Glucose Indices, Health Behaviors, and Incidence of Diabetes in Australia

Magliano, Dianna J.; Barr, Elizabeth L.M.; Zimmet, Paul; Cameron, Adrian J.; Dunstan, David W.; Colagiuri, Stephen; Jolley, Damien; Owen, Neville; Phillips, Patrick J.; Tapp, Robyn J.; Welborn, T.; Shaw, Jonathan E.

doi:10.2337/dc07-0912

Cited by 186 publications

(226 citation statements)

References 32 publications

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“…This discordance between indices of glucose metabolism has been observed by others, 1,4,12 is well documented in the able-bodied population, 13,14 and is likely because of the different metabolic determinants underlying impaired fasting glycemia and IGT. That is, IGT is thought to reflect peripheral insulin resistance, predominantly within skeletal muscle, whereas impaired fasting glycemia is thought to reflect hepatic insulin resistance and b-cell deficiency.…”

Section: Discussionsupporting

confidence: 56%

Glucose tolerance and physical activity level in people with spinal cord injury

et al. 2010

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Study design: Cross-sectional, observational study. Objectives: To evaluate the associations of physical activity and neurological lesion level with glucose tolerance in people with spinal cord injury (SCI). Setting: New South Wales, Australia. Methods: Twenty-five people (5 women, 20 men) with SCI (46 months post-injury) aged between 18 and 65 years were recruited. Exclusion criteria included known coronary heart disease, stroke or diabetes. Participants underwent an oral glucose tolerance test. Fasting and 2-h plasma glucose concentrations were classified according to the World Health Organization categories of glycemia. Participants also completed the Physical Activity Scale for Individuals with Physical Disabilities and mean MET-hours day À1 was calculated. Associations with the 2-h plasma glucose concentration were calculated through multiple and stepwise regressions. Results: Participants presented with complete or incomplete tetraplegia (n ¼ 11 TETRA) or complete or incomplete paraplegia (n ¼ 14 PARA) with neurological lesion levels ranging from C3/4 to T12. Mean 2-h plasma glucose was 7.13 ± 2.32 mmol l À1 . Nine participants had disordered glycemia (n ¼ 6 TETRA; n ¼ 3 PARA) and the remaining participants had normal glucose tolerance. Those participants with normal glucose tolerance participated in more moderate-vigorous and strength exercise and undertook more non-exercise-related mobility than those with disordered glycemia. Physical activity and age, but not lesion level were independent determinants of 2-h plasma glucose concentration (r ¼ 0.683, P ¼ 0.001), explaining 47% of the variance. Conclusion: Physical activity level is independently associated with glucose tolerance in people with SCI. Non-exercise activity may also be important for maintaining normal glycemia.

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Section: Discussionsupporting

confidence: 56%

Glucose tolerance and physical activity level in people with spinal cord injury

et al. 2010

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“…These low response rates and high loss to follow-up may mean that the proportion of people who underwent WC gain is not wholly reflective of the population incidence rates (16) . The low response rates could lead to either an under-or overestimation of weight gain (32) .…”

Section: Discussionmentioning

confidence: 99%

“…Plasma diabetes status was determined by a blood sample undertaken during the physical examination (16) .…”

Section: Methodsmentioning

confidence: 99%

“…Specifically, the study aimed at analysing the relationship between lifestyle behaviours including levels of physical activity, TV viewing time, smoking, alcohol consumption, energy intake, diet quality and portion size and change in WC. (16) . At baseline and follow-up, questionnaires were administered, anthropometric measurements were taken and a fasting blood sample was collected.…”

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confidence: 99%

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Predictors of increasing waist circumference in an Australian population

Walls

Magliano

McNeil

et al. 2010

Public Health Nutr.

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Objective: To identify predictors of increasing waist circumference (WC) over a 5-year period in a contemporary population of Australian adults. Design: Longitudinal national cohort of adults participating in the Australian Diabetes, Obesity and Lifestyle Study (AusDiab). Settings: Australian adults in 2000 and 2005. Subjects: A total of 2521 men and 2726 women aged $25 years at baseline who participated in AusDiab and provided anthropometric measurements at baseline (1999)(2000) and follow-up (2005). Results: A $5 % increase of baseline WC occurred in 27 % of men and 38 % of women over the 5-year period. In the multivariate analysis of the total population, there was a higher risk of $5 % gain in baseline WC in women, younger people, people with a lower baseline WC, people who never married compared with married/de facto, current smokers compared with never smokers, people with a poorer diet quality and people with a low energy intake. However, there was no significant association with many expected predictors of waist gain such as physical activity. There were some associations between other lifestyle factors and change of WC by sex, age, level of education and across WC categories, but the associations differed across these groups. Conclusions: A $5 % increase of baseline WC occurred in a significant proportion of men and women over the 5-year period. Of the behavioural factors, poor diet quality was the key predictor of the $5 % increase of baseline WC in this cohort. The findings highlight the need to understand better the causal role of lifestyle in regard to increasing WC over time. Keywords Waist circumferenceWeight gain Obesity Predictors DietRecent reports have shown faster increases in waist circumference (WC) than BMI (1,2) , suggesting that the nature of excess body weight may be changing over time to one of greater central adiposity, rather than a more peripheral distribution of body fat (1,2) . This has significant implications, considering that WC measures the central or abdominal distribution of excess body fat, which appears to be strongly correlated with metabolic and cardiovascular risk (3,4) . However, little is known about the drivers of increases in WC. Few studies have examined the predictors of increasing weight in adults, and we are not aware of any that have examined a range of behavioural lifestyle factors potentially predictive of abdominal weight gain. Table 1 summarises those studies exploring predictors of change in BMI, weight and/or WC. The only study we were able to source that explored behavioural predictors of change in WC examined a limited selection of predictors in women (5) . Previous cross-sectional analyses have found lifestyle factors such as higher television (TV) viewing time and lower levels of physical activity to be associated with higher WC (6)(7)(8)(9) , and studies analysing predictors of gain in BMI/weight have found associations with factors such as higher TV viewing time and lower levels of physical activity (5,(10)(11)(12)(13)(14) . Sternfeld et al...

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“…Prospective studies have shown that increased levels of physical activity can reduce progression to diabetes [5,6]. Recent population-based studies have examined the relationship between physical activity and overall progression to diabetes [7][8][9]. Most studies have classified physical activity into a two or three category variable not analysing dose-response relationships and not focusing on different types of physical activity (leisure, commuting and occupational) [10].…”

Section: Introductionmentioning

confidence: 99%

Differential relationship between physical activity and progression to diabetes by glucose tolerance status: the Inter99 Study

Engberg

Glümer²,

Witte

et al. 2009

Diabetologia

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Aims/hypothesis The aim of the study was to analyse how strongly commuting and leisure-time physical activity affect progression to diabetes and to study whether this relationship is different in individuals with isolated impaired fasting glucose (i-IFG) and isolated impaired glucose tolerance (i-IGT). Methods We studied the incidence of diabetes in 4,031 individuals without diabetes at baseline who participated in the baseline and 5 year follow-up examinations of a population-based primary prevention study, the Inter99 Study. Glucose tolerance status at baseline and at followup were based on OGTTs. Commuting and leisure-time physical activity at baseline were assessed by questionnaire. We present rate ratios from Poisson regression analyses adjusted for relevant confounders. Results The progression rate to diabetes was lower among physically active individuals in the total study population and particularly among those with i-IGT. The associations were attenuated and lost statistical significance after further adjustment for BMI. We observed no impact of physical activity on the progression to diabetes in individuals with i-IFG. Conclusions/interpretation Physical activity was associated with a lower progression to diabetes in the total study population and in individuals with i-IGT, a condition primarily characterised by muscle insulin resistance. Physical activity did not predict progression to diabetes in individuals with i-IFG, a condition primarily characterised by hepatic insulin resistance. Our results suggest that there is a differential relationship between physical activity and progression to diabetes among those with i-IFG and i-IGT. Therefore, clinical trials testing the effect of physical activity on progression from i-IFG to diabetes are needed.

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Glucose Indices, Health Behaviors, and Incidence of Diabetes in Australia

Cited by 186 publications

References 32 publications

Glucose tolerance and physical activity level in people with spinal cord injury

Glucose tolerance and physical activity level in people with spinal cord injury

Predictors of increasing waist circumference in an Australian population

Differential relationship between physical activity and progression to diabetes by glucose tolerance status: the Inter99 Study

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