BackgroundMultimorbidity, the simultaneous occurrence of two or more chronic conditions, is usually associated with older persons. This research assessed multimorbidity across a range of ages so that planners are informed and appropriate prevention programs, management strategies and health service/health care planning can be implemented.MethodsMultimorbidity was assessed across three age groups from data collected in a major biomedical cohort study (North West Adelaide Health Study). Using randomly selected adults, diabetes, asthma, and chronic obstructive pulmonary disease were determined clinically and cardio-vascular disease, osteoporosis, arthritis and mental health by self-report (ever been told by a doctor). A range of demographic, social, risk and protective factors including high blood pressure and high cholesterol (assessed bio-medically), health service use, quality of life and medication use (linked to government records) were included in the multivariate modelling.ResultsOverall 4.4% of the 20-39 year age group, 15.0% of the 40-59 age group and 39.2% of those aged 60 years of age or older had multimorbidity (17.1% of the total). Of those with multimorbidity, 42.1% were aged less than 60 years of age. A variety of variables were included in the final logistic regression models for the three age groups including family structure, marital status, education attainment, country of birth, smoking status, obesity measurements, medication use, health service utilisation and overall health status.ConclusionsMultimorbidity is not just associated with older persons and flexible care management support systems, appropriate guidelines and care-coordination programs are required across a broader age range. Issues such as health literacy and polypharamacy are also important considerations. Future research is required into assessing multimorbidity across the life course, prevention of complications and assessment of appropriate self-care strategies.

Background: The objectives of the study were to explore a self-report measure for psychological well-being and to investigate the relationship between psychological well-being and psychological distress. Method: Telephone interviews of a representative sample of adults (N = 1933) collected information about sociodemographic variables, a standardised measure of psychological distress, and three brief existing scales to assess aspects of psychological well-being: Positive Relations with Others, Environmental Mastery, and Satisfaction with Life. The total of these three scales was also computed and explored as a measure of overall well-being. Results: Variables positively associated with psychological well-being were negatively associated with psychological distress and vice versa. For example low psychological well-being and high psychological distress were associated with being the only adult in the household, speaking a language other than English at home, being divorced or separated, having no educational qualifications beyond secondary school, being unable to work, having a low income, renting one's accommodation, and receiving a pension. Conclusions: The measure of well-being shows psychometric promise for community surveys. Psychological well-being is not exactly the opposite end of the continuum to psychological distress, but more debate is needed about whether and when, research participants need to be asked questions about both.

BackgroundWorksite health promotion (WHP) initiatives are increasingly seen as having potential for large-scale health gains. While health insurance premiums are directly linked to workplaces in the USA, other countries with universal health coverage, have less incentive to implement WHP programs. Size of the business is an important consideration with small worksites less likely to implement WHP programs. The aim of this study was to identify key intervention points and to provide policy makers with evidence for targeted interventions.MethodsThe worksites (n = 218) of randomly selected, working participants, aged between 30 and 65 years, in two South Australian cohort studies were surveyed to assess the practices, beliefs, and attitudes regarding WHP. A survey was sent electronically or by mail to management within each business.ResultsSmaller businesses (<20 employees) had less current health promotion activies (mean 1.0) compared to medium size businesses (20–200 employees – mean 2.4) and large businesses (200+ employees – mean 2.9). Management in small businesses were less likely (31.0 %) to believe that health promotion belonged in the workplace (compared to 55.7 % of medium businesses and 73.9 % of large businesses) although half of small businesses did not know or were undecided (compared to 36.4 and 21.6 % of medium and large businesses). In total, 85.0 % of smaller businesses believed the health promotion activities currently employed in the worksite were effective (compared to 89.2 % of medium businesses and 83.1 % of large businesses). Time and funding were the most cited responses to the challenges to implementing health promoting strategies regardless of business size. Small businesses ranked morale and work/life balance the highest among a range of health promotion activities that were important for their workplace while work-related injury was the highest ranked consideration for large businesses.ConclusionThis study found that smaller workplaces had many barriers, beliefs and challenges regarding WHP. Often small businesses find health promotion activities a luxury and not a serious focus of their activities although this study found that once a health promoting strategy was employed, the perceived effectiveness of the activities were high for all business regardless of size. Tailored low-cost programs, tax incentives, re-orientation of work practices and management support are required so that the proportion of small businesses that have WHP initiatives is increased.

Aims/hypothesis Evidence of an association between maternal smoking during pregnancy (prenatal smoking) and childhood type 1 diabetes is mixed. Previous studies have been small and potentially biased due to unmeasured confounding. The objectives of this study were to estimate the association between prenatal smoking and childhood type 1 diabetes, assess residual confounding with a negative control design and an E-value analysis, and summarise published effect estimates from a meta-analysis. Methods This whole-of-population study (births from 1999 to 2013, participants aged ≤15 years) used de-identified linked administrative data from the South Australian Early Childhood Data Project. Type 1 diabetes was diagnosed in 557 children (ICD, tenth edition, Australian Modification [ICD-10-AM] codes: E10, E101-E109) during hospitalisation (2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014). Families not given financial assistance for school fees was a negative control outcome. Adjusted Cox proportional HRs were calculated. Analyses were conducted on complete-case (n = 264,542, type 1 diabetes = 442) and imputed (n = 286,058, type 1 diabetes = 557) data. A random-effects meta-analysis was used to summarise the effects of prenatal smoking on type 1 diabetes. Results Compared with non-smokers, children exposed to maternal smoking only in the first or second half of pregnancy had a 6% higher type 1 diabetes incidence (adjusted HR 1.06 [95% CI 0.73, 1.55]). Type 1 diabetes incidence was 24% lower (adjusted HR 0.76 [95% CI 0.58, 0.99]) among children exposed to consistent prenatal smoking, and 16% lower for exposure to any maternal smoking in pregnancy (adjusted HR 0.84 [95% CI 0.67, 1.08]), compared with the unexposed group. Meta-analytic estimates showed 28-29% lower risk of type 1 diabetes among children exposed to prenatal smoking compared with those not exposed. The negative control outcome analysis indicated residual confounding in the prenatal smoking and type 1 diabetes association. E-value analysis indicated that unmeasured confounding associated with prenatal smoking and childhood type 1 diabetes, with a HR of 1.67, could negate the observed effect. Conclusions/interpretation Our best estimate from the study is that maternal smoking in pregnancy was associated with 16% lower childhood type 1 diabetes incidence, and some of this effect was due to residual confounding.

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