Association of environmental tobacco smoke exposure with metabolic syndrome: A longitudinal Cohort Study of 71,055 never smokers

Metabolic syndrome prediction based on body composition indices

BACKGROUND

Metabolic syndrome (MetS) is an important public health issue that has been lately linked as a growing concern worldwide.

THE OBJECTIVE

To find out which anthropometric and body composition indices can prognosticate MetS in Jordanian adult females.

METHODS

A sample of 656 Jordanian adult females was recruited (January-March 2024) in the middle of Jordan. Weight, height, waist and hip circumference, lipid profile (triglycerides and high-density lipoprotein), fasting plasma glucose, and blood pressure were measured. Fat mass index (FMI), body mass index (BMI), fat-to-muscle ratio, and waist-to-hip ratio (WHR) were calculated. The presence or absence of MetS was the outcome of interest. Receiver operating characteristic (ROC) analyses were used to examine the predictive accuracy of the indices, and the area under the curve (AUC) was measured.

RESULTS

40.6% had MetS, and their mean age was 45.5 years. 90.2% of the participants with MetS were obese based on body fat percentage. The MetS participants had significantly higher means of all the anthropometric indices except the fat-to-muscle ratio. None of the MetS participants were underweight, and 70.8% and 73.8% were obese based on BMI and WHR, respectively (p < 0.001). The highest proportion of the MetS participants (35.5%) was within the Q4 of the FMI compared to those without MetS (p<0.001). The discrimination ability for all indices was almost equal in predicting the existence of MetS (fair prediction power; AUC = 0.66-0.72), except for the fat-to-muscle ratio, which had poor prediction power.

CONCLUSION

Fat mass %, muscle mass %, FMI, BMI, and WHR could be used as predictors of MetS in Jordanian females, while the fat-to-muscle ratio was not. We suggested that more extensive sample size studies from both genders and different age categories are necessary to develop a superior predictor for MetS in Jordan.

Associations of urinary nicotine metabolites and essential metals with metabolic syndrome in older adults: The mediation effect of insulin resistance

Exposure to tobacco smoke and essential metals is linked with metabolic syndrome (MS). However, the joint effect of them on MS in older adults and the underlying mechanisms are still unclear. This large-scale study measured the urinary concentrations of 8 nicotine metabolites and 8 essential metals in 4564 older adults from Shenzhen, China. The biomarker of insulin resistance, triglyceride-glucose index (TyG), was also calculated. Restricted cubic splines (RCS), Bayesian kernel machine regression and quantile-based g-computation were used to access the single and joint effects of urinary nicotine metabolites and essential metals on MS and insulin resistance. Mediation analysis was performed to investigate the role of TyG in these relationships. Single urinary nicotine metabolite and essential metal had non-linear relationships with MS in RCS. The overall effect of urinary nicotine metabolites and essential metals was positively associated with MS. Urinary zinc (52.2 %) and copper (20.1 %) were the major contributors to MS, whereas molybdenum had a negative association with MS. TyG mediated 64.7 % of the overall effect of urinary nicotine metabolites and essential metals on MS. Overall, the mixture of urinary nicotine metabolites and essential metals had a dose-response relationship with MS. Insulin resistance was as a crucial mediated pathway in this association.

Association of Zinc Intake, Tobacco Smoke Exposure, With Metabolic Syndrome: Evidence from NHANES 2007-2018

The objective was to explore the effect modification of zinc (Zn) intake levels on the relationship of tobacco smoke exposure and risk of metabolic syndrome (MetS) in children and adolescents. We used data from 2007-2018 National Health and Nutrition Examination Survey (N = 3701). MetS was considered as main endpoint. Weighted multivariable logistic regression models showed that high cotinine level (≥ 0.05 ng/mL) was associated with increased odds of MetS [odds ratio = 1.54, 95% confidence interval: 1.01, 2.36], and the association between Zn intake levels and MetS did not demonstrate statistical significance. Importantly, the multiplicative interaction term between low Zn intake (≤ 4.89 mg/1000 kcal) and high cotinine level was related to higher odds of MetS (p-value for interaction 0.018). For the group with low Zn intake, high cotinine level was associated with increased odds of MetS. However, there was no significant relationship between cotinine levels and MetS risk in the group with high Zn intake. The effect modification by Zn intake on the relationship of tobacco smoke exposure and risk of MetS is significant in individuals who had a sedentary time of ≥ 6 h, identified as non-Hispanic White, or resided in households with smokers. In short, low Zn intake may potentiate the association of tobacco smoke exposure and MetS risk in children and adolescents.

The inverse relationship between Life's Essential 8 and risk of metabolic syndrome: evidence from NHANES 2005-2018

Background

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.

Methods

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.

Results

In this study, a total of 21,543 participants represented 146.6 million non-institutionalized 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 a high CVH level (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 (P for nonlinearity > 0.05).

Conclusions

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.

Obesity- and lipid-related indices as a predictor of obesity metabolic syndrome in a national cohort study

Objective

Metabolic syndrome is a common condition among middle-aged and elderly people. Recent studies have reported the association between obesity- and lipid-related indices and metabolic syndrome, but whether those conditions could predict metabolic syndrome is still inconsistent in a few longitudinal studies. In our study, we aimed to predict metabolic syndrome by obesity- and lipid-related indices in middle-aged and elderly Chinese adults.

Method

A national cohort study that consisted of 3,640 adults (≥45 years) was conducted. A total of 13 obesity- and lipid-related indices, including body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), conicity index (CI), visceral adiposity index (VAI), Chinese visceral adiposity index (CVAI), lipid accumulation product (LAP), a body shape index (ABSI), body roundness index (BRI), and triglyceride glucose index (TyG-index) and its correlation index (TyG-BMI, TyG-WC, and TyG-WHtR), were recorded. Metabolic syndrome (MetS) was defined based on the criteria of the National Cholesterol Education Program Adult Treatment Panel III (2005). Participants were categorized into two groups according to the different sex. Binary logistic regression analyses were used to evaluate the associations between the 13 obesity- and lipid-related indices and MetS. Receiver operating characteristic (ROC) curve studies were used to identify the best predictor of MetS.

Results

A total of 13 obesity- and lipid-related indices were independently associated with MetS risk, even after adjustment for age, sex, educational status, marital status, current residence, history of drinking, history of smoking, taking activities, having regular exercises, and chronic diseases. The ROC analysis revealed that the 12 obesity- and lipid-related indices included in the study were able to discriminate MetS [area under the ROC curves (AUC > 0.6, P < 0.05)] and ABSI was not able to discriminate MetS [area under the ROC curves (AUC < 0.6, P > 0.05)]. The AUC of TyG-BMI was the highest in men, and that of CVAI was the highest in women. The cutoff values for men and women were 187.919 and 86.785, respectively. The AUCs of TyG-BMI, CVAI, TyG-WC, LAP, TyG-WHtR, BMI, WC, WHtR, BRI, VAI, TyG index, CI, and ABSI were 0.755, 0.752, 0.749, 0.745, 0.735, 0.732, 0.730, 0.710, 0.710, 0.674, 0.646, 0.622, and 0.537 for men, respectively. The AUCs of CVAI, LAP, TyG-WC, TyG-WHtR, TyG-BMI, WC, WHtR, BRI, BMI, VAI, TyG-index, CI, and ABSI were 0.687, 0.674, 0.674, 0.663, 0.656, 0.654, 0.645, 0.645, 0.638, 0.632, 0.607, 0.596, and 0.543 for women, respectively. The AUC value for WHtR was equal to that for BRI in predicting MetS. The AUC value for LAP was equal to that for TyG-WC in predicting MetS for women.

Conclusion

Among middle-aged and older adults, all obesity- and lipid-related indices, except ABSI, were able to predict MetS. In addition, in men, TyG-BMI is the best indicator to indicate MetS, and in women, CVAI is considered the best hand to indicate MetS. At the same time, TyG-BMI, TyG-WC, and TyG-WHtR performed better than BMI, WC, and WHtR in predicting MetS in both men and women. Therefore, the lipid-related index outperforms the obesity-related index in predicting MetS. In addition to CVAI, LAP showed a good predictive correlation, even more closely than lipid-related factors in predicting MetS in women. It is worth noting that ABSI performed poorly, was not statistically significant in either men or women, and was not predictive of MetS.