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

How do older people with sight loss manage their general health? A qualitative study

Purpose: Older people with sight loss experience a number of barriers to managing their health. The purpose of this qualitative study was to explore how older people with sight loss manage their general health and explore the techniques used and strategies employed for health management. Methods: Semi-structured face-to-face interviews were conducted with 30 participants. Interviews were audio-recorded, transcribed verbatim and analysed using thematic analysis. Results: Health management challenges experienced included: managing multiple health conditions; accessing information; engaging in health behaviours and maintaining wellbeing. Positive strategies included: joining support groups, clubs and societies; using low vision aids; seeking support from family and friends and accessing support through health and social care services. Conclusion: Healthcare professionals need to be more aware of the challenges faced by older people with sight loss. Improved promotion of group support and charity services which are best placed to share information, provide fora to learn about coping techniques and strategies, and give older people social support to prevent isolation is needed. Rehabilitation and support services and equipment can only be beneficial if patients know what is available and how to access them. Over-reliance on self-advocacy in current healthcare systems is not conducive to patient-centred care. Implications for Rehabilitation Sight loss in older people can impact on many factors including health management. This study identifies challenges to health management and highlights strategies used by older people with sight loss to manage their health. Access to support often relies on patients seeking information for themselves. However, self-advocacy is challenging due to information accessibility barriers. Informal groups and charities play an important role in educating patients about their condition and advising on available support to facilitate health management

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

Fruit and vegetable knowledge and intake within an Australian population: The ausdiab study

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Understanding the relationship between fruit and vegetable knowledge (FVK) and fruit and vegetable intake (FVI) is an important consideration for improved public health and successful targeting of health promotion messaging. The aim of this study was to investigate the association between FVK and FVI in Australian adults and to identify subgroups most at risk of poor knowledge. Using data from the Australian Diabetes, Obesity, and Lifestyle Study (AusDiab), we investigated associations between FVK and FVI, as well as demographic and lifestyle factors. Baseline FVK was measured using two self-reported questions. FVI was assessed using a validated, self-reported, food frequency questionnaire in 1999/00 (baseline), 2004/05, and 2011/12. Amongst the 8966 participants assessed at baseline, 24.1% had adequate, 73.0% had insufficient, and 2.9% had poor FVK. Using linear regression, those with insufficient or poor FVK reported significantly lower FVI (grams/day) compared to those with adequate FVK: baseline (coefficient (95%CI)): −67.1 (−80.0, −54.3) and −124.0 (−142.9, −105.1), respectively, whilst, at 12 years, the differences were −42.5 (−54.6, −30.5) and −94.6 (−133.8, −55.5) grams/day, respectively (all p \u3c 0.001). Poor FVK was more likely to be reported in males, older individuals (\u3e65 years), socio-economically disadvantaged, smokers, and those with insufficient physical activity/sedentary behavior. We demonstrate that having adequate knowledge of FVI, defined as knowing to consume fruit and vegetables several times a day for a well-balanced diet, is strongly associated with FVI, with several demographic and lifestyle factors predicting FVK. Health promotion messages aimed at increasing FVK should target these subgroups for maximal effect

Abdominal obesity and other risk factors largely explain the high CRP in Indigenous Australians relative to the general population, but not gender differences: a cross-sectional study

Background: Previous studies reported high C-reactive protein (CRP) levels in Indigenous Australians, which may contribute to their high risk of cardiovascular disease. We compared CRP levels in Indigenous Australians and the general population, accounting for obesity and other risk factors.Methods: Cross-sectional study of CRP and risk factors (weight, height, waist and hip circumferences, blood pressure, lipids, blood glucose, and smoking status) in population-based samples from the Diabetes and Related conditions in Urban Indigenous people in the Darwin region (DRUID) study, and the Australian Diabetes, Obesity and Lifestyle study (AusDiab) follow-up.Results: CRP concentrations were higher in women than men and in DRUID than AusDiab. After multivariate adjustment, including waist circumference, the odds of high CRP (&gt;3.0 mg/L) in DRUID relative to AusDiab were no longer statistically significant, but elevated CRP was still more likely in women than men. After adjusting for BMI (instead of waist circumference) the odds for elevated CRP in DRUID participants were still higher relative to AusDiab participants among women, but not men. Lower HDL cholesterol, impaired glucose tolerance (IGT), and higher diastolic blood pressure were associated with having a high CRP in both men and women, while current smoking was associated with high CRP in men but not women.Conclusions: High concentrations of CRP in Indigenous participants were largely explained by other risk factors, in particular abdominal obesity. Irrespective of its independence as a risk factor, or its aetiological association with coronary heart disease (CHD), the high CRP levels in urban Indigenous women are likely to reflect increased vascular and metabolic risk. The significance of elevated CRP in Indigenous Australians should be investigated in future longitudinal studies

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

Associations of vegetable and potato intakes with markers of type 2 diabetes risk in the ausdiab cohort

Context: The associations of vegetable and potato intakes with type 2 diabetes (T2D) appear to be nuanced, depending on vegetable types and preparation method, respectively. Objective: We investigated the associations of total vegetable, vegetable subgroup, and potato intakes with (1) markers of T2D at baseline and (2) incident T2D cumulative over a 12-year follow-up period in Australian adults. Methods: Using data from the Australian Diabetes, Obesity and Lifestyle Study, intakes of vegetables and potatoes were assessed via a food frequency questionnaire at baseline. Associations between vegetable intake and (1) fasting plasma glucose (FPG), 2-hour postload plasma glucose (PLG), updated homeostasis model assessment of β-cell function (HOMA2-%β), HOMA2 of insulin sensitivity (HOMA2-%S), and fasting insulin levels at baseline; and (2) cumulative incident T2D at the end of 12-year follow-up were examined using generalized linear and Cox proportional hazards models, respectively. Results: In total, 8009 participants were included having median age of 52 years, and vegetable intake of 132 g/day. Higher intake of total vegetable, green leafy, yellow/orange/red, and moderate intakes of cruciferous vegetables was associated with lower PLG. Additionally, higher green leafy vegetable intake was associated with lower HOMA2-% and serum insulin. Conversely, higher potato fries/chips intakes were associated with higher FPG, HOMA2-% , serum insulin, and lower HOMA2-%S. Participants with moderate cruciferous vegetables intake had a 25% lower risk of T2D at the end of 12 years of follow-up. Conclusion: A higher intake of vegetables, particularly green leafy vegetables, may improve while consuming potato fries/chips, but not potatoes prepared in a healthy way, may worsen glucose tolerance and insulin sensitivity. Our findings suggest a nuanced relationship between vegetable subgroups and their impact on glucose toleranc

Associations between fruit intake and risk of diabetes in the AusDiab cohort

Context Fruit, but not fruit juice, intake is inversely associated with type 2 diabetes mellitus (T2DM). However, questions remain about the mechanisms by which fruits may confer protection. Objective The aims of this work were to examine associations between intake of fruit types and 1) measures of glucose tolerance and insulin sensitivity and 2) diabetes at follow-up. Methods Among participants of the Australian Diabetes, Obesity and Lifestyle Study, fruit and fruit juice intake was assessed by food frequency questionnaire at baseline. Associations between fruit and fruit juice intake and 1) fasting plasma glucose, 2-hour postload plasma glucose, updated homeostasis model assessment of insulin resistance of β-cell function (HOMA2-%β), HOMA2 of insulin sensitivity (HOMA2-%S), and fasting insulin levels at baseline and 2) the presence of diabetes at follow-up (5 and 12 years) were assessed using restricted cubic splines in logistic and linear regression models. Results This population of 7675 Australians (45% males) had a mean ± SD age of 54 ± 12 years at baseline. Total fruit intake was inversely associated with serum insulin and HOMA2-%β, and positively associated with HOMA2-%S at baseline. Compared to participants with the lowest intakes (quartile 1), participants with moderate total fruit intakes (quartile 3) had 36% lower odds of having diabetes at 5 years (odds ratio, 0.64; 95% CI, 0.44-0.92), after adjusting for dietary and lifestyle confounders. Associations with 12-year outcomes were not statistically significant. Conclusion A healthy diet including whole fruits, but not fruit juice, may play a role in mitigating T2DM risk