Life expectancy in Australian senior with or without cognitive impairment: the Australia Diabetes, Obesity and Lifestyle Study Wave 3

Objective: To determine prevalence of cognitive impairment (CI) and to estimate life expectancy with and without cognitive impairment in the Australian population over age 60. Method: Adults aged 60 and older participating in the 12 year follow-up of the Australia Diabetes Obesity and Lifestyle Study (AusDiab) were included in the sample (n=1666). The mean age was 69.5 years, and 46.3% of the sample was male. The Mini-Mental State Examination was used to assess cognitive impairment. Logistic regression analysis was used to determine the effect of predictor variables (age, gender, education), measured at baseline, on cognitive impairment status. The Sullivan Method was used to estimate Total Life Expectancy (TLE), Cognitively Impaired (CILE) and Cognitive Impairment-free life expectancies (CIFLE). Results: Odds of CI were greater for males than females (OR 2.1, 95% confidence interval: 1.2-3.7) and among Australians with low education levels compared with Australians with high education levels (OR 2.1, 95% confidence interval: 1.2-3.7). The odds of CI also increased each year with age (OR 1.1, (95% confidence interval: 1.0-1.1). It was found that in all age groups females have greater TLE and CIFLE when compared to their male counterparts.This research was supported by the Australian Research Council Centre of Excellence in Population Aging Research (project number CE110001029). KJA is funded by NHMRC Fellowship #1002560. We acknowledge support from the NHMRC Dementia Collaborative Research Centres. The AusDiab study co-coordinated by the Baker IDI Heart and Diabetes Institute, gratefully acknowledges the support and assistance given by: K Anstey, B Atkins, B Balkau, E Barr, A Cameron, S Chadban, M de Courten, D Dunstan, A Kavanagh, D Magliano, S Murray, N Owen, K Polkinghorne, J Shaw, T Welborn, P Zimmet and all the study participants. Also, for funding or logistical support, we are grateful to: National Health and Medical Research Council (NHMRC grants 233200 and 1007544), Australian Government Department of Health and Aging, Abbott Australasia Pty Ltd, Alphapharm Pty Ltd, Amgen Australia, AstraZeneca, Bristol-Myers Squibb, City Health Centre-Diabetes Service-Canberra, Department of Health and Community Services- Northern Territory, Department of Health and Human Services– Tasmania, Department of Health–New South Wales, Department of Health–Western Australia, Department of Health–South Australia, Department of Human Services–Victoria, Diabetes Australia, Diabetes Australia Northern Territory, Eli Lilly Australia, Estate of the Late Edward Wilson, GlaxoSmithKline, Jack Brockhoff Foundation, Janssen-Cilag, Kidney Health Australia, Marian & FH Flack Trust, Menzies Research Institute, Merck Sharp & Dohme, Novartis Pharmaceuticals, Novo Nordisk Pharmaceuticals, Pfizer Pty Ltd, Pratt Foundation, Queensland Health, Roche Diagnostics Australia, Royal Prince Alfred Hospital, Sydney, Sanofi Aventis, sanofi-synthelabo, and the Victorian Government’s OIS Program

The effectiveness and cost effectiveness of dark chocolate consumption as prevention therapy in people at high risk of cardiovascular disease: best case scenario analysis using a Markov model

Objective To model the long term effectiveness and cost effectiveness of daily dark chocolate consumption in a population with metabolic syndrome at high risk of cardiovascular disease

Association of cognitive function with glucose tolerance and trajectories of glucose tolerance over 12 years in the AusDiab study

INTRODUCTION: We investigated the association between glucose tolerance status and trajectories of change in blood glucose, and cognitive function in adults aged 25 to 85. METHODS: The sample (n = 4547) was drawn from a national, population-based cohort study in Australia (AusDiab). Fasting plasma glucose (FPG), glycated haemoglobin (HbA1c) and general health were assessed at 0, 5 and 12 years. Covariates included age, education, body mass index, blood pressure and physical activity. At 12 years, participants completed assessments of memory, processing speed and verbal ability. RESULTS: Known diabetes at baseline was associated with slower processing speed at 12 years in both younger (25–59 years) and older (>60 years) age-groups. After 12 years of follow-up, adults aged < 60 with diabetes at baseline had a mean speed score of 49.17 (SE = 1.09) compared with 52.39 (SE = 0.20) in normals. Among younger males without diagnosed diabetes, reduced memory at 12 years was associated with higher HbA1c at 5 years (β = −0.91, SE = 0.26, p < 0.001). No effects were apparent for females or older males. Adjusting for insulin sensitivity (HOMA-%S) and hs-C reactive protein attenuated these associations, but depression and CVD risk did not. Latent class analysis was used to analyse the associations between trajectories of HbA1C and glucose over 12 years, and cognition. Identified classes were described as 1) normal and stable blood glucose over time (reference), 2) high intercept but stable blood glucose over time, and 3) increasing blood glucose over time. In both young males and females, high stable glucose measures were associated with poorer cognitive function after 12 years. CONCLUSIONS: Those with type 2 diabetes, younger males with high non-diabetic HbA1c, and adults with high stable blood glucose are at increased risk of poorer cognition. The findings reinforce the need for management of diabetes risk factors in midlife.For funding or logistical support, the authors are grateful to the National Health and Medical Research Council (NHMRC grants 233200 and 1007544), the Australian Government Department of Health and Ageing, Abbott Australasia Pty Ltd, Alphapharm Pty Ltd, Amgen Australia, AstraZeneca, Bristol-Myers Squibb, City Health Centre—Diabetes Service—Canberra, Department of Health and Community Services—Northern Territory, Department of Health and Human Services—Tasmania, Department of Health—New South Wales, Department of Health—Western Australia, Department of Health—South Australia, Department of Human Services— Victoria, Diabetes Australia, Diabetes Australia Northern Territory, Eli Lilly Australia, Estate of the Late Edward Wilson, GlaxoSmithKline, Jack Brockhoff Foundation, Janssen-Cilag, Kidney Health Australia, Marian & FH Flack Trust, Menzies Research Institute, Merck Sharp & Dohme, Novartis Pharmaceuticals, Novo Nordisk Pharmaceuticals, Pfizer Pty Ltd, Pratt Foundation, Queensland Health, Roche Diagnostics Australia, Royal Prince Alfred Hospital, Sydney, Sanofi Aventis, sanofi-synthelabo, and the Victorian Government’s OIS Program. KJA is funded by NHMRC Research Fellowship No. 1002560. JES is funded by NHMRC Research Fellowship No. 586623

Incidence of cardiovascular risk factors by education level 2000-2005 : the Australian diabetes, obesity and lifestyle (AusDiab) cohort study

Lower socioeconomic status (SES) is associated with a higher prevalence of major risk factors for cardiovascular disease (CVD). However, few longitudinal studies have examined the association between SES and CVD risk factors over time. We aimed to determine whether SES, using education as a proxy, is associated with the onset of CVD risk factors over 5 years in an Australian adult cohort study. Participants in the Australian Diabetes, Obesity and Lifestyle study (AusDiab) study aged 25 years and over who attended both baseline and 5-year follow-up examinations (n=5 967) were categorised according to educational attainment. Cardiovascular risk factor data at both time points were ascertained through questionnaire and physical measurement. Women with lower education had a greater risk of progressing from normal weight to overweight or obesity than those with higher education (age-adjusted OR 1.57, 95% CI 1.06-2.31). Both men and women with lower education were more likely to develop diabetes (age-adjusted OR from higher education 1.75, 95% CI 1.14-2.71 and 3.01, 95% CI 1.26-7.20, respectively). A lower level of education was associated with a greater number of risk factors accumulated over time in women (OR of progressing from having two or less risk factors at baseline to three or more at follow up, 2.04, 95% 1.32-3.14). In this Australian population-based study, lower educational attainment was associated with an increased risk of developing both individual and total CVD risk factors over a 5-year period. These findings suggest that SES inequalities in CVD will persist into the future.<br /

The neighbourhood environment and profiles of the metabolic syndrome

Background: There is a dearth of studies on how neighbourhood environmental attributes relate to the metabolic syndrome (MetS) and profiles of MetS components. We examined the associations of interrelated aspects of the neighbourhood environment, including air pollution, with MetS status and profiles of MetS components. Methods: We used socio-demographic and MetS-related data from 3681 urban adults who participated in the 3rd wave of the Australian Diabetes, Obesity and Lifestyle Study. Neighbourhood environmental attributes included area socio-economic status (SES), population density, street intersection density, non-commercial land use mix, percentages of commercial land, parkland and blue space. Annual average concentrations of NO2 and PM2.5 were estimated using satellite-based land-use regression models. Latent class analysis (LCA) identified homogenous groups (latent classes) of participants based on MetS components data. Participants were then classified into five metabolic profiles according to their MetS-components latent class and MetS status. Generalised additive mixed models were used to estimate relationships of environmental attributes with MetS status and metabolic profiles. Results: LCA yielded three latent classes, one including only participants without MetS ("Lower probability of MetS components" profile). The other two classes/profiles, consisting of participants with and without MetS, were "Medium-to-high probability of high fasting blood glucose, waist circumference and blood pressure" and "Higher probability of MetS components". Area SES was the only significant predictor of MetS status: participants from high SES areas were less likely to have MetS. Area SES, percentage of commercial land and NO2 were associated with the odds of membership to healthier metabolic profiles without MetS, while annual average concentration of PM2.5 was associated with unhealthier metabolic profiles with MetS. Conclusions: This study supports the utility of operationalising MetS as a combination of latent classes of MetS components and MetS status in studies of environmental correlates. Higher socio-economic advantage, good access to commercial services and low air pollution levels appear to independently contribute to different facets of metabolic health. Future research needs to consider conducting longitudinal studies using fine-grained environmental measures that more accurately characterise the neighbourhood environment in relation to behaviours or other mechanisms related to MetS and its components

Fasting triglycerides are positively associated with cardiovascular mortality risk in people with diabetes

Aims: We investigated the association of fasting triglycerides with cardiovascular disease (CVD) mortality. Methods and results: This cohort study included US adults from the National Health and Nutrition Examination Surveys from 1988 to 2014. CVD mortality outcomes were ascertained by linkage to the National Death Index records. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) of triglycerides for CVD mortality. The cohort included 26 570 adult participants, among which 3978 had diabetes. People with higher triglycerides had a higher prevalence of diabetes at baseline. The cohort was followed up for a mean of 12.0 years with 1492 CVD deaths recorded. A 1-natural-log-unit higher triglyceride was associated with a 30% higher multivariate-adjusted risk of CVD mortality in participants with diabetes (HR, 1.30; 95% CI, 1.08–1.56) but not in those without diabetes (HR, 0.95; 95% CI, 0.83–1.07). In participants with diabetes, people with high triglycerides (200–499 mg/dL) had a 44% (HR, 1.44; 95% CI, 1.12–1.85) higher multivariate-adjusted risk of CVD mortality compared with those with normal triglycerides (<150 mg/dL). The findings remained significant when diabetes was defined by fasting glucose levels alone, or after further adjustment for the use of lipid-lowering medications, or after the exclusion of those who took lipid-lowering medications. Conclusion: This study demonstrates that fasting triglycerides of ≥200 mg/dL are associated with an increased risk of CVD mortality in patients with diabetes but not in those without diabetes. Future clinical trials of new treatments to lower triglycerides should focus on patients with diabetes

Changes in the rates of weight and waist circumference gain in Australian adults over time: a longitudinal cohort study

OBJECTIVE: To assess in a single cohort whether annual weight and waist circumference (WC) change has varied over time. DESIGN: Longitudinal cohort study with three surveys (1) 1999/2000; (2) 2004/2005 and (3) 2011/2012. Generalised linear mixed models with random effects were used to compare annualised weight and WC change between surveys 1 and 2 (period 1) with that between surveys 2 and 3 (period 2). Models were adjusted for age to analyse changes with time rather than age. Models were additionally adjusted for sex, education status, area-level socioeconomic disadvantage, ethnicity, body mass index, diabetes status and smoking status. SETTING: The Australian Diabetes, Obesity and Lifestyle study (AusDiab)-a population-based, stratified-cluster survey of 11247 adults aged &ge;25 years. PARTICIPANTS: 3351 Australian adults who attended each of three surveys and had complete measures of weight, WC and covariates. PRIMARY OUTCOME MEASURES: Weight and WC were measured at each survey. Change in weight and WC was annualised for comparison between the two periods. RESULTS: Mean weight and WC increased in both periods (0.34 kg/year, 0.43 cm/year period 1; 0.13 kg/year, 0.46 cm/year period 2). Annualised weight gain in period 2 was 0.11 kg/year (95% CI 0.06 to 0.15) less than period 1. Lesser annual weight gain between the two periods was not seen for those with greatest area-level socioeconomic disadvantage, or in men over the age of 55. In contrast, the annualised WC increase in period 2 was greater than period 1 (0.07 cm/year, 95% CI 0.01 to 0.12). The increase was greatest in men aged 55+ years and those with a greater area-level socioeconomic disadvantage. CONCLUSIONS: Between 2004/2005 and 2011/2012, Australian adults in a national study continued to gain weight, but more slowly than 1999/2000-2004/2005. While weight gain may be slowing, this was not observed for older men or those in more disadvantaged groups, and the same cannot be said for WC

The neighbourhood environment and profiles of the metabolic syndrome

Background There is a dearth of studies on how neighbourhood environmental attributes relate to the metabolic syndrome (MetS) and profiles of MetS components. We examined the associations of interrelated aspects of the neighbourhood environment, including air pollution, with MetS status and profiles of MetS components. Methods We used socio-demographic and MetS-related data from 3681 urban adults who participated in the 3rd wave of the Australian Diabetes, Obesity and Lifestyle Study. Neighbourhood environmental attributes included area socio-economic status (SES), population density, street intersection density, non-commercial land use mix, percentages of commercial land, parkland and blue space. Annual average concentrations of NO2 and PM2.5 were estimated using satellite-based land-use regression models. Latent class analysis (LCA) identified homogenous groups (latent classes) of participants based on MetS components data. Participants were then classified into five metabolic profiles according to their MetS-components latent class and MetS status. Generalised additive mixed models were used to estimate relationships of environmental attributes with MetS status and metabolic profiles. Results LCA yielded three latent classes, one including only participants without MetS (“Lower probability of MetS components” profile). The other two classes/profiles, consisting of participants with and without MetS, were “Medium-to-high probability of high fasting blood glucose, waist circumference and blood pressure” and “Higher probability of MetS components”. Area SES was the only significant predictor of MetS status: participants from high SES areas were less likely to have MetS. Area SES, percentage of commercial land and NO2 were associated with the odds of membership to healthier metabolic profiles without MetS, while annual average concentration of PM2.5 was associated with unhealthier metabolic profiles with MetS. Conclusions This study supports the utility of operationalising MetS as a combination of latent classes of MetS components and MetS status in studies of environmental correlates. Higher socio-economic advantage, good access to commercial services and low air pollution levels appear to independently contribute to different facets of metabolic health. Future research needs to consider conducting longitudinal studies using fine-grained environmental measures that more accurately characterise the neighbourhood environment in relation to behaviours or other mechanisms related to MetS and its components

Associations between Traffic-Related Air Pollution and Cognitive Function in Australian Urban Settings: The Moderating Role of Diabetes Status

Traffic-related air pollution (TRAP) is associated with lower cognitive function and diabetes in older adults, but little is known about whether diabetes status moderates the impact of TRAP on older adult cognitive function. We analysed cross-sectional data from 4141 adults who participated in the Australian Diabetes, Obesity and Lifestyle (AusDiab) study in 2011–2012. TRAP exposure was estimated using major and minor road density within multiple residential buffers. Cognitive function was assessed with validated psychometric scales, including: California Verbal Learning Test (memory) and Symbol–Digit Modalities Test (processing speed). Diabetes status was measured using oral glucose tolerance tests. We observed positive associations of some total road density measures with memory but not processing speed. Minor road density was not associated with cognitive function, while major road density showed positive associations with memory and processing speed among larger buffers. Within a 300 m buffer, the relationship between TRAP and memory tended to be positive in controls (β = 0.005; p = 0.062), but negative in people with diabetes (β = −0.013; p = 0.026) and negatively associated with processing speed in people with diabetes only (β = −0.047; p = 0.059). Increased TRAP exposure may be positively associated with cognitive function among urban-dwelling people, but this benefit may not extend to those with diabetes

Both low and high levels of low-density lipoprotein cholesterol are risk factors for diabetes diagnosis in Chinese adults

Aims: This study aimed to investigate whether both high and low levels of low-density lipoprotein cholesterol (LDL-C), i.e., hypercholesterolemia and hypocholesterolemia, were associated with diabetes in Chinese adults. Methods: This cross-sectional study included 22,557 Chinese adults. The LDL-C reference interval was determined from a healthy sub-cohort. Associations between hypocholesterolemia or hypercholesterolemia with diabetes were analyzed using binary logistic regression. Results: The LDL-C reference interval was 1.48–3.77 mmol/L (57.23–145.78 mg/dL). Therefore, hypocholesterolemia, normocholesterolemia, and hypercholesterolemia were defined as an LDL-C concentration of 3.77 mmol/L, respectively. Prevalence of diabetes was higher in people with hypocholesterolemia or hypercholesterolemia than that in people with normocholesterolemia. Hypocholesterolemia was associated with an increased multivariable-adjusted risk for diabetes diagnosis (odds ratio, 1.57; 95% confidence interval, 1.18–2.08), and so was hypercholesterolemia (odds ratio, 1.29; 95% confidence interval, 1.10–1.51). The results remained significant after exclusion of those who took lipid-lowering drugs from the analysis. Conclusions: This study demonstrated that both low and high levels of LDL-C were associated with a higher risk of diabetes diagnosis. Patients with either high or low LDL-C may need to be closely monitored for the risk of diabetes