Mediation of 10-Year Cardiovascular Disease Risk between Inflammatory Diet and Handgrip Strength: Base on NHANES 2011–2014

Xie, Zechun; Sun, Mengzi; Wang, Rui; Li, Jing; Wang, Xuhan; Guo, Ruirui; Dong, Yuchen; Wang, Yuxiang; Li, Bo

doi:10.3390/nu15040918

Cited by 8 publications

(3 citation statements)

References 49 publications

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“…Postmenopausal women have decreased ET B R expression in endothelial cells and vasodilatory dysfunction, often resulting in systemic vascular dysfunction [28]. Additionally, women intake more pro-in ammatory substances than males [29]. Therefore, we assume from these results that the relationship between SIRI and HF in female patients is in uenced by other variables, such as age and hormone level, which may explain the inconsistency between the two smoothing curves in men and women after strati cation by gender.…”

Section: Discussionmentioning

confidence: 99%

The association between Heart failure and Systemic inflammatory response index: A cross‐sectional study

Zheng

Guo

2023

Preprint

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Background: The Systemic Inflammatory Response Index (SIRI) is a novel inflammatory composite measure widely utilized for evaluating the prognosis of patients with cardiovascular and cerebrovascular disorders and cancer. It has been proven that people with heart failure (HF) have a chronic inflammatory response in their hearts. The aim of this study is to evaluate the potential connection between SIRI with HF. Methods: The cross-sectional investigation used National Health and Nutrition Examination Survey (NHANES) database information from 2009 to 2018. SIRI is computed using the monocyte, neutrophil, and lymphocyte counts. The Monetary Choice Questionnaire (MCQ) results define HF. The linear association between SIRI and HF was analyzed using a weighted linear regression model with multiple variables. The nonlinear link was defined using smoothing curve fittings and threshold effect analysis. Results: 26,361 individuals were included in our analysis; HF was diagnosed in 3.26% of participants, and this proportion increased with higher SIRI levels (Quartile 1, 1.76%; Quartile 2, 1.87%; Quartile 3, 2.98%; Quartile 4, 6.43%; p for trend <0.001). Multiple logistic regression analysis demonstrated a relationship between higher SIRI levels and an elevated chance of HF (OR = 1.15;95% CI, 1.05-1.27, p=0.0029). In addition, a nonlinear relationship existed between SIRI and HF. A two-segment linear regression model showed an inverse S-shaped connection between SIRI with HF by an inflection point of 2.66 (1,000 cells/μl). In males the SIRI-HF association was inverted U-shaped, with an inflection point at 2.8 (1,000 cells/μl) after stratification; among females, there was no statistically significant inflection point. Conclusions: Our results imply the existence of a positive correlation between HF. To corroborate the association between SIRI and HF, that was required to perform prospective investigations on a huge scale and clinical experiments.

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Section: Discussionmentioning

confidence: 99%

The association between Heart failure and Systemic inflammatory response index: A cross‐sectional study

Zheng

Guo

2023

Preprint

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“…Concurrently, it jeopardizes peripheral systems by promoting free fatty acid circulation and deposition into myocytes, leading to intramuscular fat accumulation and perturbed muscle metabolism [26]. Physiologically, metrics like BMI and grip strength correlate with nutritional risk, reflecting body fat, muscle mass, and muscular strength-essential parameters for nutritional evaluation [27]. Post-stroke muscle and weight loss are frailty hallmarks and diminished BMI and grip strength might signify muscle and adipose tissue loss.…”

Section: Analysis Of Pertinent Risk Factorsmentioning

confidence: 99%

Development and Validation of a Nomogram for Predicting Nutritional Risk Based on Frailty Scores in Older Stroke Patients

Liu,

He,

Yang

et al. 2024

Aging Clin Exp Res

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Background In older stroke patients with frailty, nutritional deficiencies can amplify their susceptibility, delay recovery, and deteriorate prognosis. A precise predictive model is crucial to assess their nutritional risk, enabling targeted interventions for improved clinical outcomes. Objective To develop and externally validate a nutritional risk prediction model integrating general demographics, physical parameters, psychological indicators, and biochemical markers. The aim is to facilitate the early identification of older stroke patients requiring nutritional intervention. Methods This was a multicenter cross-sectional study. A total of 570 stroke patients were included, 434 as the modeling set and 136 as the external validation set. The least absolute shrinkage selection operator (LASSO) regression analysis was used to select the predictor variables. Internal validation was performed using Bootstrap resampling (1000 iterations). The nomogram was constructed based on the results of logistic regression. The performance assessment relied on the receiver operating characteristic curve (ROC), Hosmer–-Lemeshow test, calibration curves, Brier score, and decision curve analysis (DCA). Results The predictive nomogram encompassed seven pivotal variables: Activities of Daily Living (ADL), NIHSS score, diabetes, Body Mass Index (BMI), grip strength, serum albumin levels, and depression. Together, these variables comprehensively evaluate the overall health and nutritional status of elderly stroke patients, facilitating accurate assessment of their nutritional risk. The model exhibited excellent accuracy in both the development and external validation sets, evidenced by AUC values of 0.934 and 0.887, respectively. Such performance highlights its efficacy in pinpointing elderly stroke patients who require nutritional intervention. Moreover, the model showed robust goodness of fit and practical applicability, providing essential clinical insights to improve recovery and prognosis for patients prone to malnutrition. Conclusions Elderly individuals recovering from stroke often experience significant nutritional deficiencies. The nomogram we devised accurately assesses this risk by combining physiological, psychological, and biochemical metrics. It equips healthcare providers with the means to actively screen for and manage the nutritional care of these patients. This tool is instrumental in swiftly identifying those in urgent need of targeted nutritional support, which is essential for optimizing their recovery and managing their nutrition more effectively.

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“…Eventually, 24 researches involving 56,536 participants met the eligibility criteria (Figure 1). Twenty studies were crosssectional designed and four were longitudinal studies (20)(21)(22)(23)(24)(25)(42)(43)(44)(45)(46)(47)(48)(49)(50)(51)(52)(53)(54)(55)(56)(57)(58)(59). No interventional study was available for this meta-analysis.…”

Section: Study Selection and Characteristicsmentioning

confidence: 99%

The association of dietary inflammatory potential with skeletal muscle strength, mass, and sarcopenia: a meta-analysis

Xie

Wang

et al. 2023

Front. Nutr.

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AimsEvidence suggested that dietary inflammatory potential may be associated with age-related skeletal muscle decline, but the results remained controversial. To summarize the evidence for the relationships between dietary inflammatory potential and skeletal muscle strength, mass, and sarcopenia in adults we conducted this meta-analysis.MethodsEmbase, Pubmed, and Web of Science were searched from inception up to 12 March 2023 for studies that evaluated the associations of dietary inflammatory potential [estimated by the Dietary inflammatory index (DII)] with skeletal muscle strength, mass, and sarcopenia. A meta-analysis was then performed to calculate the pooled regression coefficient (β) and odds ratio (OR). The non-linear dose-response relation between DII and sarcopenia was assessed using random-effects dose-response meta-analysis.ResultsThis meta-analysis included 24 studies involving 56,536 participants. It was found that high DII was associated with low skeletal muscle strength [OR 1.435, 95% confidence interval (CI) 1.247–1.651, P < 0.001, I2 = 4.97%]. There was a negative association of DII with skeletal muscle strength (β−0.031, 95% CI −0.056 to −0.006, P = 0.017, I2 = 72.69%). High DII was also associated with low skeletal muscle mass (OR 1.106, 95% CI 1.058–1.157, P < 0.001, I2 = 0%). DII had a negative relationship with skeletal muscle mass with high heterogeneity (β−0.099, 95% CI −0.145 to −0.053, P < 0.001, I2 = 88.67%); we downgraded the inconsistency in the subgroup analysis of overweight/obese participants (β−0.042, 95% CI −0.065 to −0.019, I2 = 12.54%). Finally, the pooled results suggested that high DII was significantly associated with sarcopenia with significant heterogeneity (OR 1.530, 95% CI 1.245–1.880, P < 0.001, I2 = 69.46%); age and BMI may contribute partially to the heterogeneity since heterogeneity was decreased in the subgroup of older age (OR 1.939, 95% CI 1.232–3.051, I2 = 0%) and the group of overweight/obesity (OR 1.853, 95% CI 1.398–2.456, I2 = 0%). There was a non-linear dose-response association between DII and sarcopenia (P = 0.012 for non-linearity).ConclusionThis meta-analysis suggested that higher dietary inflammatory potential was significantly associated with lower skeletal muscle strength, mass, and risk of sarcopenia. Future studies with consistent assessment and standardized methodology are needed for further analysis.

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Mediation of 10-Year Cardiovascular Disease Risk between Inflammatory Diet and Handgrip Strength: Base on NHANES 2011–2014

Cited by 8 publications

References 49 publications

The association between Heart failure and Systemic inflammatory response index: A cross‐sectional study

The association between Heart failure and Systemic inflammatory response index: A cross‐sectional study

Development and Validation of a Nomogram for Predicting Nutritional Risk Based on Frailty Scores in Older Stroke Patients

The association of dietary inflammatory potential with skeletal muscle strength, mass, and sarcopenia: a meta-analysis

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