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. 2010 Aug;33(8):1865-71.
doi: 10.2337/dc10-0641.

Epidemiology of type 2 diabetes and cardiovascular disease: translation from population to prevention: the Kelly West award lecture 2009

James B Meigs  1
Affiliations

Epidemiology of type 2 diabetes and cardiovascular disease: translation from population to prevention: the Kelly West award lecture 2009

James B Meigs. Diabetes Care. 2010 Aug.

Abstract

In the book Epidemiology of Diabetes and Its Vascular Lesions (1978), Kelly West summarized extant knowledge of the distribution and causes of diabetes. The 30 years of epidemiological research that followed have seen remarkable advances in the understanding of obesity as a risk factor for type 2 diabetes, and diabetes and pre-diabetes as risk factors for cardiovascular disease. Increasingly detailed understanding of these relationships has, unfortunately, been accompanied by an alarming increase in the prevalence of obesity, diabetes, and cardiovascular disease. West recognized that pre-diabetes is recognizable as what we now call metabolic syndrome. He predicted that novel insight into diabetes pathogenesis would come from biochemical and genetic epidemiology studies. He predicted that type 2 diabetes could be prevented by healthy lifestyle change. The challenge now is for us to translate these insights into effective strategies for the prevention of the modern epidemic of diabetes and vascular disease.

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Figures

Figure 1
Figure 1
Increasing rates of obesity are associated with increasing rates of diabetes, which in turn are associated with increasing rates of CVD in FHS. A: Shows the dramatically rising 30-year mortality-adjusted cumulative incidence rate of obesity (BMI ≥30 kg/m2) for men in different age-groups; the experience was similar among women (adapted from Vasan et al. [2]). B: Shows that the 8-year incidence rate of diabetes increased primarily in those with obesity (among both men and women) (adapted from Fox et al. [3]). C: Shows a 1.6-fold increase over time in the attributable risk percent for CVD associated with diabetes (arrows); among common CVD risk factors, only diabetes contributed significantly to increased rates of CVD (adapted from Fox et al. [5]). HTN, hypertension.
Figure 2
Figure 2
Type 2 diabetes and CVD risk factor clustering is called metabolic syndrome. A: Shows that the observed co-occurrence of two or more of elevated fasting glucose (FG), fasting insulin (FI), triglycerides (TG), blood pressure (BP), BMI, or low HDL cholesterol (all defined in A as the extreme 20th percentile, light gray bars for women and dark gray bars for men) co-occur to a far greater degree than would be expected by change alone (compared with a binomial distribution, dashed line, P < 0.0001). B: Shows that the pattern of risk factor clustering for these risk factors (including, as well, glucose levels 2 h after an oral glucose tolerance test [2-h G] and waist-to-hip ratio [WHR]) represent three clinically identifiable phenotypes: impaired glucose tolerance (IGT), hypertension (HTN), and central obesity-dyslipidemia, linked together by obesity (in this figure, BMI) and fasting hyperinsulinemia (reflecting, in part, insulin resistance). C: Illustrates that obesity and insulin resistance constitute the common physiological antecedents leading to increased risk for the development of both type 2 diabetes (T2D) and CVD; the name currently applied to this phenomenon is metabolic syndrome. A and B are adapted from Wilson et al. (7) and Meigs et al. (8). DBP, diastolic blood pressure; SBP, systolic blood pressure.
Figure 3
Figure 3
Metabolic syndrome (MetS) is a risk factor for both type 2 diabetes (T2D) and CVD. A: Shows that among men in FHS, the 7- to 11-year risk for CVD increases from 1.5 for those with one or two MetS risk factors (RFs) to 4.0 for those with three or more (that is, with MetS) relative to those with no MetS risk factors, even after accounting for other CVD–specific risk factors. The bars in the figure represent the odds ratio and its 95% confidence bounds. The relative risk for CVD is 2.9 comparing MetS vs. no MetS. Risk for type 2 diabetes increases from 4.2 for men with one or two MetS risk factors to 24 for those with MetS relative to those with no MetS risk factors, even after accounting for other type 2 diabetes–specific risk factors. The relative risk for type 2 diabetes is 6.9 comparing MetS vs. no MetS. Patterns are similar for FHS women. Risk rises steadily in a dose-response relationship as the number of component traits increases and is increased regardless of which of the various heterogeneous combinations of specific traits are present, and even in the absence of impaired glycemia (B) (adapted from Wilson et al. [10]). BP, blood pressure; FG, fasting glucose; TG, triglycerides.
Figure 4
Figure 4
Plasma biomarkers of endothelial dysfunction predict both type 2 diabetes (T2D) and CVD. A: Shows the 7-year cumulative incidence of type 2 diabetes by quartile (Q1-Q4) of plasminogen activator inhibitor-1 (PAI-1) or von Willebrand factor (vWF). The type 2 diabetes–risk factor adjusted relative risk (RR) for type 2 diabetes per interquartile (IQR) increase in vWF was 1.4 (95% CI 1.1–1.8, P = 0.009) (adapted from Meigs et al. [21]). B: Shows survival free of CVD events in FHS as a function of the presence or absence of type 2 diabetes and by low (Q1-Q3) or high (Q4) levels of vWF. Risk of CVD is increased in individuals with elevated levels of vWF, especially in individuals with type 2 diabetes and elevated vWF (P < 0.0001) (adapted from Frankel et al. [22]). DM, diabetes mellitus.
Figure 5
Figure 5
A genetic risk score of 18 SNPs predicts type 2 diabetes. A: Shows the distribution of an 18-SNP genetic risk score, where FHS individuals were scored with a 0 if they had no risk alleles at a given SNP, one if they were heterozygous, and two if they were homozygous for the risk allele. Individuals who developed type 2 diabetes over 28 years of follow-up have about 0.6 more risk alleles than those who remain free of diabetes (P < 0.0001). B: Shows that risk for type 2 diabetes increases with increasing genetic risk burden. Those with 16–20 risk alleles have a risk of diabetes of 1.6, and those with ≥21 risk alleles have a risk of 2.5 relative to those with ≤15 risk alleles (P < 0.001). However, the genetic risk score does not discriminate those who will develop type 2 diabetes from those who will not after accounting for common clinical risk factors (age, sex, family history of diabetes, and metabolic syndrome traits). C: Shows that the area under the receiver operating characteristic curve (the C statistic) was 0.900 for a simple clinical model including clinical risk factors (gray line), and 0.901 for a model including clinical risk factors and the genetic risk score (black line) (adapted from Meigs et al. [[29]).
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References

    1. West KM: Epidemiology of diabetes and its vascular lesions. New York, Elsevier, 1978.
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