Abstract
Background/Objectives:Fat distribution is a strong and independent predictor of type 2 diabetes (T2D) and cardiovascular disease (CVD) and is usually determined using conventional anthropometry in epidemiological studies. Dual-energy X-ray absorptiometry (DXA) can measure total and regional adiposity more accurately. Nonetheless, whether DXA provides more precise estimates of cardiovascular risk in relation to total and regional adiposity is not known. We determined the strength of the associations between DXA- and conventional anthropometry determined fat distribution and T2D and CVD risk markers.Subjects/Methods:Waist (WC) and hip circumference (HC) and DXA was used to measure total and regional adiposity in 4950 (2119 men) participants aged 29–55 years from the Oxford Biobank without pre-existing T2D or CVD. Cross-sectional associations were compared between WC and HC vs. DXA-determined regional adiposity (all z-score normalised) with impaired fasting glucose, hypertriglyceridemia, hypertension and insulin resistance (IR).Results:Following adjustment for total adiposity, upper body adiposity measurements showed consistently increased risk of T2D and CVD risk markers except for abdominal subcutaneous fat in both sexes, and arm fat in men, which showed protective associations. Among upper adiposity depots, visceral fat mass showed stronger odds ratios (OR) ranging from 1.69 to 3.64 compared with WC 1.07–1.83. Among lower adiposity depots, HC showed modest protection for IR in both sexes (men: OR 0.80 (95% confidence interval 0.67, 0.96); women: 0.69 (0.56, 0.86)), whereas gynoid fat and in particular leg fat showed consistent and strong protective effects for all outcomes in both men and women. The differential effect of body fat distribution on CVD and T2D were more pronounced at higher levels of total adiposity.Conclusions:Compared with DXA, conventional anthropometry underestimates the associations of regional adiposity with T2D and CVD risk markers. After correcting for overall adiposity, greater subcutaneous fat mass in particular in the lower body is protective relative to greater android or visceral adipose tissue mass.
Highlights
Higher Body mass index (BMI) was associated with higher WC, hip circumferences (HC) and DXAquantified total fat mass in both sexes (Supplementary Table 1)
We demonstrate that (i) WC and HC are imprecise surrogates of regional adiposity as they reflect total fat (ii) dual-energy X-ray absorptiometry (DXA)-measured fat masses are strongly associated with type 2 diabetes (T2D) and cardiovascular disease (CVD) risk factors and bring out the dichotomy between upper and lower body adiposity in relation to cardiac and metabolic risk more robustly than conventional anthropometry (iii) Subcutaneous fat depots are associated with a favourable cardiometabolic profile with modest associations observed with arm fat and abdominal subcutaneous adipose tissue (aSAT) (iv) the opposing associations of upper and lower fat depots with risk factors are more evident at higher levels of total adiposity
In a systematic approach to understanding the relationship between anthropometry and DXA-assessed regional fat masses and T2D and CVD risk factors, we first sought to understand how the measurements of regional adiposity assessed by two different instruments relate to each other
Summary
Upper body (android and visceral fat) and lower body fat depots (gynoid and leg fat) show directionally opposite associations with T2D and CVD risks.[5,6,7,8,9] Data demonstrating the differential impact of regional fat depots on metabolic and CVD risk has been reported using either conventional anthropometric measurements[3,5,6,7,9] or imaging methods; namely computed tomography (CT), magnetic resonance imaging (MRI) and dual-energy X-ray absorptiometry (DXA),[10,11,12,13,14,15] but direct comparisons of magnitude of risk between conventional anthropometry and imaging platforms have not been systematically evaluated Circumference measurements such as waist (WC) and hip circumferences (HC) are subject to significant measurement variability and reproducibility, and this highlights the importance of quantifying body fat distribution more accurately using imaging techniques as regional adiposity has been shown to causally relate to CVD risk through multiple intermediate phenotypes.[16]. Recent advances in DXA technology have enabled accurate quantification of VAT,[19]
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