Advanced search
1 file | 605.65 KB

Total body fat and central fat mass independently predict insulin resistance but not hyperandrogenemia in women with polycystic ovary syndrome

Author
Organization
Abstract
Context/Objective: Obesity is a common feature of women with polycystic ovary syndrome (PCOS). The aim of this study was to assess the role of body fat on insulin resistance and androgen excess in these subjects. Patients/Design: One hundred sixteen consecutive Caucasian women with PCOS, diagnosed by the Rotterdam criteria, underwent accurate assessment of clinical, anthropometric, hormonal, and metabolic features. In particular, total fat mass and fat distribution were assessed by dual-energy x-ray absorptiometry, serum-free T by liquid chromatography mass spectrometry and equilibrium dialysis and insulin sensitivity by the glucose clamp technique. Results: Total fat mass and truncal fat were significantly higher in insulin-resistant than in insulin-sensitive PCOS subjects (+/- 89% and +127%, respectively, both P < .001), and both tended to be higher in hyperandrogenemic than in normoandrogenemic women (+22% and +28%, respectively, P = .087 and P = .090). All parameters of adiposity correlated inversely with insulin sensitivity (P < .001) and directly with serum-free T (P <= .001). A statistically significant inverse relationship was observed between insulin sensitivity and serum-free T concentrations (r = -0.527, P < .001). In a multiple regression analysis, either total fat mass or truncal fat, in addition to serum-free T and age, were independent predictors of insulin sensitivity. However, insulin sensitivity, but not total fat mass or truncal fat, was an independent predictor of free T concentrations. Conclusions: These data suggest that body fat contributes to determining insulin resistance in PCOS women. However, the association between body fat and hyperandrogenism seems to be to a large extent explained by insulin resistance.
Keywords
SYNDROME PCOS, X-RAY ABSORPTIOMETRY, METABOLIC SYNDROME, GLOBAL ADIPOSITY, ANDROGEN EXCESS, ABDOMINAL FAT, OBESE WOMEN, TESTOSTERONE, SENSITIVITY, MUSCLE

Downloads

  • (...).pdf
    • full text
    • |
    • UGent only
    • |
    • PDF
    • |
    • 605.65 KB

Citation

Please use this url to cite or link to this publication:

Chicago
Tosi, Flavia, Daniela Di Sarra, Jean Kaufman, Cecilia Bonin, Rosa Moretta, Enzo Bonora, Elisabetta Zanolin, and Paolo Moghetti. 2015. “Total Body Fat and Central Fat Mass Independently Predict Insulin Resistance but Not Hyperandrogenemia in Women with Polycystic Ovary Syndrome.” Journal of Clinical Endocrinology & Metabolism 100 (2): 661–669.
APA
Tosi, F., Di Sarra, D., Kaufman, J., Bonin, C., Moretta, R., Bonora, E., Zanolin, E., et al. (2015). Total body fat and central fat mass independently predict insulin resistance but not hyperandrogenemia in women with polycystic ovary syndrome. JOURNAL OF CLINICAL ENDOCRINOLOGY & METABOLISM, 100(2), 661–669.
Vancouver
1.
Tosi F, Di Sarra D, Kaufman J, Bonin C, Moretta R, Bonora E, et al. Total body fat and central fat mass independently predict insulin resistance but not hyperandrogenemia in women with polycystic ovary syndrome. JOURNAL OF CLINICAL ENDOCRINOLOGY & METABOLISM. 2015;100(2):661–9.
MLA
Tosi, Flavia, Daniela Di Sarra, Jean Kaufman, et al. “Total Body Fat and Central Fat Mass Independently Predict Insulin Resistance but Not Hyperandrogenemia in Women with Polycystic Ovary Syndrome.” JOURNAL OF CLINICAL ENDOCRINOLOGY & METABOLISM 100.2 (2015): 661–669. Print.
@article{6850735,
  abstract     = {Context/Objective: Obesity is a common feature of women with polycystic ovary syndrome (PCOS). The aim of this study was to assess the role of body fat on insulin resistance and androgen excess in these subjects. 
Patients/Design: One hundred sixteen consecutive Caucasian women with PCOS, diagnosed by the Rotterdam criteria, underwent accurate assessment of clinical, anthropometric, hormonal, and metabolic features. In particular, total fat mass and fat distribution were assessed by dual-energy x-ray absorptiometry, serum-free T by liquid chromatography mass spectrometry and equilibrium dialysis and insulin sensitivity by the glucose clamp technique. 
Results: Total fat mass and truncal fat were significantly higher in insulin-resistant than in insulin-sensitive PCOS subjects (+/- 89\% and +127\%, respectively, both P {\textlangle} .001), and both tended to be higher in hyperandrogenemic than in normoandrogenemic women (+22\% and +28\%, respectively, P = .087 and P = .090). All parameters of adiposity correlated inversely with insulin sensitivity (P {\textlangle} .001) and directly with serum-free T (P {\textlangle}= .001). A statistically significant inverse relationship was observed between insulin sensitivity and serum-free T concentrations (r = -0.527, P {\textlangle} .001). In a multiple regression analysis, either total fat mass or truncal fat, in addition to serum-free T and age, were independent predictors of insulin sensitivity. However, insulin sensitivity, but not total fat mass or truncal fat, was an independent predictor of free T concentrations. 
Conclusions: These data suggest that body fat contributes to determining insulin resistance in PCOS women. However, the association between body fat and hyperandrogenism seems to be to a large extent explained by insulin resistance.},
  author       = {Tosi, Flavia and Di Sarra, Daniela and Kaufman, Jean and Bonin, Cecilia and Moretta, Rosa and Bonora, Enzo and Zanolin, Elisabetta and Moghetti, Paolo},
  issn         = {0021-972X},
  journal      = {JOURNAL OF CLINICAL ENDOCRINOLOGY \& METABOLISM},
  keyword      = {SYNDROME PCOS,X-RAY ABSORPTIOMETRY,METABOLIC SYNDROME,GLOBAL ADIPOSITY,ANDROGEN EXCESS,ABDOMINAL FAT,OBESE WOMEN,TESTOSTERONE,SENSITIVITY,MUSCLE},
  language     = {eng},
  number       = {2},
  pages        = {661--669},
  title        = {Total body fat and central fat mass independently predict insulin resistance but not hyperandrogenemia in women with polycystic ovary syndrome},
  url          = {http://dx.doi.org/10.1210/jc.2014-2786},
  volume       = {100},
  year         = {2015},
}

Altmetric
View in Altmetric
Web of Science
Times cited: