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Dietary Fat and Carbohydrates Are Independently Associated With Circulating Insulin-Like Growth Factor 1 and Insulin-Like Growth Factor–Binding Protein 3 Concentrations in Healthy Adults

From the Division of Endocrinology, Department of Internal Medicine, Beth Israel Deaconess Medical Center, Boston, and Department of Internal Medicine, Newton Wellesley Hospital, Newton, MA; and Department of Epidemiology, Athens University Medical School, Athens, Greece.

Address reprint requests to Christos S. Mantzoros, MD, DSc, Endocrinology, RN 325, Beth Israel Deaconess Medical Center, 99 Brookline Ave, Boston, MA 02215; email cmantzor{at}bidmc.harvard.edu

PURPOSE: To evaluate and quantify the association between consumption of specific food groups/macronutrients and concentrations of serum insulin-like growth factor 1 (IGF-1) and insulin-like growth factor–binding protein 3 (IGFBP-3).

SUBJECTS AND METHODS: Data from a comprehensive food-frequency questionnaire administered to 115 healthy subjects were used to study cross-sectionally the relationship between nutritional factors and circulating IGF-1 and IGFBP-3 concentrations. Adjustment for the effect of total energy intake and a series of epidemiologic parameters (age, sex, height, body mass index, smoking, alcohol consumption, and coffee drinking) was implemented through multivariate linear regression.

RESULTS: We observed that serum levels of IGF-1 are positively associated with consumption of redmeats, fats, and oils. In addition, serum levels of IGF-1 are independently and positively associated with energy intake from lipids and negatively associated with energy intake from carbohydrates. Finally, serum levels of IGFBP-3 are independently and negatively associated with energy intake from saturated fat.

CONCLUSION: Serum IGF-1 and/or IGFBP-3 concentrations are associated with red meat, carbohydrate intake, and fat intake and, thus, may mediate the effect of these dietary factors on the pathogenesis of several disease states. Additional studies are needed to further quantify these associations and elucidate the underlying mechanisms.

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