Anthropometric and Biochemical Correlations of Insulin Resistance in a Middle-Aged Maltese Caucasian Population

Abstract

Background: Insulin resistance (IR) is associated with increased cardiovascular disease risk, and with increased all-cause, cardiovascular, and cancer mortality. A number of surrogate markers are used in clinical practice to diagnose IR. The aim of this study was to investigate the discriminatory power of a number of routinely available anthropometric and biochemical variables in predicting IR and to determine their optimal cutoffs.

Methods: We performed a cross-sectional study in a cohort of middle-aged individuals. We used receiver operator characteristics (ROC) analyses in order to determine the discriminatory power of parameters of interest in detecting IR, which was defined as homeostatic model assessment-insulin resistance ≥2.5.

Results: Both the lipid accumulation product (LAP) and visceral adiposity index (VAI) exhibited good discriminatory power to detect IR in both males and females. The optimal cutoffs were 42.5 and 1.44, respectively, in males and 36.2 and 1.41, respectively, in females. Serum triglycerides (TG) and waist circumference (WC) similarly demonstrated good discriminatory power in detecting IR in both sexes. The optimal cutoffs for serum TG and WC were 1.35 mmol/L and 96.5 cm, respectively, in men and 1.33 mmol/L and 82 cm, respectively, in women. On the other hand, systolic and diastolic blood pressure, liver transaminases, high-density lipoprotein cholesterol, serum uric acid, ferritin, waist-hip ratio, "A" body shape, thigh circumference, and weight-adjusted thigh circumference all had poor discriminatory power.

Conclusions: Our data show that LAP, VAI, TG, and WC all have good discriminatory power in detecting IR in both men and women. The optimal cutoffs for TG and WC were lower than those currently recommended in both sexes. Replication studies are required in different subpopulations and different ethnicities in order to be able to update the current cut points to ones which reflect the contemporary population as well as to evaluate their longitudinal relationship with longer-term cardiometabolic outcomes.

Figure 1

Flowchart of participant recruitment.

Figure 2

Correlation matrix between HOMA-IR level and anthropometric/clinical indices of adiposity (a) and biochemical parameters (b). Colour depicts Spearman's rank order correlation coefficient, with circle size and colour intensity indicating the magnitude of the correlation coefficient. Significant correlation coefficients are labelled; empty cells represent insignificant correlation between indices. HOMA-IR = homeostatic model assessment of insulin resistance; BMI = body mass index; WC = waist circumference; HC = hip circumference; NC = neck circumference; WHR = waist-hip ratio; WI = waist index; BAI = body adiposity index; CI = conicity index; BRI = body roundedness index; AVI = abdominal volume index; FPG = fasting plasma glucose; TC = total cholesterol; LDL = low-density lipoprotein cholesterol; HDL = high-density lipoprotein cholesterol; TG = triglycerides; HbA1c = glycated haemoglobin; ALP = alkaline phosphatase; GGT = gamma glutamyl transferase; ALT = alanine transaminase; LAP = lipid accumulation product; hsCRP = high-sensitivity C-reactive protein; and VAI = visceral adiposity index.

Figure 3

Receiver operator characteristic curves for lipid accumulation index, visceral adiposity index, and waist circumference to predict insulin resistance (HOMA-IR > 2.5) in males.

Figure 4

Receiver operator characteristic curves for lipid accumulation index, visceral adiposity index, and waist circumference to predict insulin resistance (HOMA-IR > 2.5) in females.