3/25/2010. Age-adjusted incidence rates for coronary heart disease according to body mass index and waist circumference tertiles

Transcription

1 Outline Relationships among Regional Adiposity, Physical Activity, and CVD Risk Factors: Preliminary Results from Two Epidemiologic Studies Molly Conroy, MD, MPH Obesity Journal Club February 18, 2010 Measuring regional adiposity in epidemiological studies Regional adiposity, physical activity, and cardiometabolic risk factors in the WOMAN study Regional adiposity and subclinical carotid disease in the SAVE study Discussion Measuring regional adiposity in epidemiological studies What is regional adiposity? Regional adiposity is a measure of both the quantity and location of adipose (fat) tissue Many different techniques can measure regional adiposity: MRI > CT >> DXA > skinfold > waist/hip Selection of method depends on research question and budget Why does regional adiposity matter? Measuring Waist Circumference (WC) Fat deposition in certain areas (e.g., around visceral organs) associated with poorer metabolic and cardiovascular outcomes Distribution of body fat is independently associated with the metabolic syndrome in older men and women, particularly among those of normal body weight 1

2 Waist Circumference (WC) Cutoffs WC of > 88 cm (35 inches) for women (or > 102 cm (40 inches) for men) is associated with increased risk of hypertension, diabetes, dyslipidemia, and metabolic syndrome These findings are consistent independent of BMI category In women, cutoff consistent across non- Asian racial/ethnic groups WC in Epidemiological Studies Given (relative) ease of measurement, WC data available in many large epi studies Some large studies (e.g., Nurse s Health, Women s Health) use participant-reported p reported measurement, with decent validity compared to technician-measured values Pearson correlation 0.89 for WC in NHS In NHS, WC independently associated with risk of coronary heart disease Age-adjusted incidence rates for coronary heart disease according to body mass index and waist circumference tertiles Limitations of WC As with any method, correlational findings may not be consistent across all groups In Framingham cohort, WC only associated with CVD in overweight women (Freiberg, et al. Obesity (2008) 16, ) 469) Among normal weight or obese women and men (regardless of BMI category) WC did not appear to substantially add to prediction of CVD WC does not differentiate between types of abdominal fat (i.e., visceral vs. subcutaneous) Rexrode, K. M. et al. JAMA 1998;280: Computed Tomography (CT) to Measure Regional Adiposity CT can obtain images of adipose tissue at waist, which can then be divided into subcompartments Volume of visceral adipose tissue (VAT) usually associated with worse cardiometabolic outcomes CT measurements done in subgroups or larger epi studies (e.g., Framingham, SWAN Heart) 2

3 Prevalence of hypertension (HTN), impaired fasting glucose (IFG), diabetes (DM), and MetS among normal-weight (A), overweight (B), and obese (C) individuals across quartiles of VAT Computed Tomography (CT) to Measure Thigh Adiposity Fox, C. S. et al. Circulation 2007;116:39-48 Thigh Adiposity Also a Predictor of Metabolic Disease Health Aging and Body Composition (Health ABC) Study measured adipose tissue at waist and mid-thigh in a biracial, elderly cohort Higher rates of intermuscular fat (IMAT) and VAT were associated with higher fasting insulin in normal-weight (BMI <25 kg/m2) men (r = 0.24 for IMAT, r = 0.37 for VAT, both P < ) and women (r = 0.20 for intermuscular fat, r = 0.40 for VAT, both P < ) Associations were not found in obese subjects (Goodpaster BH, et al Diabetes Care 2003; 26 (2): ) Limitations of CT Cost Participant burden Does not add info beyond WC/BMI in all studies Radiation dose Estimated range in the lifetime attributable risk of cancer if a 20-year-old woman underwent one of several types of computed tomographic (CT) studies using the distribution in radiation dose Regional adiposity, physical activity, and cardiometabolic risk factors in the WOMAN study Smith-Bindman, R. et al. Arch Intern Med 2009;169:

4 The WOMAN Study Women on the Move through Activity and Nutrition (WOMAN) NHLBI-funded study of a non- pharmacological lifestyle intervention Diet and physical activity to reduce weight subclinical markers of CVD in women aged (PI: L. Kuller) 508 women randomized to an intensive intervention or control group Measures Outcome: CT-measured regional adiposity and muscle strength Primary yp predictors: Physical activity Weight Potential moderator: hormone therapy Measures: Regional adiposity and muscle strength CT used to measure two slices: Abdomen at L4-5 Leg at mid-thigh At each region, adipose tissue can be compartmentalized: subcutaneous, subfascial (deep), visceral or intramuscular Thigh muscle size and attenuation KinCom used to measure leg strength isokinetically Measures: Muscle quality Muscle strength: isokinetic quadriceps strength measured by KinCom Muscle mass: thigh muscle area measured by computed tomography (CT) Muscle quality = strength/area CT Image Analysis CT scans analyzed using Slice-o-Matic computer software in Obesity and Nutrition Research Center Analysis takes approximately 20 minutes per scan (abdominal and thigh slice) 4

5 Results: Participant characteristics at 48 months Results: Regional adiposity and muscle quality at 48 months Age (years) Education: college Race: White Hormone Therapy (HT) Use Weight (lbs) BMI Median PA (MET-hrs/week) N=199; data are means or % % 90% 21% Total abdominal fat (cm 2 ) Subcutaneous abdominal fat (cm 2 ) Visceral abdominal fat (cm 2 ) Total leg fat (cm 2 ) Intramuscular leg fat (cm 2 ) Peak strength (Newton meters) Leg muscle area (cm 2 ) Muscle quality (Newton meters/ cm 2 ) Correlations: PA and Regional adiposity/muscle quality PA Total abdominal Visceral abdominal Intramuscular Muscle strength Muscle area Muscle quality P <0.05; P <0.01; P <0.001 Correlations: PA, Regional adiposity/muscle quality, by HT + HT -HT Total abdominal Visceral abdominal Intramuscular Muscle strength Muscle area Muscle quality P <0.05; P <0.01; P <

6 Additional PA analyses No relationship between consistently high activity at various time points and regional adiposity/muscle quality Higher levels of physical activity do not seem to ameliorate/alter the relationship between higher weight and greater levels of adiposity and poorer muscle quality Possible explanations for low correlation between PA and regional adiposity Less variability of PA than in general population Also less variability in adiposity measures by hormone therapy than expected Limitations of PA measure Further analyses could use pedometer or corridor walk data Weight, adiposity and muscle quality Weight Total abdominal 0.79 Visceral abdominal Intramuscular 0.45 Muscle strength 0.22 Muscle area 0.52 Muscle quality Weight, adiposity and muscle quality Intramuscular adiposity is more strongly correlated with muscle quality (r=-0.27) than other regional adiposity measures or weight Also strongest predictor in multivariable models, although not statistically significant (p=0.12) Regional Adiposity, lipids, and glucose/insulin Gluc Ins HDL TG Total abdominal Visceral abdominal Intramuscular Muscle strength Muscle quality Regional Adiposity and NMR lipids Increased visceral adiposity associated with: More large and medium VLDL More large, medium and small LDL Less large HDL; more small HDL Greater VLDL and VLDL TG size Smaller LDL and HDL size Increased intermuscular adiposity only associated with more large VLDL and greater VLDL size P <0.05; P <0.01; P <

7 CT vs. DXA measures High correlation between DXA and CT measures of trunk/abdominal adiposity (r= ) 0.75) and total leg adiposity (0.85) but lower correlation between DXA and intramuscular adiposity (r=0.26) Intramuscular adiposity more strongly associated with muscle quality than DXA measures Conclusions Impact of physical activity on regional adiposity and muscle quality is not significant after considering body weight Intramuscular adiposity measured by CT is the strongest predictor of muscle quality; higher levels of intramuscular fat were associated with poorer muscle quality DXA measures relate to total leg adiposity on CT, but not intramuscular fat Regional adiposity and subclinical carotid disease in the SAVE study Giang (Suzane) T. Le Helen A. Smith Emma Barinas-Mitchell Kim Sutton-Tyrrell (PI) Kazanna C. Hames Molly B. Conroy The SAVE Study Population: Slow Adverse Vascular Effects (SAVE) study (N=300): mean age 38 (±6) years; mean BMI 33 (±4) kg/m2; 78% women; 83% non-black; Pittsburgh, PA Inclusion Criteria: Age 20-45, BMI kg/m2, Reside in Pittsburgh area, Not pregnant, No hypertension, No diabetes, No known CVD Study Design: Cross-sectional analysis of 2- year, ongoing, clinical trial of a behavioral weight loss intervention Measurements Regional Adiposity: Single-slice CT scans measuring VAT taken at spinal column level L4-L5 and thigh IMAT at 15 cm above upper patellar border Carotid AD and IMT: evaluated by B-mode ultrasound Statistical Analysis Pearson correlation coefficients (rho) determined to examine associations of VAT, IMAT, and BMI with carotid AD and IMT Standardized β coefficients (STB) Derived from multivariable linear regression Used to evaluate relationships between both carotid AD and IMT and regional adiposity while controlling for BMI, age, gender, and race 7

8 Characteristics of SAVE Population Characteristic Mean (SD) Age, y 38 (6) Gender, female 234 (78)* Race, nonblack 248 (82.7)* BMI, kg/m (3.8) Weight, kg 92.0 (14.9) Waist Circumference, cm (11.2) Carotid IMT, mm 0.61 (0.10) Carotid AD, mm 690(053) 6.90 (0.53) Abdominal CT Measurements: Subcutaneous Fat, cm (134.0) Visceral Fat, cm (55.7) Total Fat, cm (141.9) Thigh CT Measurements: Subcutaneous Fat, cm (48.1) IMAT, cm (4.8) Total Fat, cm (49.1) *n (%) Univariable and Multivariable Associations between Measures of Regional Adiposity and Carotid Artery Adventitial Diameter Rho STB 1 STB+ 2 VAT IMAT 0.171* Rho, Pearson Correlation Coefficient; STB, Standardized β Coefficient 1 Multivariable Regression Analysis, adjusted for BMI; 2 Multivariable Regression Analysis, adjusted for BMI, age, gender, and race P< * P<0.05 Univariable and Multivariable Associations between Measures of Regional Adiposity and Carotid Artery Intima-Media Thickness Rho STB 1 STB+ 2 VAT * IMAT Rho, Pearson Correlation Coefficient; STB, Standardized β Coefficient 1 Multivariable Regression Analysis, adjusted for BMI; 2 Multivariable Regression Analysis, adjusted for BMI, age, gender, and race P< * P<0.05 Results Increased VAT was significantly associated with increased AD (rho=0.35; p<0.0001) and IMT (rho=0.24; p<0.0001) IMAT was only significantly associated with AD (rho=0.17; p=0.004) Higher BMI was also significantly associated with increased AD (rho=0.33; p<0.0001) and IMT (rho=0.23; p<0.0001) In both fully adjusted multivariable models, VAT was not significantly related to either AD or IMT Male gender, black race, higher BMI, and increasing age were significant predictors of AD and IMT in fully adjusted models (data not shown) Conclusions SAVE participants with greater VAT, IMAT or higher BMI had greater carotid AD and/or IMT measurements, indicating poorer vascular health VAT remained an independent predictor of carotid AD and IMT after adjusting for BMI, but was not a significant predictor of subclinical carotid disease in either fully adjusted model Further work is needed to determine the utility of regional adiposity measures in predicting CVD in younger populations, as well as tracking how regional adiposity and BMI changes over time relate to CVD development Discussion What is your experience with using regional adiposity measurements? Do you find regional adiposity to be a useful concept/tool for your research population(s)? How do you balance the pros and cons of various methods for your subjects? Other questions? 8