Stephanie K. Tanamas

Adverse associations of car time with markers of cardio-metabolic risk

Objective To examine associations of time spent sitting in cars with markers of cardio-metabolic risk in Australian adults. Method Data were from 2800 participants (age range: 34–65) in the 2011–12 Australian Diabetes, Obesity and Lifestyle Study. Self-reported time spent in cars was categorized into four groups: ≤ 15 min/day; > 15 to ≤ 30 min/day; > 30 to ≤ 60 min/day; and > 60 min/day. Markers of cardio-metabolic risk were body mass index (BMI), waist circumference, systolic and diastolic blood pressure, triglycerides, HDL (high-density lipoprotein)-cholesterol, fasting plasma glucose, 2-h plasma glucose, a clustered cardio-metabolic risk score, and having the metabolic syndrome or not. Multilevel linear and logistic regression analyses examined associations of car time with each cardio-metabolic risk outcome, adjusting for socio-demographic and behavioral variables and medication use for blood pressure and cholesterol/triglycerides. Results Compared to spending 15 min/day or less in cars, spending more than 1 h/day in cars was significantly associated with higher BMI, waist circumference, fasting plasma glucose, and clustered cardio-metabolic risk, after adjusting for socio-demographic attributes and potentially relevant behaviors including leisure-time physical activity and dietary intake. Gender interactions showed car time to be associated with higher BMI in men only. Conclusions Prolonged time spent sitting in cars, in particular over 1 h/day, was associated with higher total and central adiposity and a more-adverse cardio-metabolic risk profile. Further studies, ideally using objective measures of sitting time in cars and prospective designs, are needed to confirm the impact of car use on cardio-metabolic disease risk.

Twelve‐year weight change, waist circumference change and incident obesity: The Australian diabetes, obesity and lifestyle study

This study aimed to describe the changes in weight and waist circumference (WC), examine the incidence of obesity as defined by body mass index (BMI) and WC, and describe the changes in the prevalence of obesity over 12 years.

Estimating the risk of cardiovascular disease using an obese-years metric

Objective To examine the association between obese-years and the risk of cardiovascular disease (CVD). Study design Prospective cohort study. Setting Boston, USA. Participants 5036 participants of the Framingham Heart Study were examined. Methods Obese-years was calculated by multiplying for each participant the number of body mass index (BMI) units above 29 kg/m2 by the number of years lived at that BMI during approximately 50 years of follow-up. The association between obese-years and CVD was analysed using time-dependent Cox regression adjusted for potential confounders and compared with other models using the Akaike information criterion (AIC). The lowest AIC indicated better fit. Primary outcome CVD. Results The median cumulative obese-years was 24 (range 2–556 obese-years). During 138 918 person-years of follow-up, 2753 (55%) participants were diagnosed with CVD. The incidence rates and adjusted HR (AHR) for CVD increased with an increase in the number of obese-years. AHR for the categories 1–24.9, 25–49.9, 50–74.9 and ≥75 obese-years were, respectively, 1.31 (95% CI 1.15 to 1.48), 1.37 (95% CI 1.14 to 1.65), 1.62 (95% CI 1.32 to 1.99) and 1.80 (95% CI 1.54 to 2.10) compared with those who were never obese (ie, had zero obese-years). The effect of obese-years was stronger in males than females. For every 10 unit increase in obese-years, the AHR of CVD increased by 6% (95% CI 4% to 8%) for males and 3% (95% CI 2% to 4%) for females. The AIC was lowest for the model containing obese-years compared with models containing either the level of BMI or the duration of obesity alone. Conclusions This study demonstrates that obese-years metric conceptually captures the cumulative damage of obesity on body systems, and is found to provide slightly more precise estimation of the risk of CVD than the level or duration of obesity alone.

Higher heart rate increases risk of diabetes among men: The Australian Diabetes Obesity and Lifestyle (AusDiab) Study

A very limited number of prospective studies have reported conflicting data on the relation between heart rate and diabetes risk. Our aim therefore was to determine in a large, national, population‐based cohort if heart rate predicts the development of diabetes.

Changing guards: time to move beyond body mass index for population monitoring of excess adiposity

With the obesity epidemic, and the effects of aging populations, human phenotypes have changed over two generations, possibly more dramatically than in other species previously. As obesity is an important and growing hazard for population health, we recommend a systematic evaluation of the optimal measure(s) for population-level excess body fat. Ideal measure(s) for monitoring body composition and obesity should be simple, as accurate and sensitive as possible, and provide good categorization of related health risks. Combinations of anthropometric markers or predictive equations may facilitate better use of anthropometric data than single measures to estimate body composition for populations. Here, we provide new evidence that increasing proportions of aging populations are at high health-risk according to waist circumference, but not body mass index (BMI), so continued use of BMI as the principal population-level measure substantially underestimates the health-burden from excess adiposity.

Quantifying the proportion of deaths due to body mass index- and waist circumference-defined obesity

To determine the risk of mortality associated with and quantify the deaths attributable to combinations of body mass index (BMI) and waist circumference (WC).

Duration of obesity and incident hypertension in adults from the Framingham Heart Study

Background: Previous studies exploring the association between obesity and hypertension generally used a single baseline measurement of obesity. The effect of accumulating excess adiposity over time on the risk of hypertension is uncertain. This study aimed to examine the relationship between duration of obesity and incident hypertension using the Framingham Heart Study. Methods: Two thousand, nine hundred and fifty-three participants aged 30–62 years without baseline hypertension were included. Blood pressure, height and weight were measured biennially. Duration of obesity was calculated. Time to incident hypertension was analysed using time-varying Cox proportional hazards regression with age as the time scale and censoring at time of death or end of follow-up. Results: Eighty percent of participants developed hypertension (median follow-up 15.9 years). A positive association between obesity duration and incident hypertension was observed in women. There was no longer an association when time-varying BMI was adjusted for (hazard ratio 0.95; (95% confidence interval 0.85–1.05)). Conclusion: These findings suggest that the mechanism by which excess adiposity may increase blood pressure is primarily immediate and that long-term exposure to obesity does not further increase the risk of developing hypertension beyond the level of BMI attained.

Advanced Glycation End Products Predict Loss of Renal Function and Correlate With Lesions of Diabetic Kidney Disease in American Indians With Type 2 Diabetes

We examined associations of advanced glycation end products (AGEs) with renal function loss (RFL) and its structural determinants in American Indians with type 2 diabetes. Data were from a 6-year clinical trial that assessed renoprotective efficacy of losartan. Participants remained under observation after the trial concluded. Glomerular filtration rate (GFR) was measured annually. Kidney biopsies were performed at the end of the trial. Five AGEs were measured in serum collected at enrollment and at kidney biopsy. RFL was defined as ≥40% decline of measured GFR from baseline. Of 168 participants (mean baseline age 41 years, HbA1c 9.2%, GFR 164 mL/min, and albumin-to-creatinine ratio 31 mg/g), 104 reached the RFL end point during median follow-up of 8.0 years. After multivariable adjustment, each doubling of carboxyethyl lysine (hazard ratio [HR] 1.60 [95% CI 1.08–2.37]) or methylglyoxal hydroimidazolone (HR 1.30 [95% CI 1.02–1.65]) concentration was associated with RFL. Carboxyethyl lysine, carboxymethyl lysine, and methylglyoxal hydroimidazolone correlated positively with cortical interstitial fractional volume (partial r = 0.23, P = 0.03; partial r = 0.25, P = 0.02; and partial r = 0.31, P = 0.003, respectively). Glyoxyl hydroimidazolone and methylglyoxal hydroimidazolone correlated negatively with total filtration surface per glomerulus (partial r = −0.26, P = 0.01; and partial r = −0.21, P = 0.046, respectively). AGEs improve prediction of RFL and its major structural correlates.

Neighborhood environmental attributes and adults' maintenance of regular walking.

PURPOSE Environmental initiatives to support walking are keys to noncommunicable disease prevention, but the relevant evidence comes mainly from cross-sectional studies. We examined neighborhood environmental attributes associated cross-sectionally with walking and those associated prospectively with walking maintenance. METHODS Data were from the Australian Diabetes, Obesity and Lifestyle study collected in 2004-2005 (baseline) and in 2011-2012 (follow-up). Participants who did not move residence during the study period (n = 2684, age range: 30-77 yr at baseline) were categorized as regular walkers (walked five times per week or more) or not at baseline. Regular walkers were divided into those who stopped and those who maintained regular walking at follow-up. Regression analyses examined relationships of regular walking and walking maintenance with perceived attributes of neighborhood destinations and pedestrian environments. RESULTS Regular walking at baseline was significantly associated with availability of shops (odds ratio [OR] = 1.13, 95% confidence interval [CI] = 1.04-1.22), many alternative routes (OR = 1.12, 95% CI = 1.01-1.23), park or nature reserve (OR = 1.13, 95% CI = 1.02-1.26), bicycle or walking tracks (OR = 1.08, 95% CI = 1.00-1.17), and feeling safe to walk (OR = 1.18, 95% CI = 1.01-1.38). Maintenance of regular walking was associated with the availability of multiple alternative routes (OR = 1.19, 95% CI = 1.03-1.38). Having many alternative routes and walking tracks was associated with walking maintenance among those who were not or had stopped working. CONCLUSIONS Neighborhood destinations (shops and parks) and pedestrian environments (alternative routes, walking trails, and safety from crime) were found to be associated with regular walking, but only pedestrian environment attributes were found to be related to the maintenance of regular walking. Further evidence from prospective studies is required to identify other neighborhood environmental attributes that might support walking maintenance.

The performance of diabetes risk prediction models in new populations: the role of ethnicity of the development cohort

It is believed that diabetes risk scores need to be ethnic specific. However, this prerequisite has not been tested. We examined the performance of several risk models, developed in various populations, in a Europid and a South Asian population. The performance of 14 published risk prediction models were tested in two prospective studies: the Australian Diabetes, Obesity and Lifestyle (AusDiab) study and the Mauritius non-communicable diseases survey. Eight models were developed in Europid populations; the remainder in various non-Europid populations. Model performance was assessed using area under the receiver operating characteristic curves (discrimination), Hosmer–Lemeshow tests (goodness-of-fit) and Brier scores (accuracy). In both AusDiab and Mauritius, discrimination was highest for a model developed in a mixed population (non-Hispanic white and African American) and lowest for a model developed in a Europid population. Discrimination for all scores was higher in AusDiab than in Mauritius. For almost all models, goodness-of-fit was poor irrespective of the ethnicity of the development cohort, and accuracy was higher in AusDiab compared to Mauritius. Our results suggest that similarity of ethnicity or similarity of diabetes risk may not be the best way of identifying models that will perform well in another population. Differences in study methodology likely account for much of the difference in the performance. Thus, identifying models which use measurements that are clearly described and easily reproducible for both research and clinical settings may be more important.