Cardiorespiratory fitness as a predictor of short-term and lifetime estimated cardiovascular disease risk.

Development of cardiovascular disease (CVD) remains a public health concern for young to middle-aged adults, now exacerbated by the increasing prevalence of obesity and sedentary lifestyles. Cardiorespiratory fitness (CRF) improves the reclassification of short-term (10-year) CVD risk, but has not been uniformly defined across studies. This study evaluated cross-sectional differences in short-term and lifetime CVD risk scores, across both absolute metabolic equivalent (MET) and sex- and age-standardized CRF categories in 805 apparently healthy young to middle-aged adults (68% male; 47.4 ± 7.2 years). CVD risk factors were evaluated, and estimated cardiorespiratory fitness (CRF) measurements (METS and peak VO2 ) were derived from a submaximal Bruce treadmill test. CRF measures also included post-exercise heart rate recovery (HRR) data. Consistent trends showing more favorable risk factor profiles and lower short-term CVD (QRISK2), and CVD mortality (SCORE) scores, associated with higher levels of CRF were evident in both sexes. Lifetime CVD risk (Q-Lifetime) was highest in the lowest CRF categories. Peak VO2 and HRR following submaximal exercise testing contributed to the variability in short-term and lifetime CVD risk. Global CVD risk predictions were examined across different contemporary CRF classifications with inconsistent findings. Recommended absolute MET and sex- and age-standardized CRF categories were significantly associated with both short-term and lifetime risk of CVD outcomes. However, compared to internationally derived normative CRF standards, cohort-specific CRF categories resulted in markedly different proportion of individuals classified in the "poor" CRF category at higher CVD risk.

Prediction of whole-body fat percentage and visceral adipose tissue mass from five anthropometric variables.

BACKGROUND: The conventional measurement of obesity utilises the body mass index (BMI) criterion. Although there are benefits to this method, there is concern that not all individuals at risk of obesity-associated medical conditions are being identified. Whole-body fat percentage (%FM), and specifically visceral adipose tissue (VAT) mass, are correlated with and potentially implicated in disease trajectories, but are not fully accounted for through BMI evaluation. The aims of this study were (a) to compare five anthropometric predictors of %FM and VAT mass, and (b) to explore new cut-points for the best of these predictors to improve the characterisation of obesity. METHODS: BMI, waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR) and waist/height0.5 (WHT.5R) were measured and calculated for 81 adults (40 women, 41 men; mean (SD) age: 38.4 (17.5) years; 94% Caucasian). Total body dual energy X-ray absorptiometry with Corescan (GE Lunar iDXA, Encore version 15.0) was also performed to quantify %FM and VAT mass. Linear regression analysis, stratified by sex, was applied to predict both %FM and VAT mass for each anthropometric variable. Within each sex, we used information theoretic methods (Akaike Information Criterion; AIC) to compare models. For the best anthropometric predictor, we derived tentative cut-points for classifying individuals as obese (>25% FM for men or >35% FM for women, or > highest tertile for VAT mass). RESULTS: The best predictor of both %FM and VAT mass in men and women was WHtR. Derived cut-points for predicting whole body obesity were 0.53 in men and 0.54 in women. The cut-point for predicting visceral obesity was 0.59 in both sexes. CONCLUSIONS: In the absence of more objective measures of central obesity and adiposity, WHtR is a suitable proxy measure in both women and men. The proposed DXA-%FM and VAT mass cut-offs require validation in larger studies, but offer potential for improvement of obesity characterisation and the identification of individuals who would most benefit from therapeutic intervention.