Constructing a metabolic integral score model for the quantification of metabolic dysfunction and tendency

Nutr Metab Cardiovasc Dis. 2022 Mar;32(3):658-665. doi: 10.1016/j.numecd.2021.12.014. Epub 2021 Dec 21.

Abstract

Background and aims: The binary nature of metabolic syndrome (MetS) cannot quantitatively describe the severity of metabolic abnormalities. We aim to establish a metabolic integral score (MIS) model to quantify the severity and polarity of metabolic disorders and their relationship with insulin sensitivity and secretion.

Methods and results: We performed factor analysis on 9950 participants from a cross-sectional study conducted in China. The MIS model was established using 10 variables including body mass index (BMI), waist circumference, hip circumference, glycosylated hemoglobin (HbA1c), fasting and 2-h plasma glucose (FPG, 2h-PG), systolic blood pressure (SBP), diastolic blood pressure (DBP), high-density lipoprotein (HDL) and triglyceride (TG) levels. Four common factors were identified as "glucose factor," "obesity factor," "blood pressure factor," and "lipid factor," respectively, in MIS model (KMO = 0.755, P < 0.001). MIS = 0.433 × Factor 1 + 0.267 × Factor 2 + 0.172 × Factor 3 + 0.128 × Factor 4. Insulin sensitivity and β-cell function decreased with the increase of MIS (P < 0.001). We classified four metabolic tendencies according to factor quartiles. Individuals in Tendency 1 (severe hyperglycemia) had the worst β-cell function. Tendency 3 (severe hypertension) had the best insulin sensitivity. Tendency 4 (severe dyslipidemia) had preferable β-cell function (P < 0.05).

Conclusions: Our MIS model provides a quantitative scoring system to assess various patterns of metabolic abnormality that indicate different underlying pathophysiology.

Keywords: Insulin sensitivity; Metabolic integral score model; Metabolic tendency; β-cell function.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Blood Glucose* / metabolism
  • Body Mass Index
  • Cross-Sectional Studies
  • Humans
  • Metabolic Syndrome* / diagnosis
  • Metabolic Syndrome* / epidemiology
  • Waist Circumference

Substances

  • Blood Glucose