Department of Kinesiology and Community Health, College of Applied Health Sciences, University of Illinois at Urbana-Champaign, Champaign, IL, USA.
School of Sports Journalism and Foreign Studies, Shanghai University of Sport, Shanghai, China.
Obes Rev. 2018 May;19(5):737-759. doi: 10.1111/obr.12666. Epub 2018 Jan 19.
Anthropometric measures are simple, inexpensive, noninvasive tools to assess the risk of morbidity and mortality. This systematic review assessed the performance of A Body Shape Index (ABSI) in predicting hypertension, cardiovascular disease, type 2 diabetes and all-cause mortality and compared the differential predictability between ABSI and two other common anthropometric measures - body mass index and waist circumference. A keyword and reference search were conducted in the PubMed and Web of Science for articles published until 1 November 2017. Thirty-eight studies were included in the review, including 24 retrospective cohort studies and 14 cross-sectional studies conducted in 15 countries. Meta-analysis found that a standard deviation increase in ABSI was associated with an increase in the odds of hypertension by 13% and type 2 diabetes by 35% and an increase in cardiovascular disease risk by 21% and all-cause mortality risk by 55%. ABSI outperformed body mass index and waist circumference in predicting all-cause mortality but underperformed in predicting chronic diseases. ABSI is highly clustered around the mean with a rather small variance, making it difficult to define a clinical cutoff for clinical practice. Future studies are warranted to assess ABSI's potential usefulness as an anthropometric measure in population-level health surveillance.
人体测量指标是一种简单、廉价、无创的工具，可用于评估发病率和死亡率的风险。本系统评价评估了身体形状指数 (ABSI) 在预测高血压、心血管疾病、2 型糖尿病和全因死亡率方面的性能，并比较了 ABSI 与另外两种常见人体测量指标（体重指数和腰围）的预测差异。在 PubMed 和 Web of Science 中进行了关键词和参考文献搜索，以检索截至 2017 年 11 月 1 日发表的文章。本综述共纳入 38 项研究，包括 24 项回顾性队列研究和 14 项横断面研究，这些研究在 15 个国家进行。荟萃分析发现，ABSI 每增加一个标准差，患高血压的几率增加 13%，患 2 型糖尿病的几率增加 35%，患心血管疾病的风险增加 21%，全因死亡率风险增加 55%。ABSI 在预测全因死亡率方面优于体重指数和腰围，但在预测慢性病方面表现不佳。ABSI 在平均值周围高度集中，方差相当小，因此很难为临床实践定义一个临床截止值。未来的研究有必要评估 ABSI 作为人群健康监测中人体测量指标的潜在有用性。
