EASI demonstrated the highest inter-rater and intrarater reliability, supporting it as the optimal AD severity outcome measure.

ObjectivesTo evaluate a multifaceted intervention on diet, physical activity and health literacy of overweight and obese patients attending primary care.DesignA pragmatic two-arm cluster randomised controlled trial.SettingUrban general practices in lower socioeconomic areas in Sydney and Adelaide.ParticipantsWe aimed to recruit 800 patients in each arm. Baseline assessment was completed by 215 patients (120 intervention and 95 control).InterventionA practice nurse-led preventive health check, a mobile application and telephone coaching.Primary and secondary outcome measuresPrimary outcomes were measured at baseline, 6 and 12 months, and included patient health and eHealth literacy, weight, waist circumference and blood pressure. Secondary outcomes included changes in diet and physical activity, preventive advice and referral, blood lipids, quality of life and costs. Univariate and multivariate analyses of difference-in-differences (DiD) estimates for each outcome were conducted.ResultsAt 6 months, the intervention group, compared with the control group, demonstrated a greater increase in Health Literacy Questionnaire domain 8 score (ability to find good health information; mean DiD 0.22; 95% CI 0.01 to 0.44). There were similar differences for domain 9 score (understanding health information well enough to know what to do) among patients below the median at baseline. Differences were reduced and non-statistically significant at 12 months. There was a small improvement in diet scores at 6 months (DiD 0.78 (0.10 to 1.47); p=0.026) but not at 12 months. There were no differences in eHealth literacy, physical activity scores, body mass index, weight, waist circumference or blood pressure.ConclusionsTargeted recruitment and engagement were challenging in this population. While the intervention was associated with some improvements in health literacy and diet, substantial differences in other outcomes were not observed. More intensive interventions and using codesign strategies to engage the practices earlier may produce a different result. Codesign may also be valuable when targeting lower socioeconomic populations.Trial registration numberAustralian New Zealand Clinical Trials Registry (ACTRN 12617001508369) (http://www.ANZCTR.org.au/ACTRN12617001508369.aspx).Trial protocolThe protocol for this trial has been published (open access;https://bmjopen.bmj.com/content/8/6/e023239).

ObjectivesMultimorbidity (MM, co-occurrence of two or more chronic conditions) and complex multimorbidity (CMM, three or more chronic conditions affecting three or more different body systems) are used in the assessment of complex healthcare needs and their impact on health outcomes. However, little is known about the impacts of MM and CMM on mortality in Australia.DesignCommunity-based prospective cohort study.SettingNew South Wales, Australia.ParticipantsPeople aged 45 years and over who completed the baseline survey of the 45 and Up Study.MeasuresBaseline survey data from the 45 and Up Study were linked with deaths registry data. Deaths that occurred within 8 years from the baseline survey date were the study outcome. Eleven self-reported chronic conditions (cancer, heart disease, diabetes, stroke, Parkinson’s disease, depression/anxiety, asthma, allergic rhinitis, hypertension, thrombosis and musculoskeletal conditions) from the baseline survey were included in the MM and CMM classifications. Cox proportional hazard models were used to estimate adjusted and unadjusted 8-year mortality hazard ratios (HRs).ResultsOf 251 689 people (53% female and 54% aged ≥60 years) in the cohort, 111 084 (44.1%) were classified as having MM and 39 478 (15.7%) as having CMM. During the 8-year follow-up, there were 25 891 deaths. Cancer (34.7%) was the most prevalent chronic condition and the cardiovascular system (50.9%) was the body system most affected by a chronic condition. MM and CMM were associated with a 37% (adjusted HR 1.36, 95% CI 1.32 to 1.40) and a 22% (adjusted HR 1.22, 95% CI 1.18 to 1.25) increased risk of death, respectively. The relative impact of MM and CMM on mortality decreased as age increased.ConclusionMM and CMM were common in older Australian adults; and MM was a better predictor of all-cause mortality risk than CMM. Higher mortality risk in those aged 45–59 years indicates tailored, person-centred integrated care interventions and better access to holistic healthcare are needed for this age group.