The Indian subcontinent is undergoing epidemiological transition, as noncommunicable

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1 22 Journal of the association of physicians of india vol 63 january, 2015 Original Article Correlation and Comparison of Various Anthropometric Measurements of Body Fat Distribution and Sagittal Abdominal Diameter as a Screening Tool for Cardio Metabolic Risk Factors and Ischaemic Heart Disease in Elderly Population Meenaxi Sharda, Pankaj Jain, Atul Gupta, Deepti Nagar, Anil Soni Abstract Objective: Primary objective of this study was to assess utility of sagittal abdominal diameter (SAD) as a cardio vascular risk predictor and compare various anthropometric measurement of body fat distribution in elderly patients. Method: Four hundred patients were enrolled in study. Elderly patients more than 60 year of age attending medical OPD, geriatric OPD and suitable indoor patients who were willing to participate in the study were included. Result : SAD was significantly higher in patient with ischaemic heart disease (group 1) than patient without ischaemic heart disease (Group 2) (P < for male and female). SAD was better than WC to ascertain individual cardio metabolic risk factors in male, especially FBS (Pearson correlation.33 vs..29), total cholesterol (Pearson correlation.24 vs..20) as well as LDL cholesterol (Pearson correlation.13 vs..05), while in female WC and SAD showed equal correlation with individual cardio metabolic risk factors. Conclusion: In patient with metabolic syndrome IHD group showed considerably higher mean SAD values. SAD also showed very good correlation with individual cardio metabolic risk factors especially in elderly male, while in female both SAD and WC were almost equivalent. Professor, Assistant Prof., Resident, Department of Medicine, Govt. Medical College, Kota Received: ; Revised: ; Re-revised: ; Accepted: Introduction The Indian subcontinent is undergoing epidemiological transition, as noncommunicable diseases like coronary heart disease and type 2 diabetes mellitus are fast replacing infections as the leading cause of morbidity and mortality. The metabolic syndrome is characterised by a group of metabolic risk factors in one person. Criteria for diagnosis of metabolic syndrome: IDF (International Diabetes Federation) 1 consensus worldwide definition of the metabolic syndrome (2006). 1. Central obesity (defined as waist circumference with ethnicity specific values) and any two of the following: 2. Raised triglycerides: > 150 mg/dl, or specific treatment for this lipid abnormality. 3. Reduced HDL cholesterol: < 40 mg/dl in males, < 50 mg/dl in females, or specific treatment for this lipid abnormality 4. Raised blood pressure: systolic BP > 130 or diastolic BP > 85 mm Hg, or treatment of previously diagnosed hypertension.

2 Journal of the association of physicians of india vol 63 january, Raised fasting plasma glucose: (FPG) >100 mg/dl, or previously diagnosed type 2 diabetes. BMI represents a useful measure of body composition in populations, but is simultaneously unreliable for individuals. This apparent paradox may reflect intrinsic limitations of BMI in differentiating lean and adipose tissues and in accounting for body fat distribution. These limitations are important given that the relevance of both the composition (i.e. fat and lean components) and localisation of body mass in explaining health outcomes are increasingly recognised. In this regard, it is now widely appreciated that body fat distribution is an important risk factor for both morbidity and mortality, above and beyond total excess body weight. 2-4 Consequently, current national and international guidelines advocate for the routine measurement of waist circumference (WC) in the assessment of obesity-related health risk. 5 Additional anthropometric measures of body composition, including indicators of lean tissue or peripheral fat depots have also demonstrated the ability to help differentiate health risk above and beyond BMI. 2,6 SAD is also an excellent estimate of visceral fat 7-9 implying that SAD particularly might be a good marker of insulin resistance, which also has been demonstrated in men 10 and women. 11 Despite these promising data, the role of SAD has been overlooked whereas waist girth has received more attention. 12 It was previously reported that SAD maybe a better predictor of cardio metabolic risk compared to waist girth and other conventional measures. Methods Study Objective Primary objective of this study was to assess utility of sagittal abdominal diameter as a cardio metabolic risk predictor in elderly and compare various anthropometric measurement of body fat distribution in elderly patients. Study population Four hundred patients were enrolled in the study. Patient diagnosed as metabolic syndrome according to IDF criteria. 1 IHD (ischaemic heart disease) was diagnosed either on the basis of clinical history supported by documentary evidence of treatment in a hospital or at home, or on ECG evidence in accordance with the Minnesota Code. Subjects were assigned to four Groups. Group 1 metabolic syndrome with ischaemic heart disease (M: F; 55:45) Group-2 metabolic syndrome without ischaemic heart disease (M: F; 53:47) Group 3 non metabolic syndrome with ischaemic heart disease (M:F; 20:17) Group-4 non metabolic syndrome without ischaemic heart disease(m:f; 80:83). Inclusion Criteria All elderly patient > 60 yr of age attending medical OPD, geriatric OPD and suitable indoor patients who were willing to participate in the study were included. Exclusion Criteria Subjects with spinal deformity, abdominal tumours, lump, significant ascites, pathological diseases (cancer, insufficient renal and hepatic performance, and chronic inflammatory pathologies) and subjects in whom anthropometry measurements were not feasible. 1. Detailed history is taken and scrutiny of previous medical record was done with thorough clinical examination of every patient included in the study. 2. Complete laboratory work up was also done. a. Renal function test b. Fasting and postprandial plasma glucose (Glucose peroxidase method). c. Lipid profile: Serum total cholesterol, HDL, LDL, and triglyceride d. Standard 12 lead ECG e. X-ray chest PA view Weight and height are measured while the subjects are barefoot and wearing light clothing only. BMI was calculated from formula: BMI= Weight (kg) / Height(m) 2. WHO (modified) classification for Indo Asian Patients was used to classify Body mass index: Normal: , Overweight: 23-25, Obese: 25-30, Morbid Obesity: more than 30 SAD or supine abdominal height is measured after a normal expiration to nearest 0.1 cm in supine position with straight legs on a firm examination table, without clothes in the measurement area, at the level of iliac crest (L4-5) level. SAD is the vertical distance between examination table and the horizontal limb of the caliper. SAD cutoffs taken for identifying subjects with an elevated cardio metabolic risk are taken as 22 cm in men and 20 cm in women. 10 SAD was measured with a portable, sliding-beam, abdominal caliper while the subjects were in a supine position. This instrument was hand-made under our supervision by an artisan. Waist circumference is measured according to the WHO in standing position after normal expiration, midway between the lower rib margin and the iliac crest (WHO). The waist-hip ratio is the index of regional distribution of body fat most used in the epidemiological research. It is based on the ratio between the WC values and the hip circumference (HC). The anatomical place most used for assessing of HC is in the height of the greatest trochanter,

3 24 Journal of the association of physicians of india vol 63 january, 2015 Table 1 : Base line characters of the study groups 1 and 2 recommended by the WHO. Waist hip ratio of 0.80 and more in female and 0.90 and more in males is considered as abnormal and subjects were considered as having abdominal obesity. Statistical Analysis Statistical methods used were unpaired student s t-test, chi square test and calculation of Pearson correlation coefficient using bivariate analysis. A value of p > 0.05 is considered as not significant, p < 0.05 as mildly significant, p < 0.01 as significant, p < as highly significant, p < as very significant. Pearson correlation coefficient (r) value varies from -1 to +1 (r value <.4 = weak positive correlation,.4 to.6 = moderate positive correlation, >.6 = strong positive correlation and r value less than 1= negative correlation). Result Group 1 () (n=55) Group 2 () (n=45) Four hundred cases of both sexes between age years were included in our study of which 200 were diagnosed as metabolic syndrome according to IDF criteria. 1 Subjects were further divided into ischaemic heart disease and non IHD Group. Majority of cases Group 1 () (n=47) Group 2 () (n=53) Variables Mean ± SD Mean ± SD Mean ± SD Mean ± SD Age (yrs) ± ± ± ± 5.10 Fasting Blood Sugar ± ± ± ± 21.5 TC(mg/dl) ± ± ± ± 9.39 LDL(mg/dl) ± ± ± ± 13.4 TG (mg/dl) ± ± ± ± 19.2 HDL (mg/dl) ± ± ± ± 1.51 Waist Circumference ± ± ± ± 7.64 Hip Circumference ± ± ± ± 9.22 Waist Hip Ratio ± ± ± ±.097 Body Mass Index ± ± ± ± 3.58 SAD ± ± ± ± 2.57 Table 2 : Base line characters of the study groups 3 and 4 Group 3 () (n=20) Group 4 () (n=80) Group 3 () (n=17) Group 4 () (n=83) Variables Mean ± SD Mean ± SD Mean ± SD Mean ± SD Age (yrs) ± ± ± ± 6.5 Fasting Blood Sugar ± ± ± ± 19.3 TC (mg/dl) ± ± ± ± 15.9 LDL (mg/dl) ± ± ± ± 17.3 TG (mg/dl) ± ± ± ± 11.9 HDL (mg/dl) 42.4 ± ± ± ± 8.1 WC 81.9 ± ± ± ± 6.01 HC 87.3 ± ± ± ± 15.5 Waist Hip Ratio.93 ± ± ± ±.06 Body Mass Index ± ± ± ± 3.38 SAD 20.3 ± ± ± ± 1.87 in our study were in the age group year. Mean age of male in various groups in our study population was between ± 5.59 and ± 6.18 while mean age for female was between ± 5.1 to 74.6 ± 9.9 (Tables 1 and 2). In line with previous studies 11,17 FBS was significantly higher in male participants ( ± 41.4 vs ± 37.5) (p value <.01). In MS and non MS groups a statistically significant difference was found between total cholesterol (180.2 ± 13.1 vs ± 9.4 in male and ± 13.1 vs. 174 ± 17.8 in female) as well as LDL cholesterol (116.2 ± 12.1 vs ± 14.4 in male and ± 8.7 vs ± 21.3 in female). This suggest that there is a significant association of non HDL cholesterol with MS (Tables 1 and 2). Mean SAD values were significantly higher in group 1 (24.78 ± 1.64 vs ± 1.94 in s and ± 2.84 vs ± 2.57 in female) than Group 2 (P < for both sex ). In same study groups BMI was also higher in patient with group 1 (27.87 ± 3.14 vs ± 1.99 in s) (p value <.001) and (27.23 ± 4.28 vs ± 3.58 in females, p value.49) than Group 2. Statistically significant difference in WHR was also observed in both male as well as female between Group 1 and 2 subjects (p value <.05), while WC showed statistically significant difference in males only. SAD, BMI and WC showed strong positive correlation with each other while WHR showed only moderate positive Pearson correlation coefficient (r) with other anthropometric parameters of our study (Table 3). SAD was better than WC to ascertain cardio metabolic risk factors especially FBS (Pearson correlation.33 vs..29), Total cholesterol (Pearson correlation.24 vs..20) as well as LDL cholesterol (Pearson correlation.13 vs..05), while in female WC showed better correlation with FBS (.38 vs..32) and LDL cholesterol (.21 vs..13) than SAD (Tables 4 and 5). Among various cardio metabolic risk factors only FPG, LDL cholesterol and total cholesterol have shown

4 Journal of the association of physicians of india vol 63 january, Table 3 : Pearson correlations between anthropometric measures specified for sex in study population SAD BMI WC WHR SAD BMI WC WHR All correlations are statistically significant (p value <.01) Table 4 : Correlation between anthropometric measurements and cardio metabolic risk factors in mean values were statistically not significant in females (p value.49 and.06 respectively). Better correlation between SAD and WC values in men compared to females may be explained by the higher visceral fat in men vs women at a given BMI and thus may better predict cardiometabolic risk in men. This is relevant since visceral adiposity may confer a higher cardiometabolic risk than other fat depots. 8 obesity which is more in the peripheral Mean SAD FBS HDL TG TC LDL SAD BMI WC WHR (p value <.05) Table 5 : Correlations between anthropometric measurements and cardio metabolic risk factors in FBS HDL TG TC LDL SAD BMI WC WHR All correlations are statistically significant (p value <.01) except association between WHR and LDL in male statistically significant difference between IHD and non IHD groups (Tables 1 and 2). Discussion Anthropometric measures remain the preferred means of evaluating body fatness in settings where time-consuming and costly diagnostic tests are not feasible. Indicators of body fat distribution are associated with cardiovascular risk factors in the elderly independently of BMI. Aging is associated with a decrease in height, 14 a more central fat distribution, 15 and a loss of muscle mass (sarcopenia). Accumulating data suggest that sagittal abdominal diameter (SAD) or abdominal height may be a better marker of intra-abdominal adiposity and cardio metabolic risk. 13 SAD seems particularly good in capturing visceral fat which during the supine measurement does not float out sideways, as would more be the case for subcutaneous fat. 14 SAD as well as WHR showed statistically significant difference in mean values between IHD and non IHD groups among metabolic syndrome (group 1 and 2), statistically significant difference between mean values between group 1 and 2 was limited to male participants in case of BMI and WC while difference between Group 1 Group 2 Group 3 Group 4 Metabolic Syndrome Non Metabolic Syndrome Chart 1 : Comparison of Mean SAD of Study Groups (Graph) regions (pear shaped) may be overestimated by WC compared to SAD which has higher measurement reliability. In male participants SAD showed strongest correlation with FBS and LDL cholesterol, while in females WC followed by SAD showed better correlation with FBS and LDL cholesterol. Turcato et al 16 studied 146 women and 83 men aged 67 to 78 yr selected from the general population in down-town Verona, Italy to determine association of SAD with cardiovascular risk factors. They also concluded that waist circumference and SAD are the anthropometric indicators which are most closely related to cardio metabolic risk factors in old age. SAD was more closely related to hyperlipidaemia and cardiovascular risk than BMI, waist girth and WHR. 13 U. Ris erus et al, 2010 also suggested that in line with the previous studies, SAD was the best marker of an elevated cardio metabolic risk score related to metabolic syndrome in men, and at least as good as other anthropometric measures in women, 10 which supports our study. Thus, SAD may be used as a simple screening tool in research aiming at recruiting subjects at elevated cardio metabolic risk, especially men, but due to non availability of commercially available caliper it is an underutilised contraption. Further evaluation of SAD is warranted in younger age Groups. There are few limitations of this study. This is a cross sectional study with limited sample size (precision (d) =.06 at

5 26 Journal of the association of physicians of india vol 63 january, % confidence interval when considering prevalence of MS 25%). Our study is hospital based study. Large multi centric population based study is required for further assessment of our data. In addition, the cardio metabolic risk factors used are not consistently the only determinant of cardiovascular events and mortality. Further prospective analyses will be needed to verify SAD as a predictor of mortality. Conclusion Anthropometric measurements of body fat distribution are simple and noninvasive tool for prediction of cardio vascular risk in elderly. Among patient with metabolic syndrome IHD group showed considerably higher mean SAD values. SAD is also a very good predictor of individual cardio metabolic risk factors especially in elderly male, while in female both SAD and WC are almost equivalent. References 1. Alberti KG, Zimmet P, Shaw J. Metabolic syndrome-a new world-wide definition. A consensus statement from the International Diabetes Federation. Diabet Med 2006;23: Romero-Corral A, Montori VM, Somers VK, et al. Association of bodyweight with total mortality and with cardiovascular events in coronary artery disease: a systematic review of cohort studies. Lancet 2006;368: Koster A, Leitzmann MF, Schatzkin A, et al. Waist circumference and mortality. Am J Epidemiol 2008;167: Expert Panel on the Identification, Evaluation, and Treatment of Overweight in Adults. Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults: Executive summary. Am J Clin Nutr 1998;68: Snijder MB, Dekker JM, Visser M, et al. Associations of hip and thigh circumferences independent of waist circumference with the incidence of type 2 diabetes: the Hoorn Study. Am J Clin Nutr 2003;77: Allison DB, Zhu SK, Plankey M, Faith MS, Heo M. Differential associations of body mass index and adiposity with all-cause mortality among men in the first and second National Health and Nutrition Examination Surveys (NHANES I and NHANES II) follow-up studies. Int J Obes Relat Metab Disord 2002;26: Kvist H, Chowdhury B, Grangard U, Tylen U, and Sjostrom L. Total and visceral adipose-tissue volumes derived from measurements with computed tomography in adult men and women: predictive equations. American Journal of Clinical Nutrition 1988;48: Van der Kooy K, Leenen R, Seidell JC, Deurenberg P, and Visser M. Abdominal diameters as indicators of visceral fat: comparison between magnetic resonance imaging and anthropometry. British Journal of Nutrition 1993;70: Clasey JL, Bouchard C, Teates CD, et al. The use of anthropometric and dual-energy X-ray absorptiometry (DXA) measures to estimate total abdominal and abdominal visceral fat in men and women. Obesity Research 1999;7: Ris erus U, Arnl ov J, Brismar K, Zethelius B, Berglund L and Vessby B. Sagittal abdominal diameter is a strong anthropometric marker of insulin resistance and hyperproinsulinemia in obese men. Diabetes Care 2004;27: Mazzali G, Di Francesco V, Zoico E, et al. Interrelations between fat distribution,muscle lipid content, adipocytokines, and insulin resistance: effect of moderate weight loss in older women. American Journal of Clinical Nutrition 2006;84: Richelsen B, Pedersen SB. Associations between different anthropometric measurements of fatness and metabolic risk parameters in non-obese, healthy, middle-aged men. International Journal of Obesity 1995;19: Ohrvall M, Berglund L and Vessby B. Sagittal abdominal diameter compared with other anthropometric measurements in relation to cardiovascular risk. Int J Obes 2000;24: Van der Kooy K, Leenen R, Seidell JC, Deurenberg P, Visser M. Abdominal diameters as indicators of visceral fat: comparison between magnetic resonance imaging and anthropometry. Br J Nutr 1993;70: Clasey JL, Bouchard C, Teates CD, Riblett JE, Thorner MO, Hartman ML, Weltman A. The use of anthropometric and dual-energy x-ray absorptiometry (DXA) measures to estimate total abdominal and abdominal visceral fat in men and women. Obes Res 1999;7: Turcato E, Bosello O, Di Francesco V, Harris TB, Zoico E, Bissoli L, Fracassi E and Zamboni M. Waist circumference and abdominal sagittal diameter as surrogates of body fat distribution in the elderly: their relation with cardiovascular risk factors. Int J Obes Relat Metab Disord 2000;24: Valsamakis G, Chetty R, Anwar A, Banerjee AK, Barnett A, Kumar S. Association of simple anthropometric measures of obesity with visceral fat and the metabolic syndrome in male Caucasian and Indo-Asian subjects. Diabet Med 2004;21:

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