Krakauer Nir Y, Krakauer Jesse C
Department of Civil Engineering, The City College of New York, New York, NY, USA.
Metro Detroit Diabetes and Endocrinology, Southfield, MI, USA.
J Obes. 2018 Jul 12;2018:9241904. doi: 10.1155/2018/9241904. eCollection 2018.
Independent indices (height, body mass index, a body shape index, and hip index) derived from basic anthropometrics have been found to be powerful predictors of mortality hazard, especially when the attributable risks are summed over these indices to give an anthropometric risk index (ARI). The metabolic syndrome (MS) is defined based on the co-occurrence of anthropometric, clinical, and laboratory criteria and is also widely employed for evaluating disease risk. Here, we investigate correlations between ARI and MS in a general population sample, the United States Third National Health and Nutrition Examination Survey. Baseline values of ARI and MS were also evaluated for their association with mortality over approximately 20 years of follow-up. ARI was found to be positively correlated with each component of MS, suggesting connections between the two entities as measures of cardiometabolic risk. ARI and MS were both significant predictors of mortality hazard. Although the association of ARI with mortality hazard was stronger than that of MS, a combined model with both ARI and MS score as predictors improved predictive ability over either construct in isolation. We conclude that the combination of anthropometrics and clinical and laboratory measurements holds the potential to increase the effectiveness of risk assessment compared to using either anthropometrics or the current components of MS alone.
源自基本人体测量学的独立指标(身高、体重指数、体型指数和臀围指数)已被发现是死亡风险的有力预测指标,尤其是当这些指标的归因风险相加得出人体测量风险指数(ARI)时。代谢综合征(MS)是根据人体测量、临床和实验室标准的共同出现来定义的,也被广泛用于评估疾病风险。在此,我们在美国第三次全国健康与营养检查调查这一普通人群样本中,研究ARI与MS之间的相关性。还评估了ARI和MS的基线值在约20年随访期内与死亡率的关联。发现ARI与MS的每个组分呈正相关,表明这两个实体作为心脏代谢风险指标之间存在联系。ARI和MS都是死亡风险的重要预测指标。虽然ARI与死亡风险的关联比MS更强,但将ARI和MS评分作为预测指标的联合模型比单独使用任何一个指标的预测能力都有所提高。我们得出结论,与单独使用人体测量学或MS的当前组分相比,人体测量学与临床及实验室测量相结合有可能提高风险评估的有效性。