Dominguez Ligia J, Sayón-Orea Carmen, Gea Alfredo, Toledo-Atucha Estefania, Bes-Rastrollo Maira, Barbagallo Mario, Martínez-González Miguel A
Department of Medicine and Surgery, University Kore of Enna, 94100 Enna, Italy; Geriatric Unit, Department of Internal Medicine and Geriatrics, University of Palermo, 90127 Palermo, Italy.
Department of Preventive Medicine and Public Health, University of Navarra-IdiSNA, 31008 Pamplona, Spain; CIBER Fisiopatologia de la Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III, 28029 Madrid, Spain; Public Health Institute, 31003 Navarra, Spain.
J Nutr Health Aging. 2025 May;29(5):100545. doi: 10.1016/j.jnha.2025.100545. Epub 2025 Mar 26.
Obesity is currently a pandemic and a cardinal risk factor for incident diabetes, a parallel growing pandemic. Measures commonly used to define obesity, i.e., BMI and waist circumference, do not accurately reflect body fatness.
We examined the prognostic value of body fatness assessed with the 'Clínica Universidad de Navarra-Body Adiposity Estimator' (CUN-BAE, range: 18.4-65.0 %) in 18,594 participants of the "Seguimiento Universidad de Navarra" prospective longitudinal cohort (60.5% women) without diabetes at baseline. Participants were followed-up with biennial questionnaires and multivariable-adjusted Cox models were used to estimate incident diabetes.
During 13.7 years of median follow-up, 209 participants developed diabetes. Progressively ascending quartiles of CUN-BAE were significantly associated with incident diabetes in multivariable-adjusted models, even after adjusting for BMI > 30 kg/m. For each 2-unit increment in the CUN-BAE index, diabetes risk relatively increased by 46% in men and women (95% CI: 33%-62%). When comparing ROC AUC for CUN-BAE and BMI the association was stronger for CUN-BAE (p < 0.001).
CUN-BAE index, an easy equation that can be used in any clinical setting, predicted better the risk of incident diabetes compared to BMI. Our results emphasize the importance of reducing and maintaining a low adiposity in order to prevent diabetes.
肥胖目前是一种流行病，也是并发糖尿病这一同样在不断蔓延的流行病的主要危险因素。常用于定义肥胖的指标，即体重指数（BMI）和腰围，并不能准确反映身体脂肪含量。
我们在“纳瓦拉大学跟踪研究”这一前瞻性纵向队列的18594名参与者（60.5%为女性）中，研究了用“纳瓦拉大学临床人体脂肪估计器”（CUN - BAE，范围：18.4 - 65.0%）评估的身体脂肪含量的预后价值，这些参与者在基线时无糖尿病。通过每两年一次的问卷调查对参与者进行随访，并使用多变量调整的Cox模型来估计糖尿病的发病率。
在中位随访13.7年期间，209名参与者患上了糖尿病。在多变量调整模型中，即使在调整了BMI > 30 kg/m²之后，CUN - BAE的四分位数逐渐升高仍与糖尿病的发生显著相关。CUN - BAE指数每增加2个单位，男性和女性患糖尿病的风险相对增加46%（95%置信区间：33% - 62%）。比较CUN - BAE和BMI的ROC曲线下面积（AUC）时，CUN - BAE的相关性更强（p < 0.001）。
CUN - BAE指数是一个可在任何临床环境中使用的简单公式，与BMI相比，它能更好地预测糖尿病的发病风险。我们的结果强调了降低并维持低脂肪含量以预防糖尿病的重要性。
