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Phenotypic characteristics associated with insulin resistance in metabolically obese but normal-weight young women.
Abstract
Metabolically obese, normal-weight (MONW) individuals are a hypothesized subgroup of the general population. These normal-weight individuals potentially display a cluster of obesity-related features, although this has not been systematically tested in young women. We hypothesized that MONW young women would display higher levels of total and visceral fat and lower levels of physical activity than normal women. In a cohort of 71 healthy nonobese women (21-35 years old), we identified MONW women based on cut points for insulin sensitivity (normal = glucose disposal >8 mg x min(-1) x kg(-1) of fat-free mass [FFM], n = 58; impaired = glucose disposal <8 ml x min(-1) x kg(-1) of FFM, n = 13). Thereafter, we measured body composition (dual energy X-ray absorptiometry) and body fat distribution (computed tomography), cardiorespiratory fitness (VO2max on a treadmill), physical activity energy expenditure (doubly labeled water and indirect calorimetry), glucose tolerance (oral glucose tolerance test), serum lipid profile, and dietary intake. We found a higher body fat percentage (32 +/- 6 vs. 27 +/- 6%, P = 0.01) and higher subcutaneous (213 +/- 61 vs. 160 +/- 78 cm2, P = 0.03) and visceral (44 +/- 16 vs. 35 +/- 14 cm2, P < 0.05) abdominal adiposity in the MONW group versus the normal group. The MONW group showed a lower physical activity energy expenditure (2.66 +/- 0.92 vs. 4.39 +/- 1.50 MJ/day, P = 0.01), but no difference in cardiorespiratory fitness was noted between groups. In conclusion, despite a normal body weight, a subset of young, apparently healthy women displayed a cluster of risky phenotypic characteristics that, if left untreated, may eventually predispose them to type 2 diabetes and cardiovascular disease.
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“Indeed, as mentioned before, some individuals exhibit the metabolic syndrome with only a moderate degree of total body obesity.43,44”
From Diagnosis and Management of the Metabolic Syndrome: An American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement (2005) · cites this paper as [44]
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“Moreover, the population of the United States varies considerably in degree of insulin resistance 46 ; those having more inherent insulin resistance can develop the metabolic syndrome with only moderate excess in abdominal fat, 43,44 but even people with little or no inherent insulin resistance can develop the metabolic syndrome if they accumulate marked abdominal obesity.3,8”
From Diagnosis and Management of the Metabolic Syndrome: An American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement (2005) · cites this paper as [44]
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Al-Jaber, H., Mohamed, N. A., Govindharajan, V. K., Taha, S., John, J., Halim, S., Alser, M., Almuraikhy, S., Anwardeen, N. R., Agouni, A., et al. (2022) · Research Square · doi:10.21203/rs.3.rs-1646980/v1
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Metadata
- Authors
- Dvorak, R. V., DeNino, W. F., Ades, P. A., & Poehlman, E. T.
- Affiliations
- Department of Medicine, College of Medicine, University of Vermont, Burlington 05405, USA.
- University of Vermont (US)
- Venue
- Diabetes
- Publisher
- American Diabetes Association
- Published
- 1999-11-01
- Volume
- 48
- Issue
- 11
- Pages
- 2210-2214
- ISSN
- 0012-1797 (ISSN-L)
- 1939-327X
- OpenAlex
- W2155025864
- Cited by
- 243
- References
- 0
- Citations by year
- 2026: 2 · 2025: 1 · 2024: 4 · 2023: 6 · 2022: 9 · 2021: 7 · 2020: 4 · 2019: 10 · 2018: 15 · 2017: 8 · 2016: 16 · 2015: 11 · 2014: 12 · 2013: 12 · 2012: 17
- FWCI
- 3.86
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Diabetes (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (5r01ag015114-03)
- National Institute on Aging (R01-AG15114)
- National Institute of Dental and Craniofacial Research (DE 950226)
- National Center for Research Resources (RR-00109)
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Obesity, Physical Activity, Diet
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Adipokines, Inflammation, and Metabolic Diseases
- Keywords
- insulin resistance, visceral fat, subcutaneous abdominal fat, physical activity energy expenditure, cardiorespiratory fitness, body composition, glucose tolerance, type 2 diabetes risk, cardiovascular risk, young women
- MeSH terms
- Adipose Tissue, Adult, Blood Glucose, Blood Pressure, Body Constitution, Body Weight, Contraceptives, Oral, Diabetes Mellitus, Female, Glucose, Humans, Obesity, Phenotype, Reference Values, Body Mass Index
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