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Lipid accumulation product ‘simple, powerful tool’ to predict metabolic syndrome
In Brazilian adults without diabetes or cardiovascular disease, lipid accumulation product is a strong predictor of metabolic syndrome, according to results from a cross-sectional study.
“[Lipid accumulation product] is emerging as a valuable tool for health screening purposes,” Marcus Vinicius Nascimento-Ferreira, a PhD student at the University of Sao Paulo School of Medicine in Brazil, and colleagues wrote. “However, studies addressing the predictor performance of this tool in clinical practice are scarce, as well as studies assessing [lipid accumulation product] predictability against [the] different [metabolic syndrome] definitions simultaneously. We hypothesized that [lipid accumulation product] has better predictor capacity to find [metabolic syndrome] in adults without a diagnosis of [CVD] and type 2 diabetes (in clinical practice) than the classical anthropometric parameters such as BMI, [waist circumference], [waist-to-hip ratio] and [waist-to-height ratio].”
Researchers analyzed data from 201 adults without previous diabetes or CVD (37.8% men; mean age, 51 years), recruited from the cardiovascular unit of University Hospital of the Federal University of Piaui between January and June 2014. Researchers assessed BMI, waist circumference, waist-to-height ratio, waist-to-hip ratio and lipid accumulation product (LAP), a measurement for estimating lipid over-accumulation among adults. Researchers defined LAP as a combination of waist circumference (as a proxy for visceral fat) and a fasting concentration of circulating triglycerides. Primary outcome was metabolic syndrome as defined by criteria from three different organizations (the American Heart Association; the National Heart, Lung, and Blood Institute; and the International Diabetes Federation) and the harmonized criteria among the three organizations. All participants also provided fasting blood samples. Researchers calculated LAP as (waist circumference – 65) x triglyceride measurement for men and (waist circumference – 58) x triglyceride measurement for women. Researchers used Poisson regression analysis, adjusted for age and sex, to calculate the prevalence ratio for developing metabolic syndrome based on the predictor variables, and estimated LAP cutoff points to predict metabolic syndrome, based on the harmonized criteria.
Within the cohort, 78.9% of men and 69.6% of women had metabolic syndrome.
Researchers found that LAP showed a lower prevalence ratio for predicting metabolic syndrome vs. waist-to-height ratio; however, LAP as a predictor performed better in the accuracy test after adjustment, followed by waist-to-height ratio and waist-to-hip ratio.
Researchers noted that the best cutoff point for LAP to identify metabolic syndrome, according to harmonized criteria, was 34.2 cm x mmol/L (sensitivity, 89.9; specificity, 61.11; positive likelihood ratio, 2.31; negative likelihood ratio, 0.17).
“In our study, LAP proved to be the most accurate instrument to predict [metabolic syndrome] according to three different criteria tested, in comparison with other common tools used,” the researchers wrote. “Regarding the harmonized criteria, a LAP cutoff point of 34.2 cm x mmol/L showed the best accuracy. These results show LAP as a simple and powerful tool to use in clinical practice.” The researchers noted that the general cutoff point identified in the study could represent lower screening costs in the long term in clinical practice. – by Regina Schaffer
Disclosure: The researchers report no relevant financial disclosures.