Cutoffs of abdominal adipose tissue compartments as measured by magnetic resonance imaging for detection of cardiovascular risk factors in apparently healthy adult Asian Indians in North India.
BACKGROUND
We aimed to define cutoffs of abdominal adipose tissue depots [total abdominal adipose tissue (TAAT), intraabdominal adipose tissue (IAAT), and abdominal subcutaneous adipose tissue (SCAT)] in adult Asian Indians in North India.


METHODS
We carried out a cross-sectional study that included 100 healthy adult Asian Indians. Anthropometric measurement (waist circumference, body mass index), metabolic profile [oral glucose tolerance test (OGTT), lipid profile], and imaging (for quantification of area of abdominal adipose tissue components using single slice magnetic resonance imaging) were done. Odds ratios (ORs) for detecting presence of greater than one cardiovascular (CV) risk factor were computed using tertiles of adipose tissue compartments and cutoffs were generated using receiver operating characteristics curve analysis.


RESULTS
The gender-specific cutoff limits for of TAAT, IAAT, and SCAT were 245.6 cm(2) (male) and 203.46 cm(2) (female), 135.3 cm(2) (male) and 75.73 cm(2) (female), and 110.74 cm(2) (male) and 134.02 cm(2) (female), respectively. For detection of CV risk factors, distinct gender differences were seen in ORs for SCAT [3.54 (95% confidence interval [CI], 1.10-11.46) and 6.6 (95% CI, 1.75-24.85) in males and females, respectively] but not for IAAT.


CONCLUSIONS
The cutoffs of TAAT, IAAT, and SCAT generated for the first time in Asian Indians could be used for metabolic research, interethnic comparisons of adiposity and CV risk factors, and optimal selection of anthropometric parameters.
Misra
Anoop
A
Department of Diabetes and Metabolic Diseases, Fortis Hospital, Vasant Kunj, New Delhi, India. anoopmisra@metabolicresearchindia.com
Wasir
Jasjeet S
JS
Vikram
Naval K
NK
Pandey
Ravindra M
RM
Kumar
Pawan
P
D050153:Abdominal Fat / Q000473:pathology*; D050154:Adiposity / Q000208:ethnology*; D000328:Adult; D044466:Asian People / Q000706:statistics & numerical data*; D015415:Biomarkers / Q000097:blood; D001786:Blood Glucose / Q000378:metabolism; D015992:Body Mass Index; D002318:Cardiovascular Diseases / Q000208:ethnology / Q000209:etiology* / Q000473:pathology; D003430:Cross-Sectional Studies; D005260:Female; D006801:Humans; D007194:India / Q000453:epidemiology; D050152:Intra-Abdominal Fat / Q000473:pathology; D008055:Lipids / Q000097:blood; D016015:Logistic Models; D008279:Magnetic Resonance Imaging; D008297:Male; D056128:Obesity, Abdominal / Q000150:complications / Q000208:ethnology* / Q000473:pathology; D016017:Odds Ratio; D050177:Overweight / Q000150:complications / Q000208:ethnology* / Q000473:pathology; D011237:Predictive Value of Tests; D015995:Prevalence; D012372:ROC Curve; D018570:Risk Assessment; D012307:Risk Factors; D012737:Sex Factors; D050507:Subcutaneous Fat, Abdominal / Q000473:pathology; D055105:Waist Circumference; D055815:Young Adult
D015415:Biomarkers; D001786:Blood Glucose; D008055:Lipids