Is there a Benefit to Use Calculated Percent Body Fat or Age- and Gender-adjusted BMI-SDS_LMS to Predict Risk Factors for Cardiovascular Disease? A German/Austrian Multicenter DPV-Wiss Analysis on 42 048 Type 2 Diabetic Patients

Abstract

Objective:

In clinical practice Body Mass Index is generally used to evaluate overweight status in adults. The present multicenter study examines whether Body Mass Index (BMI), age- and gender-adjusted Body Mass Index Standard Deviation Score, or calculated %body fat is a better predictor for cardiovascular disease risk factors, specifically hypertension and dyslipidemia, in a high-risk population.

Methods:

Data of 42 048 adult type 2 diabetic patients (median age: 67.1 years) from 161 ­centers in Germany (n=158) and Austria (n=3) registered in a standardized, prospective, computer-based documentation program, were included in the study. For each patient body weight, height, blood pressure and blood lipids were documented. Spearman correlation analyses as well as multivariable logistic regression models were used to examine the relationship between anthropometric measurements and cardiovascular disease risk factors.

Results:

Correlation and regression analyses revealed minor, non significant differences between the 3 anthropometric measurements (all p>0.05). In both genders, relationships between anthropometric measurements and hypertension or reduced HDL-cholesterol were nearly identical. Only for increased triglycerides, the relations with the 3 anthropometric measurements were significantly stronger in males than in females (p<0.0001, respectively). With increasing age, associations between anthropometric measurements and hypertension, reduced HDL-cholesterol or increased triglycerides became weaker. Spearman correlation coefficients for total cholesterol and LDL-cholesterol revealed weak associations with the 3 anthropometric measurements.

Conclusion:

Compared to Body Mass Index, age- and gender-adjusted Body Mass Index Standard Deviation Score, or calculation of %body fat, has no further benefit to predict cardiovascular disease risk factors in adult type 2 diabetic patients.

Key words

body mass index - body fat percentage - body mass index standard deviation score - hypertension - dyslipidemia

• References

• 1 World Health Organization . [Internet]. Geneva: World Health Organization; c2012 [updated 2011 September; cited 2012 Aug 3]. Cardiovascular diseases (CVDs) Fact sheet N°317; [about 4 screens]. Available from http://www.who.int/mediacentre/factsheets/fs317/en/index.html
• 2 National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) . Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) final report. Circulation 2002; 106: 3143-3421
• 3 World Health Organization . [Internet]. Geneva: World Health Organization; c2006 [updated 2012 August 3; cited 2012 Aug 3]. BMI classification; [about 2 screens]. Available from http://apps.who.int/bmi/index.jsp?introPage=intro_3.html
• 4 Hemmelmann C, Brose S, Vens M et al. Percentiles of body mass index of 18–80-year-old German adults based on data from the Second National Nutrition Survey. Dtsch Med Wochenschr 2010; 135: 848-852 German
• 5 Gómez-Ambrosi J, Silva C, Catalán V et al. Clinical usefulness of a new equation for estimating body fat. Diabetes Care 2012; 35: 383-388
• 6 Gómez-Ambrosi J, Silva C, Galofré JC et al. Body mass index classification misses subjects with increased cardiometabolic risk factors related to elevated adiposity. Int J Obes (Lond) 2012; 36: 286-294
• 7 Can AS, Bersot TP, Gönen M et al. Anthropometric indices and their relationship with cardiometabolic risk factors in a sample of Turkish adults. Public Health Nutr 2009; 12: 538-546
• 8 van Dijk SB, Takken T, Prinsen EC et al. Different anthropometric adiposity measures and their association with cardiovascular disease risk factors: a meta-analysis. Neth Heart J 2012; 20: 208-218
• 9 Dervaux N, Wubuli M, Megnien JL et al. Comparative associations of adiposity measures with cardiometabolic risk burden in asymptomatic subjects. Atherosclerosis 2008; 201: 413-417
• 10 Schneider HJ, Glaesmer H, Klotsche J et al. Accuracy of anthropometric indicators of obesity to predict cardiovascular risk. J Clin Endocrinol Metab 2007; 92: 589-594
• 11 Lee CM, Huxley RR, Wildman RP et al. Indices of abdominal obesity are better discriminators of cardiovascular risk factors than BMI: a meta-analysis. J Clin Epidemiol 2008; 61: 646-653
• 12 Bertsias G, Mammas I, Linardakis M et al. Overweight and obesity in relation to cardiovascular disease risk factors among medical students in Crete, Greece. BMC Public Health 2003; 3: 3-11
• 13 Reeder BA, Senthilselvan A, Després JP et al. The association of cardio­vascular disease risk factors with abdominal obesity in Canada. ­Canadian Heart Health Surveys Research Group. CMAJ 1997; 157 (Suppl. 01) S39-S45
• 14 Shen W, Punyanitya M, Chen J et al. Waist circumference correlates with metabolic syndrome indicators better than percentage fat. Obesity (Silver Spring) 2006; 14: 727-736
• 15 Eeg-Olofsson K, Cederholm J, Nilsson PM et al. Risk of cardiovascular disease and mortality in overweight and obese patients with type 2 diabetes: an observational study in 13 087 patients. Diabetologia 2009; 52: 65-73
• 16 Mancia G, Laurent S, Agabiti-Rosei E et al. Reappraisal of European guidelines on hypertension management: a European Society of Hypertension Task Force document. J Hypertens 2009; 27: 2121-2158
• 17 Cole TJ. The LMS method for constructing normalized growth standards. Eur J Clin Nutr 1990; 44: 45-60
• 18 Max Rubner-Institut . Bundesforschungsinstitut für Ernährung und Lebensmittel [Internet]. Karlsruhe: Max Rubner-Institut, Bundesforschungsinstitut für Ernährung und Lebensmittel; c2008 [updated 2008 March 7; cited 2012 May 23]. Nationale Verzehrsstudie II, Ergebnisbericht Teil 1; Available from http://www.was-esse-ich.de/uploads/media/NVS_II_Abschlussbericht_ Teil_1_mit_Ergaenzungsbericht.pdf
• 19 Huxley R, Mendis S, Zheleznyakov E et al. Body mass index, waist circumference and waist:hip ratio as predictors of cardiovascular risk – a review of the literature. Eur J Clin Nutr 2010; 64: 16-22
• 20 Chan LC, Ware RS, Kesting J et al. Association between anthropometric measures of obesity and cardiovascular risk markers in a self-selected group of indigenous Australians. Eur J Cardiovasc Prev Rehabil 2007; 14: 515-517
• 21 Albu JB, Lu J, Mooradian AD et al. Relationships of obesity and fat distribution with atherothrombotic risk factors: baseline results from the Bypass Angioplasty Revascularization Investigation 2 Diabetes (BARI 2D) trial. Obesity (Silver Spring) 2010; 18: 1046-1054
• 22 Ali ZA, Al-Zaidi MS. The association between body mass index, lipid profile and serum estradiol levels in a sample of iraqi diabetic premenopausal women. Oman Med J 2011; 26: 263-266
• 23 Arora M, Koley S, Gupta S et al. A Study on Lipid Profile and Body Fat in Patients with Diabetes Mellitus. The Anthropologist 2007; 9: 295-298
• 24 Holl RW, Hoffmeister U, Thamm M et al. Does obesity lead to a specific lipid disorder? Analysis from the German/Austrian/Swiss APV registry. Int J Pediatr Obes 2011; 6 (Suppl. 01) S53-S58
• 25 Deutsche Hochdruckliga e.V. – Deutsche Hypertonie Gesellschaft [­Internet]. Heidelberg: Deutsche Hochdruckliga e.V. – Deutsche Hypertonie Gesellschaft; c1997-2012 [updated 2008 June 1; cited 2012 May 24]. Leitlinien zur Behandlung der arteriellen Hypertonie; Available from http://www.paritaet.org/hochdruckliga
• 26 Bundesärztekammer . Richtlinie der Bundesärztekammer zur Qualitäts­sicherung laboratoriumsmedizinischer Untersuchungen (RiliBÄK). Dtsch Arztebl 2008; 105: 341-355 German