Anthropometric indices and cut-off points in the diagnosis of metabolic disorders

PLoS One. 2020 Jun 22;15(6):e0235121. doi: 10.1371/journal.pone.0235121. eCollection 2020.

Abstract

Objective: Identifying metabolic disorders at the earliest phase of their development allows for an early intervention and the prevention of serious consequences of diseases. However, it is difficult to determine which of the anthropometric indices of obesity is the best tool for diagnosing metabolic disorders. The aims of this study were to evaluate the usefulness of selected anthropometric indices and to determine optimal cut-off points for the identification of single metabolic disorders that are components of metabolic syndrome (MetS).

Design: Cross-sectional study.

Participants: We analyzed the data of 12,328 participants aged 55.7±5.4 years. All participants were of European descent.

Primary outcome measure: Four MetS components were included: high glucose concentration, high blood triglyceride concentration, low high-density lipoprotein cholesterol concentration, and elevated blood pressure. The following obesity indices were considered: waist circumference (WC), body mass index (BMI), waist-to-height ratio (WHtR), body fat percentage (%BF), Clínica Universidad de Navarra-body adiposity estimator (CUN-BAE), body roundness index (BRI), and a body shape index (ABSI).

Results: The following indices had the highest discriminatory power for the identification of at least one MetS component: CUN-BAE, BMI, and WC in men (AUC = 0.734, 0.728, and 0.728, respectively) and WHtR, CUN-BAE, and WC in women (AUC = 0.715, 0.714, and 0.712, respectively) (p<0.001 for all). The other indices were similarly useful, except for the ABSI.

Conclusions: For the BMI, the optimal cut-off point for the identification of metabolic abnormalities was 27.2 kg/m2 for both sexes. For the WC, the optimal cut-off point was of 94 cm for men and 87 cm for women. Prospective studies are needed to identify those indices in which changes in value predict the occurrence of metabolic disorders best.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Anthropometry*
  • Area Under Curve
  • Female
  • Humans
  • Male
  • Metabolic Diseases / diagnosis*
  • Middle Aged

Grants and funding

The project was supported under the program of the Minister of Science and Higher Education under the name “Regional Initiative of Excellence” in 2019–2022, project number: 024/RID/2018/19, financing amount: 11.999.000,00PLN. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.