with poorer health were more likely to be current antidepressant users than non-users and were also more likely to use TCAs-only versus SSRIs-only.

CONCLUSIONS

Use of antidepressants is substantially higher in those with physical ill-health and in those reporting a range of adverse mental health measures. In addition, sociodemographic factors, including sex, age and education were also associated with antidepressant use and the class of antidepressant used.

Income-related inequalities in chronic conditions, physical functioning and psychological distress among older people in Australia: cross-sectional findings from the 45 and up study

Background

The burden of chronic disease continues to rise as populations age. There is relatively little published on the socioeconomic distribution of this burden in older people. This study quantifies absolute and relative income-related inequalities in prevalence of chronic diseases, severe physical functioning limitation and high psychological distress in mid-age and older people in Australia.

Methods

Cross-sectional study of 208,450 participants in the 45 and Up Study, a population-based cohort of men and women aged 45–106 years from New South Wales, Australia. Chronic conditions included self-reported heart disease, diabetes, Parkinson’s disease, cancer and osteoarthritis; physical functioning limitation (severe/not) was measured using Medical Outcomes Study measures and psychological distress (high/not) using the Kessler Psychological Distress Scale. For each outcome, prevalence was estimated in relation to annual household income (6 categories). Prevalence differences (PDs) and ratios (PRs) were generated, comparing the lowest income category (<$20,000) to the highest (≥$70,000), using Poisson regression with robust standard errors, weighted for age, sex and region of residence. Analyses were stratified by age group (45–64, 65–79 and ≥80 years) and sex and adjusted for age and country of birth.

Results

With few exceptions, there were income gradients in the prevalence of chronic conditions among all age-sex groups, with prevalence decreasing with increasing income. Of the chronic diseases, PDs were highest for diabetes (ranging between 5.69% and 10.36% across age-sex groups) and in women, also for osteoarthritis (5.72% to 8.14%); PRs were highest for osteoarthritis in men aged 45–64 years (4.01), otherwise they were highest for diabetes (1.78 to 3.43). Inequalities were very high for both physical functioning limitation and psychological distress, particularly among those aged 45–64 (PDs between 18.67% and 29.23% and PRs between 4.63 and 16.51). Absolute and relative inequalities tended to decrease with age, but remained relatively high for diabetes and physical functioning in the elderly (≥80 years).

Conclusions

Significant inequalities in the prevalence of chronic conditions, physical functioning and psychological distress persist into old age. The additional health burden placed on those who are already disadvantaged is likely to become an increasingly important issue in an ageing population.

Variation in health inequalities according to measures of socioeconomic status and age

OBJECTIVE

To examine variation in the magnitude of socioeconomic inequalities in health and age-related variations in inequalities, according to the socioeconomic status (SES) measure used.

METHODS

Cross-sectional study involving 205,709 participants in the 45 and Up Study. We used the Relative Index of Inequality (RII) to quantify health inequalities in relation to income, education and Socio-Economic Indexes for Areas (SEIFA). The outcomes used were heart disease and self-rated health. Analyses were stratified by age (45-64, 65-79, ≥80 years).

RESULTS

RIIs were largest for income and smallest for SEIFA; they were generally largest in the youngest age group and smallest in the oldest group. Age-related differences in RIIs were particularly marked for income (e.g. for fair/poor health, RII=11.81, 95%CI 11.14-12.53 in the 45-64 age group and RII=2.42, 95%CI 2.10-2.78 in ≥80 group), and less marked for SEIFA (e.g. respectively, RII=2.68, 95%CI 2.53-2.84 and RII=1.32, 95%CI 1.22-1.44).

CONCLUSIONS

The magnitude of socioeconomic inequality in health varies substantially according to the type of SES measure used and age. Income is the most sensitive measure.

IMPLICATIONS

Researchers and policy makers should be aware of the extent to which SEIFA-based estimates underestimate the magnitude of health inequality compared to individual-level measures, especially in younger age groups.

How weight change is modelled in population studies can affect research findings: empirical results from a large-scale cohort study

OBJECTIVES

To investigate how results of the association between education and weight change vary when weight change is defined and modelled in different ways.

DESIGN

Longitudinal cohort study.

PARTICIPANTS

60 404 men and women participating in the Social, Environmental and Economic Factors (SEEF) subcomponent of the 45 and Up Study-a population-based cohort study of people aged 45 years or older, residing in New South Wales, Australia.

OUTCOME MEASURES

The main exposure was self-reported education, categorised into four groups. The outcome was annual weight change, based on change in self-reported weight between the 45 and Up Study baseline questionnaire and SEEF questionnaire (completed an average of 3.3 years later). Weight change was modelled in four different ways: absolute change (kg) modelled as (1) a continuous variable and (2) a categorical variable (loss, maintenance and gain), and relative (%) change modelled as (3) a continuous variable and (4) a categorical variable. Different cut-points for defining weight-change categories were also tested.

RESULTS

When weight change was measured categorically, people with higher levels of education (compared with no school certificate) were less likely to lose or to gain weight. When weight change was measured as the average of a continuous measure, a null relationship between education and annual weight change was observed. No material differences in the education and weight-change relationship were found when comparing weight change defined as an absolute (kg) versus a relative (%) measure. Results of the logistic regression were sensitive to different cut-points for defining weight-change categories.

CONCLUSIONS

Using average weight change can obscure important directional relationship information and, where possible, categorical outcome measurements should be included in analyses.