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Metabolic Markers Predict Insulin Resistance
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Am Fam Physician. 2004 Jun 15;69(12):2927.
The large number of overweight persons in the United States is increasing the incidence of type 2 diabetes mellitus and cardiovascular disease (CVD). Weight control might be enhanced if better identification of a high-risk population were available, particularly if weight reduction actually could decrease risk. Measurement of insulin resistance and compensatory hyperinsulinemia might provide a clue, because the prevalence of insulin resistance is increased in patients with type 2 diabetes mellitus, essential hypertension, and CVD. Unfortunately, measurement of insulin-meditated glucose disposal, which would represent insulin resistance, is not yet clinically practical. Measurement of plasma glucose or insulin levels in nondiabetic patients may help identify insulin-resistant patients. McLaughlin and associates attempted to develop a simple clinical approach to identify patients with insulin resistance.
The presence of a dyslipidemia characteristic of insulin-resistance might be a useful predictive tool. Plasma triglyceride and high-density lipoprotein (HDL) cholesterol levels, which are independently associated with insulin resistance, are predictors of CVD. Patients with a high ratio of triglycerides to HDL have an increased CVD risk independent of the more conventional risk factors. Because weight reduction is known to decrease CVD risk in overweight patients with disturbances in glucose and lipid metabolism, developing measurements to provide early identification of insulin resistance would be useful.
In their study, healthy persons with a body mass index of 25 or greater underwent testing to estimate insulin-mediated glucose disposal as a way to measure insulin activity. A steady-state plasma glucose concentration in the upper tertile of the 490 participants in a large database who were gathered for an ongoing 10-year research study was defined as insulin resistance. Fifty percent of the 258 overweight or obese participants in this study were in the most insulin-resistant tertile. Metabolic markers that were correlated with insulin resistance included insulin levels, triglyceride concentrations, and the triglyceride:HDL ratio.
The authors conclude that because insulin resistance is a risk factor for CVD, and weight reduction can decrease that risk, identification of overweight or obese patients who are insulin resistant can help direct weight reduction efforts. The plasma insulin level probably is most closely related to insulin resistance, but the absence of a standardized insulin assay decreases the clinical utility of this analysis. Plasma triglyceride levels and the triglyceride:HDL cholesterol ratio also accurately identify insulin resistance. The latter analysis is more attractive because of the consistent observation that low HDL cholesterol is related to CVD.
editor’s note: The presence of insulin resistance imparts a significantly higher relative risk of a cardiovascular event in patients with or without diabetes. Obesity and weight gain are associated with hypertension, hyperinsulinemia, and dyslipidemia. Weight increases of more than 10 percent over the 30 years starting at age 20 appear to be related to the insulin resistance syndrome in a linear manner.1 Clearly, weight gain from young to middle adulthood is a strong indicator of health risk. Diet and exercise have been found to improve insulin sensitivity, probably a result of weight reduction, in obese persons. The ability to identify patients with common risk factors who have the highest risk for insulin resistance or who are insulin resistant will allow us to concentrate our efforts on a particularly endangered group.—r.s.
McLaughlin T, et al. Use of metabolic markers to identify overweight individuals who are insulin resistant. Ann Intern Med. November 18, 2003;139:802–9.
1. Everson SA, Goldberg DE, Helmrich SP, Lakka TA, Lynch JW, Kaplan GA, et al. Weight gain and the risk of developing insulin resistance syndrome. Diabetes Care. 1998;21:1637–43.
Copyright © 2004 by the American Academy of Family Physicians.
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