Adrian J. Cameron

Television Viewing Time and Mortality The Australian Diabetes, Obesity and Lifestyle Study (AusDiab)

Background— Television viewing time, the predominant leisure-time sedentary behavior, is associated with biomarkers of cardiometabolic risk, but its relationship with mortality has not been studied. We examined the associations of prolonged television viewing time with all-cause, cardiovascular disease (CVD), cancer, and non-CVD/noncancer mortality in Australian adults. Methods and Results— Television viewing time in relation to subsequent all-cause, CVD, and cancer mortality (median follow-up, 6.6 years) was examined among 8800 adults ≥25 years of age in the Australian Diabetes, Obesity and Lifestyle Study (AusDiab). During 58 087 person-years of follow-up, there were 284 deaths (87 CVD deaths, 125 cancer deaths). After adjustment for age, sex, waist circumference, and exercise, the hazard ratios for each 1-hour increment in television viewing time per day were 1.11 (95% confidence interval [CI], 1.03 to 1.20) for all-cause mortality, 1.18 (95% CI, 1.03 to 1.35) for CVD mortality, and 1.09 (95% CI, 0.96 to 1.23) for cancer mortality. Compared with a television viewing time of <2 h/d, the fully adjusted hazard ratios for all-cause mortality were 1.13 (95% CI, 0.87 to 1.36) for ≥2 to <4 h/d and 1.46 (95% CI, 1.04 to 2.05) for ≥4 h/d. For CVD mortality, corresponding hazard ratios were 1.19 (95% CI, 0.72 to 1.99) and 1.80 (95% CI, 1.00 to 3.25). The associations with both cancer mortality and non-CVD/noncancer mortality were not significant. Conclusions— Television viewing time was associated with increased risk of all-cause and CVD mortality. In addition to the promotion of exercise, chronic disease prevention strategies could focus on reducing sitting time, particularly prolonged television viewing.

Risk of Cardiovascular and All-Cause Mortality in Individuals With Diabetes Mellitus, Impaired Fasting Glucose, and Impaired Glucose Tolerance The Australian Diabetes, Obesity, and Lifestyle Study (AusDiab)

Background— Diabetes mellitus increases the risk of cardiovascular disease (CVD) and all-cause mortality. The relationship between milder elevations of blood glucose and mortality is less clear. This study investigated whether impaired fasting glucose and impaired glucose tolerance, as well as diabetes mellitus, increase the risk of all-cause and CVD mortality. Methods and Results— In 1999 to 2000, glucose tolerance status was determined in 10 428 participants of the Australian Diabetes, Obesity, and Lifestyle Study (AusDiab). After a median follow-up of 5.2 years, 298 deaths occurred (88 CVD deaths). Compared with those with normal glucose tolerance, the adjusted all-cause mortality hazard ratios (HRs) and 95% confidence intervals (CIs) for known diabetes mellitus and newly diagnosed diabetes mellitus were 2.3 (1.6 to 3.2) and 1.3 (0.9 to 2.0), respectively. The risk of death was also increased in those with impaired fasting glucose (HR 1.6, 95% CI 1.0 to 2.4) and impaired glucose tolerance (HR 1.5, 95% CI 1.1 to 2.0). Sixty-five percent of all those who died of CVD had known diabetes mellitus, newly diagnosed diabetes mellitus, impaired fasting glucose, or impaired glucose tolerance at baseline. Known diabetes mellitus (HR 2.6, 95% CI 1.4 to 4.7) and impaired fasting glucose (HR 2.5, 95% CI 1.2 to 5.1) were independent predictors for CVD mortality after adjustment for age, sex, and other traditional CVD risk factors, but impaired glucose tolerance was not (HR 1.2, 95% CI 0.7 to 2.2). Conclusions— This study emphasizes the strong association between abnormal glucose metabolism and mortality, and it suggests that this condition contributes to a large number of CVD deaths in the general population. CVD prevention may be warranted in people with all categories of abnormal glucose metabolism.

WAIST CIRCUMFERENCE, WAIST-HIP RATIO AND BODY MASS INDEX AND THEIR CORRELATION WITH CARDIOVASCULAR DISEASE RISK FACTORS IN AUSTRALIAN ADULTS

Objectives.  To compare body mass index (BMI), waist circumference and waist–hip ratio (WHR) as indices of obesity and assess the respective associations with type 2 diabetes, hypertension and dyslipidaemia.

The Australian Diabetes, Obesity and Lifestyle Study (AusDiab)--methods and response rates.

The Australian Diabetes, Obesity and Lifestyle Study (AusDiab) addresses the urgent need for data on diabetes prevalence, risk factors and associated conditions in Australia. Here we describe the methods used and the response rates obtained. AusDiab was a population-based cross-sectional survey of national diabetes mellitus prevalence and associated risk factors in people aged > or =25 years, conducted between May 1999 and December 2000 in the six states and the Northern Territory of Australia. The study involved an initial household interview, followed by a biomedical examination that included an oral glucose tolerance test (OGTT), standard anthropometric tests, blood pressure measurements and the administration of questionnaires. Of the 20347 eligible people (aged > or =25 years and resident at the address for > or =6 months) who completed a household interview, 11247 (55.3%) attended for the biomedical examination. Of those who completed the biomedical examination 55.1% were female. Comparisons with the 1998 Australian population estimates showed that younger age responders were under-represented at the biomedical examination, while the middle-aged and older age groups were over-represented. Weighting of the AusDiab data for age and gender have corrected for this bias. AusDiab, which is the largest national diabetes prevalence study undertaken in a developed nation to have used an OGTT, provides a valuable national resource for the study of the prevalence and possible causes of diabetes, as well as identifying possible risk factors that may lead to diabetes. Furthermore, it generates the baseline data for a prospective 5-year cohort study. The data will be important for national and regional public health and lifestyle education and health promotion programs.

Glucose indices, health behaviors, and incidence of diabetes in Australia: The Australian diabetes, obesity and lifestyle study

OBJECTIVE—This national, population-based study reports diabetes incidence based on oral glucose tolerance tests (OGTTs) and identifies risk factors for diabetes in Australians. RESEARCH DESIGN AND METHODS—The Australian Diabetes, Obesity and Lifestyle Study followed-up 5,842 participants over 5 years. Normal glycemia, impaired fasting glucose (IFG), impaired glucose tolerance (IGT), and diabetes were defined using World Health Organization criteria. RESULTS—Age-standardized annual incidence of diabetes for men and women was 0.8% (95% CI 0.6–0.9) and 0.7% (0.5–0.8), respectively. The annual incidence was 0.2% (0.2–0.3), 2.6% (1.8–3.4), and 3.5% (2.9–4.2) among those with normal glycemia, IFG, and IGT, respectively, at baseline. Among those with IFG, the incidence was significantly higher in women (4.0 vs. 2.0%), while among those with IGT, it was significantly higher in men (4.4 vs. 2.9%). Using multivariate logistic regression, hypertension (odds ratio 1.64 [95% CI 1.17–2.28]), hypertriglyceridemia (1.46 [1.05–2.02]), log fasting plasma glucose (odds ratio per 1 SD 5.25 [95% CI 3.98–6.92]), waist circumference (1.26 [1.08–1.48]), smoking (1.70 [96% CI 1.11–2.63]), physical inactivity (1.56 [1.12–2.16]), family history of diabetes (1.82 [1.30–2.52]), and low education level (1.85 [1.04–3.31]) were associated with incident diabetes. In age- and sex-adjusted models, A1C was a predictor of diabetes in the whole population, in those with normal glycemia, and in those with IGT or IFG. CONCLUSIONS—Diabetes incidence is 10–20 times greater in those with IGT or IFG than those with normal glycemia. Measures of glycemia, A1C, metabolic syndrome components, education level, smoking, and physical inactivity are risk factors for diabetes.

Glucose indices, health behaviours and incidence of diabetes in Australia: the AusDiab study.

OBJECTIVE—This national, population-based study reports diabetes incidence based on oral glucose tolerance tests (OGTTs) and identifies risk factors for diabetes in Australians. RESEARCH DESIGN AND METHODS—The Australian Diabetes, Obesity and Lifestyle Study followed-up 5,842 participants over 5 years. Normal glycemia, impaired fasting glucose (IFG), impaired glucose tolerance (IGT), and diabetes were defined using World Health Organization criteria. RESULTS—Age-standardized annual incidence of diabetes for men and women was 0.8% (95% CI 0.6–0.9) and 0.7% (0.5–0.8), respectively. The annual incidence was 0.2% (0.2–0.3), 2.6% (1.8–3.4), and 3.5% (2.9–4.2) among those with normal glycemia, IFG, and IGT, respectively, at baseline. Among those with IFG, the incidence was significantly higher in women (4.0 vs. 2.0%), while among those with IGT, it was significantly higher in men (4.4 vs. 2.9%). Using multivariate logistic regression, hypertension (odds ratio 1.64 [95% CI 1.17–2.28]), hypertriglyceridemia (1.46 [1.05–2.02]), log fasting plasma glucose (odds ratio per 1 SD 5.25 [95% CI 3.98–6.92]), waist circumference (1.26 [1.08–1.48]), smoking (1.70 [96% CI 1.11–2.63]), physical inactivity (1.56 [1.12–2.16]), family history of diabetes (1.82 [1.30–2.52]), and low education level (1.85 [1.04–3.31]) were associated with incident diabetes. In age- and sex-adjusted models, A1C was a predictor of diabetes in the whole population, in those with normal glycemia, and in those with IGT or IFG. CONCLUSIONS—Diabetes incidence is 10–20 times greater in those with IGT or IFG than those with normal glycemia. Measures of glycemia, A1C, metabolic syndrome components, education level, smoking, and physical inactivity are risk factors for diabetes.

A Parent-Focused Intervention to Reduce Infant Obesity Risk Behaviors: A Randomized Trial

OBJECTIVE: To assess the effectiveness of a parent-focused intervention on infants’ obesity-risk behaviors and BMI. METHODS: This cluster randomized controlled trial recruited 542 parents and their infants (mean age 3.8 months at baseline) from 62 first-time parent groups. Parents were offered six 2-hour dietitian-delivered sessions over 15 months focusing on parental knowledge, skills, and social support around infant feeding, diet, physical activity, and television viewing. Control group parents received 6 newsletters on nonobesity-focused themes; all parents received usual care from child health nurses. The primary outcomes of interest were child diet (3 × 24-hour diet recalls), child physical activity (accelerometry), and child TV viewing (parent report). Secondary outcomes included BMI z-scores (measured). Data were collected when children were 4, 9, and 20 months of age. RESULTS: Unadjusted analyses showed that, compared with controls, intervention group children consumed fewer grams of noncore drinks (mean difference = –4.45; 95% confidence interval [CI]: –7.92 to –0.99; P = .01) and were less likely to consume any noncore drinks (odds ratio = 0.48; 95% CI: 0.24 to 0.95; P = .034) midintervention (mean age 9 months). At intervention conclusion (mean age 19.8 months), intervention group children consumed fewer grams of sweet snacks (mean difference = –3.69; 95% CI: –6.41 to –0.96; P = .008) and viewed fewer daily minutes of television (mean difference = –15.97: 95% CI: –25.97 to –5.96; P = .002). There was little statistical evidence of differences in fruit, vegetable, savory snack, or water consumption or in BMI z-scores or physical activity. CONCLUSIONS: This intervention resulted in reductions in sweet snack consumption and television viewing in 20-month-old children.

Gender differences in the prevalence of impaired fasting glycaemia and impaired glucose tolerance in Mauritius. Does sex matter

Objective  To examine gender differences in the characteristics and prevalence of various categories of glucose tolerance in a population study in Mauritius.

Central Obesity as a Precursor to the Metabolic Syndrome in the AusDiab Study and Mauritius

Evidence from epidemiologic studies that central obesity precedes future metabolic change and does not occur concurrently with the appearance of the blood pressure, glucose, and lipid abnormalities that characterize the metabolic syndrome (MetS) has been lacking. Longitudinal surveys were conducted in Mauritius in 1987, 1992, and 1998, and in Australia in 2000 and 2005 (AusDiab). This analysis included men and women (aged ≥25 years) in three cohorts: AusDiab 2000–2005 (n = 5,039), Mauritius 1987–1992 (n = 2,849), and Mauritius 1987–1998 (n = 1,999). MetS components included waist circumference, systolic blood pressure, fasting and 2‐h postload plasma glucose, high‐density lipoprotein (HDL) cholesterol, triglycerides, and homeostasis model assessment of insulin sensitivity (HOMA‐S) (representing insulin sensitivity). Linear regression was used to determine which baseline components predicted deterioration in other MetS components over 5 years in AusDiab and 5 and 11 years in Mauritius, adjusted for age, sex, and ethnic group. Baseline waist circumference predicted deterioration (P < 0.01) in four of the other six MetS variables tested in AusDiab, five of six in Mauritius 1987–1992, and four of six in Mauritius 1987–1998. In contrast, an increase in waist circumference between baseline and follow‐up was only predicted by insulin sensitivity (HOMA‐S) at baseline, and only in one of the three cohorts. These results suggest that central obesity plays a central role in the development of the MetS and appears to precede the appearance of the other MetS components.

The metabolic syndrome as a tool for predicting future diabetes: the AusDiab study

Objective.  To compare the ability of the metabolic syndrome (MetS), a diabetes prediction model (DPM), a noninvasive risk questionnaire and individual glucose measurements to predict future diabetes.