Self-rated health scores predict mortality among people with type 2 diabetes differently across three different country groupings: findings from the ADVANCE and ADVANCE-ON trials.

AIMS: To explore whether there is a different strength of association between self-rated health and all-cause mortality in people with type 2 diabetes across three country groupings: nine countries grouped together as 'established market economies'; Asia; and Eastern Europe. METHODS: The ADVANCE trial and its post-trial follow-up were used in this study, which included 11 140 people with type 2 diabetes from 20 countries, with a median follow-up of 9.9 years. Self-rated health was reported on a 0-100 visual analogue scale. Cox proportional hazard models were fitted to estimate the relationship between the visual analogue scale score and all-cause mortality, controlling for a range of demographic and clinical risk factors. Interaction terms were used to assess whether the association between the visual analogue scale score and mortality varied across country groupings. RESULTS: The visual analogue scale score had different strengths of association with mortality in the three country groupings. A 10-point increase in visual analogue scale score was associated with a 15% (95% CI 12-18) lower mortality hazard in the established market economies, a 25% (95% CI 21-28) lower hazard in Asia, and an 8% (95% CI 3-13) lower hazard in Eastern Europe. CONCLUSIONS: Self-rated health appears to predict 10-year all-cause mortality for people with type 2 diabetes worldwide, but this relationship varies across groups of countries.

Modelling obesity trends in Australia: unravelling the past and predicting the future.

BACKGROUND/OBJECTIVES: Modelling is increasingly being used to predict the epidemiology of obesity progression and its consequences. The aims of this study were: (a) to present and validate a model for prediction of obesity among Australian adults and (b) to use the model to project the prevalence of obesity and severe obesity by 2025. SUBJECTS/METHODS: Individual level simulation combined with survey estimation techniques to model changing population body mass index (BMI) distribution over time. The model input population was derived from a nationally representative survey in 1995, representing over 12 million adults. Simulations were run for 30 years. The model was validated retrospectively and then used to predict obesity and severe obesity by 2025 among different aged cohorts and at a whole population level. RESULTS: The changing BMI distribution over time was well predicted by the model and projected prevalence of weight status groups agreed with population level data in 2008, 2012 and 2014.The model predicts more growth in obesity among younger than older adult cohorts. Projections at a whole population level, were that healthy weight will decline, overweight will remain steady, but obesity and severe obesity prevalence will continue to increase beyond 2016. Adult obesity prevalence was projected to increase from 19% in 1995 to 35% by 2025. Severe obesity (BMI>35), which was only around 5% in 1995, was projected to be 13% by 2025, two to three times the 1995 levels. CONCLUSIONS: The projected rise in obesity severe obesity will have more substantial cost and healthcare system implications than in previous decades. Having a robust epidemiological model is key to predicting these long-term costs and health outcomes into the future.

Estimating the effect of sulfonylurea on HbA1c in diabetes: a systematic review and meta-analysis.

AIMS/HYPOTHESIS: Sulfonylureas are widely prescribed glucose-lowering medications for diabetes, but the extent to which they improve glycaemia is poorly documented. This systematic review evaluates how sulfonylurea treatment affects glycaemic control. METHODS: Medline, EMBASE, the Cochrane Library and clinical trials registries were searched to identify double-blinded randomised controlled trials of fixed-dose sulfonylurea monotherapy or sulfonylurea added on to other glucose-lowering treatments. The primary outcome assessed was change in HbA1c, and secondary outcomes were adverse events, insulin dose and change in body weight. RESULTS: Thirty-one trials with a median duration of 16 weeks were included in the meta-analysis. Sulfonylurea monotherapy (nine trials) lowered HbA1c by 1.51% (17 mmol/mol) more than placebo (95% CI, 1.25, 1.78). Sulfonylureas added to oral diabetes treatment (four trials) lowered HbA1c by 1.62% (18 mmol/mol; 95% CI 1.0, 2.24) compared with the other treatment, and sulfonylurea added to insulin (17 trials) lowered HbA1c by 0.46% (6 mmol/mol; 95% CI 0.24, 0.69) and lowered insulin dose. Higher sulfonylurea doses did not reduce HbA1c more than lower doses. Sulfonylurea treatment resulted in more hypoglycaemic events (RR 2.41, 95% CI 1.41, 4.10) but did not significantly affect the number of other adverse events. Trial length, sulfonylurea type and duration of diabetes contributed to heterogeneity. CONCLUSIONS/INTERPRETATION: Sulfonylurea monotherapy lowered HbA1c level more than previously reported, and we found no evidence that increasing sulfonylurea doses resulted in lower HbA1c. HbA1c is a surrogate endpoint, and we were unable to examine long-term endpoints in these predominately short-term trials, but sulfonylureas appear to be associated with an increased risk of hypoglycaemic events.