Abdominal obesity predicts declining insulin sensitivity in non-obese normoglycaemics: the Insulin Resistance Atherosclerosis Study (IRAS)

  1. A. J. Karter1,*,
  2. R. B. D'Agostino Jr2,
  3. E. J. Mayer-Davis3,
  4. L. E. Wagenknecht2,
  5. A. J. G. Hanley4,
  6. R. F. Hamman5,
  7. R. Bergman6,
  8. M. F. Saad7,
  9. S. M. Haffner8,
  10. for the IRAS investigators1

Article first published online: 7 DEC 2004

DOI: 10.1111/j.1463-1326.2004.00441.x

Issue

Diabetes, Obesity and Metabolism

Diabetes, Obesity and Metabolism

Volume 7, Issue 3, pages 230–238, May 2005

Additional Information

How to Cite

Karter, A. J., D'Agostino, R. B., Mayer-Davis, E. J., Wagenknecht, L. E., Hanley, A. J. G., Hamman, R. F., Bergman, R., Saad, M. F., Haffner, S. M. and for the IRAS investigators (2005), Abdominal obesity predicts declining insulin sensitivity in non-obese normoglycaemics: the Insulin Resistance Atherosclerosis Study (IRAS). Diabetes, Obesity and Metabolism, 7: 230–238. doi: 10.1111/j.1463-1326.2004.00441.x

Author Information

  1. 1

    Kaiser Permanente, Division of Research, Northern California Region, Oakland, CA, USA

  2. 2

    Department of Public Health Sciences, Bowman Gray School of Medicine, Wake Forest University, Winston Salem, NC, USA

  3. 3

    Department of Epidemiology and Biostatistics and Center for Research in Nutrition and Health Disparities, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA

  4. 4

    Leadership Sinai Centre for Diabetes, Mt Sinai Hospital, Toronto, ON, Canada

  5. 5

    Department of Preventive Medicine/Biometrics, University of Colorado Health Sciences Center, Denver, CO, USA

  6. 6

    Department of Physiology and Biophysics, University of Southern California Keck School of Medicine, University of Southern California, Los Angeles, CA, USA

  7. 7

    Division of Endocrinology and Epidemiology, University of California Los Angeles School of Medicine, Los Angeles, CA, USA

  8. 8

    Division of Clinical Epidemiology, University of Texas Health Sciences Center at San Antonio, San Antonio, TX, USA

* *Andrew J. Karter, PhD, 2000 Broadway, Oakland, CA 94612, USA. E-mail: andy.j.karter@kp.org

Publication History

  1. Issue published online: 4 APR 2005
  2. Article first published online: 7 DEC 2004
  3. Received 8 April 2004; returned for revision 2 August 2004; revised version accepted 3 August 2004

SEARCH

SEARCH BY CITATION

ARTICLE TOOLS

View Full Article (HTML) Get PDF (109K)

Keywords:

  • epidemiology;
  • insulin sensitivity;
  • obesity;
  • visceral obesity

Aim:  Cross-sectional studies have demonstrated a relationship between obesity and insulin sensitivity (SI); however, there is a lack of evidence from longitudinal studies.

Methods:  The Insulin Resistance Atherosclerosis Study (IRAS) estimated SI (×10−4/min·µU/ml) directly using a frequently sampled intravenous glucose tolerance test with minimal model analysis in 504 normoglycaemic subjects. Partial correlation coefficients (r) were calculated to compare the relationship of change in SI from baseline to 5 years later (ΔSI) with baseline waist circumference (waist) as a measure of abdominal obesity and body mass index (BMI) as a measure of overall obesity. Mean ΔSI was −1.06 (SD = 1.85).

Results:  Higher baseline waist (r = −0.16; p = 0.0005), but not BMI (r = −0.005; p = 0.91), was associated with (–) ΔSI in models including sex, ethnicity, clinical centre and baseline SI, BMI, waist, age and physical activity. The waist–ΔSI relationship differed across the levels of baseline BMI, being significant only in normal weight (r = −0.21) and overweight subjects (r = −0.16), but not in obese subjects. ΔSI was correlated with a 5-year change in either obesity measure (Δwaist: r = −0.22 and ΔBMI: r = −0.20; p = 0.0001).

Conclusions:  Among non-diabetics, waist circumference was a strong predictor of declining SI among lean subjects, a modest predictor among overweight subjects, but was not predictive among obese individuals. Waist circumference should be considered, in addition to BMI, when identifying individuals at high risk of diabetes or the insulin resistance syndrome.

View Full Article (HTML) Get PDF (109K)