The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
Body Mass Index, Metabolic Syndrome, and Risk of Type 2 Diabetes or Cardiovascular Disease
Abstract
CONTEXT: Metabolic risk conferred by adiposity may be due to associated risk factor clustering. OBJECTIVE: The objective of this study was to assess risk for diabetes or cardiovascular disease (CVD) stratified by body mass index (BMI) and the presence or absence of metabolic syndrome (MetS) or insulin resistance (IR). DESIGN, SETTING, AND PARTICIPANTS: This was a community-based, longitudinal study of 2902 people (55% women, mean age 53 yr) without diabetes or CVD in 1989-1992 followed for up to 11 yr. We categorized subjects by normal weight (BMI < 25 kg/m(2)), overweight (25-29.9 kg/m(2)), or obese (>30 kg/m(2)) and by the National Cholesterol Education Program's Adult Treatment Panel MetS or the top quartile of homeostasis model IR. We used proportional hazard models to estimate risk relative to normal weight and no MetS or IR. MAIN OUTCOME MEASURE: Incident type 2 diabetes (treatment or fasting glucose > or = 7 mmol/liter, 141 events) or CVD (myocardial infarction, stroke, or claudication, 252 events) were measured. RESULTS: Among 1056 normal-weight subjects, 7% had MetS and a risk factor-adjusted relative risk for diabetes of 3.97 (95% confidence interval, 1.35-11.6) and for CVD of 3.01 (1.68-5.41). Among 638 obese subjects, 37% did not have MetS or significantly increased risk. Obese subjects with MetS had an adjusted relative risk for diabetes of 10.3 (5.44-19.5) and for CVD of 2.13 (1.43-3.18). Results were similar in analyses of BMI-IR categories. CONCLUSIONS: People with normal weight and MetS or IR or with obesity but no MetS or IR were not uncommon in our sample. Risk factor clustering or IR appear to confer much of the risk for diabetes or CVD commonly associated with elevated BMI.
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Cites
Matthews, D. R., Hosker, J. P., Rudenski, A. S., Naylor, B. A., Treacher, D. F., & Turner, R. C. (1985) · Diabetologia · doi:10.1007/bf00280883 · Cited by 31,502
Comment on the provisional report from the WHO consultation
(1999) · Diabetic Medicine · doi:10.1046/j.1464-5491.1999.00059.x · Cited by 1,820
Obesity, Fat Distribution, and Weight Gain as Risk Factors for Clinical Diabetes in Men
Chan, J. M., Rimm, E. B., Colditz, G. A., Stampfer, M. J., & Willett, W. C. (1994) · Diabetes Care · doi:10.2337/diacare.17.9.961 · Cited by 1,808
Use and misuse of population attributable fractions
Rockhill, B., Newman, B., & Weinberg, C. (1998) · American Journal of Public Health · doi:10.2105/ajph.88.1.15 · Cited by 1,683
Carr, D. B., Utzschneider, K. M., Hull, R. L., Kodama, K., Retzlaff, B. M., Brunzell, J. D., Shofer, J. B., Fish, B. E., Knopp, R. H., & Kahn, S. E. (2004) · Diabetes · doi:10.2337/diabetes.53.8.2087 · Cited by 993
Ferrannini, E., Natali, A., Bell, P., Cavallo-Perin, P., Lalic, N., & Mingrone, G. (1997) · Journal of Clinical Investigation · doi:10.1172/jci119628 · Cited by 898 · cited 1×
“The latter interpretation is supported by our observation that the prevalence of BMI-metabolic risk subphenotypes and the magnitude of their associated risks for diabetes or CVD were very similar when metabolic risk was defined by the presence of IR rather than MetS (6, 7, 10, 11).”
BackgroundCarey, V. J., Walters, E. E., Colditz, G. A., Solomon, C. G., Willet, W. C., Rosner, B. A., Speizer, F. E., & Manson, J. E. (1997) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a009158 · Cited by 827
Parental transmission of type 2 diabetes: the Framingham Offspring Study
Meigs, J. B., Cupples, L. A., & Wilson, P. W. (2000) · Diabetes · doi:10.2337/diabetes.49.12.2201 · Cited by 666
Self-citationBiomarkers of Endothelial Dysfunction and Risk of Type 2 Diabetes Mellitus
Meigs, J. B. (2004) · JAMA · doi:10.1001/jama.291.16.1978 · Cited by 643
Self-citationObesity, Regional Body Fat Distribution, and the Metabolic Syndrome in Older Men and Women
Goodpaster, B. H., Krishnaswami, S., Harris, T. B., Katsiaras, A., Kritchevsky, S. B., Simonsick, E. M., Nevitt, M., Holvoet, P., & Newman, A. B. (2005) · Archives of Internal Medicine · doi:10.1001/archinte.165.7.777 · Cited by 637
Cited by
The worldwide epidemiology of type 2 diabetes mellitus—present and future perspectives
Chen, L., Magliano, D. J., & Zimmet, P. Z. (2012) · Nature Reviews Endocrinology · doi:10.1038/nrendo.2011.183 · Cited by 2,227
Cornier, M.-A., Dabelea, D., Hernandez, T. L., Lindstrom, R. C., Steig, A. J., Stob, N. R., Van Pelt, R. E., Wang, H., & Eckel, R. H. (2008) · Endocrine Reviews · doi:10.1210/er.2008-0024 · Cited by 2,162
Garvey, W. T., Mechanick, J. I., Brett, E. M., Garber, A. J., Hurley, D. L., Jastreboff, A. M., Nadolsky, K., Pessah-Pollack, R., & Plodkowski, R. (2016) · Endocrine Practice · doi:10.4158/ep161365.gl · Cited by 1,914
Blüher, M. (2020) · Endocrine Reviews · doi:10.1210/endrev/bnaa004 · Cited by 1,090
Metabolically healthy obesity: Epidemiology, mechanisms, and clinical implications
Stefan, N., Häring, H.-U., Hu, F. B., & Schulze, M. B. (2013) · The Lancet Diabetes & Endocrinology · doi:10.1016/s2213-8587(13)70062-7 · Cited by 857
Metadata
- Authors
- Meigs, J. B., Wilson, P. W. F., Fox, C. S., Vasan, R. S., Nathan, D. M., Sullivan, L. M., & D’Agostino, R. B.
- Venue
- The Journal of Clinical Endocrinology & Metabolism
- Publisher
- The Endocrine Society
- Published
- 2006-08
- Volume
- 91
- Issue
- 8
- Pages
- 2906-2912
- ISSN
- 0021-972X (ISSN-L)
- 1945-7197
- OpenAlex
- W2119609179
- Cited by
- 1,062
- References
- 14
- FWCI
- 17.75
- Type
- journal article
- Language
- en
- Open access
- closed
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- Meigs, J. B., Wilson, P. W. F., Fox, C. S., Vasan, R. S., Nathan, D. M., Sullivan, L. M., & D’Agostino, R. B. (2006). Body Mass Index, Metabolic Syndrome, and Risk of Type 2 Diabetes or Cardiovascular Disease. The Journal of Clinical Endocrinology & Metabolism. https://doi.org/10.1210/jc.2006-0594
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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