Dose-response relationship between physical exercise and risk of physician-diagnosed dementia in 206 073 Thai community-dwelling men and women: HCUR study.

BACKGROUND AND PURPOSE: Little evidence exists to describe the incidence and risk factors for dementia in developing countries. This study aimed to examine the incidence and factors associated with the risk of developing dementia in a Thai general population. METHODS: Data on 206 073 men and women aged ≥50 years participating in the Health Check Ubon Ratchathani Project in 2006 were merged with diagnostic information from the hospital's electronic medical records in the following 6 years (2006-2012). The incidence of physician-diagnosed dementia over 6 years was examined. Factors associated with the risk of developing dementia were examined using multivariate Cox proportional hazard regression. RESULTS: Over a total time at risk of 1 196 433 person-years, 480 individuals developed dementia; the incidence rate was 0.40 [95% confidence interval (CI) 0.37-0.44] per 1000 person-years. Dementia incidence rose exponentially with increasing age to 1.37 (95% CI 1.07-1.75) per 1000 person-years in those aged 80-84 years and dropped after the age of 85 years. Factors independently associated with the risk of developing dementia included increasing age, diabetes and lack of physical exercise. The risk of dementia rose by 7% for every 1 year of age older [adjusted hazard ratio (aHR) 1.07, 95% CI 1.06-1.08]. Diabetes increased the risk of dementia by 51% (aHR 1.51, 95% CI 1.12-2.03). Compared to no physical exercise, having 3-5 days/week and> 5 days/week of physical exercise reduced the risk of dementia by 37% and 59% (aHR 0.63, 95% CI 0.50-0.79, and 0.41, 95% CI 0.26-0.66, respectively). CONCLUSIONS: Dementia incidence in a Thai population was lower than Western populations and its independent risk factors included increasing age, diabetes and a lack of physical exercise. Adequate physical exercise may counterbalance the ageing process, the main drive of dementia.

Change in HbA1c over 3 years does not improve the prediction of cardiovascular disease over and above HbA1c measured at a single time point.

AIMS/HYPOTHESIS: HbA1c is an important risk factor for cardiovascular disease (CVD), with 1% higher HbA1c levels associated with a 10-20% increased risk of CVD. Little is known about the association between change in HbA1c over time and cardiovascular risk in non-diabetic populations. This study examined the association between change in HbA1c over time and cardiovascular risk in a non-diabetic British population. METHODS: We used data on HbA1c collected at baseline and at a second health examination 3 years later among a population of 5,790 non-diabetic men and women who participated in the European Prospective Investigation of Cancer (EPIC)-Norfolk. The association between change in HbA1c over 3 years and incident cardiovascular events over the following 8 years was examined using multivariate Cox regression. We also examined whether information on change in HbA1c over time improved prediction of cardiovascular events over a single measure of HbA1c by comparing the area under the receiver operating characteristic curves (aROC) and computing the net reclassification improvement. RESULTS: The mean change (SD) in HbA1c over 3 years was 0.13% (0.52). During 44,596 person-years of follow-up, 529 cardiovascular events occurred (incidence 11.9 per 1,000 person-years). Each 0.5% rise in HbA1c over 3 years was associated with a 9% increase in risk of a cardiovascular event (HR 1.09; 95% CI 1.01, 1.18) after adjustment for baseline HbA1c and other major cardiovascular risk factors. However, change in HbA1c was not associated with cardiovascular risk after adjustment for HbA1c at follow-up. Multivariate models with and without information on change in HbA1c over time showed a similar aROC of 0.78. Adding change in HbA1c to the model with HbA1c at follow-up did not improve risk classification. CONCLUSIONS/INTERPRETATION: Addition of information on change in HbA1c over 3 years did not improve the prediction of CVD over and above information on HbA1c and other major cardiovascular risk factors from a single time point.

Estimating the potential population impact of stepwise screening strategies for identifying and treating individuals at high risk of Type 2 diabetes: a modelling study.

BACKGROUND: Diabetes risk assessment has been proposed as part of the National Health Service Health Checks programme, and HbA(1c) has recently been recommended as a diagnostic test for diabetes at a threshold of 48 mmol/mol (6.5%). We estimated the potential population impact of different stepwise screening strategies to identify individuals at high risk who might be offered preventive interventions. METHODS: Using data from 5910 participants in the European Prospective Investigation of Cancer (EPIC)-Norfolk cohort with HbA(1c) measurements, we modelled different stepwise screening strategies for identifying and treating individuals at high risk of Type 2 diabetes using different HbA(1c) cut-off points with and without a stage of prestratification. For each strategy, we estimated the number needed to have a diagnostic test, the number needed to treat to prevent one new case of Type 2 diabetes, and the number of new cases that could be prevented in the population over 3 years. Relative risk reductions for estimated effects of intensive lifestyle intervention were derived from the US Diabetes Prevention Program. RESULTS: Compared with inviting all individuals in an average primary care trust for a diagnostic test, a stepwise screening approach using simple routine data such as age and anthropometric indices could prevent a slightly lower number (lower-upper estimates) of new cases of Type 2 diabetes over 3 years (224 [130-359] and 193 [109-315] cases respectively) but would only require half the population to be invited for a diagnostic blood test. A total of 162 (88-274) cases could be prevented by inviting individuals with a Cambridge risk score of ≥ 0.15, with only 40% of the total population requiring diagnostic blood tests. Using a participant completed questionnaire for risk assessment (FINDRISC) was less effective, mainly relating to the questionnaire response rate. Providing preventive interventions to those with a lower HbA(1c) of 37-< 48 mmol/mol (5.5-< 6.5%) could prevent more cases but with a disproportionately higher workload, compared with using the recommended HbA(1c) threshold of 42-< 48 mmol/mol (6.0-< 6.5%). CONCLUSIONS: Compared with mass screening, an approach using routine data for risk stratification followed by an HbA(1c) test with a threshold of 42-< 48 mmol/mol (6.0-< 6.5%) for identifying individuals suitable for preventive interventions might prevent slightly fewer cases of Type 2 diabetes but with potential cost-savings.

Non-diabetic hyperglycaemia and cardiovascular risk: moving beyond categorisation to individual interpretation of absolute risk.

AIMS/HYPOTHESIS: Non-diabetic hyperglycaemia is usually not considered at all or is viewed as a binary risk category in isolation from other factors when quantifying cardiovascular risk. We argue that hyperglycaemia should be considered as a continuous risk factor and only in the context of other vascular risk factors. To examine the potential impact of hyperglycaemia on cardiovascular disease (CVD) risk, we calculated the absolute CVD risk in groups defined by different levels of HbA(1c) and other CVD risk factors. METHODS: We used data on 10,144 men and women from the European Prospective Investigation of Cancer-Norfolk cohort to calculate CVD rates across levels of HbA(1c) in groups characterised by different levels of traditional risk factors. RESULTS: We found significant differences in CVD rates across levels of HbA(1c) in groups defined by different levels of the other risk factors. CVD rates for non-diabetic individuals with an HbA(1c) of <5.5% increased from 0.6 (95% CI 0.3-1.2) to 29.6 (95% CI 14.8-59.1) per 1,000 person-years when traditional CVD risk factors were added sequentially to the lowest risk reference group. In most cases, non-diabetic individuals with an HbA(1c) of <5.5% and high values for all other CVD risk factors had substantially higher absolute CVD rates than those with an HbA(1c) of 6.0% to 6.4% but with no other raised CVD risk factors (29.6 [95% CI 14.8-59.1] and 2.5 [95% CI 0.4-18.1], respectively). A history of diabetes significantly increased CVD risk over the non-diabetic hyperglycaemia range. Comparisons of CVD rates across tertiles of total cholesterol:HDL-cholesterol ratio or mean systolic blood pressure in groups characterised by different levels of other risk factors showed similar findings. CONCLUSIONS/INTERPRETATION: In people with non-diabetic hyperglycaemia, cardiovascular risk is highly dependent on the presence of other CVD risk factors. Attention should be given not to whether an individual has 'pre-diabetes', 'hypertension' or 'hypercholesterolaemia', but to an integrated assessment of CVD risk, based on the combination of risk factors present and potential benefits of treatment.

Cardiovascular risk assessment scores for people with diabetes: a systematic review.

People with type 2 diabetes have an increased risk of cardiovascular disease (CVD). Multivariate cardiovascular risk scores have been used in many countries to identify individuals who are at high risk of CVD. These risk scores include those originally developed in individuals with diabetes and those developed in a general population. This article reviews the published evidence for the performance of CVD risk scores in diabetic patients by: (1) examining the overall rationale for using risk scores; (2) systematically reviewing the literature on available scores; and (3) exploring methodological issues surrounding the development, validation and comparison of risk scores. The predictive performance of cardiovascular risk scores varies substantially between different populations. There is little evidence to suggest that risk scores developed in individuals with diabetes estimate cardiovascular risk more accurately than those developed in the general population. The inconsistency in the methods used in evaluation studies makes it difficult to compare and summarise the predictive ability of risk scores. Overall, CVD risk scores rank individuals reasonably accurately and are therefore useful in the management of diabetes with regard to targeting therapy to patients at highest risk. However, due to the uncertainty in estimation of true risk, care is needed when using scores to communicate absolute CVD risk to individuals.