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Background: Chronic diseases are highly prevalent and cluster in individuals (multimorbidity). This study investigated the association between multimorbidity and Health-Related Quality of Life (HRQoL), assessing the combination of chronic diseases highly correlated with this outcome.Methods: We conducted a household survey in 2015 in a random sample of 2912 South Australian adults (48.9 ± 18.1 years; 50.9% females), obtaining information on sociodemographics, lifestyle, and 17 chronic conditions clustered in four different groups (metabolic, cardiovascular, gastrointestinal, and musculoskeletal). Information on physical (PCS) and mental components scores (MCS) of HRQoL were assessed using the SF-12 questionnaire. Multivariable linear regression models considering individual diseases (mutually adjusted) and clusters within- and between-groups were used to test the associations.Results: Only 41% of the sample was negative for all the investigated diseases. The most prevalent conditions were osteoarthritis, obesity and hypertension, which affected one in every four individuals. PCS was markedly lower among those reporting stroke, heart failure, and osteoarthritis, but they were not associated with MCS. Direct-trend relationships were observed between the number of chronic conditions (clusters within- and between-groups) and PCS, but not with MCS. The strongest association with PCS was for musculoskeletal conditions (difference between those affected by 2+ conditions and those free of these conditions -6.7 95%CI -8.5;-5.4), and lower PCS were observed in any combination of clusters between-group including musculoskeletal diseases.Conclusion: In the context of multimorbidity, musculoskeletal diseases are a key determinant group of PCS, amplifying the association of other chronic conditions on physical but not on mental health. [ABSTRACT FROM AUTHOR]

Background: Adherence to a traditional Mediterranean diet has been associated with lower mortality and cardiovascular disease risk. The relative importance of diet compared to other lifestyle factors and effects of dietary patterns over time remains unknown., Methods: We used the parametric G-formula to account for time-dependent confounding, in order to assess the relative importance of diet compared to other lifestyle factors and effects of dietary patterns over time. We included healthy Melbourne Collaborative Cohort Study participants attending a visit during 1995-1999. Questionnaires assessed diet and physical activity at each of three study waves. Deaths were identified by linkage to national registries. We estimated mortality risk over approximately 14 years (1995-2011)., Results: Of 22,213 participants, 2163 (9.7%) died during 13.6 years median follow-up. Sustained high physical activity and adherence to a Mediterranean-style diet resulted in an estimated reduction in all-cause mortality of 1.82 per 100 people (95% confidence interval (CI): 0.03, 3.6). The population attributable fraction was 13% (95% CI: 4, 23%) for sustained high physical activity, 7% (95% CI: - 3, 17%) for sustained adherence to a Mediterranean-style diet and 18% (95% CI: 0, 36%) for their combination., Conclusions: A small reduction in mortality may be achieved by sustained elevated physical activity levels in healthy middle-aged adults, but there may be comparatively little gain from increasing adherence to a Mediterranean-style diet.

Background: The last few years have seen renewed interest in use-of-time recalls in epidemiological studies, driven by a focus on the 24-h day [including sleep, sitting, and light physical activity (LPA)] rather than just moderate-vigorous physical activity (MVPA). This paper describes four different computerised use-of-time instruments (ACT24, PAR, MARCA and cpar24) and presents population time-use data from a collective sample of 8286 adults from different population studies conducted in Australia/New Zealand, Germany and the United States., Methods: The instruments were developed independently but showed a number of similarities: they were self-administered through the web or used computer-assisted telephone interviews; all captured energy expenditure using variants of the Ainsworth Compendium; each had been validated against criterion measures; and they used a domain structure whereby activities were aggregated under categories such as Personal Care and Work., Results: Estimates of physical activity level (average daily rate of energy expenditure in METs) ranged from 1.53 to 1.78 in the four studies, strikingly similar to population estimates derived from doubly labelled water. There was broad agreement in the amount of time spent in sleep (7.2-8.6 h), MVPA (1.6-3.1 h), personal care (1.6-2.4 h), and transportation (1.1-1.8 h). There were consistent sex differences, with women spending 28-81% more time on chores, 8-40% more time in LPA, and 3-39% less time in MVPA than men., Conclusions: Although there were many similarities between instruments, differences in operationalizing definitions of sedentary behaviour and LPA resulted in substantive differences in the amounts of time reported in sedentary and physically active behaviours. Future research should focus on deriving a core set of basic activities and associated energy expenditure estimates, an agreed classificatory hierarchy for the major behavioural and activity domains, and systems to capture relevant social and environmental contexts.

Background: Addressing evidence-practice gaps in primary care remains a significant public health challenge and is likely to require action at different levels of the health system. Whilst Continuous Quality Improvement (CQI) is associated with improvements in overall delivery, little is known about delivery of different types of care processes, and their relative improvement during CQI., Methods: We used data from over 15,000 clinical audit records of clients with Type 2 diabetes collected as part of a wide-scale CQI program implemented between 2005 and 2014 in 162 Aboriginal and Torres Strait Islander health centres. We abstracted data from clinical records on 15 service items recommended in clinical guidelines and categorised these items into five modes of care on the basis of the mechanism through which care is delivered: laboratory tests; generalist-delivered physical checks; specialist-delivered checks; education/counselling for nutrition and physical activity and education/counselling for high risk substance use. We calculated delivery for each patient for each of mode of care by determining the proportion of recommended services delivered for that mode. We used multilevel regression models to quantify variation attributable to health centre or client level factors and to identify factors associated with greater adherence to clinical guidelines for each mode of care., Results: Clients on average received 43 to 60 % of recommended care in 2005/6. Different modes of care showed different patterns of improvement. Generalist-delivered physical checks (delivered by a non-specialist) showed a steady year on year increase, delivery of laboratory tests showed improvement only in the later years of the study, and delivery of counselling/education interventions showed early improvement which then plateaued. Health centres participating in CQI had increased odds of top quartile service delivery for all modes compared to baseline, but effects differed by mode. Health centre factors explained 20-52 % of the variation across jurisdictions and health centres for different modes of care., Conclusions: Levels of adherence to clinical guidelines and patterns of improvement during participation in a CQI program differed for different modes of care. Policy and funding decisions may have had important effects on the level and nature of improvements achieved.