Identification of metabolic syndrome using lipid accumulation product and cardiometabolic index based on NHANES data from 2005 to 2018.

BACKGROUND

Numerous studies indicate that visceral adipose tissue (VAT) significantly contribute to metabolic syndrome (MetS) development. This study aims to assess the distinguishing value of novel obesity markers, specifically lipid accumulation products (LAP) and cardiometabolic index (CMI), in relation to MetS. Considering the gender disparity in MetS prevalence, it is essential to explore whether LAP and CMI exhibit differential distinguishing capabilities by gender.

METHOD

The investigation included a total of 11,687 qualified individuals who participated in the NHANES survey spanning a 14-year period from 2005 to 2018. Biochemical analysis of blood and body measurements were utilized to determine LAP and CMI values for each participant. Inclusion of gender as a variable was a key factor in the examination of all data. Restricted cube plots (RCS) were utilized to analyze the strength of the relationship between LAP, CMI, and MetS. The study delved into potential connections between LAP and CMI with MetS, all-cause and cardiovascular mortality using various statistical models such as multivariate logistic regression and Cox regression.

RESULTS

The findings revealed a significant nonlinear association between CMI, LAP, and MetS (P-non-linear < 0.001), irrespective of gender, with all models exhibiting a J-shaped trend. The multivariable logistic regression analysis considered both LAP and CMI as continuous variables or tertiles, revealing significant associations with MetS in male, female, and general populations (All the P < 0.001). Although males displayed a higher risk of MetS, no gender differences were observed in the area under the curve (AUC) values of LAP and CMI for distinguishing (P > 0.005) MetS. Impressively, LAP and CMI were identified as the primary predictors of MetS in both genders from AUC (P < 0.005). More specifically, the cutoff points for distinguishing MetS in females were LAP = 49.87 or CMI = 0.56, while for males, they were LAP = 52.76 or CMI = 0.70. Additionally, the Cox regression analysis revealed that LAP and CMI were correlated with all-cause mortality in both general population and females (P < 0.005), but not in males.

CONCLUSION

In comparison to other measures of obesity, LAP and CMI demonstrated superior diagnostic accuracy for MetS in both males and females. Additionally, LAP and CMI were found to be predictive of all-cause mortality in both general population and females. These markers are cost-effective, easily accessible, and widely applicable for the early identification and screening of MetS in clinical settings.