Categorising major cardiovascular disease hospitalisations from routinely collected data

Impact of integrative care on cardiovascular disease risk in newly diagnosed type 2 diabetes mellitus patients: A BI-VitalLife Cohort study

INTRODUCTION

Type 2 diabetes mellitus (T2DM), a chronic metabolic disorder, significantly increases cardiovascular disease (CVD) risk. Integrative care (IC) offers a personalized health management approach, utilizing various interventions to mitigate this risk. However, the impact of IC on CVD risk in newly diagnosed T2Dm patients remains unclear. This study aims to assess the differences in CVD risk development within 120 months following a new diagnosis of T2DM, using real-world data from Bumrungrad International Hospital and Vitallife Scientific Wellness Center.

METHODS

This study utilized the BI-VitalLife Cohort dataset that contains de-identified demographics, vitals, diagnoses and clinical information, laboratory and radiological data, medications, and treatments of more than 2.8 million patients who visited Bumrungrad International Hospital and/or VitalLife Scientific Wellness Center from June 1, 1999, to May 31, 2022. This study focused on newly diagnosed T2DM patients, defined according to American Diabetes Association criteria. We compared CVD risk between the IC and conventional care (CC) groups using the Kaplan-Meier curve and Cox proportional hazard model, adjusted for age, sex, and laboratory values. Propensity score matching was employed to enhance comparability.

RESULTS

Of the 5,687 patients included, 236 were in the IC group and 5,451 in the CC group. The IC group, characterized by a lower age at T2DM diagnosis, showed favorable hematological and metabolic profiles. The Cox proportional hazard ratios revealed a significantly lower CVD risk in the IC group within 120 months post-T2DM diagnosis compared to the CC group, consistent even after adjusting for confounding factors. Propensity score-matched analysis supported these findings.

CONCLUSION

Personalized integrative care may offer a significant advantage in reducing CVD risk among newly diagnosed T2DM patients compared to conventional care, even when considering various confounding factors. This study sheds light on the potential of integrative care in informing treatment strategies for T2DM patients at risk of developing CVD.

Comparison of long-term outcomes of bioprosthetic and mechanical aortic valve replacement in patients younger than 65 years

OBJECTIVES

The objectives of this study were to compare rates of mortality and reoperations for patients aged younger than 65 years who underwent surgical aortic valve replacement (AVR). AVR with a bioprosthetic valve (BV) is increasing among younger patients, however evidence to inform the choice between BV or mechanical valve is limited.

METHODS

We performed a retrospective cohort study using linked hospital and mortality data from Australia, for 3969 AVR patients between 2003 and 2018. We compared outcomes for valves in inverse probability of treatment-weighted cohorts, stratified according to age (18-54 years; 55-64 years). We used weighted Cox regression models to estimate hazard ratios (HRs) and weighted cumulative incidence function for subdistribution hazards, for follow-up intervals: 0 to 10 and >10 to 15 years.

RESULTS

Among patients aged 55 to 64 years, there was no difference in mortality at 0 to 10 years. However, at >10 to 15 years, mortality was higher among BV recipients (HR, 1.56; 95% CI, 1.01-2.42). There was no difference among patients aged 18 to 54 years. Reoperation rates for patients aged 55 to 64 years did not differ according to valve type at 0 to 10 years, but were higher for BV than mechanical valve at >10 to 15 years (HR, 2.87; 95% CI, 1.69-4.86). For patients aged 18 to 54 years, reoperation rates were consistently higher for BV at both time intervals (HR, 2.54 [95% CI, 1.03-6.25] and HR, 4.48 [95% CI, 2.15-9.32], respectively).

CONCLUSIONS

Patients aged 55 to 64 years who received a BV had a higher risk of mortality beyond 10 years. Rates of reoperations were higher among patients implanted with a BV in the entire cohort. Further investigation of long-term outcomes among patients with a BV is necessary. Continuous long-term monitoring of BV technologies will ensure evidence-based decision-making and regulation.

Does affirmative action reduce disparities in healthcare use by Indigenous peoples? Evidence from Australia's Indigenous Practice Incentives Program

Globally, Indigenous populations experience poorer health but use less primary healthcare than their non-Indigenous counterparts. In 2010, the Australian government introduced a targeted reform aimed at reducing these disparities. The reform reduced, or abolished prescription medicine co-payments and provided financial incentives for GPs to better manage chronic disease care for Indigenous peoples. Exploiting the framework of a natural experiment, we investigate how the reform affected these health disparities in primary and specialist healthcare utilization using longitudinal administrative data from 75,826 Australians, including 1896 Indigenous peoples, with cardiovascular disease. The differences-in-differences estimates indicate that the reform increased primary healthcare use among Indigenous peoples, including 12.9% more prescription medicines, 6.6% more GP services, and 34.0% more chronic disease services, but also reduced specialist attendances by 11.8%. Increases in primary care were larger for those who received the largest co-payment relief and lived in metropolitan regions, whereas the reduction in specialist attendances was concentrated among lower income Indigenous patients. Affirmative action can reduce inequalities in Indigenous use of primary healthcare, albeit careful design is required to ensure that benefits are equitable and do not lead to substitution away from valuable, or necessary, care.

Impact of Malnutrition on Clinical Outcomes of Acutely Hospitalised Heart Failure Patients at Two Tertiary Hospitals in Australia: An Observational Study

BACKGROUND

Malnutrition is common in patients with heart failure (HF) but is often neglected, despite guidelines suggesting that all hospitalised patients should undergo nutritional screening within 24-hours of admission.

AIMS

This study investigated the nutritional screening rates and determined the immediate and long-term clinical outcomes in patients with HF admitted at two tertiary hospitals in Australia.

METHODS

Nutritional screening was assessed by the Malnutrition Universal Screening Tool (MUST) completion rates. Patients were classified into two categories based on their MUST scores (0=low malnutrition risk and ≥1=at risk of malnutrition). Propensity-score-matching (PSM) was used to match 20 variables depending upon the risk of malnutrition. Clinical outcomes included the days-alive-and-out-of-hospital at 90 days of discharge (DAOH90), length of hospital stay, in-hospital, 30-day and 180-day mortality and 30-day readmissions.

RESULTS

There were 5,734 HF admissions between 2013-2020, of whom, only 789 (13.8%) patients underwent MUST screening. The mean (SD) age was 76.2 (14.0) years and 51.9% were males. Five-hundred and fifty-four (554) (70.2%) patients were at low malnutrition risk and 235 (29.8%) at risk of malnutrition. In HF patients, who were at risk of malnutrition, the DAOH90 were lower by 5.9 days (95% CI -11.49 to -0.42, p=0.035) and 180-day mortality was significantly worse (coefficient 0.10, 95% CI 0.02-0.18, p=0.007) compared to those who were at low risk of malnutrition. However, other clinical outcomes were similar between the two groups.

CONCLUSION

Nutrition screening is poor in hospitalised HF patients and long-term but not short-term clinical outcomes were worse in malnourished HF patients.

Uptake of prescription smoking cessation pharmacotherapies after hospitalization for major cardiovascular disease

AIMS

We determined the prevalence of prescription smoking cessation pharmacotherapy (SCP) use after hospitalization for major cardiovascular disease (MCD) among people who smoke and whether this varies by sex.

METHODS AND RESULTS

We conducted a population-based cohort study including all people hospitalized in New South Wales, Australia, between July 2013 and December 2018 (2017 for private hospitals) with an MCD diagnosis. For patients who also had a diagnosis of current tobacco use, we used linked pharmaceutical dispensing records to identify prescription SCP dispensings within 90 days post-discharge. We determined the proportion who were dispensed an SCP within 90 days, overall and by type of SCP. We used logistic regression to estimate the odds of females being dispensed an SCP relative to males. Of the 150 758 patients hospitalized for an MCD, 20 162 (13.4%) had a current tobacco use diagnosis, 31% of whom were female. Of these, 11.3% (12.4% of females, 10.9% of males) received prescription SCP within 90 days post-discharge; 3.0% were dispensed varenicline, and 8.3% were dispensed nicotine replacement therapy patches. Females were more likely than males to be dispensed a prescription SCP [odds ratio (OR) 1.16, 95% confidence interval (CI) 1.06-1.27)]; however, this was not maintained after adjusting for potential confounders (adjusted OR 1.04, 95% CI 0.94-1.15).

CONCLUSION

Very few females and males who smoke use prescription SCPs after hospitalization for an MCD. The use of varenicline, the SCP with the highest efficacy, was particularly low. This represents a missed opportunity to increase smoking cessation in this high-risk population, thereby reducing their risk of recurrent cardiovascular events.

Joint associations of social health and movement behaviours with mortality and cardiovascular disease: an analysis of 497,544 UK biobank participants

Background

Poor physical activity and excessive sedentary behaviour are well-established risk factors for morbidity and mortality. In the presence of emerging social problems, including loneliness and social isolation, these risks may be even greater. We aimed to investigate the joint effects of social health and movement behaviours on mortality and cardiovascular disease (CVD).

Methods

497,544 UK Biobank participants were followed for an average of 11 years. Loneliness and social isolation were measured via self-report. Physical activity was categorised around current World Health Organisation (WHO) guidelines as low (< 600 metabolic equivalent of task [MET]-mins/week), moderate (600 < 1200) and high (≥ 1200). Sedentary behaviour was classified as low (≤ 3.5 h/day), moderate (3.5 ≤ 5) and high (> 5.5). We derived 24 social health–movement behaviour combinations, accordingly. Mortality and hospitalisations were ascertained to May 2020 for all-cause and CVD mortality, and non-fatal cardiovascular events.

Results

Social isolation amplified the risk of both all-cause and CVD death across all physical activity and sedentary levels (hazard ratio, 95% confidence interval [HR, 95% CIs] for all-cause mortality; 1.58 [1.49 to 1.68] for low active-isolated vs. 1.26 [1.22 to 1.30] for low active-not isolated). Loneliness was only found to amplify the risk of death from cardiovascular disease among the high active and low sedentary participants. Loneliness and social isolation did not add to the risk of non-fatal cardiovascular events across most activity levels.

Conclusion

The detrimental associations of poor physical activity and sedentary behaviour with mortality were consistently amplified by social isolation. Our study supports the need to target the socially isolated as a priority group in preventive public health strategies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12966-022-01372-3.

Characteristics and outcomes of patients with heart failure discharged from different speciality units in Australia: an observational study

BACKGROUND

Previous studies have reported differing clinical outcomes among hospitalized heart failure (HF) patients admitted under cardiology and general medicine (GM) without consideration of patients' frailty.

AIMS

To explore outcomes in patients admitted under the two specialities after taking into account their frailty and other characteristics.

METHODS

This retrospective study included all HF patients ≥18 years admitted between 1 January 2013 and 31 December 2019 at two Australian tertiary hospitals. Frailty was determined by use of the Hospital Frailty Risk Score (HFRS) and patients with HFRS ≥ 5 were classified as frail. Propensity score matching (PSM) was used to match 11 variables between the two specialities. The primary outcomes included the days-alive-and-out-of-hospital (DAOH90) at 90 days of discharge, 30-day mortality and readmissions.

RESULTS

Of 4913 HF patients, mean age 76.2 (14.1) years, 51% males, 2653 (54%) were admitted under cardiology compared to 2260 (46%) under GM. Patients admitted under GM were more likely to be older females, with a higher Charlson index and poor renal function than those admitted under cardiology. Overall, 23.8% patients were frail and frail patients were more likely to be admitted under GM than cardiology (33.6% vs. 15.3%, P < 0.001). PSM created 1532 well-matched patients in each group. After PSM, the DAOH90 was not significantly different among patients admitted in GM when compared to cardiology (coefficient -5.36, 95% confidence interval -11.73 to 1.01, P = 0.099). Other clinical outcomes were also similar between the two specialities.

CONCLUSIONS

Clinical characteristics of HF patients differ between GM and cardiology; however, clinical outcomes were not significantly different after taking into account frailty and other variables.

Benefits of heart failure-specific pharmacotherapy in frail hospitalised patients: a cross-sectional study

OBJECTIVES

Up to 50% of heart failure (HF) patients may be frail and have worse clinical outcomes than non-frail patients. The benefits of HF-specific pharmacotherapy (beta-blockers, ACE-inhibitors/angiotensin-receptor-blockers and mineralocorticoid-receptor-antagonist) in this population are unclear. This study explored whether HF-specific pharmacotherapy improves outcomes in frail hospitalised HF patients.

DESIGN

Observational, multicentre, cross-sectional study.

SETTINGS

Tertiary care hospitals.

PARTICIPANTS

One thousand four hundred and six hospitalised frail HF patients admitted between 1 January 2013 and 31 December 2020.

MEASURES

The Hospital Frailty Risk Score (HFRS) determined frailty status and patients with HFRS ≥5 were classified as frail. The primary outcomes included the days alive and out of hospital (DAOH) at 90 days following discharge, 30-day and 180-day mortality, length of hospital stay (LOS) and 30-day readmissions. Propensity score matching (PSM) compared clinical outcomes depending on the receipt of HF-specific pharmacotherapy.

RESULTS

Of 5734 HF patients admitted over a period of 8 years, 1406 (24.5%) were identified as frail according to the HFRS and were included in this study. Of 1406 frail HF patients, 1025 (72.9%) received HF-specific pharmacotherapy compared with 381 (27.1%) who did not receive any of these medications. Frail HF patients who did not receive HF-specific pharmacotherapy were significantly older, with higher creatinine and brain natriuretic peptide but with lower haemoglobin and albumin levels (p<0.05) when compared with those frail patients who received HF medications. After PSM frail patients on treatment were more likely to have an increased DAOH (coefficient 16.18, 95% CI 6.32 to 26.04, p=0.001) than those who were not on treatment. Both 30-day (OR 0.30, 95% CI 0.23 to 0.39, p<0.001) and 180-day mortality (OR 0.43, 95% CI 0.33 to 0.54, p<0.001) were significantly lower in frail patients on HF treatment but, there were no significant differences in LOS and 30-day readmissions (p>0.05).

CONCLUSION

This study found an association between the use of HF-specific pharmacotherapy and improved clinical outcomes in frail HF hospitalised patients when compared to those who were not on treatment.

TRIAL REGISTRATION NUMBER

ANZCTRN383195.

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.

External Validation of the Hospital Frailty-Risk Score in Predicting Clinical Outcomes in Older Heart-Failure Patients in Australia

Frailty is common in older hospitalised heart-failure (HF) patients but is not routinely assessed. The hospital frailty-risk score (HFRS) can be generated from administrative data, but it needs validation in Australian health-care settings. This study determined the HFRS scores at presentation to hospital in 5735 HF patients ≥ 75 years old, admitted over a period of 7 years, at two tertiary hospitals in Australia. Patients were classified into 3 frailty categories: HFRS < 5 (low risk), 5−15 (intermediate risk) and >15 (high risk). Multilevel multivariable regression analysis determined whether the HFRS predicts the following clinical outcomes: 30-day mortality, length of hospital stay (LOS) > 7 days, and 30-day readmissions; this was determined after adjustment for age, sex, Charlson index and socioeconomic status. The mean (SD) age was 76.1 (14.0) years, and 51.9% were female. When compared to the low-risk HFRS group, patients in the high-risk HFRS group had an increased risk of 30-day mortality and prolonged LOS (adjusted OR (aOR) 2.09; 95% CI 1.21−3.60) for 30-day mortality, and an aOR of 1.56 (95% CI 1.01−2.43) for prolonged LOS (c-statistics 0.730 and 0.682, respectively). Similarly, the 30-day readmission rate was significantly higher in the high-risk HFRS group when compared to the low-risk group (aOR 1.69; 95% CI 1.06−2.69; c-statistic = 0.643). The HFRS, derived at admission, can be used to predict ensuing clinical outcomes among older hospitalised HF patients.

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

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

Trends in Frailty and Use of Evidence-Based Pharmacotherapy for Heart Failure in Australian Hospitalised Patients: An Observational Study

Frailty increases morbidity and mortality in heart failure (HF) patients. Current risk-adjustment models do not include frailty-status and the relationship between frailty and pharmacotherapy is unclear. This study explored trends in frailty over time and its relationship with prescription of heart failure specific pharmacotherapy in hospitalised HF patients. We used the Hospital Frailty Risk Score (HFRS) to determine frailty status of patients ≥18 years admitted between 2015-2019 at two tertiary hospitals in Australia. Patients with an HFRS ≥ 5 were classified as frail. In the 3706 patients with a mean (SD) age of 76.1 (14.4) years, 876 (23.6%) were classified as frail. HFRS was weakly correlated with age (r = 0.16) and Charlson-index (r = 0.35) (both p values < 0.001). Whilst frailty was more common in older HF patients (28.9% of patients ≥80 years), 15.1% of patients ≤65 years of age were also found to be frail. The proportion of frail patients increased from 19.4% in 2015 to 29.2% in 2019 despite no significant change in age during this period. The proportion of patients who received heart failure specific pharmacotherapy decreased from 86.7% in 2015 to 82.9% in 2019 (p value = 0.03) and frail patients were significantly less likely to be prescribed HF specific pharmacotherapy than non-frail patients (77.4% vs. 85.9%, p < 0.001).

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.

Cardiovascular disease subtypes, physical disability and workforce participation: A cross-sectional study of 163,562 middle-aged Australians

Background

Workforce participation is reduced among people with cardiovascular disease (CVD). However, detailed quantitative evidence on this is limited. We examined the relationship of CVD to workforce participation in older working-age people, by CVD subtype, within population subgroups and considering the role of physical disability.

Methods

Questionnaire data (2006–2009) for participants aged 45–64 years (n = 163,562) from the population-based 45 and Up Study (n = 267,153) were linked to hospitalisation data through the Centre for Health Record Linkage. Prior CVD was from self-report or hospitalisation. Modified Poisson regression estimated adjusted prevalence ratios (PRs) for non-participation in the workforce in people with versus without CVD, adjusting for sociodemographic factors.

Results

There were 19,161 participants with CVD and 144,401 without. Compared to people without CVD, workforce non-participation was greater for those with CVD (40.0% vs 23.5%, PR = 1.36, 95%CI = 1.33–1.39). The outcome varied by CVD subtype: myocardial infarction (PR = 1.46, 95%CI = 1.36–1.55); cerebrovascular disease (PR = 1.92, 95%CI = 1.80–2.06); heart failure (PR = 1.83, 95%CI = 1.68–1.98) and peripheral vascular disease (PR = 1.76, 95%CI = 1.65–1.88). Workforce non-participation in those with CVD versus those without was at least 21% higher in all population subgroups examined, with PRs ranging from 1.75 (95%CI = 1.65–1.85) in people aged 50–55 years to 1.21 (95%CI = 1.19–1.24) among those aged 60–64. Compared to people with neither CVD nor physical functioning limitations, those with physical functional limitations were around three times as likely to be out of the workforce regardless of CVD diagnosis; participants with CVD but without physical functional limitations were 13% more likely to be out of the workforce (PR = 1.13, 95%CI = 1.07–1.20).

Conclusions

While many people with CVD participate in the workforce, participation is substantially lower, especially for people with cerebrovascular disease, than for people without CVD, highlighting priority areas for research and support, particularly for people experiencing physical functioning limitations.

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.

Breastfeeding and Cardiovascular Disease Hospitalization and Mortality in Parous Women: Evidence From a Large Australian Cohort Study

Background

Few studies have investigated the longitudinal association between breastfeeding and maternal cardiovascular disease (CVD) outcomes. This study examined the association between breastfeeding and CVD hospitalization and mortality in a large Australian cohort.

Methods and Results

Baseline questionnaire data (2006–2009) from a sample of 100 864 parous women aged ≥45 years from New South Wales, Australia, were linked to hospitalization and death data until June 2014 and December 2013, respectively. Analysis was restricted to women without self‐reported medically diagnosed CVD at baseline or without past CVD hospitalization 6 years before study entry. Never versus ever breastfeeding and average breastfeeding duration per child, derived from self‐reported lifetime breastfeeding duration and number of children, and categorized as never breastfed, <6, >6 to 12, or >12 months/child, were assessed. Cox proportional hazards models were used to explore the association between breastfeeding and CVD outcomes. Covariates included sociodemographic characteristics, lifestyle risk factors, and medical and reproductive history. There were 3428 (3.4%) first CVD‐related hospital admissions and 418 (0.4%) deaths during a mean follow‐up time of 6.1 years for CVD hospitalization and 5.7 years for CVD mortality. Ever breastfeeding was associated with lower risk of CVD hospitalization (adjusted hazard ratio [95% CI]: 0.86 [0.78, 0.96]; P=0.005) and CVD mortality (adjusted hazard ratio [95% CI]: 0.66 [0.49, 0.89]; P=0.006) compared with never breastfeeding. Breastfeeding ≤12 months/child was significantly associated with lower risk of CVD hospitalization.

Conclusions

Breastfeeding is associated with lower maternal risk of CVD hospitalization and mortality in middle‐aged and older Australian women. Breastfeeding may offer long‐term maternal cardiovascular health benefits.

Sitting Time, Physical Activity, and Risk of Mortality in Adults

BACKGROUND

It is unclear what level of moderate to vigorous intensity physical activity (MVPA) offsets the health risks of sitting.

OBJECTIVES

The purpose of this study was to examine the joint and stratified associations of sitting and MVPA with all-cause and cardiovascular disease (CVD) mortality, and to estimate the theoretical effect of replacing sitting time with physical activity, standing, and sleep.

METHODS

A longitudinal analysis of the 45 and Up Study calculated the multivariable-adjusted hazard ratios (HRs) of sitting for each sitting-MVPA combination group and within MVPA strata. Isotemporal substitution modeling estimated the per-hour HR effects of replacing sitting.

RESULTS

A total of 8,689 deaths (1,644 due to CVD) occurred among 149,077 participants over an 8.9-year (median) follow-up. There was a statistically significant interaction between sitting and MVPA only for all-cause mortality. Sitting time was associated with both mortality outcomes in a nearly dose-response manner in the least active groups reporting <150 MVPA min/week. For example, among those reporting no MVPA, the all-cause mortality HR comparing the most sedentary (>8 h/day) to the least sedentary (<4 h/day) groups was 1.52 (95% confidence interval: 1.13 to 2.03). There was inconsistent and weak evidence for elevated CVD and all-cause mortality risks with more sitting among those meeting the lower (150 to 299 MVPA min/week) or upper (≥300 MVPA min/week) limits of the MVPA recommendation. Replacing sitting with walking and MVPA showed stronger associations among high sitters (>6 sitting h/day) where, for example, the per-hour CVD mortality HR for sitting replaced with vigorous activity was 0.36 (95% confidence interval: 0.17 to 0.74).

CONCLUSIONS

Sitting is associated with all-cause and CVD mortality risk among the least physically active adults; moderate-to-vigorous physical activity doses equivalent to meeting the current recommendations attenuate or effectively eliminate such associations.

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.

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.

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.