Association of triglyceride-glucose index with atherosclerotic cardiovascular disease and mortality among familial hypercholesterolemia patients

Joint association of TyG index and LDL-C with all-cause and cardiovascular mortality among patients with cardio-renal-metabolic disease

Both triglyceride-glucose (TyG) index, as a surrogate marker of insulin resistance, and low-density lipoprotein cholesterol (LDL-C) are independent risk factors for long-term prognosis among patients with cardio-renal-metabolic (CRM) disease. However, the co-exposures of TyG index and LDL-C to mortality is unclear. The aim of this study is to investigate the joint effects and risk stratification of the TyG index and LDL-C on all-cause and cardiovascular mortality in CRM patients. We analyzed CRM patients from the National Health and Nutrition Examination Survey (NHANES) database (1999-2018), calculating TyG index as Ln[fasting triglyceride (mg/dL)×fasting glucose (mg/dL)/2] and using multivariable Cox regression models to assess the joint effects of TyG index and LDL-C on all-cause and cardiovascular mortality. The interaction between the TyG index and LDL-C to mortality was also evaluated. During a median follow-up of 7.6 years, 22.8% and 8.4% of patients died from all-cause and cardiovascular causes, respectively. Among patients with LDL-C < 2.6 mmol/L, no significant differences were observed in all-cause and cardiovascular mortality when comparing higher TyG index to the lowest tertile (T1). Specifically, the hazard ratio (HR) for all-cause mortality in the second (T2) and third tertiles (T3) were 0.81 (95% confidence interval(CI): 0.59-1.09) and 0.87 (95%CI: 0.62-1.22), respectively, with a P for trend of 0.468. For cardiovascular mortality, the HR for T2 and T3 compared to T1 were 0.80 (95%CI: 0.48-1.32) and 0.72 (95%CI: 0.45-1.15), respectively, with a P for trend of 0.173. However, elevated TyG index was related to markedly increased risk of all-cause and cardiovascular mortality in patients with LDL-C ≥ 2.6 mmol/L. Specifically, for all-cause mortality, HR for T2 and T3 compared to T1 were 1.01 (95%CI: 0.79-1.28) and 1.38 (95%CI: 1.07-1.79), respectively, with a P for trend of 0.009. For cardiovascular mortality, the HR was 1.09 (95% CI: 0.72-1.65) for T2 and 1.80 (95% CI: 1.18-2.75) for T3, with a P for trend of 0.005. Interactive analysis also demonstrated that a significant association of TyG index and LDL-C with the risk of all-cause (P for interaction = 0.011) and cardiovascular (P for interaction = 0.050) mortality was observed. The findings highlight that elevated TyG index can significantly increase the risk of all-cause and cardiovascular mortality only among CRM patients with LDL-C ≥ 2.6 mmol/L, but not among patients with LDL-C < 2.6 mmol/L.

The associations of physical activity patterns and the triglyceride-glucose index in US adults: a secondary data analysis of NHANES (2007-2018)

The triglyceride-glucose (TyG) index, a readily accessible surrogate biomarker for insulin resistance and metabolic health, has been extensively investigated across various ethnic populations. The critical role of physical activity (PA) in enhancing insulin sensitivity has been corroborated by numerous studies. Nonetheless, the relationship between different patterns of PA and the TyG index remains ambiguous. This study seeks to elucidate the association between different PA patterns and the TyG index. Participants with complete data on TyG index, PA patterns, and other covariates from the National Health and Nutrition Examination Survey database (2007-2018) were included in this study. Participant characteristics across PA groups were compared using Rao-Scott chi-squared test or Kruskal-Wallis test. Multivariate linear regression models were used to assess the relationship between PA patterns and the TyG index, with subgroup analyses, interaction tests and restricted cubic spline (RCS) regression analyses conducted to explore the stability and potential nonlinearity of PA-TyG index association, respectively. A total of 16,440 participants were included, with 12,909, 164, 118, and 3249 individuals being inactive, insufficiently active, weekend warriors (WWs), and regularly active (RA), respectively. Multivariate adjusted linear regression models showed that insufficiently active adults (β = - 0.05, P = 0.3524), WWs (β = -0.01, P = 0.9129), and RA adults (β = - 0.110, P < 0.0001) all had significantly lower TyG indices compared to inactive adults. Significant difference was observed between WWs and RA adults (P for trend < 0.0001). Stratified analyses and interact tests revealed that the PA-TyG index association in RA group was more pronounced in individuals being male, with higher education levels, and without diabetes. Additionally, a significant, non-linear, and negative relationship between weekly total PA and TyG index in non-inactive individuals was determined by RCS analysis (P for overall < 0.001, P for nonlinearity = 0.054). Being regularly active is linked to a substantial reduction in the TyG index, whereas weekend warriors and those with insufficient activity do not experience comparable benefits. Nevertheless, the weekend warrior approach can provide a practical alternative for individuals who are unable to engage in consistent exercise.

Machine learning for predicting in-hospital mortality in elderly patients with heart failure combined with hypertension: a multicenter retrospective study

BACKGROUND

Heart failure combined with hypertension is a major contributor for elderly patients (≥ 65 years) to in-hospital mortality. However, there are very few models to predict in-hospital mortality in such elderly patients. We aimed to develop and test an individualized machine learning model to assess risk factors and predict in-hospital mortality in in these patients.

METHODS

From January 2012 to December 2021, this study collected data on elderly patients with heart failure and hypertension from the Chongqing Medical University Medical Data Platform. Least absolute shrinkage and the selection operator was used for recognizing key clinical variables. The optimal predictive model was chosen among eight machine learning algorithms on the basis of area under curve. SHapley Additive exPlanations and Local Interpretable Model-agnostic Explanations was employed to interpret the outcome of the predictive model.

RESULTS

This study ultimately comprised 4647 elderly individuals with hypertension and heart failure. The Random Forest model was chosen with the highest area under curve for 0.850 (95% CI 0.789-0.897), high accuracy for 0.738, recall 0.837, specificity 0.734 and brier score 0.178. According to SHapley Additive exPlanations results, the most related factors for in-hospital mortality in elderly patients with heart failure and hypertension were urea, length of stay, neutrophils, albumin and high-density lipoprotein cholesterol.

CONCLUSIONS

This study developed eight machine learning models to predict in-hospital mortality in elderly patients with hypertension as well as heart failure. Compared to other algorithms, the Random Forest model performed significantly better. Our study successfully predicted in-hospital mortality and identified the factors most associated with in-hospital mortality.

The triglyceride-glucose index: a predictor of mortality risk among myocardial infarction survivors

The relationship between the triglyceride-glucose (TyG) index and mortality among survivors of myocardial infarction (MI) remains understudied. This study aims to evaluate the association between the TyG index and mortality among adult MI patients in the US. Our study included 986 MI patients, sourced from the National Health and Nutrition Examination Survey conducted from 1999 to 2018. Employing a multivariate Cox proportional hazards model, we examined the association between the TyG index and mortality. To explore potential nonlinear relationships, we employed restricted cubic splines in our analysis. Additionally, we applied a two-piecewise Cox proportional hazards model for a more nuanced analysis of the data, using key turning points as boundaries. To validate the robustness of our research findings, we also performed subgroup analyses. During a 7,342 person-years follow-up period, 434 MI survivors succumbed to various causes, including 158 cardiovascular disease-related deaths. The study revealed a U-shaped pattern between the TyG index and mortality. At TyG index levels below the thresholds (8.85 for all-cause mortality and 9.02 for cardiovascular mortality), mortality exhibited a negative correlation with the TyG index (HR = 0.56, 95%CI 0.39-0.82; HR = 0.67, 95%CI 0.39-1.14). Conversely, mortality rates increased when the TyG index surpassed these thresholds (HR = 1.38, 95%CI 1.08-1.76; HR = 1.56, 95%CI 1.02-2.38). Furthermore, among diabetic patients, subgroup analyses demonstrated that the U-shaped pattern between the TyG index and cardiovascular mortality was particularly pronounced. Our research indicates that among MI survivors, a U-shaped pattern exists between the TyG index and mortality rates, which is particularly pronounced in the diabetic patient subgroup. The corresponding threshold values for all-cause and cardiovascular mortality are 8.85 and 9.02, respectively.

Associations between nine dietary minerals intake and all-cause mortality in individuals with atherosclerotic cardiovascular disease

Background

Varied intake of dietary minerals critically affects cardiovascular health. This study examines the associations of nine dietary minerals intake with all-cause mortality in atherosclerotic cardiovascular diseases (ASCVDs).

Methods

This study analyzed 4,125 individuals with ASCVD from the National Health and Nutrition Examination Survey, employing Kaplan-Meier survival analyses, weighted Cox models, and restricted cubic splines to assess linear and nonlinear relationships between dietary minerals intake and all-cause mortality. Associations across different body mass index (BMI) categories were also evaluated separately.

Results

Over 6.25 years of median follow-up, 1,582 deaths were documented. Adjusted for potential covariates, results show a negative linear correlation between dietary magnesium intake and all-cause mortality (p for trend <0.001). Compared to the lowest quartile, all-cause mortality risk in the highest quartile was found to be 0.63 (95% CI 0.49-0.81). The associations between intake of the other eight dietary minerals and all-cause mortality were not robust. BMI significantly influenced the links between dietary minerals intake and all-cause mortality (p for interaction <0.05). Across BMI categories, significant negative associations were found between intake of magnesium, phosphorus, potassium, sodium, and copper and all-cause mortality in underweight or normal weight groups. In overweight individuals, intake of calcium, iron, magnesium, and potassium was negatively linked to all-cause mortality. For obese groups, sodium intake negatively affected all-cause mortality (p for trend <0.001).

Conclusion

Unlike other dietary minerals, increased magnesium intake significantly reduced all-cause mortality risk in ASCVD. BMI influenced the associations between dietary minerals intake and all-cause mortality.

Predictors of cardiovascular risk in familial hypercholesterolemia

PURPOSE OF REVIEW

Familial Hypercholesterolemia is associated with an increased risk of cardiovascular disease. The current international guidelines of the main scientific societies consider that all people with familial hypercholesterolemia have a high or very high cardiovascular risk. However, the occurrence of atherosclerotic cardiovascular disease is very heterogeneous in this population. Stratifying risk within people with familial hypercholesterolemia is essential to identify individuals who require intensive cholesterol-lowering therapies.

RECENT FINDINGS

In the last year, several studies have been published focusing on the contribution of diabetes to familial hypercholesterolemia, the role of stroke, as a manifestation of atherosclerotic disease, and the external validation of the SAFEHEART risk equation in the English population diagnosed with Familial Hypercholesterolemia.

SUMMARY

It is necessary the development of a tool that allows us to identify, in a simple, reproducible, and universal way, patients who may have a high risk of suffering a cardiovascular event and who are susceptible to more intensive treatments to reduce cholesterol levels.

The nutritional metabolic risk index as a predictor of all-cause and cardiovascular mortality: A national cohort study

BACKGROUND

Recent studies show that malnutrition increases all-cause mortality by 1.11 times and cardiovascular mortality by 2.60 times. Similarly, metabolic syndrome raises overall mortality by 40% and cardiovascular mortality by 37%. This research assesses the Nutritional Metabolic Risk Index (NMRI) for predicting these mortality risks.

METHODS

We analyzed data from 14,209 participants in the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2018, where the NMRI was calculated based on the ratio of GNRI to TyG-WHtR. The relationship between NMRI and mortality was investigated using Kaplan-Meier methods and Cox regression models, with restricted cubic splines (RCS) employed to examine non-linear associations. The predictive capabilities of NMRI, GNRI, and TyG-WHtR for mortality were assessed using receiver operating characteristic curve (ROC) curve analysis.

RESULTS

Over a median follow-up period of 89 months, there were 1358 all-cause deaths and 345 cardiovascular deaths recorded. Cox regression analysis indicated that each unit increase in NMRI was associated with an 8% reduction in all-cause mortality risk and a 15% reduction in cardiovascular mortality risk. RCS analysis found a nonlinear negative correlation between NMRI and both all-cause and cardiovascular mortality. NMRI demonstrated superior predictive accuracy for all-cause mortality (AUC: 0.696, 95% CI: 0.682-0.710) and cardiovascular mortality (AUC: 0.713, 95% CI: 0.689-0.737) compared to GNRI and TyG-WHtR (P < 0.05).

CONCLUSIONS

The NMRI is inversely associated with the risk of all-cause and cardiovascular mortality in American adults.

Insulin-based or non-insulin-based insulin resistance indicators and risk of long-term cardiovascular and all-cause mortality in the general population: A 25-year cohort study

OBJECTIVE

Although insulin resistance (IR) has been recognized to be a causal component in various diseases, current information on the relationship between IR and long-term mortality in the general population is limited and conclusions varied among different IR indicators and different populations. We aimed to assess associations between different measurements of IR with long-term all-cause mortality and cardiovascular mortality risk for the general population.

RESEARCH DESIGN AND METHODS

We included 13,909 individuals from the Third National Health and Nutrition Examination Survey. Mortality was identified via National Death Index information until December 31, 2019. IR was measured using fasting insulin, homeostasis model assessment of IR (HOMA-IR), homeostasis model assessment of β-cell function, quantitative insulin sensitivity check index (QUICKI), insulin-to-glucose ratio (IGR), triglyceride glucose (TyG) index, TyG-body mass index (TyG-BMI), and hypertriglyceridemic-waist phenotype.

RESULTS

During median 25-year follow-up, 5,306 all-cause mortality events occurred. After multivariate adjustment, variables significantly associated with elevated all-cause mortality risk were (hazard ratio [95 % confidence interval]): higher insulin (1.07 [1.02;1.13]); HOMA-IR (1.08 [1.03;1.13]); IGR (1.05 [1.00;1.11]); TyG (1.07 [1.00;1.14]); TyG-BMI (1.24 [1.02;1.51]); lower QUICKI (0.91 [0.86-0.96]). After stratification by diabetes status, higher insulin, HOMA-IR, TyG-BMI and lower QUICKI were significantly associated with increased risk of all-cause mortality in both diabetes and non-diabetes populations (all P for interaction > 0.05). Higher TyG (adjusted HR 1.17 [1.09;1.26], P for interaction = 0.018) and hypertriglyceridemic-waist phenotype (adjusted HR 1.26 [1.08;1.46], P for interaction = 0.047) were significantly associated with increased risk of all-cause mortality in patients with diabetes, however, these associations could not be seen in people without diabetes. Similar results were observed between the above-mentioned IR indicators and cardiovascular death.

CONCLUSIONS

Fasting insulin, HOMA-IR, TyG-BMI, and QUICKI may indicate mortality risk in diabetes and non-diabetes populations, with TyG and the hypertriglyceridemic-waist phenotype showing particular relevance for individuals with diabetes. Further studies are needed to validate these findings and determine their broader applicability.

Oxidative stress mediates the association between triglyceride-glucose index and risk of cardiovascular and all-cause mortality in metabolic syndrome: evidence from a prospective cohort study

Background

The aim of this study was to investigate the relationship between triglyceride-glucose (TyG) index and cardiovascular disease (CVD) and all-cause mortality in adults with metabolic syndrome (MeS) and explore the mediating role of oxidative stress.

Methods

This study included 6131 adults with MeS from the National Health and Nutrition Examination Survey (NHANES). The relationships between TyG index and mortality were elucidated using multivariate Cox proportional hazards models, restricted cubic splines (RCS) Fine-Gray competing risk model. In addition, mediation analysis was used to test the indirect effect of oxidative stress indicators.

Results

Over a median 106-month follow-up, a total of 357 CVD and 1292 all-cause deaths were recorded. After multivariate adjustment, there was a J-type relationship between TyG index and CVD and all-cause mortality, with optimal inflection point of 9.13 and 8.92. After the threshold point, TyG index was positively associated with CVD (HR: 4.21, 95%CI: 1.82, 9.78) and all-cause mortality(HR: 2.93, 95%CI: 2.05, 4.18). Even using non-cardiovascular mortality as a competitive risk, the Fine-Gray model also illustrated that the cumulative CVD mortality incidence was higher in MeS with TyG index >9.13 (Fine-Gray P< 0.01). Mediation analysis revealed that biomarkers of oxidative stress, including gamma-glutamyl transferase and uric acid, collectively mediated 10.53% of the association between the TyG index and CVD mortality, and 8.44% of the association with all-cause mortality (P < 0.05).

Conclusion

In the cohort study, TyG index was found to have a J-shaped association with CVD mortality and all-cause mortality in MeS population and oxidative stress may play a key mediating role in this relationship.

Association between TyG index and risk of carotid atherosclerosis in NAFLD patients: a retrospective cohort study

Background

The TyG index, or triglyceride-glucose index, is primarily used as a marker to assess insulin resistance and metabolic health. It increases mortality risk in patients with NAFLD, atherosclerosis, ischemic stroke, or heart failure. However, its association with Carotid Atherosclerosis (CAS) risk in NAFLD patients remains uncertain.

Methods

This retrospective cohort study enrolled 739 individuals who participated comprehensive health evaluations at a large public hospital in Yangzhou, China, between January 2021 and December 2023. Among them, 436 were men and 303 were women, and their mean (SD) age was 51.53 ± 11.46 years. The individuals were categorized into three tertiles (Q1, Q2, and Q3), according to the baseline TyG index. Our investigation focused on exploring the correlativity between the TyG and the occurrence of CAS utilizing Cox regression and RCS analyses.

Results

During a 3-year follow-up period, 199 patients developed CAS (cumulative incidence rate: 26.93%). A statistical model, adjusted for age, gender, BMI, and other confounders indicated that the HR (95%CI) values for CAS risk in the Q2 and Q3 groups were 3.11(1.87-5.17) and 4.51(2.69-7.56), respectively, with P-values <0.001 for both groups. A sensitivity analysis confirmed these results. Kaplan-Meier survival analysis revealed that CAS risk varied across the groups (P non-linear < 0.05).

Conclusion

In individuals diagnosed as NAFLD, the possibility for CAS escalates with the elevation of the TyG value. Therefore, the TyG index is an effective marker for assessing the risk of CAS within this demographic. Large-sample prospective studies are needed to confirm this conclusion in the future.

Value of the triglyceride-glucose index and related parameters in heart failure patients

The triglyceride-glucose (TyG) index, proven to be a crucial insulin resistance biomarker (better than the Homeostasis Model Assessment for Insulin Resistance), is simple and non-invasive. Recently, indisputable evidence has shown that the TyG index is strongly associated with cardiovascular disease [CVD, including atherosclerosis, heart failure (HF), and hypertension] prognosis and mortality. Nevertheless, the value of the TyG index in HF patients treated with sodium-glucose cotransporter 2 inhibitors (SGLT2is) has not been systematically evaluated. Therefore, in this review, we summarized the value of the TyG index and its related parameters as markers of CVD, especially HF. Furthermore, we addressed the use of SGLT2is and GLP-1 receptor antagonists in HF patients. Finally, we summarized the mechanism of the "obesity paradox."

Association of the triglyceride-glucose index with early-onset atherosclerotic cardiovascular disease events and all-cause mortality: a prospective cohort study

BACKGROUND

The association between the triglyceride glucose (TyG) index and the risk of early-onset atherosclerotic cardiovascular disease (ASCVD) events or all-cause mortality in young and middle-aged people is not fully elucidated.

METHODS

The present study included 64,489 young and middle-aged people who participated in the 2006 Kailuan Study physical examination. Multivariate Cox proportional hazards models and restricted cubic spline curves were used to assess the association of TyG index with early-onset ASCVD events and all-cause mortality.

RESULTS

During a median of 11-year follow-up, 1984 (3.08%) participants experienced at least one ASCVD event and 1,392 (2.16%) participants experienced all-cause death. A higher TyG index was significantly associated with a higher risk of early-onset ASCVD events (HR: 1.61, 95% CI 1.38-1.89) and all-cause mortality (HR: 1.39, 95% CI 1.17-1.65), respectively. For each unit increase in TyG index, the risk of early-onset ASCVD events increased by 20%. In addition, there was a non-linear association between the TyG index and early-onset ASCVD events (P for non-linear < 0.01), and a linear association between TyG index and all-cause mortality (P for non-linear = 0.476).

CONCLUSIONS

A higher TyG index is significantly associated with an increased incidence of early-onset ASCVD events and all-cause mortality in a young and middle-aged population from North China.

Associations of triglyceride-glucose (TyG) index with chest pain incidence and mortality among the U.S. population

BACKGROUND

The triglyceride and glucose (TyG) index, a simple surrogate marker of insulin resistance, is related to cardiovascular disease. However, there is a lack of evidence for the relationship between the TyG index and chest pain. This study aimed to investigate the association of the TyG index with chest pain and to evaluate the relationship between the TyG index and all-cause mortality in participants with or without chest pain.

METHODS

The present study utilized data from the 2001-2012 National Health and Nutrition Examination Survey (NHANES), employing a combination of cross-sectional and cohort study designs. The association between the TyG index and chest pain was investigated using weighted logistic regression models. Weighted Cox proportional hazards models were used to estimate the hazard ratios (HRs) and 95% confidence intervals (95% CIs) for all-cause mortality. Restricted cubic spline analysis was used to explore linear or nonlinear relationships between the TyG index and chest pain or all-cause mortality.

RESULTS

The findings revealed a positive correlation between the TyG index and chest pain, even after adjusting for potential confounding factors (quartile 4 versus quartile 1, odds ratio [OR] 1.42, 95% confidence interval [CI] 1.14-1.77, P = 0.002). During a mean follow-up time of 139 months, a total of 2286 individuals (27.43%) experienced mortality. Weighted multivariate Cox regression models indicated that for each one-unit increase in the TyG index, the adjusted hazard ratio (HR) for mortality was 1.14 (95% CI = 0.94-1.37) for participants with chest pain and 1.25 (95% CI = 1.09-1.43) for those without chest pain. Furthermore, restricted cubic spline analysis revealed a linear relationship between the TyG index and chest pain (P for nonlinearity = 0.902), whereas a nonlinear relationship was shown between the TyG index and all-cause mortality among populations regardless of chest pain (all P for nonlinearity < 0.01).

CONCLUSION

The TyG index was positively linked to a higher incidence of chest pain. Moreover, the TyG index was associated with all-cause mortality not only in participants with chest pain but also in those without chest pain.

TyG index is a predictor of all-cause mortality during the long-term follow-up in middle-aged and elderly with hypertension

BACKGROUND

The triglyceride and glucose (TyG) index has been found to be significantly associated with a higher risk of mortality. However, there has been a lack of studies exploring the specific relationship between the TyG index and all-cause and cardiovascular mortality among middle-aged and elderly with hypertension.

METHODS

A total of 3,614 participants with hypertension were enrolled from the National Health and Nutrition Examination Survey. The TyG index was calculated using the formula log [fasting triglycerides (mg/dL) x fasting glucose (mg/dL)/2]. The Cox proportional hazard ratios were used to evaluate the association between the TyG index and the risk of mortality.

RESULTS

Over a follow-up period of 7.87 years, 991 all-cause death and 189 cardiovascular deaths occurred. Compared with the reference quartile, the multivariate-adjusted hazard ratios and 95% confidence intervals were 1.28 (1.07-1.53; p = .006) in the fourth quartile for all-cause mortality and 0.63 (0.42-0.96; p = .031) in the second quartile for cardiovascular mortality. Dose-response analysis indicated an L-shaped relationship.

CONCLUSIONS

The TyG index exhibited an L-shaped association with the risk of all-cause mortality among middle-aged and elderly with hypertension.

Predictors of cardiovascular risk in familial hypercholesterolemia

PURPOSE OF REVIEW

Familial hypercholesterolemia is associated with an increased risk of cardiovascular disease. The current international guidelines of the main scientific societies consider that, all people with Familial Hypercholesterolemia have a high or very high cardiovascular risk. However, the occurrence of atherosclerotic cardiovascular disease is very heterogeneous in this population. Stratifying risk within people with familial hypercholesterolemia is essential to identify individuals who require intensive cholesterol-lowering therapies.

RECENT FINDINGS

In the last year, several studies have been published focusing on the contribution of diabetes to Familial Hypercholesterolemia, the role of stroke, as a manifestation of atherosclerotic disease, and the external validation of the SAFEHEART risk equation in the English population diagnosed with Familial Hypercholesterolemia.

SUMMARY

It is necessary the development of a tool that allows us to identify, in a simple, reproducible, and universal way, patients who may have a high risk of suffering a cardiovascular event and who are susceptible to more intensive treatments to reduce cholesterol levels.

Association of Dietary Inflammation Index and Helicobacter pylori Immunoglobulin G Seropositivity in US Adults: A Population-Based Study

Background

Dietary patterns play important role in Helicobacter pylori (H. pylori) infection. We aimed to investigate the potential relationship between Dietary Inflammation Index (DII) and H. pylori infection in US adults.

Methods

This cross-sectional study was based on National Health and Nutrition Examination Survey (1999-2000). Individuals aged ≥20 years who provided a 24 hr dietary intake history and underwent H. pylori testing were included in the analysis. Multivariate weighted logistic regression analysis, smooth curve fitting, and subgroup analysis were used to investigate the relationship between DII and H. pylori infection. Subgroup analyses were based on demographic and clinical variables.

Results

There were 4,000 individuals enrolled in our final analysis. The overall mean age was 45.92 years and 46.77% were males. The overall prevalence of H. pylori infection in the study population was 45.9%. The smooth curve fitting analysis indicated a near-linear relationship between DII and H. pylori. In multivariate weighted logistic regression analysis, the odds ratio (OR) of DII is 1.17 (95% confidence interval (CI), 1.09-1.27) for H. pylori infection. In subgroup analysis, DII still increased the risk of H. pylori infection independently.

Conclusions

The increased DII levels were associated with an increased risk of H. pylori infection among US adults. Further studies are needed to elucidate the exact mechanisms of DII and H. pylori infection.

Association between systemic immune-inflammation index and low muscle mass in US adults: a cross-sectional study

BACKGROUND

Chronic inflammatory responses have been reported to be associated with low muscle mass and systemic immune-inflammation index(SII) is a novel indicator of inflammation. The purpose of our study was to clarify the relationship between SII and low muscle mass.

METHODS

This study was a cross-sectional study based on National Health and Nutrition Examination Survey (2011-2018). SII was calculated as the platelet count × neutrophil count/lymphocyte count. Appendicular skeletal muscle index was used to define low muscle mass. The individuals were divided into four groups by the quartile of SII (Q1-Q4). Multivariate weighted logistic regression analysis, smooth curve fitting and subgroup analysis were used to investigate the relationship between SII and sarcopenia. Subgroup analysis were based on demographic and clinical variables.

RESULTS

There were 10,367 individuals enrolled in our final analysis. The overall mean age was 39.39 years and 49.17% were males. The overall prevalence of low muscle mass in the study population was 8.77%. The smooth curve fitting analysis indicated a near-linear relationship between SII and low muscle mass. In multivariate weighted logistic regression analysis, the odds ratio (OR) of Q4 is 1.28 (95% CI, 1.16-1.40) for low muscle mass when compared to lowest quartile of the SII. In subgroup analysis, SII still increased the risk of low muscle mass independently.

CONCLUSION

The increased SII levels were associated with an increased risk of low muscle mass in a large population. Our study increased the understanding between inflammation and low muscle mass. Anti-inflammation therapy may be important for low muscle mass.