Feasibility of anthropometric indices to identify dyslipidemia among adults in Jilin Province: a cross-sectional study

Lipids Health Dis. 2018 Jan 22;17(1):16. doi: 10.1186/s12944-017-0648-6.

Abstract

Background: Dyslipidemia and other cardiovascular disease (CVD) risk factors have a strong association with obesity. Anthropometric indices have been widely used to evaluate obesity in clinical and epidemiological studies. We aim to investigate association between serum lipid levels and different anthropometric indices.

Methods: Our study included 17,554 participants. We mainly investigated area under the receiver operating characteristic (AUROC) curves and optimal operating points (OOPs) between the anthropometric indices and serum lipid levels or categories of abnormal serum lipid indices.

Results: For predicting one/two categories of abnormal serum lipid indices among the anthropometric indices, AUROC value of WC was the highest in men (0.718), and AUROC values of BRI and WHtR were the highest in women (0.700 and 0.700) (all P < 0.001); OOP of WC was 82.450 in men; OOPs of BRI and WHtR were 3.435 and 0.504 in women. For predicting three/more categories of abnormal serum lipid indices among the anthropometric indices, AUROC value of WC was the highest in men (0.806), and AUROC values of BRI and WHtR were the highest in women (0.783 and 0.783) (all P < 0.001); OOP of WC was 84.150 in men; OOPs of BRI and WHtR were 3.926 and 0.529 in women.

Conclusions: WC was a good predictor for one/two or three/more categories of abnormal serum lipid indices in men. However, BRI and WHtR were good predictors for one/two or three/more categories of abnormal serum lipid indices in women. ABSI showed the weakest predictive power.

Keywords: Anthropometric indices; Dyslipidemia; Serum lipid indices.

MeSH terms

  • Adult
  • Anthropometry
  • Area Under Curve
  • China
  • Cross-Sectional Studies
  • Dyslipidemias / diagnosis
  • Dyslipidemias / epidemiology*
  • Dyslipidemias / etiology
  • Female
  • Humans
  • Male
  • Middle Aged
  • Obesity / complications*
  • ROC Curve
  • Waist Circumference*
  • Waist-Hip Ratio*