Introduction

Potentially preventable hospitalisation (PPH) has been adopted widely by international health systems as an indicator of the accessibility and overall effectiveness of primary care. The Assessing Preventable Hospitalisation InDicators (APHID) study will validate PPH as a measure of health system performance in Australia and Scotland. APHID will be the first large-scale study internationally to explore longitudinal relationships between primary care and PPH using detailed person-level information about health risk factors, health status and health service use.

Methods and analysis

APHID will create a new longitudinal data resource by linking together data from a large-scale cohort study (the 45 and Up Study) and prospective administrative data relating to use of general practitioner (GP) services, dispensing of pharmaceuticals, emergency department presentations, hospital admissions and deaths. We will use these linked person-level data to explore relationships between frequency, volume, nature and costs of primary care services, hospital admissions for PPH diagnoses, and health outcomes, and factors that confound and mediate these relationships. Using multilevel modelling techniques, we will quantify the contributions of person-level, geographic-level and service-level factors to variation in PPH rates, including socioeconomic status, country of birth, geographic remoteness, physical and mental health status, availability of GP and other services, and hospital characteristics.

Ethics and dissemination

Participants have consented to use of their questionnaire data and to data linkage. Ethical approval has been obtained for the study. Dissemination mechanisms include engagement of policy stakeholders through a reference group and policy forum, and production of summary reports for policy audiences in parallel with the scientific papers from the study.

Background

Large-scale population biobanks are critical for future research integrating epidemiology, genetic, biomarker and other factors. Little is known about the factors influencing participation in biobanks. This study compares the characteristics of biobank participants with those of non-participants, among members of an existing cohort study.

Methods

Individuals aged 45 and over participating in The 45 and Up Study and living ≤20km from central Wagga Wagga, New South Wales (NSW), Australia (rural/regional area) or ≤10km from central Parramatta, NSW (urban area) (n=2340) were invited to join a biobank, giving a blood sample and having additional measures taken, including height, weight, waist circumference, heart rate and blood pressure.

Results

The overall uptake of the invitation to participate was 33% (762/2340). The response rate was 41% (410/1002) among participants resident in the regional area, and 26% (352/1338) among those resident in the urban area. Characteristics associated with significantly decreased participation were being aged 80 and over versus being aged 45–64 (participation rate ratio: RR = 0.45, 95%CI 0.34-0.60), not being born in Australia versus being born in Australia (0.69, 0.59-0.81), having versus not having a major disability (0.54, 0.38-0.76), having full-time caregiving responsibilities versus not being a full-time carer (0.62, 0.42-0.93) and being a current smoker versus never having smoked (0.66, 0.50-0.89). Factors associated with increased participation were being in part-time work versus not being in paid work (1.24, 1.07-1.44) and having an annual household income of ≥$50,000 versus <$20,000 (1.50, 1.26-1.80).

Conclusions

A range of socio-economic, health and lifestyle factors are associated with biobank participation among members of an existing cohort study, with factors relating to health-seeking behaviours and access difficulties or time limitations being particularly important. If more widespread participation in biobanking is desired, particularly to ensure sufficient numbers among those most affected by these issues, specific efforts may be required to increase participation in certain groups such as migrants, the elderly, and those in poor health. Whilst caution should be exercised when generalising estimates of absolute prevalence from biobanks, estimates for many internal comparisons are likely to remain valid.

Background

Various options exist for collecting biospecimens and biomarkers from cohort study participants, and these have important logistic, resource and scientific implications. Evidence on how different collection methods affect participation and data quality is lacking. This parallel-design randomised trial, the Link-Up Study, involved blood sample donation and other data collection among participants in an existing cohort study, The 45 and Up Study. It aimed to investigate the relation of fasting status, reminder letters and data collection site to response rates, data quality and biospecimen yield.

Methods

Individuals aged 45 and over participating in The 45 and Up Study and living ≤20 km from central Wagga Wagga, NSW (regional area) or ≤10 km from central Parramatta, NSW (urban area) (n = 2340) were randomised, stratified by area of residence, to be invited to give a blood sample and additional data by attending either a clinic established specifically for the trial, with an appointment time (“dedicated clinic”, n = 1336) or an existing local commercial pathology centre (n = 1004). Within dedicated clinic groups, participants were randomised into fasting (n = 668) or non-fasting (n = 668) and, at the Parramatta pathology centre site, reminder letter after two weeks (n = 336) or no reminder (n = 334).

Results

Overall, 33% (762/2340) of invitees took part in the Link-Up Study; 41% (410/1002) among regional and 26% (352/1338) among urban-area residents (p < 0.0001). At the dedicated clinics, response rates were 38% (257/668) not fasting and 38% fasting (257/668) (participation rate ratio (RR) = 1.00, 95%CI 0.91-1.08, p = 0.98). The response rate was 22% among individuals randomised to attend the Parramatta pathology centre without a reminder and 23% among those sent a reminder letter (RR = 1.01, 0.93-1.09, p = 0.74). In total, the response rate was 38% (514/1336) at the dedicated clinics and 25% (248/1004) at the pathology centres (RR = 0.67, 0.56-0.78, p < 0.01); measures of height, weight and systolic and diastolic blood pressure did not vary materially between these groups, nor did the median number of aliquots of plasma, buffy coat and red cells collected.

Conclusions

Among cohort study participants, response rates for an additional study involving biospecimen collection, but not data quality or average biospecimen yield, were considerably higher at dedicated clinics than at existing commercial pathology sites.

Background

Available evidence suggests that smokers have a lower propensity than others to use primary care services. But previous studies have incorporated only limited adjustment for confounding and mediating factors such as income, access to services and health status. We used data from a large prospective cohort study (the 45 and Up Study), linked to administrative claims data, to quantify the relationship between smoking status and use of primary care services, including specific preventive services, in a contemporary Australian population.

Methods

Baseline questionnaire data from the 45 and Up Study were linked to administrative claims (Medicare) data for the 12-month period following study entry. The main outcome measures were Medicare benefit claimed for unreferred services, out-of-pocket costs (OOPC) paid, and claims for specific preventive services (immunisations, health assessments, chronic disease management services, PSA tests and Pap smears). Rate ratios with 95% confidence intervals were estimated using a hierarchical series of models, adjusted for predisposing, access- and health-related factors. Separate hurdle (two part) regression models were constructed for Medicare benefit and OOPC. Poisson models with robust error variance were used to model use of each specific preventive service.

Results

Participants included 254,382 people aged 45 years and over of whom 7.3% were current smokers. After adjustment for predisposing, access- and health-related factors, current smokers were very slightly less likely to have claimed Medicare benefit than never smokers. Among those who claimed benefit, current smokers claimed similar total benefit, but recent quitters claimed significantly greater benefit, compared to never-smokers. Current smokers were around 10% less likely than never smokers to have paid any OOPC. Current smokers were 15-20% less likely than never smokers to use immunisations, Pap smears and prostate specific antigen tests.

Conclusions

Current smokers were less likely than others to use primary care services that incurred out of pocket costs, and specific preventive services. This was independent of a wide range of predisposing, access- and health-related factors, suggesting that smokers have a lower propensity to seek health care. Smokers may be missing out on preventive services from which they would differentially benefit.

Background

Heart disease is a leading cause of the gap in burden of disease between Aboriginal and non-Aboriginal Australians. Our study investigated short- and long-term mortality after admission for Aboriginal and non-Aboriginal people admitted with acute myocardial infarction (AMI) to public hospitals in New South Wales, Australia, and examined the impact of the hospital of admission on outcomes.

Methods

Admission records were linked to mortality records for 60047 patients aged 25–84 years admitted with a diagnosis of AMI between July 2001 and December 2008. Multilevel logistic regression was used to estimate adjusted odds ratios (AOR) for 30- and 365-day all-cause mortality.

Results

Aboriginal patients admitted with an AMI were younger than non-Aboriginal patients, and more likely to be admitted to lower volume, remote hospitals without on-site angiography. Adjusting for age, sex, year and hospital, Aboriginal patients had a similar 30-day mortality risk to non-Aboriginal patients (AOR: 1.07; 95% CI 0.83-1.37) but a higher risk of dying within 365 days (AOR: 1.34; 95% CI 1.10-1.63). The latter difference did not persist after adjustment for comorbid conditions (AOR: 1.12; 95% CI 0.91-1.38). Patients admitted to more remote hospitals, those with lower patient volume and those without on-site angiography had increased risk of short and long-term mortality regardless of Aboriginal status.

Conclusions

Improving access to larger hospitals and those with specialist cardiac facilities could improve outcomes following AMI for all patients. However, major efforts to boost primary and secondary prevention of AMI are required to reduce the mortality gap between Aboriginal and non-Aboriginal people.

OBJECTIVE

To examine the effect of childbearing and maternal breastfeeding on a woman's subsequent risk of developing type 2 diabetes.

RESEARCH DESIGN AND METHODS

Using information on parity, breastfeeding, and diabetes collected from 52,731 women recruited into a cohort study, we estimated the risk of type 2 diabetes using multivariate logistic regression.

RESULTS

A total of 3,160 (6.0%) women were classified as having type 2 diabetes. Overall, nulliparous and parous women had a similar risk of diabetes. Among parous women, there was a 14% (95% CI 10–18%, P < 0.001) reduced likelihood of diabetes per year of breastfeeding. Compared to nulliparous women, parous women who did not breastfeed had a greater risk of diabetes (odds ratio 1.48, 95% CI 1.26–1.73, P < 0.001), whereas for women breastfeeding, the risk was not significantly increased.

CONCLUSIONS

Compared with nulliparous women, childbearing women who do not breastfeed have about a 50% increased risk of type 2 diabetes in later life. Breastfeeding substantially reduces this excess risk.

Background

In Australia, the Home and Community Care (HACC) program provides services in the community to frail elderly living at home and their carers. Surprisingly little is known about the health of people who use these services. In this study we sought to describe health-related factors associated with use of HACC services, and to identify potential opportunities for targeting preventive services to those at high risk.

Methods

We obtained questionnaire data from the 45 and Up Study for 103,041 men and women aged 45 years and over, sampled from the general population of New South Wales, Australia in 2006-2007, and linked this with administrative data about HACC service use. We compared the characteristics of HACC clients and non-clients according to a range of variables from the 45 and Up Study questionnaire, and estimated crude and adjusted relative risks for HACC use with generalized linear models.

Results

4,978 (4.8%) participants used HACC services in the year prior to completing the questionnaire. Increasing age, female sex, lower pre-tax household income, not having a partner, not being in paid work, Indigenous background and living in a regional or remote location were strongly associated with HACC use. Overseas-born people and those speaking languages other than English at home were significantly less likely to use HACC services. People who were underweight, obese, sedentary, who reported falling in the past year, who were current smokers, or who ate little fruit or vegetables were significantly more likely to use HACC services. HACC service use increased with decreasing levels of physical functioning, higher levels of psychological distress, and poorer self-ratings of health, eyesight and memory. HACC clients were more likely to report chronic health conditions, in particular diabetes, stroke, Parkinson's disease, anxiety and depression, cancer, heart attack or angina, blood clotting problems, asthma and osteoarthritis.

Conclusions

HACC clients have high rates of modifiable lifestyle risk factors and health conditions that are amenable to primary and secondary prevention, presenting the potential for implementing preventive health care programs in the HACC service setting.

Background

There is little empirical evidence regarding the generalisability of relative risk estimates from studies which have relatively low response rates or are of limited representativeness. The aim of this study was to investigate variation in exposure-outcome relationships in studies of the same population with different response rates and designs by comparing estimates from the 45 and Up Study, a population-based cohort study (self-administered postal questionnaire, response rate 18%), and the New South Wales Population Health Survey (PHS) (computer-assisted telephone interview, response rate ~60%).

Methods

Logistic regression analysis of questionnaire data from 45 and Up Study participants (n = 101,812) and 2006/2007 PHS participants (n = 14,796) was used to calculate prevalence estimates and odds ratios (ORs) for comparable variables, adjusting for age, sex and remoteness. ORs were compared using Wald tests modelling each study separately, with and without sampling weights.

Results

Prevalence of some outcomes (smoking, private health insurance, diabetes, hypertension, asthma) varied between the two studies. For highly comparable questionnaire items, exposure-outcome relationship patterns were almost identical between the studies and ORs for eight of the ten relationships examined did not differ significantly. For questionnaire items that were only moderately comparable, the nature of the observed relationships did not differ materially between the two studies, although many ORs differed significantly.

Conclusions

These findings show that for a broad range of risk factors, two studies of the same population with varying response rate, sampling frame and mode of questionnaire administration yielded consistent estimates of exposure-outcome relationships. However, ORs varied between the studies where they did not use identical questionnaire items.

Background

Better communication is often suggested as fundamental to increasing the use of research evidence in policy, but little is known about how researchers and policy makers work together or about barriers to exchange. This study explored the views and practice of policy makers and researchers regarding the use of evidence in policy, including: (i) current use of research to inform policy; (ii) dissemination of and access to research findings for policy; (iii) communication and exchange between researchers and policy makers; and (iv) incentives for increasing the use of research in policy.

Methods

Separate but similar interview schedules were developed for policy makers and researchers. Senior policy makers from NSW Health and senior researchers from public health and health service research groups in NSW were invited to participate. Consenting participants were interviewed by an independent research company.

Results

Thirty eight policy makers (79% response rate) and 41 researchers (82% response rate) completed interviews. Policy makers reported rarely using research to inform policy agendas or to evaluate the impact of policy; research was used more commonly to inform policy content. Most researchers reported that their research had informed local policy, mainly by increasing awareness of an issue. Policy makers reported difficulty in accessing useful research syntheses, and only a third of researchers reported developing targeted strategies to inform policy makers of their findings. Both policy makers and researchers wanted more exchange and saw this as important for increasing the use of research evidence in policy; however, both groups reported a high level of involvement by policy makers in research.

Conclusion

Policy makers and researchers recognise the potential of research to contribute to policy and are making significant attempts to integrate research into the policy process. These findings suggest four strategies to assist in increasing the use of research in policy: making research findings more accessible to policy makers; increasing opportunities for interaction between policy makers and researchers; addressing structural barriers such as research receptivity in policy agencies and a lack of incentives for academics to link with policy; and increasing the relevance of research to policy.

Correction to Banks E, Jorm L, Lujic S, Rogers K. Health, ageing and private health insurance: baseline results from the 45 and Up Study cohort. ANZ Health Policy 2009; 6: 16.

Background

This study investigates the relationships between health and lifestyle factors, age and private health insurance (PHI) in a large Australian population-based cohort study of people aged 45 years and over; the 45 and Up Study. Unlike previous Australian analyses of relationships between health, lifestyle and PHI, it incorporates adjustment for multiple confounding socioeconomic and demographic factors. Recruitment into the 45 and Up Study began in February 2006 and these analyses relate to the first 103,042 participants who joined the study prior to July 2008.

Results

The proportion with PHI decreased with increasing age. The factors independently and most strongly associated with having PHI were: higher income; higher educational attainment; not holding a health care concession card; not being of Aboriginal/Torres Strait Islander origin; being a non-smoker; high levels of self-rated health and functional capacity; and low levels of psychological distress. These factors increased the probability of having PHI by 16% to 125%, compared to individuals without these characteristics. PHI coverage was significantly but only marginally higher in people reporting non-melanoma skin cancer (adjusted RR 1.04, 95%CI 1.03–1.05), prostate cancer (1.09, 1.06–1.11) or an enlarged prostate (1.07, 1.06–1.09), those reporting a family history of a range of conditions (e.g. 1.02, 1.01–1.03 for a family history of heart disease; 1.03, 1.02–1.04 for a family history of prostate cancer) and lower in people reporting diabetes (0.92, 0.91–0.94) or stroke (0.91, 0.88–0.94), compared to people who did not have these medical or family histories. PHI was higher in those reporting certain surgical procedures with RRs (95%CI) of 1.12 (1.09–1.15) for hip replacement, 1.10 (1.08–1.13) for knee replacement and 1.12 (1.09–1.15) for prostatectomy, compared to those not reporting these interventions.

Conclusion

Compared to the rest of the study population, those with PHI are richer, better educated, more health conscious, in better health and more likely to use certain discretionary health services. Hence, PHI use is generally highest among those with the least need for health care. Whether or not people have PHI is more strongly associated with demographic and lifestyle factors than with health status.

Background

At present, we have very limited ability to compare public health activity across jurisdictions and countries, or even to ascertain differences in what is considered to be a public health activity. Existing standardised health classifications do not capture important dimensions of public health, which include its functions, the methods and interventions used to achieve these, the health issues and determinants of health that public health activities address, the resources and infrastructure they use, and the settings in which they occur. A classification that describes these dimensions will promote consistency in collecting and reporting information about public health programs, expenditure, workforce and performance. This paper describes the development of an initial version of such a classification.

Methods

We used open-source Protégé software and published procedures to construct an ontology of public health, which forms the basis of the classification. We reviewed existing definitions of public health, descriptions of public health functions and classifications to develop the scope, domain, and multidimensional class structure of the ontology. These were then refined through a series of consultations with public health experts from across Australia, culminating in an initial classification framework.

Results

The public health classification consists of six top-level classes: public health 'Functions'; 'Health Issues'; 'Determinants of Health'; 'Settings'; 'Methods' of intervention; and 'Resources and Infrastructure'. Existing classifications (such as the international classifications of diseases, disability and functioning and external causes of injuries) can be used to further classify large parts of the classes 'Health Issues', 'Settings' and 'Resources and Infrastructure', while new subclass structures are proposed for the classes of public health 'Functions', 'Determinants of Health' and 'Interventions'.

Conclusion

The public health classification captures the important dimensions of public health activity. It will facilitate the organisation of information so that it can be used to address questions relating to any of these dimensions, either singly or in combination. The authors encourage readers to use the classification, and to suggest improvements.

Background

To help improve incident preparedness this study assessed socio-demographic and socio-economic predictors of perceived risk of terrorism within Australia and willingness to comply with public safety directives during such incidents.

Methods

The terrorism perception question module was incorporated into the New South Wales Population Health Survey and was completed by a representative sample of 2,081 respondents in early 2007. Responses were weighted against the New South Wales population.

Results

Multivariate analyses indicated that those with no formal educational qualifications were significantly more likely (OR = 2.10, 95%CI:1.32–3.35, p < 0.001) to think that a terrorist attack is very or extremely likely to occur in Australia and also more likely (OR = 3.62, 95%CI:2.25–5.83, p < 0.001) to be very or extremely concerned that they or a family member would be directly affected, compared to those with a university-level qualification. Speaking a language other than English at home predicted high concern (very/extremely) that self or family would be directly affected (OR = 3.02, 95%CI:2.02–4.53, p < 0.001) and was the strongest predictor of having made associated changes in living (OR = 3.27, 95%CI:2.17–4.93, p < 0.001). Being female predicted willingness to evacuate from public facilities. Speaking a language other than English at home predicted low willingness to evacuate.

Conclusion

Low education level is a risk factor for high terrorism risk perception and concerns regarding potential impacts. The pattern of concern and response among those of migrant background may reflect secondary social impacts associated with heightened community threat, rather than the direct threat of terrorism itself. These findings highlight the need for terrorism risk communication and related strategies to address the specific concerns of these sub-groups as a critical underpinning of population-level preparedness.

This research assessed factors associated with willingness to comply with vaccination, isolation, and face mask wearing during an anticipated influenza pandemic. Data were collected from 2081 adults (16+) using a module of questions incorporated into the NSW Health Adult Population Health Survey. High levels of willingness to comply were reported with 73% either very or extremely willing to receive vaccination, 67% willing to isolate themselves, 58% willing to wear a face mask, and 48% willing to comply with all three behaviors. Further analysis indicated concern for self and family and higher levels of education were associated with high levels of willingness to comply. Younger people (16–24) were the least willing to comply; especially with wearing a face mask. Those with children reported higher levels of willingness to receive vaccination, and respondents who speak a language other than English at home were less willing to isolate themselves or comply with all behaviors. These findings provide a baseline measure of anticipated public compliance with key public health behaviors in the event of an influenza pandemic in the Australian population, and help to identify groups that may be more resistant to individual measures and may require additional attention in terms of risk communication strategies or health education.

Background

Baseline data is necessary for monitoring how a population perceives the threat of pandemic influenza, and perceives how it would behave in the event of pandemic influenza. Our aim was to develop a module of questions for use in telephone health surveys on perceptions of threat of pandemic influenza, and on preparedness to comply with specific public health behaviours in the event of pandemic influenza.

Methods

A module of questions was developed and field tested on 192 adults using the New South Wales Department of Health's in-house Computer Assisted Telephone Interviewing (CATI) facility. The questions were then modified and re field tested on 202 adults. The module was then incorporated into the New South Wales Population Health Survey in the first quarter of 2007. A representative sample of 2,081 adults completed the module. Their responses were weighted against the state population.

Results

The reliability of the questions was acceptable with kappa ranging between 0.25 and 0.51. Overall 14.9% of the state population thought pandemic influenza was very or extremely likely to occur; 45.5% were very or extremely concerned that they or their family would be affected by pandemic influenza if it occurred; and 23.8% had made some level of change to the way they live their life because of the possibility of pandemic influenza. In the event of pandemic influenza, the majority of the population were willing to: be vaccinated (75.4%), be isolated (70.2%), and wear a face mask (59.9%). People with higher levels of threat perception are significantly more likely to be willing to comply with specific public health behaviours.

Conclusion

While only 14.9% of the state population thought pandemic influenza was very or extremely likely to occur, a significantly higher proportion were concerned for self and family should a pandemic actually occur. The baseline data collected in this survey will be useful for monitoring changes over time in the population's perceptions of threat, and preparedness to comply with specific public health behaviours.

Background

Australian epidemiologists have recognised that lay readers have difficulty understanding statistical graphs in reports on population health. This study aimed to provide evidence for graph design improvements that increase comprehension by non-experts.

Methods

This was a double-blind, randomised, controlled trial of graph-design interventions, conducted as a postal survey. Control and intervention participants were randomly selected from telephone directories of health system employees. Eligible participants were on duty at the listed location during the study period. Controls received a booklet of 12 graphs from original publications, and intervention participants received a booklet of the same graphs with design modifications. A questionnaire with 39 interpretation tasks was included with the booklet. Interventions were assessed using the ratio of the prevalence of correct responses given by the intervention group to those given by the control group for each task.

Results

The response rate from 543 eligible participants (261 intervention and 282 control) was 67%. The prevalence of correct answers in the control group ranged from 13% for a task requiring knowledge of an acronym to 97% for a task identifying the largest category in a pie chart. Interventions producing the greatest improvement in comprehension were: changing a pie chart to a bar graph (3.6-fold increase in correct point reading), changing the y axis of a graph so that the upward direction represented an increase (2.9-fold increase in correct judgement of trend direction), a footnote to explain an acronym (2.5-fold increase in knowledge of the acronym), and matching the y axis range of two adjacent graphs (two-fold increase in correct comparison of the relative difference in prevalence between two population subgroups).

Conclusion

Profound population health messages can be lost through use of overly technical language and unfamiliar statistical measures. In our study, most participants did not understand age standardisation and confidence intervals. Inventive approaches are required to address this problem.

Background

In a climate of concern over bioterrorism threats and emergent diseases, public health authorities are trialling more timely surveillance systems. The 2003 Rugby World Cup (RWC) provided an opportunity to test the viability of a near real-time syndromic surveillance system in metropolitan Sydney, Australia. We describe the development and early results of this largely automated system that used data routinely collected in Emergency Departments (EDs).

Methods

Twelve of 49 EDs in the Sydney metropolitan area automatically transmitted surveillance data from their existing information systems to a central database in near real-time. Information captured for each ED visit included patient demographic details, presenting problem and nursing assessment entered as free-text at triage time, physician-assigned provisional diagnosis codes, and status at departure from the ED. Both diagnoses from the EDs and triage text were used to assign syndrome categories. The text information was automatically classified into one or more of 26 syndrome categories using automated "naïve Bayes" text categorisation techniques. Automated processes were used to analyse both diagnosis and free text-based syndrome data and to produce web-based statistical summaries for daily review. An adjusted cumulative sum (cusum) was used to assess the statistical significance of trends.

Results

During the RWC the system did not identify any major public health threats associated with the tournament, mass gatherings or the influx of visitors. This was consistent with evidence from other sources, although two known outbreaks were already in progress before the tournament. Limited baseline in early monitoring prevented the system from automatically identifying these ongoing outbreaks. Data capture was invisible to clinical staff in EDs and did not add to their workload.

Conclusion

We have demonstrated the feasibility and potential utility of syndromic surveillance using routinely collected data from ED information systems. Key features of our system are its nil impact on clinical staff, and its use of statistical methods to assign syndrome categories based on clinical free text information. The system is ongoing, and has expanded to cover 30 EDs. Results of formal evaluations of both the technical efficiency and the public health impacts of the system will be described subsequently.