Sagittal abdominal diameter as a new predictor for incident diabetes

Diabetes Care

Volumn 36, Issue 2, 2013, Pages 283-288

  Pajunen, Pia ^a   Rissanen, Harri ^a   Laaksonen, Maarit A ^a   Heliövaara, Markku ^a   Reunanen, Antti ^a   Knekt, Paul ^a  

^a NATIONAL PUBLIC HEALTH INSTITUTE   (Finland)

Author keywords

[No Author keywords available]

Indexed keywords

ABDOMINAL OBESITY; ADULT; AGED; ANTHROPOMETRIC PARAMETERS; ARTICLE; BODY MASS; FEMALE; FOLLOW UP; HEALTH SURVEY; HUMAN; INCIDENCE; INTRAABDOMINAL FAT; MALE; METABOLIC SYNDROME X; NON INSULIN DEPENDENT DIABETES MELLITUS; PREDICTION; PROSPECTIVE STUDY; RISK ASSESSMENT; RISK FACTOR; SAGITTAL ABDOMINAL DIAMETER; WAIST CIRCUMFERENCE; WAIST HIP RATIO;

ABDOMEN; ADULT; AGED; BODY MASS INDEX; DIABETES MELLITUS, TYPE 2; FEMALE; HUMANS; MALE; MIDDLE AGED; RISK FACTORS; WAIST CIRCUMFERENCE;

EID: 84873835162     PISSN: 01495992     EISSN: 19355548     Source Type: Journal    
DOI: 10.2337/dc11-2451     Document Type: Article

References (37)

1. WHO. Report of a WHO Consultation. Geneva, World Health Organization, 2000
2. Fox CS, Massaro JM, Hoffmann U, et al. Abdominal visceral and subcutaneous adipose tissue compartments: association with metabolic risk factors in the Fra-mingham Heart Study. Circulation 2007; 116:39-48
3. Meisinger C, Döring A, Thorand B, Heier M, Löwel H. Body fat distribution and risk of type 2 diabetes in the general population: are there differences between men and women? The MONICA/KORA Augsburg cohort study. Am J Clin Nutr 2006; 84:483-489
4. Ohlson LO, Larsson B, Svärdsudd K, et al. The influence of body fat distribution on the incidence of diabetes mellitus. 13.5 years of follow-up of the participants in the study of men born in 1913. Diabetes 1985;34:1055-1058
5. Laaksonen MA, Knekt P, Rissanen H, et al. The relative importance of modifiable potential risk factors of type 2 diabetes: a meta-analysis of two cohorts. Eur J Epidemiol 2010;25:115-124
6. Goodpaster BH. Measuring body fat distribution and content in humans. Curr Opin Clin Nutr Metab Care 2002;5:481-487
7. Glickman SG, Marn CS, Supiano MA, Dengel DR. Validity and reliability of dual-energy X-ray absorptiometry for the assessment of abdominal adiposity. J Appl Physiol 2004;97:509-514
8. Shen W, Punyanitya M, Wang Z, et al. Visceral adipose tissue: relations between single-slice areas and total volume. Am J Clin Nutr 2004;80:271-278
9. Molarius A, Seidell JC, Sans S, Tuomilehto J, Kuulasmaa K. Waist and hip circumferences, and waist-hip ratio in 19 populations of the WHO MONICA Project. Int J ObesRelat Metab Disord 1999;23:116-125
10. Alberti KG, Zimmet P, Shaw J; IDF Epidemiology Task Force Consensus Group. The metabolic syndromeda new worldwide definition. Lancet 2005;366:1059-1062
11. Grundy SM, Cleeman JI, Daniels SR, et al.; American Heart Association; National Heart, Lung, and Blood Institute. Diagnosis and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Circulation 2005;112:2735-2752
12. Alberti KG, Eckel RH, Grundy SM, et al.; International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; International Association for the Study of Obesity. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation 2009;120:1640-1645
13. Pou KM, Massaro JM, Hoffmann U, et al. Patterns of abdominal fat distribution: the Framingham Heart Study. Diabetes Care 2009;32:481-485
14. Kahn HS, Austin H, Williamson DF, Arensberg D. Simple anthropometric indices associated with ischemic heart disease. JClin Epidemiol 1996;49:1017-1024
15. Kvist H, Chowdhury B, Grangård U, Tylén U, Sjöström L. Total and visceral adipose-tissue volumes derived from measurements with computed tomographyinadult men and women: predictive equations. Am J Clin Nutr 1988;48:1351-1361
16. Zamboni M, Turcato E, Armellini F, et al. Sagittal abdominal diameter as a practical predictor of visceral fat. Int J Obes Relat Metab Disord 1998;22:655-660
17. Hoenig MR. MRI sagittal abdominal diameter is a stronger predictor of metabolic syndrome than visceral fat area or waist circumference in a high-risk vascular cohort. Vasc Health Risk Manag 2010;6:629-633
18. Yim JY, Kim D, Lim SH, et al. Sagittal abdominal diameter is a strong anthro-pometric measure of visceral adipose tissue in the Asian general population. Diabetes Care 2010;33:2665-2670
19. Guzzaloni G, Minocci A, Marzullo P, Liuzzi A. Sagittal abdominal diameter is more predictive of cardiovascular risk than abdominal fat compartments in severe obesity. Int J Obes (Lond) 2009;33:233-238
20. Ohrvall M, Berglund L, Vessby B. Sagittal abdominal diameter compared with other anthropometric measurements in relation to cardiovascular risk. Int J Obes Relat Metab Disord 2000;24:497-501
21. Risérus U, de Faire U, Berglund L, Hellénius ML. Sagittal abdominal diameter as a screening tool in clinical research: cutoffs for cardiometabolic risk. J Obes 2010;Article ID 757939
22. Risérus U, Arnlöv J, Brismar K, Zethelius B, Berglund L, Vessby B. Sagittal abdominal diameter is a strong anthropometric marker of insulin resistance and hyper-proinsulinemia in obese men. Diabetes Care 2004;27:2041-2046
23. Petersson H, Daryani A, Risérus U. Sagittal abdominal diameter as a marker of inflammation and insulin resistance among immigrant women from the Middle East and native Swedish women: a cross-sectional study. Cardiovasc Diabetol 2007;6:10
24. Iribarren C, Darbinian JA, Lo JC, Fireman BH, Go AS. Value of the sagittal abdominal diameter in coronary heart disease risk assessment: cohort study in a large, multiethnic population. Am J Epidemiol 2006; 164:1150-1159
25. Ehrlich AC, Smith DA. Abdominal diameter index and 12-year cardiovascular disease incidence in male bridge and tunnel workers. Int J Obes (Lond) 2011;35:409-415
26. Anjana M, Sandeep S, Deepa R, Vimaleswaran KS, Farooq S, Mohan V. Visceral and central abdominal fat and anthropometry in relation to diabetes in Asian Indians. Diabetes Care 2004;27:2948-2953
27. Vazquez G, Duval S, Jacobs DR Jr, Silventoinen K. Comparison of body mass index, waist circumference, and waist/hip ratio in predicting incident diabetes: a meta-analysis. Epidemiol Rev 2007;29:115-128
28. Aromaa A, Koskinen S, Eds. Health and Functional Capacity in Finland. Baseline Results of the Health 2000 Health Examination Survey. Publications of the National Public Health Institute B12/2004, Helsinki: National Public Health Institute, 2004.
29. Heistaro S, Ed. Methodology Report. Health 2000 Survey. Publications of the National Public Health Institute B26/2008, Helsinki: National Public Health Institute, 2008.
30. Reunanen A, Kangas T, Martikainen J, Klaukka T. Nationwide survey of co-morbidity, use, and costs of all medications in Finnish diabetic individuals. Diabetes Care 2000;23:1265-1271
31. Heliövaara M, Reunanen A, Aromaa A, Knekt P, Aho K, Suhonen O. Validity of hospital discharge data in a prospective epidemiological study on stroke and myo-cardial infarction. Acta Med Scand 1984; 216:309-315
32. Reunanen A, Aromaa A, Pyörälä K, Punsar S, Maatela J, Knekt P. The Social Insurance Institution's coronary heart disease study. Baseline data and 5-year mortality experience. Acta Med Scand Suppl 1983;673: 1-120
33. Lehtonen R, Pahkinen E. Practical Methods for Design and Analysis of Complex Surveys. Chichester, John Wiley & Sons Ltd, 1995
34. Laaksonen MA, Härkänen T, Knekt P, Virtala E, Oja H. Estimation of population attributable fraction (PAF) for disease occurrence in a cohort study design. Stat Med 2010;29:860-874
35. Laaksonen MA, Virtala E, Knekt P, Oja H, Härkänen T. SAS macros for calculation of Population Attributable Fraction in a cohort study design. J Stat Softw 2011; 43:1-25
36. SAS Institute Inc. SAS/STAT 9.2 User's Guide. Second Edition. Cary, NC, SAS Institute, Inc., 2009.
37. Pajunen P, Rissanen H, Härkänen T, Jula A, Reunanen A, Salomaa V. The metabolic syndrome as a predictor of incident diabetes and cardiovascular events in the Health 2000 Study. Diabetes Metab 2010; 36:395-401