Risk prediction models for the development of diabetes in Mauritian Indians
ABSTRACT To develop risk prediction models of future diabetes in Mauritian Indians.
Three thousand and ninety-four Mauritian Indians (1141 men, aged 20-65 years) without diabetes in 1987 or 1992 were followed up to 1992 or 1998. Subjects underwent repeated oral glucose tolerance tests and diabetes was diagnosed according to 2006 World Health Organization/International Diabetes Federation criteria. Cox regression models for interval censored data were performed using data from 1544 randomly selected participants. Predicted probabilities for diabetes were calculated and validated in the remaining 1550 subjects.
Over 11 years of follow-up, there were 511 cases of diabetes. Among variables tested, family history of diabetes, obesity (body mass index, waist circumference) and glucose were significant predictors of diabetes. Predicted probabilities derived from a simple model fitted with sex, family history of diabetes and obesity ranged from 0.05 to 0.64 in men and 0.03 to 0.49 in women. To predict the onset of diabetes, area under the receiver operating characteristic (ROC) curve (AROC) of predicted probabilities was 0.62 (95% confidence interval, 0.56-0.68) in men and 0.64 (0.59-0.69) in women. At a cut-off point of 0.12, the sensitivity and specificity were 0.72 (0.71-0.74) and 0.47 (0.45-0.49) in men and 0.77 (0.75-0.78) and 0.50 (0.48-0.52) in women, respectively. Addition of fasting plasma glucose (FPG) to the model improved the prediction slightly [AROC curve 0.70 (0.65-0.76) in men, 0.71 (0.67-0.76) in women].
A diabetes prediction model based on obesity and family history yielded moderate discrimination in Mauritian Indians, which was slightly inferior to the model with the FPG but may be useful in low-income countries to promote identification of people at high risk of diabetes.
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ABSTRACT: Aims: To determine the gender-specific incidence and risk factors of type-2 diabetes mellitus (T2DM) in a general population. Methods: The study is based on 12,431 men and 13,737 women aged 25-98 years, attending the Tromsø Study in 1994 and followed through 2005, who did not have diabetes when entering the study. Sex-specific hazard ratios were estimated from Cox proportional hazard models. Results: A total of 522 cases of T2DM were registered, 308 among men and 214 among women. The age-standardised incidence rate was higher in men than in women, 2.6 (95% CI 2.32-2.90) and 1.6(95% CI 1.40-1.83) per 1000 person-years, respectively. In multivariate survival analysis, age, body mass index (BMI),triglycerides, high-density lipoprotein (HDL) cholesterol, hypertension, family history of diabetes, low education and smoking were independent predictors of T2DM in both genders (p<0.05). Total cholesterol and lack of leisure-time physical activity were independent predictors in men only. We found an interaction between HDL cholesterol and triglyceride levels(p<0.001) and between triglyceride levels and a positive family history of diabetes (p=.04). These interactions were independent of BMI. A positive family history combined with triglycerides in the highest tertile and BMI >25 kg/m(2) conveyed a 10-year risk of T2DM of 10% (95% CI 8-12%) vs. 0.2% (95% CI 0.08-0.31%) for the lowest risk group.Conclusions: A family history of diabetes, elevated BMI, and high triglyceride levels identifies independent of cardiovascular risk factors, a group with especially high risk of T2DM. [corrected]Scandinavian Journal of Public Health 11/2010; 38(7):768-75. DOI:10.1177/1403494810380299 · 3.13 Impact Factor
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ABSTRACT: We conducted a systematic review and meta-analysis, the first to our knowledge, summarizing and quantifying the published evidence on associations between type 2 diabetes incidence and socio-economic position (SEP) (measured by educational level, occupation and income) worldwide and when sub-divided into high-, middle- and low-income countries. Relevant case-control and cohort studies published between 1966 and January 2010 were searched in PubMed and EMBASE using the keywords: diabetes vs educational level, occupation or income. All identified citations were screened by one author, and two authors independently evaluated and extracted data from relevant publications. Risk estimates from individual studies were pooled using random-effects models quantifying the associations. Out of 5120 citations, 23 studies, including 41 measures of association, were found to be relevant. Compared with high educational level, occupation and income, low levels of these determinants were associated with an overall increased risk of type 2 diabetes; [relative risk (RR) = 1.41, 95% confidence interval (CI): 1.28-1.51], (RR = 1.31, 95% CI: 1.09-1.57) and (RR = 1.40, 95% CI: 1.04-1.88), respectively. The increased risks were independent of the income levels of countries, although based on limited data in middle- and low-income countries. The risk of getting type 2 diabetes was associated with low SEP in high-, middle- and low-income countries and overall. The strength of the associations was consistent in high-income countries, whereas there is a strong need for further investigation in middle- and low-income countries.International Journal of Epidemiology 02/2011; 40(3):804-18. DOI:10.1093/ije/dyr029 · 9.20 Impact Factor
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ABSTRACT: To evaluate how to most efficiently screen populations to detect people at high risk of incident Type 2 diabetes and those with prevalent, but undiagnosed, Type 2 diabetes. Data from 5814 adults in the Australian Diabetes, Obesity and Lifestyle study were used to examine four different types of screening strategies. The strategies incorporated various combinations of cut-points of fasting plasma glucose, the non-invasive Australian Type 2 Diabetes Risk Assessment Tool (AUSDRISK1) and a modified version of the tool incorporating fasting plasma glucose (AUSDRISK2). Sensitivity, specificity, positive predictive value, screening costs per case of incident or prevalent undiagnosed diabetes identified and intervention costs per case of diabetes prevented or reverted were compared. Of the four strategies that maximized sensitivity and specificity, use of the non-invasive AUSDRISK1, followed by AUSDRISK2 in those found to be at increased risk on AUSDRISK1, had the highest sensitivity (80.3%; 95% confidence interval 76.6-84.1%), specificity (78.1%; 95% confidence interval 76.9-79.2%) and positive predictive value (22.3%; 95% confidence interval 20.2-24.4%) for identifying people with either prevalent undiagnosed diabetes or future incident diabetes. It required the fewest people (24.1%; 95% confidence interval 23.0-25.2%) to enter lifestyle modification programmes, and also had the lowest intervention costs and combined costs of running screening and intervention programmes per case of diabetes prevented or reverted. Using a self-assessed diabetes risk score as an initial screening step, followed by a second risk score incorporating fasting plasma glucose, would maximize efficiency of identifying people with undiagnosed Type 2 diabetes and those at high risk of future diabetes.Diabetic Medicine 04/2011; 28(4):414-23. DOI:10.1111/j.1464-5491.2010.03188.x · 3.06 Impact Factor