DOI: 10.6084/m9.figshare.26927497.v1
title: The inverse relationship between Life’s essential 8 and risk of metabolic syndrome evidence from NHANES 2005-2018

description: <b>Background: </b>Metabolic syndrome (MetS) has a close association with cardiovascular diseases. Few studies have investigated the association of Life's Essential 8 (LE8), the updated measurement of cardiovascular health (CVH), with MetS.<b>Methods: </b>The National Health and Nutrition Examination Survey (2005–2018) data was extracted. The LE8 comprised 4 health behaviors [diet, physical activity, nicotine exposure, and sleep health)] and 4 health factors [(body mass index (BMI), blood lipids, blood glucose, and blood pressure (BP)]. The total LE8 score is the average of 8 metric scores (0-100), categorized into low (0–49), moderate (50–79), and high CVH (80–100) levels. Multivariable logistic regression models, restricted cubic spline models and stratified analyses were performed to examine the relationship between LE8 and MetS.<b>Results: </b>The results demonstrated that a weighted sample of 21,543 participants represented 146.6 million noninstitutionalized U.S. adults. Following adjustment for various potential covariates, participants who attained a moderate [adjusted odds ratio (AOR) = 0.234, 95 % CI: 0.209, 0.262] or high CVH levels (AOR = 0.026, 95 % CI: 0.021, 0.032) exhibited an inverse correlation with MetS risks when comparing those with a low CVH level. An inverse linear dose-response relationship between LE8 scores and MetS risks was also identified (<i>P</i> for nonlinearity &gt; 0.05).<b>Conclusions: </b>LE8 was inversely associated with the risk of MetS. Adhering to LE8 guidelines to sustain a higher CVH level may be beneficial for preventing MetS.<b>Statistical analyses</b>Due to the NHANES methodology, all the conducted statistical analyses were subject to weighting. One-way ANOVA analysis was deployed for comparing continuous variables by assessing their mean values together with their standard errors (SE). The chi-square test was utilized to examine counts and percentages of categorical data. The Pearson correlation coefficients were deployed for evaluating the pairwise correlation between 8 LE8 metrics. A survey-multivariable logistic regression model was employed to estimate the adjusted odds ratio (AOR) and 95 % confidence interval (CI) for LE8 score associations with MetS (low CVH levels as the reference). Specifically, we used three different models: non-adjusted crude model, adjusted model 1 for age, gender, and race/ethnicity, and additionally adjusted model 2 for education level, marital status, PIR, and alcohol consumption. When the association of each LE8 metric score with MetS was evaluated, the remaining 7 LE8 components were further adjusted in model 2. In addition, our study deployed a restricted cubic spline model for examining the exposure-response relationship between LE8 score and MetS. Furthermore, stratified analyses were conducted according to different demographic characteristics. To identify our findings’ robustness, we performed sensitivity analyses: 1) identifying LE8 score association with MetS in male and female populations; 2) adding covariates of survey cycle, DM, hypertension, CVD, depression, and total energy intake, respectively, to minimize their influences on the outcome; 3) setting high CVH (80–100) as the reference. Here, we conducted the statistical analyses in R language (X64 Version 4.3.1, R Foundation for Statistical Computing), with two-sided P &lt; 0.05 representing statistical significance.