It is not clear if dual-energy X-ray absorptiometry (DXA) adiposity measures are superior to standard anthropometric measures for predicting cardiometabolic (CM) risk factors in a middle-aged general population. In the Busselton Healthy Ageing Study, we assessed a range of standard anthropometric and DXA-derived adiposity measures to predict metabolic syndrome (MetS) and CM risk factors in 4831 “baby boomers” aged 45–69 yr. Anthropometric and whole body DXA (GE Lunar Prodigy) measures were collected. Cross-sectional relationships of overall adiposity (BMI; DXA fat mass index, body fat %), central adiposity (waist circumference (WC); DXA trunk fat, android fat, abdominal visceral adipose tissue (VAT)) and ratio index (waist-to-hip ratio; DXA trunk/legs fat, android/gynoid ratio, VAT/total fat) with MetS and its components (as both continuous and binary outcomes) were evaluated using linear and logistic regression adjusting for age and lifestyle factors. Youden's Index was used to determine the optimal cut-points for predicting MetS. In linear regression analyses, central adiposity measures showed stronger associations with MetS score and CM risk factors than overall adiposity measures and fat ratio index, and DXA-VAT provided stronger associations than WC. Logistic regression models showed similar findings. For MetS diagnosis present in 35.9% of males and 24.4% of females, the highest odds ratio (95% CI) per SD change was observed for DXA-VAT (males: 5.02 [4.28, 5.88]; females: 3.91 [3.40, 4.49]), which remained significant (all p < 0.001) after further adjustment for BMI (males: 3.27 [2.65, 4.02]; females: 3.37 [2.79, 4.06]) or WC (males: 2.46 [1.95, 3.10]; females: 2.75 [2.21, 3.43]). The optimal DXA-VAT mass cut-point for predicting MetS was 1608 grams in males and 893 grams in females. DXA-VAT was superior to standard anthropometric and other DXA-derived adiposity measures for prediction of cardiometabolic risk factors, and has clinical utility for identifying middle-aged individuals at increased risk of MetS.

目前尚不清楚双能 X 射线骨密度仪 (DXA) 肥胖测量是否优于标准人体测量测量来预测中年一般人群的心脏代谢 (CM) 风险因素。在巴瑟尔顿健康老龄化研究中，我们评估了一系列标准人体测量学和 DXA 衍生的肥胖测量来预测代谢综合征(MetS) 和 CM 风险因素在 4831 名 45-69 岁的“婴儿潮一代”中。收集人体测量和全身 DXA（GE Lunar Prodigy）测量值。总体肥胖（BMI；DXA 脂肪质量指数，体脂百分比）、中央肥胖（腰围（WC）；DXA 躯干脂肪、机器人脂肪、腹部内脏脂肪组织（VAT））和比率指数（腰围）的横截面关系臀比例；DXA 躯干/腿部脂肪、机器人/女性比例、增值税/总脂肪）与 MetS 及其成分（作为连续和二元结果）使用线性和逻辑回归调整年龄和生活方式因素进行评估。Youden 指数用于确定预测 MetS 的最佳切点。在线性回归分析显示，中央肥胖测量与 MetS 评分和 CM 风险因素的相关性强于整体肥胖测量和脂肪比率指数，并且 DXA-VAT 提供的相关性强于 WC。逻辑回归模型显示了类似的发现。对于 35.9% 的男性和 24.4% 的女性存在 MetS 诊断，DXA-VAT 观察到每次 SD 变化的最高比值比 (95% CI)（男性：5.02 [4.28, 5.88]；女性：3.91 [3.40, 4.49] ]），这仍然很重要（所有p< 0.001) 进一步调整 BMI（男性：3.27 [2.65, 4.02]；女性：3.37 [2.79, 4.06]）或 WC（男性：2.46 [1.95, 3.10]；女性：2.75 [2.21, 3.43]）。预测 MetS 的最佳 DXA-VAT 质量切点是男性 1608 克，女性 893 克。DXA-VAT 在预测心脏代谢危险因素方面优于标准人体测量学和其他 DXA 衍生的肥胖测量方法，并且具有识别 MetS 风险增加的中年个体的临床实用性。