Identifying risk factors for developing obesity: a record linkage longitudinal study in metropolitan Sydney using the 45 and Up Study.

BACKGROUND: Primary care clinicians have key responsibilities in obesity prevention and weight management. AIMS: We aimed to identify risk factors for developing obesity among people aged ≥45 years. METHODS: We conducted a record linkage longitudinal study of residents of metropolitan Sydney, Australia using data from the: (1) 45 and Up Study at baseline (2005-2009) and first follow-up (2012-2015); (2) Medicare claims; (3) Pharmaceutical Benefits Scheme; and (4) deaths registry. We examined risk factors for developing obesity (body mass index [BMI]: 30-40) at follow-up, separately for people within the: (1) healthy weight range (BMI 18.5-<25) and (2) overweight range (BMI 25-<30) at baseline. Covariates included demographics, modifiable behaviours, health status, allied health use, and medication use. Crude and adjusted relative risks were estimated using Poisson regression modelling. RESULTS: At follow-up, 1.1% (180/16,205) of those in the healthy weight range group, and 12.7% (1,939/15,266) of those in the overweight range group developed obesity. In both groups, the following were associated with developing obesity: current smoking at baseline, physical functioning limitations, and allied health service use through team care planning, while any alcohol consumption and adequate physical activity were found to be associated with a lower risk of developing obesity. In the healthy weight group, high psychological distress and the use of antiepileptics were associated with developing obesity. In the overweight group, female sex and full-time work were associated with developing obesity, while older age was found to be associated with a lower risk of developing obesity. CONCLUSIONS: These findings may inform the targeting of preventive interventions for obesity in clinical practice and broader public health programs.

Early intervention to prevent weight gain requires a targeted multidisciplinary team-based approach to improve diet, increase physical activity, and change behaviour. However, the capacity to provide this within primary care is limited and there is little funding for consultations with allied health professionals. There is a need to identify priority at-risk groups to help primary care clinicians target interventions to those in most need. We have identified, using a longitudinal study of residents of metropolitan Sydney, key characteristics of older adults who are at risk of gaining weight and developing obesity, including risk behaviours (smoking and physical inactivity), and chronic conditions or their treatment (physical function, psychological distress, and use of anti-epileptic medications). These findings may help alert clinicians to the need for preventive interventions in selected cases, as well as informing the targeting of public health programs.

Impact of multimorbidity and complex multimorbidity on healthcare utilisation in older Australian adults aged 45 years or more: a large population-based cross-sectional data linkage study.

OBJECTIVES: As life expectancy increases, older people are living longer with multimorbidity (MM, co-occurrence of ≥2 chronic health conditions) and complex multimorbidity (CMM, ≥3 chronic conditions affecting ≥3 different body systems). We assessed the impacts of MM and CMM on healthcare service use in Australia, as little was known about this. DESIGN: Population-based cross-sectional data linkage study. SETTING: New South Wales, Australia. PARTICIPANTS: 248 496 people aged ≥45 years who completed the Sax Institute's 45 and Up Study baseline questionnaire. PRIMARY OUTCOME: High average annual healthcare service use (≥2 hospital admissions, ≥11 general practice visits and ≥2 emergency department (ED) visits) during the 3-year baseline period (year before, year of and year after recruitment). METHODS: Baseline questionnaire data were linked with hospital, Medicare claims and ED datasets. Poisson regression models were used to estimate adjusted and unadjusted prevalence ratios for high service use with 95% CIs. Using a count of chronic conditions (disease count) as an alternative morbidity metric was requested during peer review. RESULTS: Prevalence of MM and CMM was 43.8% and 15.5%, respectively, and prevalence increased with age. Across three healthcare settings, MM was associated with a 2.02-fold to 2.26-fold, and CMM was associated with a 1.83-fold to 2.08-fold, increased risk of high service use. The association was higher in the youngest group (45-59 years) versus the oldest group (≥75 years), which was confirmed when disease count was used as the morbidity metric in sensitivity analysis.When comparing impact using three categories with no overlap (no MM/CMM, MM with no CMM, and CMM), CMM had greater impact than MM across all settings. CONCLUSION: Increased healthcare service use among older adults with MM and CMM impacts on the demand for primary care and hospital services. Which of MM or CMM has greater impact on risk of high healthcare service use depends on the analytic method used. Ageing populations living longer with increasing burdens of MM and CMM will require increased Medicare funding and provision of integrated care across the healthcare system to meet their complex needs.

Impact of multimorbidity and complex multimorbidity on mortality among older Australians aged 45 years and over: a large population-based record linkage study.

OBJECTIVES: Multimorbidity (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. DESIGN: Community-based prospective cohort study. SETTING: New South Wales, Australia. PARTICIPANTS: People aged 45 years and over who completed the baseline survey of the 45 and Up Study. MEASURES: Baseline 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). RESULTS: Of 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. CONCLUSION: MM 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.

Effect of availability of HIV self-testing on HIV testing frequency in gay and bisexual men at high risk of infection (FORTH): a waiting-list randomised controlled trial.

BACKGROUND: Frequent testing of individuals at high risk of HIV is central to current prevention strategies. We aimed to determine if HIV self-testing would increase frequency of testing in high-risk gay and bisexual men, with a particular focus on men who delayed testing or had never been tested before. METHODS: In this randomised trial, HIV-negative high-risk gay and bisexual men who reported condomless anal intercourse or more than five male sexual partners in the past 3 months were recruited at three clinical and two community-based sites in Australia. Enrolled participants were randomly assigned (1:1) to the intervention (free HIV self-testing plus facility-based testing) or standard care (facility-based testing only). Participants completed a brief online questionnaire every 3 months, which collected the number of self-tests used and the number and location of facility-based tests, and HIV testing was subsequently sourced from clinical records. The primary outcome of number of HIV tests over 12 months was assessed overall and in two strata: recent (last test ≤2 years ago) and non-recent (>2 years ago or never tested) testers. A statistician who was masked to group allocation analysed the data; analyses included all participants who completed at least one follow-up questionnaire. After the 12 month follow-up, men in the standard care group were offered free self-testing kits for a year. This trial is registered with the Australian New Zealand Clinical Trials Registry, number ACTRN12613001236785. FINDINGS: Between Dec 1, 2013, and Feb 5, 2015, 182 men were randomly assigned to self-testing, and 180 to standard care. The analysis population included 178 (98%) men in the self-testing group (174 person-years) and 165 (92%) in the standard care group (162 person-years). Overall, men in the self-testing group had 701 HIV tests (410 self-tests; mean 4·0 tests per year), and men in the standard care group had 313 HIV tests (mean 1·9 tests per year); rate ratio (RR) 2·08 (95% CI 1·82-2·38; p<0·0001). Among recent testers, men in the self-testing group had 627 tests (356 self-tests; mean 4·2 per year), and men in the standard care group had 297 tests (mean 2·1 per year); RR 1·99 (1·73-2·29; p<0·0001). Among non-recent testers, men in the self-testing group had 74 tests (54 self-tests; mean 2·8 per year), and men in the standard care group had 16 tests (mean 0·7 per year); RR 3·95 (2·30-6·78; p<0·0001). The mean number of facility-based HIV tests per year was similar in the self-testing and standard care groups (mean 1·7 vs 1·9 per year, respectively; RR 0·86, 0·74-1·01; p=0·074). No serious adverse events were reported during follow-up. INTERPRETATION: HIV self-testing resulted in a two times increase in frequency of testing in gay and bisexual men at high risk of infection, and a nearly four times increase in non-recent testers, compared with standard care, without reducing the frequency of facility-based HIV testing. HIV self-testing should be made more widely available to help increase testing and earlier diagnosis. FUNDING: The National Health and Medical Research Council, Australia.

HIV testing self-efficacy is associated with higher HIV testing frequency and perceived likelihood to self-test among gay and bisexual men.

Background Regular testing of individuals at higher-risk of HIV is central to current prevention strategies. The aim of the present study was to examine the extent to which confidence in one's perceived ability to undertake various aspects of HIV testing and self-testing (self-efficacy) affected HIV testing outcomes. We assessed factors, including self-efficacy, associated with HIV testing frequency and the likelihood to self-test among gay and bisexual men (GBM). METHODS: Participants were HIV-negative GBM at an increased risk of HIV (more than five partners or condomless anal intercourse in the previous 3 months) enrolled in a randomised controlled trial of HIV self-testing. The baseline questionnaire captured data regarding sociodemographic characteristics, HIV and/or sexually transmissible infection testing history, sexual behaviour, beliefs and attitudes towards HIV and eight items capturing confidence in HIV testing ability that were combined as a single broad measure of HIV testing self-efficacy (α=0.81). Factors associated with three or more HIV tests in the past year and the likelihood of self-testing in the future were determined using logistic regression. RESULTS: Of 354 GBM, 34% reported three or more HIV tests in the past year, and 64% reported being 'very likely' to self-test. Factors independently associated with three or more HIV tests in the past year were: higher self-efficacy (adjusted odds ratio (aOR) 1.08 per unit increase; 95% confidence interval (CI) 1.02-1.14; P=0.004); >10 male partners in the past 6 months (aOR 1.79; 95% CI 1.05-3.04; P=0.031) and higher optimism regarding the effects of HIV treatments on HIV transmission (aOR 1.14; 95% CI 1.00-1.29; P=0.044). Only higher self-efficacy was independently associated with reporting a greater likelihood to self-test in the future (aOR 1.10; 95% CI 1.05-1.15; P < 0.001). CONCLUSIONS: Improving self-efficacy by enhancing GBM's knowledge and experience may lead to higher testing frequency. The self-efficacy measure used in the present study could be useful in identifying GBM likely to face difficulties with HIV testing and self-testing.

Rationale and design of FORTH: a randomised controlled trial assessing the effectiveness of HIV self-testing in increasing HIV testing frequency among gay and bisexual men.

BACKGROUND: Gay and bisexual men (GBM) are a major risk group for HIV acquisition, yet the majority of higher-risk GBM test for HIV less often than recommended (3-6 monthly). HIV self-testing has the potential to increase testing frequency and improve awareness of personal HIV status. HIV self-tests have been approved in some countries, however there are concerns whether self-testing would increase HIV testing frequency enough to compensate for the reduced sensitivity of self-tests in early infection. We describe here a randomised controlled trial to assess the effectiveness of self-testing in increasing HIV testing frequency among higher-risk GBM, and its acceptability. METHODS/DESIGN: Participants are higher-risk HIV negative GBM (>5 partners or condomless anal intercourse in previous 3 months; n = 350), including 50 GBM who tested for HIV over two years ago or never tested before ('infrequent-testers'). Participants are recruited from sexual health clinics and community-based organisations, and randomised 1:1 to either self-testing or standard-care (routine clinic-based testing) arms. The trial employs a wait-list control design: participants in the standard-care arm switch to self-testing arm in the second year, and gain access to self-test kits. Participants in the self-testing arm receive four oral-fluid self-test kits at enrolment, with additional kits provided on request. Demographics, sexual behaviour and HIV testing preferences are collected at baseline, and the frequency and pattern of HIV and sexually transmissible infection (STI) testing is collected via online 3-monthly questionnaires. The acceptability of self-testing is assessed at 12 months via an online questionnaire and in-depth interviews. A 24-h telephone support is provided, with expedited follow-up of those with reactive self-test results. The primary outcome is HIV testing frequency (mean number of HIV tests per person) over 12 months, and the secondary outcomes are: mean number of STI tests (chlamydia, gonorrhoea, syphilis) per person; reasons for HIV testing; and acceptability of HIV self-testing. DISCUSSION: This is the first trial to evaluate the use of self-testing among GBM in Australia, and the first internationally among infrequent testers. The study will provide evidence on whether self-testing increases HIV testing frequency, and its acceptability among GBM. The findings will improve our understanding of self-testing patterns, and whether GBM supplement or replace their existing testing routine. TRIAL REGISTRATION: Australian and New Zealand Clinical Trial Registration number: ACTRN12613001236785 , registered on November 12, 2013.

Multi-centre evaluation of the Determine HIV Combo assay when used for point of care testing in a high risk clinic-based population.

BACKGROUND: Determine HIV Combo (DHC) is the first point of care assay designed to increase sensitivity in early infection by detecting both HIV antibody and antigen. We conducted a large multi-centre evaluation of DHC performance in Sydney sexual health clinics. METHODS: We compared DHC performance (overall, by test component and in early infection) with conventional laboratory HIV serology (fourth generation screening immunoassay, supplementary HIV antibody, p24 antigen and Western blot tests) when testing gay and bisexual men attending four clinic sites. Early infection was defined as either acute or recent HIV infection acquired within the last six months. RESULTS: Of 3,190 evaluation specimens, 39 were confirmed as HIV-positive (12 with early infection) and 3,133 were HIV-negative by reference testing. DHC sensitivity was 87.2% overall and 94.4% and 0% for the antibody and antigen components, respectively. Sensitivity in early infection was 66.7% (all DHC antibody reactive) and the DHC antigen component detected none of nine HIV p24 antigen positive specimens. Median HIV RNA was higher in false negative than true positive cases (238,025 vs. 37,591 copies/ml; p = 0.022). Specificity overall was 99.4% with the antigen component contributing to 33% of false positives. CONCLUSIONS: The DHC antibody component detected two thirds of those with early infection, while the DHC antigen component did not enhance performance during point of care HIV testing in a high risk clinic-based population.