title: Insulin resistance as a predictor of age-related diseases.
abstract: The current study was initiated to evaluate the ability of insulin resistance to predict a variety of age-related diseases. Baseline measurements of insulin resistance and related variables were made between 1988-1995 in 208 apparently healthy, nonobese (body mass index < 30 kg/m2) individuals, who were then evaluated 4-11 yr later (mean +/- SEM = 6.3 +/- 0.2 yr) for the appearance of the following age-related diseases: hypertension, coronary heart disease, stroke, cancer, and type 2 diabetes. The effect of insulin resistance on the development of clinical events was evaluated by dividing the study group into tertiles of insulin resistance at baseline and comparing the events in these 3 groups. Clinical endpoints (n = 40) were identified in 37 individuals (18%) of those evaluated, including 12 with hypertension, 3 with hypertension + type 2 diabetes, 9 with cancer, 7 with coronary heart disease, 4 with stroke, and 2 with type 2 diabetes. Twenty-eight out of the total 40 clinical events were seen in 25 individuals (36%) in the most insulin-resistant tertile, with the other 12 occurring in the group with an intermediate degree of insulin resistance. Furthermore, insulin resistance was an independent predictor of all clinical events, using both multiple logistic regression and Cox's proportional hazards analysis. The fact that an age-related clinical event developed in approximately 1 out of 3 healthy individuals in the upper tertile of insulin resistance at baseline, followed for an average of 6 yr, whereas no clinical events were observed in the most insulin-sensitive tertile, should serve as a strong stimulus to further efforts to define the role of insulin resistance in the genesis of age-related diseases.
authors.affiliation: Department of Medicine, Stanford University, School of Medicine Stanford, California 94305, USA.
authors.forename: F S
authors.initials: FS
authors.lastname: Facchini
authors.forename: N
authors.initials: N
authors.lastname: Hua
authors.forename: F
authors.initials: F
authors.lastname: Abbasi
authors.forename: G M
authors.initials: GM
authors.lastname: Reaven
mesh_terms: D000367:Age Factors; D000375:Aging / Q000502:physiology*; D001786:Blood Glucose / Q000378:metabolism; D001794:Blood Pressure; D015992:Body Mass Index; D002784:Cholesterol / Q000097:blood; D008076:Cholesterol, HDL / Q000097:blood; D008078:Cholesterol, LDL / Q000097:blood; D003327:Coronary Disease / Q000453:epidemiology*; D003924:Diabetes Mellitus, Type 2 / Q000453:epidemiology*; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D006973:Hypertension / Q000453:epidemiology*; D007328:Insulin / Q000097:blood; D007333:Insulin Resistance; D008297:Male; D008875:Middle Aged; D009369:Neoplasms / Q000453:epidemiology*; D011237:Predictive Value of Tests; D012044:Regression Analysis; D012737:Sex Factors; D020521:Stroke / Q000453:epidemiology*; D014280:Triglycerides / Q000097:blood
chemical_list: D001786:Blood Glucose; D008076:Cholesterol, HDL; D008078:Cholesterol, LDL; D007328:Insulin; D014280:Triglycerides; D002784:Cholesterol