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Purpose: To compare the relationship of the eight SF-36 v1 subscale scores to the summary scores of the PCS and MCS derived from two different scoring algorithms: one based on the original scoring method (Ware, Kosinski and Keller, SF-36 physical and mental health summary scales: a users manual. The Health Institute, New England Medical Centre, Boston, MA, 1994); and the other based on scoring algorithms that use parameters derived from structural equation modelling. Further, to provide SF-12 scoring algorithms similarly based on structural equation modelling. Methods: The Australian Bureau of Statistics 1995 Australian National Health Survey dataset was used as the basis for the production of coefficients. There were 18,141 observations with no missing data for all eight SF-36 subscales following imputation of data items, and 17,479 observations with no missing data for the SF-12 data items. Data were analysed in LISREL V8.71. Structural equation models were fit to the data in confirmatory factor analyses producing weighted least squares estimates, which overcame anomalies found in the traditional orthogonal scoring methods. Results: Models with acceptable fits to the hypothesised factor structure were produced, generating factor score weighting coefficients for use with the SF-36 and SF-12 data items, to produce PCS and MCS summary scores consistent with their underlying subscale scores. Conclusions: The coefficients generated will score the SF-36 summary PCS and MCS in a manner consistent with their subscales. Previous Australian studies using version 1 of SF-36 or SF-12 can re-score their summary scores using these coefficients. [ABSTRACT FROM AUTHOR]

The rail industry in Australia screens workers for probable obstructive sleep apnea (OSA) due to known safety risks. However, existing criteria to trigger screening only identify a small proportion of workers with OSA. The current study sought to examine the relationship between OSA risk and rail incidents in real-world data from Australian train drivers, and conducted a proof of concept analysis to determine whether more conservative screening criteria are justified. Health assessment (2016–2018) and subsequent rail incident data (2016–2020) were collected from two passenger rail service providers. Predictors included OSA status (confirmed no OSA with a sleep study, controlled OSA, unknown OSA [no recorded sleep assessment data] and confirmed OSA with no indication of treatment); OSA risk according to the current Standard, and OSA risk according to more conservative clinical markers (BMI threshold and cardiometabolic burden). Coded rail safety incidents involving the train driver were included. Data were analysed using zero-inflated negative binomial models to account for over-dispersion with high 0 counts, and rail safety incidents are reported using Incidence Risk Ratios (IRRs). A total of 751 train drivers, typically middle-aged, overweight to obese and mostly men, were included in analyses. There were 43 (5.7%) drivers with confirmed OSA, 62 (8.2%) with controlled OSA, 13 (1.7%) with confirmed no OSA and 633 (84.4%) drivers with unknown OSA. Of the 633 train drivers with unknown OSA status, 21 (3.3%) met 'at risk' criteria for OSA according to the Standard, and incidents were 61% greater (IRR: 1.61, 95% Confidence Interval (CI) 1.02–2.56) in the years following their health assessment compared to drivers who did not meet 'at risk' criteria. A more conservative OSA risk status using lower BMI threshold and cardiometabolic burden identified an additional 30 'at risk' train drivers who had 46% greater incidents compared to drivers who did not meet risk criteria (IRR (95% CI) 1.46 (1.00–2.13)). Our more conservative OSA risk criteria identified more workers, with greater prospective incidents. These findings suggest that existing validated tools could be considered in future iterations of the Standard in order to more sensitively screen for OSA. [ABSTRACT FROM AUTHOR]

Background: On-call research and guidance materials typically focus on 'traditional' on-call work (e.g., emergency services, healthcare). However, given the increasing prevalence of non-standard employment arrangements (e.g., gig work and casualisation), it is likely that a proportion of individuals who describe themselves as being on-call are not included in current on-call literature. This study therefore aimed to describe the current sociodemographic and work characteristics of Australian on-call workers. Methods: A survey of 2044 adults assessed sociodemographic and work arrangements. Of this population, 1057 individuals were workforce participants, who were asked to provide information regarding any on-call work they performed over the last three months, occupation type, weekly work hours, and the presence or absence of non-standard work conditions. Results: Of respondents who were working, 45.5% reported working at least one day on-call in the previous month. There was a high prevalence of on-call work in younger respondents (63.1% of participants aged 18–24 years), and those who worked multiple jobs and more weekly work hours. Additionally, high prevalence rates of on-call work were reported by machinery operators, drivers, community and personal service workers, sales workers, and high-level managers. Conclusions: These data suggest that on-call work is more prevalent than previously recorded and is likely to refer to a broad set of employment arrangements. Current classification systems may therefore be inadequate for population-level research. A taxonomy for the classification of on-call work is proposed, incorporating traditional on-call work, gig economy work, relief, or unscheduled work, and out of hours work. [ABSTRACT FROM AUTHOR]

Objectives: To examine the influence of obstructive sleep apnea (OSA) on nocturia, controlling for their shared co-morbidities, in a population of community-based middle aged to elderly men.Methods: Participants were drawn from a randomly selected, community-dwelling cohort of men in Adelaide, Australia. Seven hundred and eight men (mean: 60.7 [41.6-88.2] years) who had polysomnography recordings, complete lower urinary tract symptoms (LUTS) measures (International Prostate Symptom Score), without prostate or bladder cancer and/or surgery, and no prior OSA diagnosis were selected. Nocturia was defined as ≥2 voids per main sleep. Unadjusted and multi-adjusted regression models of nocturia were combined with OSA, wake after sleep onset, total sleep period, excessive daytime sleepiness (EDS), and sleep quality (SQ) data, together with socio-demographic, and health-related factors.Results: Men with nocturia were found to have higher levels of OSA (32.2% [n = 65]), wake after sleep onset time (97.2 ± 52.9 minutes), sleep period (467.3 ± 58.4 minutes), EDS (18.2% [n = 37]), and poorer SQ (54.3% [n = 108]). Multiple-adjusted models showed nocturia was positively associated with OSA (odds ratio:1.64, 95% confidence interval [1.03,2.55]), EDS (1.72 [1.01,2.93]), and poorer SQ (1.65 [1.10,2.48]). Including other storage and voiding LUTS attenuated the effect of OSA and strengthened the association with EDS (2.44 [1.45,4.10] and 2.24 [1.19,4.22]), whereas voiding LUTS also strengthened the association with poorer SQ (2.61 [1.63,4.17]). Men with increasing nocturic frequency spent less time in N2 and rapid eye movement stage sleep.Conclusion: Nocturia is strongly associated with OSA in community-based men. Nocturia also reduces sleep efficiency/SQ, N2, and rapid eye movement sleep time, while increasing EDS. Other LUTS increase EDS through non-OSA means. [ABSTRACT FROM AUTHOR]

Objective. To obtain prevalence estimates of clinical features of obstructive sleep apnoea (OSA) and identify the dimensions of the public health problem requiring further investigation for an Australian population. Methods. The South Australian Health Omnibus Survey is an annual representative population survey of South Australians aged ≥15 years, conducted via interviewer-administered questionnaire. In 2009, 3007 participants were asked the STOP-BANG instrument measure of obstructive sleep apnoea risk, which includes symptoms of loud snoring, frequent tiredness during daytime, observed apnoea, and high blood pressure (STOP), and measured body mass index, age, neck circumference and gender (BANG). Three or more positive response categorises a person at high risk for OSA. Results. Snoring was reported by 49.7% of adults. Tiredness after sleep more than 3 -- 4 times per week was reported by 24.8%, and during wake-time by 27.7% of adults, with 8.8% reporting having fallen asleep while driving. Over half of the surveyed men (57.1%, n = 566) and 19.3% (n = 269) of the women were classified at high-risk of OSA with the STOP-BANG measure. In multivariable models, high risk was associated with less education, lower income, and residence in a regional rather than metropolitan area. Conclusion. The high prevalence of adults at risk for OSA suggests that the capacity currently available within the healthcare system to investigate and diagnose OSA is likely to be inadequate, particularly outside urban areas. This highlights an important public health problem that requires further detailed study and trials of new models of care. [ABSTRACT FROM AUTHOR]

Objective: The Australian Pharmaceutical Benefits Scheme (PBS) expanded the criteria for eligibility for subsidised lipid-lowering therapy (LLT) in 2006. The aim of this study was to determine the use of LLT in a representative Australian population in relation to cardiovascular disease (CVD) risk, and the effectiveness of the therapy in meeting target levels. Design: Cross-sectional biomedical study with telephone interviews, questionnaires, clinical measurements, and PBS dispensing data. Subjects: Representative population sample of 4060 urban adults aged ≥ 18 years attending for the biomedical examination in 2001. Results: Of the 406 who qualified for PBS-subsidised LLT at that time, only 88 (21.5%) were actually on LLT. National Heart Foundation of Australia (NHF) recommended low-density lipoprotein cholesterol (LDL-C) levels of < 2.5 mmol/L were recorded in only 13% (528) of the population, and in 46.8% of those on LLT. Of those on LLT, 76% had total cholesterol < 5.5 mmol/L, but over 80% had total cholesterol levels above NHF-recommended levels of 4.0 mmol/L. Of the 842 classified at the highest CVD risk, only 26% were using LLT. Those aged > 60 years and on low incomes were significantly more likely to use LLT. The new PBS criteria will expand eligibility to include nearly 20% of adults. Conclusions: The majority of people at high risk of CVD were not receiving LLT, and LLT is not being used to its full effectiveness. People with low incomes or on government benefits or pensions were not less likely to use LLT than others under the PBS scheme. Whether higher copayments for those on low incomes who do not qualify for concessional payments is a significant barrier to LLT use needs further research. [ABSTRACT FROM AUTHOR]

Objective. To understand what impact hospital inpatient occupancy levels have on patient throughput by analysing one hospital's occupancy levels and the rate of patient discharge. Methods. A four-stage model was fit to hospital admission and separation data and used to analyse the per-capita separation rate according to the patient load and the impact of hospital over-census actions. Results. Per-capita separation rates are significantly higher on days when the hospital declares an over-census due to emergency department crowding. Per-capita separation rates are also higher or lower on days with 8-10% higher or lower patient loads, respectively, but the response is not nearly as strong as the response to an over-census declaration, and is limited to patients with an elapsed stay of 10 days or more. Within the medical division there is an increase in per-capita separation rates on over-census days, but no significant difference in per-capita release rates for different patient loads. Within the surgical division there is no significant difference in per-capita separation rates on over-census days compared with other days, but the patient load does make a significant difference. Conclusion. Staff do discharge a greater proportion of long-stay patients when the hospital is experiencing high demand and a lower proportion when occupancy is low, but the reasons driving those changes remains unclear. What is known about the topic? The evidence regarding safe and efficient levels of hospital occupancy is limited. There is minimal empirical evidence that confirms the relationship between occupancy and discharge rates. What does the paper add? Per-capita separation rates increase strongly on over-census days. The hospital increases per-capita separation rates on days of high occupancy and reduces it on days of low occupancy, mostly for long-stay patients with over 10 days of elapsed stay. The response to high occupancy is not as strong as the response to over-census. The medical division responds strongly to the over-census and the surgical division does not. The surgical division responds more to occupancy levels within its own division than does the medical division. What are the implications for practitioners? The implementation of over-census-type responses to periods of high occupancy may result in increased per-capita separation rate. Using mathematical analysis to understand patient load on per capita separation is important to create a better understanding of health service delivery, thereby aiding hospital managers, and has the potential to guide system improvement. The clinical drivers for these changes and the service design implications require further investigation. [ABSTRACT FROM AUTHOR]

Background: Chronic insomnia is a highly prevalent disorder, with ten to thirty percent of Australian adults reporting chronic difficulties falling asleep and/or staying asleep such that it causes significant daytime impairment. Current Australian general practice guidelines recommend cognitive behavioural therapy for insomnia (CBTi) as first line treatment for insomnia, however research suggests that most general practice consultations for insomnia result in a prescription for hypnotic or sedative medicines. Although the first point of contact for patients experiencing symptoms of insomnia is often general practice, little is known about the current role, experiences and capacity of Australian general practitioners to manage insomnia. This study aimed to address that gap by exploring the attitudes and opinions of general practitioners regarding insomnia management, to inform the development and implementation of new models of best practice insomnia care within general practice. Methods: A descriptive, pragmatic qualitative study. Purposive sampling was used to recruit practising Australian general practitioners, varying in age, years of experience and geographic location. Semi-structured interviews were conducted, and data analysed using thematic analysis. Results: Twenty-eight general practitioners participated in the study. Three major themes were identified: 1) Responsibility for insomnia care; 2) Complexities in managing insomnia; and 3) Navigating treatment pathways. Whilst general practitioners readily accepted responsibility for the management of insomnia, provision of care was often demanding and difficult within the funding and time constraints of general practice. Patients presenting with comorbid mental health conditions and insomnia, and decision-making regarding long-term use of benzodiazepines presented challenges for general practitioners. Whilst general practitioners confidently provided sleep hygiene education to patients, their knowledge and experience of CBTi, and access and understanding of specialised referral pathways for insomnia was limited. Conclusions: General practitioners report that whilst assessing and managing insomnia can be demanding, it is an integral part of general practice. Insomnia presents complexities for general practitioners. Greater clarity about funding options, targeted education about effective insomnia treatments, and referral pathways to specialist services, such as benzodiazepine withdrawal support and psychologists, would benefit insomnia management within general practice. [ABSTRACT FROM AUTHOR]

Introduction: Insomnia and obstructive sleep apnoea (OSA) are the two most prevalent sleep disorders, and frequently co-occur (COMISA) in sleep clinic samples. However, few studies have investigated the prevalence or associations of COMISA in the general population.Methods: We used population-based online survey data from 2044 Australian adults. The prevalence and associations of insomnia, OSA and COMISA were investigated according to symptom-level, and disorder-level definitions. Insomnia was defined according to chronic difficulties initiating and/or maintaining sleep (DIMS; symptom-level), and ICSD-3 chronic insomnia disorder (disorder-level). OSA was defined according to self-reported frequent obstructive events, snoring or doctor-diagnosed OSA (symptom-level), and doctor-diagnosed OSA (disorder-level). COMISA was defined if both conditions were met (for symptom-level, and disorder-level threshold). Associations with other conditions, and general health were investigated with Poisson regression analyses.Results: Chronic insomnia occurred more frequently among participants with doctor-diagnosed OSA (22.3%), compared to those without (14.3%, p = 0.010). Doctor-diagnosed OSA was more common among participants with chronic insomnia (10.2%) compared to those without (6.2%; p = 0.010). DIMS also occurred more frequently among participants with OSA symptoms (66.6%), compared to those without (47.2%; p < 0.001). Participants with symptom-level COMISA reported increased co-morbid conditions, and worse general health compared to participants with symptoms of insomnia-alone, OSA-alone, or neither insomnia/OSA.Conclusions: COMISA at symptom and disorder level were common and associated with increased medical and psychiatric co-morbidity, as well as poor general health. More investigation is required to understand bi-directional associations underpinning the high co-morbidity, and improve diagnostic and treatment approaches for COMISA to reduce associated morbidity. [ABSTRACT FROM AUTHOR]

Background frailty is a dynamic condition for which a range of interventions are available. Health state utilities are values that represent the strength of an individual's preference for specific health states, and are used in economic evaluation. This is a topic yet to be examined in detail for frailty. Likewise, little has been reported on minimally important difference (MID), the extent of change in frailty status that individuals consider to be important. Objectives to examine the relationship between frailty status, for both the frailty phenotype (FP) and frailty index (FI), and utility (preference-based health state), and to determine a MID for both frailty measures. Design and setting population-based cohort of community-dwelling Australians. Participant in total, 874 adults aged ≥65 years (54% female), mean age 74.4 (6.2) years. Measurements frailty was measured using the FP and FI. Utilities were calculated using the short-form 6D health survey, with Australian and UK weighting applied. MID was calculated cross-sectionally. Results for both the FP and FI, frailty was significantly statistically associated (P  < 0.001) with lower utility in an adjusted analysis using both Australian and UK weighting. Between-person MID for the FP was identified as 0.59 [standard deviation (SD) 0.31] (anchor-based) and 0.59 (distribution-based), whereas for the FI, MID was 0.11 (SD 0.05) (anchor-based) and 0.07 (distribution-based). Conclusions frailty is significantly associated with lower preference-based health state utility. Frailty MID can be used to inform design of clinical trials and economic evaluations, as well as providing useful clinical information on frailty differences that patients consider important. [ABSTRACT FROM AUTHOR]

Background: Frailty and sarcopenia are age-related conditions with shared features and are both associated with adverse health outcomes. Relatively little is known about outcomes of these conditions in combination. The aim of this study was to examine the predictive ability of combined frailty and sarcopenia classification on mortality.Methods: Frailty was measured in 716 community-dwelling adults aged ≥65 years from the North West Adelaide Health Study (mean age 74.1(6.1) years, 55.5 % female) using the frailty phenotype (FP) and sarcopenia using the revised consensus definition from the European Working Group on Sarcopenia. Participants were classified as: neither frail nor sarcopenic, frail-only, sarcopenic-only, or both frail and sarcopenic. All participants had a minimum of 10 years of mortality follow-up.Results: We identified 2.8 % of participants as both frail and sarcopenic, 15.5 % as frail-only, and 3.5 % as sarcopenic-only. Classification as both frail and sarcopenic, in a multivariable model, resulted in significantly elevated mortality risk (HR = 3.52, p < .001), which was over three times that of those neither frail nor sarcopenic. Frail-only was also a significant mortality predictor (HR = 2.03, p = .001), while classification as sarcopenic-only was not a significant predictor of mortality (HR = 1.65, p = .141). There was no significant difference in severity of frailty (mean number of characteristics) or grip strength between frail-only and those with both conditions when stratified by sex.Conclusions: Individuals identified as frail would benefit from screening and assessment for sarcopenia, and vice versa for those identified as sarcopenic, as the mortality risk for individuals with these conditions in combination is nearly double that of each separately. [ABSTRACT FROM AUTHOR]

Aims: National 30‐day mortality and readmission rates after heart failure (HF) hospitalisations are a focus of US policy intervention and yet have rarely been assessed in other comparable countries. We examined the frequency, trends and institutional variation in 30‐day mortality and unplanned readmission rates after HF hospitalisations in Australia and New Zealand. Methods and results: We included patients >18 years hospitalised with HF at all public and most private hospitals from 2010–15. The primary outcomes were the frequencies of 30‐day mortality and unplanned readmissions, and the institutional risk‐standardised mortality rate (RSMR) and readmission rate (RSRR) evaluated using separate cohorts. The mortality cohort included 153 592 patients (mean age 78.9 ± 11.8 years, 51.5% male) with 16 442 (10.7%) deaths within 30 days. The readmission cohort included 148 704 patients (mean age 78.6 ± 11.9 years, 51.7% male) with 33 158 (22.3%) unplanned readmission within 30 days. In 392 hospitals with at least 25 HF hospitalisations, the median RSMR was 10.7% (range 6.1–17.3%) with 59 hospitals significantly different from the national average. Similarly, in 391 hospitals with at least 25 HF hospitalisations, the median RSRR was 22.3% (range 17.7–27.1%) with 24 hospitals significantly different from the average. From 2010–15, the adjusted 30‐day mortality [odds ratio (OR) 0.991/month, 95% confidence interval (CI) 0.990–0.992, P < 0.01] and unplanned readmission (OR 0.998/month, 95% CI 0.998–0.999, P < 0.01) rates declined. Conclusion: Within 30 days of a HF hospitalisation, one in 10 patients died and almost a quarter of those surviving experienced an unplanned readmission. The risk of these outcomes varied widely among hospitals suggesting disparities in HF care quality. Nevertheless, a substantial decline in 30‐day mortality and a modest decline in readmissions occurred over the study period. [ABSTRACT FROM AUTHOR]

Background: Diet is a major determining factor for many non-communicable chronic diseases (NCDs). However, evidence on diet-related NCD burden remains limited. We assessed the trends in diet-related NCDs in Australia from 1990 to 2015 and compared the results with other countries of the Organization for Economic Co-operation and Development (OECD). Methods: We used data and methods from the Global Burden of Disease (GBD) 2015 study to estimate the NCD mortality and disability-adjusted life years (DALYs) attributable to 14 dietary risk factors in Australia and 34 OECD nations. Countries were further ranked from the lowest (first) to highest (35th) burden using an age-standardized population attributable fraction (PAF). Results: In 2015, the estimated number of deaths attributable to dietary risks was 29,414 deaths [95% uncertainty interval (UI) 24,697 − 34,058 or 19.7% of NCD deaths] and 443,385 DALYs (95% UI 377,680–511,388 or 9.5% of NCD DALYs) in Australia. Young (25–49 years) and middle-age (50–69 years) male adults had a higher PAF of diet-related NCD deaths and DALYs than their female counterparts. Diets low in fruits, vegetables, nuts and seeds and whole grains, but high in sodium, were the major contributors to both NCD deaths and DALYs. Overall, 42.3% of cardiovascular deaths were attributable to dietary risk factors. The age-standardized PAF of diet-related NCD mortality and DALYs decreased over the study period by 28.2% (from 27.0% in 1990 to 19.4% in 2015) and 41.0% (from 14.3% in 1990 to 8.4% in 2015), respectively. In 2015, Australia ranked 12th of 35 examined countries in diet-related mortality. A small improvement of rank was recorded compared to the previous 25 years. Conclusions: Despite a reduction in diet-related NCD burden over 25 years, dietary risks are still the major contributors to a high burden of NCDs in Australia. Interventions targeting NCDs should focus on dietary behaviours of individuals and population groups. [ABSTRACT FROM AUTHOR]

Social jetlag is a term used to describe misalignment between biological and social time. Measured as the difference in sleep midpoints between work and free days, social jetlag has been associated with unhealthy lifestyle behaviours and adverse health outcomes. This study aimed to identify the prevalence of social jetlag, and its sociodemographic and behavioural correlates in 837 respondents who completed the Sleep Health Foundation Australia 2016 online survey. Binomial logistic regression models determined associations between social jetlag and self-reported lifestyle and work outcomes, excluding night, evening or rotating shift workers. One third (31.1%) of respondents experienced >1h of social jetlag. In analyses adjusted for sociodemographic variables associated with social jetlag (age, marital status, work status and metropolitan living plus the significant interaction term for age by metro living), social jetlag was associated with longer sleep duration on free days (OR = 2.8, CI = 1.9-4.1), evening preference (OR = 2.0, CI = 1.4-2.4), often staying up later than planned on work days (OR 1.9, CI = 1.3-2.9), and having a computer (OR = 1.7, CI = 1.2-2.4) or phone (OR = 1.6, CI = 1.1-2.4) in the bedroom and internet use in the hour before bed (OR = 1.7, CI 1.2-2.5). Almost twice as many working respondents with social jetlag reported going to work when they should have taken sick leave due to their state of health (OR = 1.9, CI = 1.3-3.0). In conclusion, social jetlag is prevalent in the Australian community and associated with bedtime technology use. Work attendance when in poor health is cause for concern in Australian day workers and requires further investigation. [ABSTRACT FROM AUTHOR]

Purpose: The relative advantages of dietary analysis methods, particularly in identifying dietary patterns associated with bone mass, have not been investigated. We evaluated principal component analysis (PCA), partial least-squares (PLS) and reduced-rank regressions (RRR) in determining dietary patterns associated with bone mass.Methods: Data from 1182 study participants (45.9% males; aged 50 years and above) from the North West Adelaide Health Study (NWAHS) were used. Dietary data were collected using a food frequency questionnaire (FFQ). Dietary patterns were constructed using PCA, PLS and RRR and compared based on the performance to identify plausible patterns associated with bone mineral density (BMD) and content (BMC).Results: PCA, PLS and RRR identified two, four and four dietary patterns, respectively. All methods identified similar patterns for the first two factors (factor 1, “prudent” and factor 2, “western” patterns). Three, one and none of the patterns derived by RRR, PLS and PCA were significantly associated with bone mass, respectively. The “prudent” and dairy (factor 3) patterns determined by RRR were positively and significantly associated with BMD and BMC. Vegetables and fruit pattern (factor 4) of PLS and RRR was negatively and significantly associated with BMD and BMC, respectively.Conclusions: RRR was found to be more appropriate in identifying more (plausible) dietary patterns that are associated with bone mass than PCA and PLS. Nevertheless, the advantage of RRR over the other two methods (PCA and PLS) should be confirmed in future studies. [ABSTRACT FROM AUTHOR]

Background and Objectives: Emerging evidence suggests potential effects of nutrients/foods on sleep parameters. However, no studies have addressed the complex interactions among nutrients/foods and relate them to sleep outcomes. To investigate the associations between dietary patterns and sleep parameters (polysomnography (PSG) measured and self-reported sleep symptoms) in a large sample of community dwelling men in South Australia.Methods and Study Design: Cross-sectional analysis was conducted of participants in the Men Androgen Inflammation Lifestyle Environment and Stress cohort enrolled in a sleep sub-study (n=784, age 35-80 years). Dietary intake was measured by a validated food frequency questionnaire. Dietary patterns were identified by factor analysis. Sleep was assessed by an overnight home PSG and self-reported questionnaires.Results: Two factors were obtained by factor analysis: Factor 1 was characterised by high intakes of vegetables, fruits, and legumes and factor 2 was characterised by processed meat, snacks, red meat and take-away foods. Three categories of the dietary patterns were defined (prudent, mixed and western) through classification of the sample according to the actual consumption higher or lower of each factor. The prudent (factor 1 dominant) and mixed dietary patterns were inversely associated with sleep onset, compared with the western dietary pattern (factor 2 dominant) (β=-6.34 (95% CI-1.11, -11.57), β=-4.34 (95% CI-8.34, -0.34) respectively)). The association was only significant with the prudent dietary pattern after multiple comparison adjustment. No associations were found with between dietary patterns and other sleep outcomes.Conclusions: The prudent dietary pattern was associated with a faster sleep onset, which may provide a solution for sleep management. [ABSTRACT FROM AUTHOR]

Introduction: Evidence demonstrates that health care professionals are more prone to burnout than other professionals due to the emotionally taxing interactions they have with their patients on a daily basis. The aims of this study were to measure occupational burnout levels among sonographers, radiographers and radiologists and to examine predictors of burnout according to demographic characteristics.Methods: A cross-sectional online survey was administered in 2010 to radiographers, sonographers and radiologists who were members of the following professional bodies: Australian Institute of Radiography, Australian Sonographers Association and The Royal Australian and New Zealand College of Radiologists. The Maslach Burnout Inventory was used to measure burnout levels for each profession. Data were analysed using SPSS Ver 20 (IBM, Chicago, IL, USA) statistical software.Results: A total of 613 radiographers, 121 sonographers and 35 radiologists participated in the survey. Radiographers, sonographers and radiologists had a high mean (±SD) burnout score for emotional exhaustion (39.9 ± 8.5, 42.2 ± 8.5 and 44.9 ± 7.1 respectively) and depersonalization (18.9 ± 5.5, 20.3 ± 5.8 and 20.6 ± 5.6) compared to MBI norms. Radiographers also had low personal achievement (30.8 ± 5.5) compared to MBI norms. Radiographers and sonographers who were male, worked >10 hours overtime and spent <10% of their time training students per week had significantly higher depersonalization scores (p < 0.05).Conclusion: Burnout levels among radiographers, sonographers and radiologists are high and likely to vary according to some demographic and work-related factors. Further research is needed to examine ways to alleviate burnout in these professions so that loss of experienced staff due to burnout can be minimized and quality of patient care can be maintained. [ABSTRACT FROM AUTHOR]

Objective: There have been substantial changes in workforce and employment patterns in Australia over the past 50 years as a result of economic globalisation. This has resulted in substantial reduction in employment in the manufacturing industry often with large-scale job losses in concentrated sectors and communities. Large-scale job loss events receive significant community attention. To what extent these mass unemployment events contribute to increased psychological distress, mental illness and suicide in affected individuals warrants further consideration. Methods: Here we undertake a narrative review of published job loss literature. We discuss the impact that large-scale job loss events in the manufacturing sector may have on population mental health, with particular reference to contemporary trends in the Australian economy. We also provide a commentary on the expected outcomes of future job loss events in this context and the implications for Australian public mental health care services. Results and conclusion: Job loss due to plant closure results in a doubling of psychological distress that peaks 9 months following the unemployment event. The link between job loss and increased rates of mental illness and suicide is less clear. The threat of impending job loss and the social context in which job loss occurs has a significant bearing on psychological outcomes. The implications for Australian public mental health services are discussed. [ABSTRACT FROM AUTHOR]

Background: Effective prevention of type 2 diabetes (T2D) requires early identification of high-risk individuals who might benefit from intervention. We sought to determine whether low serum testosterone, a novel risk factor for T2D in men, adds clinically meaningful information beyond current T2D risk models. Methods: The Men Androgen Inflammation Lifestyle Environment and Stress (MAILES) study population consists of 2563 community-dwelling men aged 35-80 years in Adelaide, Australia. Of the MAILES participants, 2038 (80.0 %) provided information at baseline (2002-2006) and follow-up (2007-2010). After excluding participants with diabetes (n = 317), underweight (n = 5), and unknown BMI status (n = 11) at baseline; and unknown diabetes status (n = 50) at follow-up; 1655 participants were followed for 5 years. T2D at baseline and follow-up was defined by self-reported diabetes, or fasting plasma glucose (FPG) ≥7.0 mmol/L (126.1 mg/dL), or glycated haemoglobin (HbA1c) ≥6.5 %, or diabetes medications. Risk models were tested using logistic regression models. Sensitivity, specificity, positive predictive values (PPV) were used to identify the optimal cut-off point for low serum testosterone for incident T2D and the area under the receiver operating characteristic (AROC) curve was used to summarise the predictive power of the model. 15.5 % of men had at least one missing predictor variable; addressed through multiple imputation. Results: The incidence rate of T2D was 8.9 % (147/1655) over a median follow-up of 4.95 years (interquartile range: 4.35-5.00). Serum testosterone level predicted incident T2D (relative risk 0.96 [95 % CI: 0.92,1.00], P = 0.032) independent of current risk models including the AUSDRISK, but did not improve corresponding AROC statistics. A cut-off point of <16 nmol/L for low serum testosterone, which classified about 43 % of men, returned equal sensitivity (61.3 % [95 % CI: 52.6,69.4]) and specificity (58.3 % [95 % CI: 55.6,60.9) for predicting T2D risk, with a PPV of 12.9 % (95 % CI: 10.4,15.8). Conclusions: Low serum testosterone predicts an increased risk of developing T2D in men over 5 years independent of current T2D risk models applicable for use in routine clinical practice. Screening for low serum testosterone in addition to risk factors from current T2D risk assessment models or tools, including the AUSDRISK, would identify a large subgroup of distinct men who might benefit from targeted preventive interventions. [ABSTRACT FROM AUTHOR]

Background: To determine the extent to which variations in monthly Mental Health Emergency Department (MHED) presentations in South Australian Public Hospitals are associated with the Australian Bureau of Statistics (ABS) monthly unemployment rates. Methods: Times series modelling of relationships between monthly MHED presentations to South Australian Public Hospitals derived from the Integrated South Australian Activity Collection (ISAAC) data base and the ABS monthly unemployment rates in South Australia between January 2004–June 2011. Results: Time series modelling using monthly unemployment rates from ABS as a predictor variable explains 69 % of the variation in monthly MHED presentations across public hospitals in South Australia. Thirty-two percent of the variation in current month’s male MHED presentations can be predicted by using the 2 months’ prior male unemployment rate. Over 63 % of the variation in monthly female MHED presentations can be predicted by either male or female prior monthly unemployment rates. Conclusions: The findings of this study highlight that even with the relatively favourable economic conditions, small shifts in monthly unemployment rates can predict variations in monthly MHED presentations, particularly for women. Monthly ABS unemployment rates may be a useful metric for predicting demand for emergency mental health services. [ABSTRACT FROM AUTHOR]

Background: Levels of vitamin D in the population have come under increasing scrutiny, however there are only a few studies in Australia which measure levels in the general population. The aim of this study was to measure the levels of vitamin D within a large population cohort and examine the association with seasons and selected demographic and health risk factors. Methods: A longitudinal cohort study of 2413 participants in the northwest suburbs of Adelaide, South Australia conducted between 2008 and 2010 was used to examine serum levels of 25-hydroxy vitamin D (25(OH)D) in relation to demographic characteristics (age, sex, income, education and country of birth), seasons, the use of vitamin D supplements and selected health risk factors (physical activity, body mass index and smoking). Both unadjusted and adjusted mean levels of serum 25(OH)D were examined, as were the factors associated with the unadjusted and adjusted prevalence of serum 25(OH)D levels below 50 and 75 nmol/L. Results: Overall, the mean level of serum 25(OH)D was 69.2 nmol/L with 22.7% of the population having a serum 25(OH)D level below 50 nmol/L, the level which is generally recognised as vitamin D deficiency. There were significantly higher levels of 25(OH)D among males compared to females (t = 4.65, p < 0.001). Higher levels of 25 (OH)D were also measured in summer and autumn compared with winter and spring. Generally, mean levels of 25 (OH)D were lower in those classified as obese. Smokers and those undertaking no or less than 150 minutes/week of physical activity also had lower levels of serum vitamin D. Obesity (as classified by body mass index), season and undertaking an insufficient level of physical activity to obtain a health benefit were significantly associated with the prevalence of vitamin D deficiency. Conclusions: Vitamin D deficiency is prevalent in South Australia, affecting almost one quarter of the population and levels are related to activity, obesity and season even when adjusted for confounding factors. Improved methods of addressing vitamin D levels in population are required. [ABSTRACT FROM AUTHOR]

Objectives: Identify factors associated with changes to health-related quality of life (HRQoL) in baby boomers. Methods: Panel data were collected on baby boomers at two time points, 2000-2002 and 2004-2006. A fixed-effects model was used to identify associations between changes in the dependent variable (SF-36 summary scales) and changes in independent variables (health indicators/employment status). Results: Mental health problems, being out of labor force, sedentary behavior, and severe lung disease were associated with deterioration in physical and mental HRQoL. Obesity was associated with deterioration in physical HRQoL whereas cardiovascular disease was associated with deterioration in mental HRQoL. Unemployment, full-time employment, and absence of lung disease symptoms were associated with improvements in physical and mental HRQoL. Discussion: If we are to maximize the future labor participation, and HRQoL, of this cohort, it will be necessary to reduce obesity and sedentary behavior and to further investigate the association between health and employment. [ABSTRACT FROM AUTHOR]

Previous studies using clinic or convenience samples have indicated that not only patients with arthritis are at increased risk of depression, but there may also be a link between depression and disability in people with arthritis. We examined the prevalence of psychological distress in a population sample with and without arthritis and the association with health-related quality of life. The WANTS Health and Well-being Survey was a population household telephone interview survey of adults (age ≥18 years) in three states of Australia. Data obtained were weighted to provide population-representative estimates. The survey included questions regarding arthritis, SF-12, the Kessler 10 index of psychological distress and presence of mental health conditions. A total of 7,473 interviews providing information on arthritis were completed, with 1,364 (18.3%) reporting arthritis. Self-reported mental health conditions were more frequent in those with arthritis (14.9 vs 12.0%, p = 0.004), and a higher proportion were at a medium or high risk for anxiety or depression (39.0 vs 31.0%, p < 0.001). People with arthritis had significantly lower scores on the SF-12 physical component summaries compared to those without arthritis. Among those with arthritis, those with coexisting psychological distress had significantly lower scores on the SF-12 physical component summary than those without psychological distress. Psychological distress is common among people with arthritis in the community. In arthritis, psychological distress makes a significant additional negative impact on the physical well-being. Physicians need to recognize and address this additional impact on physical functioning in patients with arthritis. [ABSTRACT FROM AUTHOR]

Background: Analysis was undertaken on data from randomly selected participants of a biomedical cohort study to assess representativeness. The research hypotheses was that there was no difference in participation and non-participations in terms of health-related indicators (smoking, alcohol use, body mass index, physical activity, blood pressure and cholesterol readings and overall health status) and selected socio-demographics (age, sex, area of residence, education level, marital status and work status). Methods: Randomly selected adults were recruited into a bio-medical representative cohort study based in the north western suburbs of the capital of South Australia -- Adelaide. Comparison data was obtained from cross-sectional surveys of randomly selected adults in the same age range and in the same region. The cohort participants were 4060 randomly selected adults (18+ years). Results: There were no major differences between study participants and the comparison population in terms of current smoking status, body mass index, physical activity, overall health status and proportions with current high blood pressure and cholesterol readings. Significantly more people who reported a medium to very high alcohol risk participated in the study. There were some demographic differences with study participants more likely to be in the middle level of household income and education level. Conclusion: People with risky behaviours participated in this health study in the same proportions as people without these risk factors. [ABSTRACT FROM AUTHOR]

The article focuses on the Services, Pathways, Access, Research and Knowledge (SPARK) longitudinal population health project which was initiated by the Mental Health Observatory (MHO). The project will assess change functional outcomes, examine the impact of primary and secondary care services and non-governmental organizations (NGO) on these outcomes and build local capacity in rural community mental health centers. It is suggested that SPARK project paradigm can be used in other services.