Usefulness of bioelectrical impedance analysis in multiple sclerosis patients-the interrelationship to the body mass index.

Background: Patients with multiple sclerosis (MS) have many potential factors (disease duration, spasticity, immobilization, or glucocorticoid use) that can deteriorate their nutritional status and impact both the progression and prognosis of the disease. Body mass index (BMI), the most widely used nutritional status assessment tool, has important limitations because it does not provide any data on body composition. Aim: This study aimed to assess the interrelationship between nutritional status assessment by both body mass index (BMI) and body composition using bioelectrical impedance analysis (BIA) and the consistency of diagnosis for underweight/underfat, normal weight/healthy, overweight/overfat, and obesity/obese MS patients. Methods: Anthropometric [BMI and waist-to-height ratio (WHtR)] and body composition (BIA) data were evaluated in 176 patients with MS. Patients were categorized into four nutritional status subgroups (underweight, normal weight, overweight, obese according to BMI, and underfat, healthy, overfat, and obese according to fat mass% by BIA). The median Expanded Disability Status Scale score was 4.5. Patients were then divided according to EDSS score as mild (EDSS 1.0-4.0) or moderate (EDSS 4.5-6.5) disability subgroups. Results: Based on BIA assessment, there was a significantly higher prevalence of overfat than of overweight based on BMI [n = 50 (28.41%) vs. n = 38 (21.59%); p < 0.05]. However, the prevalence of obesity did not differ significantly regardless of the mode of diagnosis and was not significantly lower when assessed using BIA [n = 26 (14.77%) vs. n = 30 (17.05%), respectively]. The overall compatibility rates (CR) of diagnoses made using both BMI and BIA were 75.6, 77.0, and 70.1% for all patients with MS and the mild and moderate subgroups, respectively. The lowest CR was observed in the overweight group. Adiposity significantly underestimated BMI in all subgroups. In the moderate MS subgroup, BMI significantly overcategorized patients with MS as having a normal weight (p < 0.05). Stratification for abdominal obesity (WHtR > 0.5) showed that BMI significantly underestimated the prevalence of MS in overweight and obese vs. overfat and obese patients, as assessed using BIA (60.5 vs. 67%; p < 0.05). Clinical status (EDSS and ΔEDSS) was more closely related to the nutritional status categorized by FAT% assessed using BIA than using BMI cutoff points. However, the relationship was not statistically significant. Conclusion: Using the BMI cutoff point for nutritional status assessment in patients with MS is associated with a significant underestimation of excess fat mass. BIA-based FAT% based on BIA have a better relationship with abdominal obesity and disability status than with BMI in patients with MS. The highest rate of false-negative diagnoses was based on the BMI in patients with MS and moderate disability. Adiposity assessment using BIA appears to be a useful method for proper nutritional status assessment in the patients group.

Association between different triglyceride-glucose index combinations with obesity indicators and arthritis: results from two nationally representative population-based study.

BACKGROUND: Insulin resistance (IR) and arthritis are strongly associated, and the triglyceride-glucose (TyG) index combinations with obesity indicators [including TyG-BMI (glucose triglyceride-body mass index), TyG-WC (glucose triglyceride-waist circumference), and TyG-WHtR (glucose triglyceride-waist height ratio)] has recently been recognized as a more effective indicator for assessing IR. However, there is a lack of research on its association with arthritis, and it is also important to assess in different populations. METHODS: The analysis utilized data from the China Health and Retirement Longitudinal Study (CHARLS) and the National Health and Nutrition Examination Survey (NHANES). Arthritis diagnosis relied on self-reporting confirmed by physicians. The association of TyG-BMI, TyG-WC, and TyG-WHtR with arthritis was analyzed through weighted logistic regression models, and exploring nonlinear effects with restricted cubic spline (RCS) models. Secondary and sensitivity analyses included receiver operating characteristic curve (ROC) analysis, comparisons of z score-related odds ratios, subgroup analyses, and multiple imputation. RESULTS: The study involved 6141 CHARLS participants and 17,091 NHANES participants. Adjusting for confounding variables, TyG-BMI and TyG-WHtR demonstrate a positive correlation with arthritis prevalence in both CHARLS (TyG-BMI: OR = 1.02, 95% CI 1.00-1.04; TyG-WHtR: OR = 1.13, 95% CI 1.03-1.24) and NHANES (TyG-BMI: OR = 1.07, 95% CI 1.06-1.08; TyG-WHtR: OR = 1.50, 95% CI 1.40-1.60). RCS regression analysis demonstrated a significant nonlinear association. ROC analysis indicated that TyG-BMI and TyG-WHtR were superior to TyG for the diagnosis of arthritis in both CHARLS and NHANES. CONCLUSIONS: TyG-BMI and TyG-WHtR demonstrate a positive correlation with arthritis prevalence in both Chinese and the U.S. populations, displaying superior diagnostic relevance compared to TyG.

Association between triglyceride glucose-waist to height ratio and coronary heart disease: a population-based study.

BACKGROUND: The Triglyceride glucose (TyG) index-related indicators improve risk stratification by identifying individuals prone to atherosclerosis early in life. This study aimed to examine the relation between TyG-waist circumference-to-height ratio (TyG-WHtR) and coronary heart disease. METHODS: Data from four National Health and Nutrition Examination Surveys (NHANES) cycles between 2011 and 2018 were used for a cross-sectional study. The association between TyG-WHtR and coronary heart disease risk was examined using a multifactorial logistic regression model, and corresponding subgroup analyses were performed. Nonlinear correlations were analyzed using smooth curve fitting and threshold effects analysis. When nonlinear connections were discovered, appropriate inflection points were investigated using recursive methods. RESULTS: TyG-WHtR and coronary heart disease were significantly positively correlated in the multifactorial logistic regression analysis. Subgroup analyses and interaction tests revealed that gender, age, smoking status, and cancer were not significantly associated with this correlation (P for interaction > 0.05). Furthermore, utilizing threshold effect analysis and smooth curve fitting, a nonlinear connection with an inflection point of 0.36 was observed between TyG-WHtR and coronary heart disease. CONCLUSIONS: According to this study, the American population is far more likely to have coronary heart disease if they have higher TyG-WHtR levels.

Association between triglyceride glucose index-related indices with gallstone disease among US adults.

BACKGROUND: Triglyceride glucose (TyG) index combined with obesity-related indicators [triglyceride glucose-body mass index (TyG-BMI), triglyceride glucose-waist to height ratio (TyG-WHtR), triglyceride glucose-waist circumference (TyG-WC)], represents emerging methodologies for assessing insulin resistance. The objective of this investigation was to explore the correlation between TyG-related indices and gallstone disease. METHODS: The study included 3740 adults from the 2017-2020 period of the National Health and Nutrition Examination Survey. TyG-BMI, TyG-WC, and TyG-WHtR were integrated as both continuous and categorical variables within the multivariate logistic model, respectively to evaluate the connection between various TyG-related indices and gallstone disease. Additionally, restriction cubic splines and subgroup analysis were employed to deepen our understanding of this relationship. RESULTS: When analyzed as continuous variables, positive correlations were observed between TyG-BMI, TyG-WC, TyG-WHtR and gallstone disease. The OR(95%CI) were 1.063(1.045,1.082) for TyG-BMI (per 10-unit), 1.026(1.018,1.034) for TyG-WC (per 10-unit) and 1.483(1.314,1.676) for TyG-WHtR (per 1-unit), respectively. When categorized into quartiles, these three TyG-related indices still show statistically significant associations with gallstone disease. Descending in order, the diagnostic capability for gallstone disease is demonstrated as follows: TyG-WHtR (AUC = 0.667), TyG-BMI (AUC = 0.647), and TyG-WC (AUC = 0.640). CONCLUSION: There were significantly positive associations between TyG-related indices, including TyG-BMI, TyG-WC, and TyG-WHtR, and gallstone disease. Of these indices, TyG-WHtR demonstrated the most favorable performance in identifying the risk of gallstone disease.

Association of triglyceride-glucose index and its related parameters with atherosclerotic cardiovascular disease: evidence from a 15-year follow-up of Kailuan cohort.

BACKGROUND: Triglyceride glucose (TyG) index and its related parameters have been introduced as cost-effective surrogate indicators of insulin resistance, while prospective evidence of their effects on atherosclerotic cardiovascular disease (ASCVD) remained scattered and inconsistent. We aimed to evaluate the association of TyG and its related parameters with new-onset ASCVD, and the predictive capacity were further compared. METHOD: A total of 95,342 ASCVD-free participants were enrolled from the Kailuan study. TyG and its related parameters were defined by fasting blood glucose, triglyceride, body mass index (BMI), waist circumstance (WC) and waist-to-height ratio (WHtR). The primary outcome was incident ASCVD, comprising myocardial infarction (MI) and ischemic stroke (IS). Cox proportional hazard models and restricted cubic spline (RCS) analyses were adopted to investigate the association between each index and ASCVD. The C-index, integrated discrimination improvement (IDI), and net reclassification improvement (NRI) were used for comparison of their predictive value for ASCVD. RESULTS: During a median follow-up of 15.0 years, 8,031 new cases of ASCVD were identified. The incidence rate of ASCVD increased along with elevated levels of each index, and the relationships were found to be nonlinear in the RCS analyses. The hazard ratio (HR) and 95% confidence interval (95% CI) for ASCVD was 1.39 (1.35, 1.43), 1.46 (1.41, 1.50), 1.50 (1.46, 1.55), and 1.52 (1.48, 1.57) per 1 IQR increase of baseline TyG, TyG-BMI, TyG-WC, and TyG-WHtR, respectively, and the association were more pronounced for females and younger individuals aged < 60 years (Pfor interaction<0.05). Using the updated mean or time-varying measurements instead of baseline indicators did not significantly alter the primary findings. Additionally, TyG-WC and TyG-WHtR showed better performance in predicting risk of ASCVD than TyG, with the IDI (95% CI) of 0.004 (0.001, 0.004) and 0.004 (0.001, 0.004) and the category-free NRI (95% CI) of 0.120 (0.025, 0.138) and 0.143 (0.032, 0.166), respectively. Similar findings were observed for MI and IS. CONCLUSIONS: Both the TyG index and its related parameters were significantly and positively associated with ASCVD. TyG-WC and TyG-WHtR had better performance in predicting incident ASCVD than TyG, which might be more suitable indices for risk stratification and enhance the primary prevention of ASCVD.

Prognostic effect of triglyceride glucose-related parameters on all-cause and cardiovascular mortality in the United States adults with metabolic dysfunction-associated steatotic liver disease.

BACKGROUNDS: Insulin resistance (IR) plays a vital role in the pathogenesis of the metabolic dysfunction-associated steatotic liver disease (MASLD). However, it remains unclear whether triglyceride-glucose (TyG) related parameters, which serve as useful biomarkers to assess IR, have prognostic effects on mortality outcomes of MASLD. METHODS: Participants in the National Health and Nutrition Examination Survey (NHANES) database from 1999 to 2018 years were included. TyG and its related parameters [TyG-waist circumference (TyG-WC) and TyG-waist to height ratio (TyG-WHtR)] were calculated. Kaplan-Meier curves, Cox regression analysis, and restricted cubic splines (RCS) were conducted to evaluate the association between TyG-related indices with the all-cause and cardiovascular mortality of adults with MASLD. The concordance index (C-index) was used to evaluate the prediction accuracy of TyG-related indices. RESULTS: A total of 8208 adults (4209 men and 3999 women, median age 49.00 years) with MASLD were included in this study. Multivariate-adjusted Cox regression analysis revealed that high quartile levels of TyG-related indices were significantly associated with the all-cause mortality of participants with MASLD [TyGadjusted hazard ratio (aHR) = 1.25, 95% confidence interval (CI) 1.05-1.50, P = 0.014; TyG-WCaHR for all-cause mortality = 1.28, 95% CI 1.07-1.52, P = 0.006; TyG-WHtRaHR for all-cause mortality = 1.50, 95% CI 1.25-1.80, P < 0.001; TyG-WCaHR for cardiovascular mortality = 1.81, 95% CI 1.28-2.55, P = 0.001; TyG-WHtRaHR for cardiovascular mortality = 2.22, 95% CI 1.55-3.17, P < 0.001]. The C-index of TyG-related indices for predicting all-cause mortality was 0.563 for the TyG index, 0.579 for the TyG-WC index, and 0.585 for the TyG-WHtR index, respectively. Regarding cardiovascular mortality, the C-index was 0.561 for the TyG index, 0.607 for the TyG-WC index, and 0.615 for the TyG-WHtR index, respectively. Nonlinear trends were observed between TyG and TyG-WC indices with all-cause mortality of MASLD (P < 0.001 and = 0.012, respectively). A non-linear relationship was observed between the TyG index and cardiovascular mortality of MASLD (P = 0.025). Subgroup analysis suggested that adults aged < 65 years old and those without comorbidities were more sensitive to the mortality prediction of TyG-related indices. CONCLUSION: Findings of this study highlight the predictive value of TyG-related indices, especially the TyG-WHtR index, in the mortality outcomes of adults with MASLD. TyG-related indices would be surrogate biomarkers for the clinical management of MASLD.

Association between triglyceride-glucose related indices with the all-cause and cause-specific mortality among the population with metabolic syndrome.

BACKGROUND: Triglyceride-glucose (TyG) index has been determined to play a role in the onset of metabolic syndrome (MetS). Whether the TyG index and TyG with the combination of obesity indicators are associated with the clinical outcomes of the MetS population remains unknown. METHOD: Participants were extracted from multiple cycles of the National Health and Nutrition Examination Survey (NHANES) between 1999 and 2018 years. Three indicators were constructed including TyG index, TyG combining with waist circumference (TyG-WC), and TyG combining with waist-to-height ratio (TyG-WHtR). The MetS was defined according to the National Cholesterol Education Program (NCPE) Adult Treatment Panel III. Kaplan-Meier (KM) curves, restricted cubic splines (RCS), and the Cox proportional hazard model were used to evaluate the associations between TyG-related indices and mortality of the MetS population. The sensitive analyses were performed to check the robustness of the main findings. RESULTS: There were 10,734 participants with MetS included in this study, with 5,570 females and 5,164 males. The median age of the study population was 59 years old. The multivariate Cox regression analyses showed high levels of TyG-related indices were significantly associated with the all-cause mortality of MetS population [TyG index: adjustedhazard ratio (aHR): 1.36, 95%confidence interval (CI): 1.18-1.56, p < 0.001; TyG-WHtR index: aHR = 1.29, 95%CI: 1.13-1.47, p < 0.001]. Meanwhile, the TyG-WC and TyG-WHtR index were associated with cardiovascular mortality of the MetS population (TyG-WC: aHR = 1.45, 95%CI: 1.13-1.85, p = 0.004; TyG-WHtR: aHR = 1.50 95%CI: 1.17-1.92, p = 0.002). Three TyG-related indices showed consistent significant correlations with diabetes mortality (TyG: aHR = 4.06, 95%CI: 2.81-5.87, p < 0.001; TyG-WC: aHR = 2.55, 95%CI: 1.82-3.58, p < 0.001; TyG-WHtR: aHR = 2.53 95%CI: 1.81-3.54, p < 0.001). The RCS curves showed a non-linear trend between TyG and TyG-WC indices with all-cause mortality (p for nonlinearity = 0.004 and 0.001, respectively). The sensitive analyses supported the positive correlations between TyG-related indices with mortality of the MetS population. CONCLUSION: Our study highlights the clinical value of TyG-related indices in predicting the survival of the MetS population. TyG-related indices would be the surrogate biomarkers for the follow-up of the MetS population.

Dietary inflammatory impact on NAFLD development in obese vs. lean individuals: an analysis based on NHANES 2003-2018.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD), often linked with obesity, can also affect individuals with normal weight, a condition known as "lean NAFLD", imposing comparable burdens and adverse effects. However, the impact of diet on lean NAFLD remains underexplored. The objective of this study is to investigate the correlation between the Dietary Inflammatory Index (DII) and NAFLD among Americans, stratified by waist-to-height ratio (WHtR) and body mass index (BMI). METHODS: Five thousand one hundred fifty-two participants from the National Health and Nutrition Examination Survey (NHANES) 2003-2018 were comprised in the final analysis. NAFLD and advanced liver fibrosis were diagnosed by serological markers. Lean and abdominal lean individuals were identified using BMI and WHtR, separately. DII was determined by assigning scores to 28 distinct food parameters based on their inflammatory potential, obtained from the NAHNES website. Differences across DII quartiles were evaluated using the Kruskal-Wallis H Test, Chi-Square Test along with One-Way ANOVA. The correlation between DII and NAFLD was determined by multiple regression models and subgroup analyses. RESULTS: Among the 5152 subjects, 2503 were diagnosed with NAFLD, including 86 cases of lean NAFLD and 8 cases of abdominal lean NAFLD. DII was positively linked with NAFLD (Odds Ratio (OR) = 1.81 [1.48-2.21], P < 0.001) and advanced liver fibrosis (OR = 1.46 [1.02-2.07], P = 0.037). Further analysis revealed that this association was primarily observed in obese or abdominal obese participants (In BMI ≥ 25.00 kg/m^2, OR = 1.56 [1.23-1.98], P < 0.001. In WHtR> 0.50, OR = 1.48 [1.23-1.79], P < 0.001.), rather than their lean counterparts. Subgroup analyses indicated that female individuals, without a diagnosis of hypertension or diabetes appeared to be more sensitive to the rise in DII. CONCLUSIONS: Our data demonstrated a significant positive correlation between DII and NAFLD in the general population. However, the impact of a pro-inflammatory diet was less prominent in lean individuals compared to obese ones.

Association of insulin resistance indicators with hepatic steatosis and fibrosis in patients with metabolic syndrome.

BACKGROUND: To investigate the association of four insulin resistance (IR) indicators with hepatic steatosis and fibrosis in patients with metabolic syndrome (MetS), as well as to compare the diagnostic value of these indicators in identifying hepatic steatosis and fibrosis in individuals with MetS. METHODS: This cross-sectional study used the data from the National Health and Nutrition Examination Survey 2017-2018. IR indicators included homeostasis model assessment of IR (HOMA-IR), triglyceride/glucose (TyG) index, triglyceride glucose-waist-to-height ratio (TyG-WHtR), and metabolic score for IR (METS-IR). The main endpoints of this study were hepatic steatosis and hepatic fibrosis. Weighted univariate and multivariate logistic regression models were employed to evaluate the association between four IR indicators and both hepatic steatosis, hepatic fibrosis. The efficacy of various IR indicators in the detection of hepatic steatosis and hepatic fibrosis were assessed using receiver operating characteristics curve (ROC). RESULTS: A total of 876 participants with MetS were enrolled. Among the participants, hepatic steatosis was observed in 587 MetS individuals, while hepatic fibrosis was identified in 151 MetS individuals. In multivariate logistic regression model, HOMA-IR, TyG, TyG-WHtR, and METS-IR were related to the increased odd of hepatic steatosis. Additionally, HOMA-IR, TyG-WHtR, and METS-IR were associated with increased odd of hepatic fibrosis. According to the ROC analysis, the area under the curve (AUC) of the TyG-WHtR (AUC = 0.705, 95%CI: 0.668-0.743) was higher than HOMA-IR (AUC = 0.693, 95%CI: 0.656-0.730), TyG (AUC = 0.627, 95%CI: 0.587-0.666), and METS-IR (AUC = 0.685, 95%CI: 0.648-0.722) for identifying hepatic steatosis of MetS patients. Likewise, TyG-WHtR was also higher than HOMA-IR, TyG, and METS-IR for identifying hepatic fibrosis of MetS patients. CONCLUSION: HOMA-IR, TyG-WHtR, and METS-IR may be associated with the risk of hepatic steatosis and fibrosis among the U.S. adult population with MetS. In addition, TyG-WHtR may have a good predictive value for hepatic steatosis and hepatic fibrosis.

The association between triglyceride-glucose index and its combination with obesity indicators and cardiovascular disease: NHANES 2003-2018.

BACKGROUND: In the American population, the relationship between the triglyceride-glucose (TyG) index and TYG combined with indicators of obesity and cardiovascular disease (CVD) and its mortality has been less well studied. METHODS: This cross-sectional study included 11,937 adults from the National Health and Nutrition Examination Survey (NHANES) 2003-2018. Cox proportional hazards model, binary logistic regression analyses, restricted cubic spline (RCS), and receiver operating characteristic (ROC) were used to analyze the relationship between TyG and its combined obesity-related indicators and CVD and its mortality. Mediation analysis explored the mediating role of glycated hemoglobin and insulin in the above relationships. RESULTS: In this study, except for no significant association between TyG and CVD mortality, TyG, TyG-WC, TyG-WHtR, and TyG-BMI were significantly and positively associated with CVD and CVD mortality. TyG-WHtR is the strongest predictor of CVD mortality (HR 1.66, 95% CI 1.21-2.29). The TyG index correlated better with the risk of coronary heart disease (OR 2.52, 95% CI 1.66-3.83). TyG-WC correlated best with total CVD (OR 2.37, 95% CI 1.77-3.17), congestive heart failure (OR 2.14, 95% CI 1.31-3.51), and angina pectoris (OR 2.38, 95% CI 1.43-3.97). TyG-WHtR correlated best with myocardial infarction (OR 2.24, 95% CI 1.45-3.44). RCS analyses showed that most of the above relationships were linear (P-overall < 0.0001, P-nonlinear > 0.05). Otherwise, ROC curves showed that TyG-WHtR and TyG-WC had more robust diagnostic efficacy than TyG. In mediation analyses, glycated hemoglobin mediated in all the above relationships and insulin-mediated in partial relationships. CONCLUSIONS: TyG-WC and TyG-WtHR enhance CVD mortality prediction, diagnostic efficacy of CVD and its mortality, and correlation with some CVD over and above the current hottest TyG. TyG-WC and TyG-WtHR are expected to become more effective metrics for identifying populations at early risk of cardiovascular disease and improve risk stratification.

Relationship Between Metabolic Syndrome and Polycystic Ovary Syndrome with Special Reference to C-Reactive Protein.

OBJECTIVES: To estimate C-reactive protein (CRP) levels in Saudi women with and without polycystic ovary syndrome (PCOS), and to investigate the associations between CRP and metabolic syndrome (MetS) components. METHODS: We randomly recruited 200 women with and without PCOS, between 18 and 38 years, in this age-matched case-control study. Study subjects were allocated to 1 of 4 groups according to the presence or absence of MetS. Interviews were conducted with all participants, and anthropometric measurements and blood samples were obtained for subsequent analysis of biochemical variables. RESULTS: Two-thirds of the study population and all study subjects had central obesity. Fasting insulin and homeostasis model assessment insulin resistance index were significantly higher in PCOS and MetS groups than all other groups (P < 0.05). CRP levels were significantly higher among women with PCOS than their age-matched controls, regardless of the presence of MetS (P < 0.05). Body mass index was the only independent predictor of serum high-sensitivity-CRP, accounting for 17% of the variability in circulating levels (ß = 0.407; 95% CI 0.248-0.472, P < 0.0001). CONCLUSIONS: Obesity and insulin resistance are important risk factors for MetS in PCOS. The presence of MetS in PCOS subjects aggravates the proinflammatory state reflected by CRP levels.

Association of hypertension with the triglyceride-glucose index and its associated indices in the Chinese population: A 6-year prospective cohort study.

The authors aim to assess the correlation between hypertension and the triglyceride-glucose (TyG) index and its associated indices, and to compare their abilities to identify hypertension. Four thousand eight hundred and sixty-six non-hypertensive participants were enrolled from the China National Health Survey in 2009. The data on new-onset hypertension were gathered in both 2011 and 2015. The TyG index and its associated indices were derived from the fasting triglyceride, blood glucose levels, and anthropometric parameters. Multivariate logistic regression analyses and receiver operating characteristic curve analysis were used. The adjusted odds ratio (OR) and 95% confidence interval (CI) for the new-onset hypertension for the TyG-waist-to-height ratio (TyG-WHtR), TyG-waist circumference (TyG-WC), TyG-waist-to-hip ratio (TyG-WHR), TyG-body mass index (TyG-BMI), and TyG index were 1.379 (1.230-1.546), 1.002 (1.001-1.003), 1.156 (1.069-1.251), 1.007 (1.005-1.009), and 1.187 (1.051-1.341), respectively. In addition, comparing the lowest quartile (Q1) group with the highest quartile (Q4), the adjusted OR and 95% CI for the new-onset hypertension were found to be 1.86 (1.48-2.35), 1.93 (1.53-2.43), 1.71 (1.36-2.16), 2.00 (1.60-2.50), and 1.49 (1.19-1.88) for TyG-WHtR, TyG-WC, TyG-WHR, TyG-BMI, and TyG index, respectively, among all participants. The TyG-WHtR had the largest area under the curve (AUC) for hypertension (AUC, 0.628; 95% CI, 0.614-0.641) in all participants. Stratified analysis also indicated that the TyG-WHtR exhibited the greatest AUC in both males (AUC, 0.608; 95% CI, 0.587-0.629) and females (AUC, 0.648; 95% CI, 0.629-0.666). In conclusions, the TyG index and its associated indices were positively associated with hypertension. Among these indices, TyG-WHtR was the most valuable indicator for predicting hypertension.

Dietary fat types consumption association with obesity and coronary indices.

This article aims to study the different dietary fat types associated with obesity and coronary indices. A sample of 491 healthy adults was included in a cross-sectional manner. Dietary fats intake, obesity indices (conicity index (CI), body adiposity index (BAI), abdominal volume index (AVI), body roundness index (BRI), and weight-adjusted-waist index (WWI)), and cardiovascular indices (cardiometabolic index (CMI), lipid accumulation product (LAP), and atherogenic index of plasma (AIP)) were calculated and studied. Participants with an acceptable intake of omega-3 had a higher BRI score (1⋅90 ± 0⋅06 v. 1⋅70 ± 0⋅06). Participants with an unacceptable intake of cholesterol had a higher CI (1⋅31 ± 0⋅11 v. 1⋅28 ± 0⋅12; P = 0⋅011), AVI (20⋅24 ± 5⋅8 v. 18⋅33 ± 6⋅0; P < 0⋅001), BRI (2⋅00 ± 1⋅01 v. 1⋅70 ± 1⋅00; P = 0⋅003), WWI (11⋅00 ± 0⋅91 v. 10⋅80 ± 0⋅97; P = 0⋅032), and lower AIP (0⋅46 ± 0⋅33 v. 0⋅53 ± 0⋅33; P = 0⋅024). Total fat, saturated fat (SFA), and polyunsaturated fat (PUFA) intake had a significant moderate correlation with AVI and BRI. The monounsaturated fat (MUFA) intake had a significantly weak correlation with CI, AVI, BRI, WWI, and AIP. Cholesterol and omega-6 had weak correlations with all indices. Similar correlations were seen among male and female participants. The different types of fat intake significantly affected obesity and coronary indices, especially SFA and PUFA, as well as omega-3 and cholesterol. Gender and the dietary type of fat intake have a relationship to influence the indicators of both obesity and coronary indices.

Comparison of Several Anthropometric Indices Related to Body Fat in Predicting Cardiorespiratory Fitness in School-Aged Children-A Single-Center Cross-Sectional Study.

Body fat (BF) and cardiorespiratory fitness (CRF) are important health markers that ought to be considered in screening exams. The aim of this study was to assess the value of six indicators, i.e., tri-ponderal mass index (TMI), relative fat mass (RFM), waist-BMI ratio, waist-to-height ratio (WHtR), waist-to-hip ratio (WHR) and body mass index (BMI) in predicting CRF in school-aged children. The analysis was based on the data coming from the examination of 190 children participating in school physical education (PE) classes. Their body weight (BW) and height (BH), waist and hip circumference (WC; HC) and percentage of body fat (%BF) were measured; the CRF test was performed with the use of the 20 m shuttle run test (20 mSRT); peak heart rate (HRpeak) was measured; TMI, relative fat mass pediatric (RFMp), waist-BMI ratio, WHtR, BMI and WHR were calculated. Statistical analysis was mainly conducted using regression models. The developed regression models, with respect to the sex and age of the children, revealed RFMp as the strongest CRF indicator (R2 = 51.1%) and WHR as well as waist-BMI ratio as the weakest ones (R2 = 39.2% and R2 = 40.5%, respectively). In predicting CRF in school-aged children, RFMp turned out to be comparable to body fat percentage obtained by means of the bioimpedance analysis (BIA) (R2 = 50.3%), and as such it can be used as a simple screening measure in prophylactic exams of school children. All of these models were statistically significant (p < 0.001).

Impact of a lifestyle intervention program on cardio-metabolic parameters among obese adults: A comparative population-based study in West Bengal, India.

The obesity epidemic is not only limited to high-income or urbanized societies, but has also become prevalent among rural communities, even in India. Approaches to modifiable behaviors, like unhealthy dietary habits or a sedentary lifestyle, could bring positive results among obese populations. This research aimed to assess the effectiveness of lifestyle intervention programs to prevent obesity and cardio-metabolic risks among Bengali obese adults (Body Mass Index of 25-30kg/m2). The population was selected from rural and urban communities of Hooghly district in west Bengal, India and included 121 participants (20-50 years), divided into four groups (rural male, rural female, urban male, and urban female) who underwent a 12-month intervention program. Anthropometric parameters, systolic and diastolic blood pressure, biochemical parameters (fasting blood glucose, fasting plasma insulin, Homeostatic Model Assessment for Insulin Resistance [HOMA-IR] and lipid profile), dietary habits, and physical activity profiles were assessed before the study (baseline), after 12 months of intervention (post-intervention), and after 24 months (follow-up), among all groups, to evaluate changes in data within and between the groups (rural vs. urban). The results showed a significant decline in anthropometric parameters and fasting blood glucose levels among all intervention groups, HOMA-IR in rural females, and serum triglyceride levels in urban groups. A significant improvement was noted regarding dietary habits and physical activity, even during follow-up. The impact of the intervention program did not show any rural-urban difference. The lifestyle intervention program was effective in reducing obesity and related health risks and promoting a healthy lifestyle among the target population.

Development and validation of a model to predict the risk of hypertension using anthropometric indicators in the Chinese population: a retrospective cohort study.

BACKGROUND: The prevalence of hypertension and obesity in China has sharply increased in recent decades. We aimed to develop and validate a novel model for predicting the risk of hypertension based on anthropometric indicators relating to obesity in the general population of China. METHODS: In this retrospective study, 6196 participants from the China Health and Nutrition Survey (CHNS) during the 2009-2015 waves were included. Risk factors for hypertension were assessed by LASSO regression combined with multivariate logistic regression analysis. A nomogram was developed as a predictive model based on the screening prediction factors. The discrimination and calibration of the model were evaluated by receiver operating curve (ROC) and calibration plots, respectively. Decision curve analysis (DCA) was used to evaluate the clinical application value of the model. RESULTS: A total of 6196 participants were divided into two sets at a ratio of 7:3, using computer-generated random numbers: 4337 individuals were assigned to the training set and 1859 to the validation set. The training set was divided into a hypertension group (n = 1016) and a non-hypertension group (n = 3321) based on the follow-up outcomes for hypertension. Predictive factors of hypertension included age, drinking, body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR) and arm-to-height ratio (AHtR) at baseline as predictors. The area under the ROC curve (AUC) for the training and validation sets was 0.906 (95% CI: 0.897-0.915) and 0.905 (95% CI: 0.887-0.922), respectively. In bootstrap validation, the C-index was 0.905 (95% CI: 0.888-0.921). The model also had good predictive accuracy according to the calibration plot. DCA demonstrated that people would benefit more when the threshold probability was between 5% and 80%. CONCLUSION: A nomogram model was successfully established to effectively predict the risk of hypertension based on anthropometric indicators. The model could be a feasible tool for hypertension screening in the general population of China.

Intergenerational Changes in the Waist Circumference and Selected Associated Indicators among Children and Adolescents from Kraków (Poland), between 1983 and 2020.

The aim of the study was to examine the direction of the secular changes in the waist and hips circumferences, as well as selected associated body proportions, among children and adolescents from Kraków, Poland. The study group included 8-18-year-olds examined in three cross-sectional studies (1983, 2010, and 2020). The analyzed characteristics included body height, circumferences of the waist and hips, which were used to calculate Waist-to-Hip Ratio (WHR), and Waist-to-Height Ratio (WHtR). There was a secular increase regarding the majority of the analyzed features, particularly for the younger children (i.e., prepubertal/early pubertal age). The trends were also especially evident when comparing the results of the 1983 series to the results of their peers examined in 2020. An opposite trend was noted in adolescent girls. The observed changes reflect the secular trend resulting from changes in body composition and fat distribution happening due to alterations in the lifestyle and socio-economic environment of the population over the years. It should also be stressed that the increase in the studied characteristics occurred mainly in younger children. This suggests that the observed changes may have resulted from a shift in the age of maturation and also from the personal and social motivators characteristic for late adolescence.

Waist-to-height ratio and new-onset hypertension in middle-aged and older adult females from 2011 to 2015: A 4-year follow-up retrospective cohort study from the China Health and Retirement Longitudinal Study.

Background: Central obesity was closely associated with hypertension. Middle-aged and older adult females, defined as those aged 45 and above, were more likely to suffer from central obesity. For waist-to-height ratio (WHtR) was used as central obesity assessment, the object of this study was to illustrate the relationship between WHtR and the incidence of hypertension in middle-aged and older adult females in China. Methods: Data used in this prospective cohort study was derived from the China Health and Retirement Longitudinal Study (CHARLS) in a baseline survey from 2011 to 2012 with a follow-up duration of 4 years. The waist-to-height ratio was calculated as waist circumstance divided by height, and the cohort was divided into different groups based on WHtR level. The outcome variable was new-onset hypertension. Results: Of the 2,438 participants included in the study, 1,821 (74.7%) had high WHtR levels (WHtR ≥ 0.5). As WHtR was closely related to new-onset hypertension in a multivariable logistics regression mode [OR: 7.89 (95% CI: 2.10-29.67)], individuals with high WHtR were also more likely to suffer from hypertension compared with low WHtR levels [OR: 1.34 (95% CI: 1.06-1.69)]. Conclusion: WHtR is positively related to the risk of hypertension incidents among middle-aged and older adult females. Individuals with WHtR ≥ 0.5 were more likely to suffer from hypertension.

Prediction of MAFLD and NAFLD using different screening indexes: A cross-sectional study in U.S. adults.

Introduction: Metabolic dysfunction-associated fatty liver disease (MAFLD), formerly known as non-alcoholic fatty liver disease (NAFLD), has become the most common chronic liver disease worldwide. We aimed to explore the gender-related association between nine indexes (BMI/WC/VAI/LAP/WHtR/TyG/TyG-BMI/TyG-WC/TyG-WHtR) and MAFLD/NAFLD and examine their diagnostic utility for these conditions. Methods: Eligible participants were screened from the 2017-2018 cycle data of National Health and Nutrition Examination Survey (NHANES). Logistic regression and receiver operating characteristic (ROC) curve were used to assess the predictive performance of 9 indexes for MAFLD/NAFLD. Results: Among the 809 eligible individuals, 478 had MAFLD and 499 had NAFLD. After adjusting for gender, age, ethnicity, FIPR and education level, positive associations with the risk of MAFLD/NAFLD were found for all the nine indexes. For female, TyG-WHtR presented the best performance in identifying MAFLD/NAFLD, with AUC of 0.845 (95% CI = 0.806-0.879) and 0.831 (95% CI = 0.791-0.867) respectively. For male, TyG-WC presented the best performance in identifying MAFLD/NAFLD, with AUC of 0.900 (95% CI = 0.867-0.927) and 0.855 (95% CI = 0.817-0.888) respectively. Conclusion: BMI/WC/VAI/LAP/WHtR/TyG/TyG-BMI/TyG-WC/TyG-WHtR are important indexes to identify the risk of MAFLD and NAFLD.

Positive association between different triglyceride glucose index-related indicators and psoriasis: evidence from NHANES.

Background: Psoriasis is a chronic inflammatory skin disease with effects that extend beyond the skin. Insulin resistance (IR) has been associated with psoriasis, but it remains unclear how indicators related to the triglyceride glucose (TyG) index, which were associate with IR, are associated with the condition. Objective: The purpose of this study was to investigate the association between psoriasis and three TyG-related indicators: triglyceride glucose-body mass index (TyG-BMI), triglyceride glucose-waist to height ratio (TyG-WHtR), and triglyceride glucose-waist circumference (TyG-WC). Methods: Data from adults aged 20 to 80 years in the National Health and Nutrition Examination Survey (NHANES) from 2003 to 2006 and 2009 to 2014 were utilized. Institutional Review Board approval and documented written consent was obtained from participants by NHANES (Protocol #2005-06). The patients were divided into three groups based on TyG-BMI, TyG-WC, and TyG-WHtR: Q1 (1st quintile), Q2 (2nd-3rd quintiles), and Q3 (4th-5th quintiles). Differences between the groups were further explored. Multivariate logistic regressions were used to investigate the correlation between these three indicators and psoriasis, with results expressed as odds ratios (OR) and 95% confidence intervals (CI). Subgroup analysis and supplementary analysis was further conducted to explore potential influencing factors. Results: The study included 9,291 participants, of which 260 had psoriasis. Compared Q2 and Q3 of TyG-BMI, TyG-WC, and TyG-WHtR to Q1, there were significantly associate with psoriasis. Among the three indicators, TyG-WC consistently had the highest OR values in Models 1 and 2 (Model 1: Q3 OR (95% CI) = 2.155 (1.442-3.220); Model 2: Q3 OR (95% CI) = 2.029 (1.341-3.069)). While in Model 3, the TyG-BMI shows more significant relationship with psoriasis (Model 3 of TyG-BMI: Q3 OR (95% CI) = 1.948 (1.300-3.000)). Similar results were observed in the majority of subgroups and in supplementary analysis. Conclusion: This study identified a stable and strong positive association between TyG-related indicators (TyG-BMI, TyG-WC, and TyG-WHtR) and psoriasis. This association persisted even after adjusting for multiple factors. It is suggested that high IR is significantly associated with psoriasis.