PDF(962 KB)
The mediating effects of triglyceride-glucose index and its combination with obesity indicators between physical activity and cognitive function
Xiaotong CHEN, Hongqin GU, Meifang SHI, Yong LIN
Chinese Journal of Alzheimer's Disease and Related Disorders ›› 2025, Vol. 8 ›› Issue (6) : 371-377.
PDF(962 KB)
Abbreviation (ISO4): Chinese Journal of Alzheimer's Disease and Related Disorders
Editor in chief: Jun WANG
PDF(962 KB)
The mediating effects of triglyceride-glucose index and its combination with obesity indicators between physical activity and cognitive function
Objective: To analyze the differences in the triglyceride-glucose index (TyG) and its combination with obesity indicators in the assessment of cognitive function, and to further explore their mediating effects between physical activity (PA) and cognitive function. Methods: Questionnaires of the physical examination population in Youyi Road Community Health Service Centre for Baoshan District, Shanghai from April to December 2020 were collected. A total of 3937 subjects were included. The association between PA and cognitive function, the association between TyG and its combined obesity indicators and cognitive function were analyzed using generalized linear regression models, and gender stratified analysis was conducted. The mediating effects of TyG and its combined obesity indicators in the relationship between PA and cognitive function were evaluated using the mediation models. Results: After full adjustment, there was a significant association between PA and cognitive function (β=0.337, P < 0.05), and the trend of the analysis results in men was consistent with that of the total population (β=0.374, P < 0.05). There was no significant association between TyG and the mini-mental state examination (MMSE) score in the total population. Compared with TyG-body mass index (TyG-BMI) and TyG-waist circumference (TyG-WC), the association between TyG-waist-to-height ratio (TyG-WHtR) and MMSE score was significantly enhanced (β=-0.588, P < 0.001), and the results of the gender subgroup analysis were consistent with those of the total population. TyG-BMI, TyG-WC and TyG-WHtR all played significant mediating roles between PA and cognitive function, among which the mediating effect of TyG-WHtR was the strongest (9.81%, P < 0.05). Conclusion: There is a significant association between PA, TyG and its combination with obesity indicators and cognitive function. TyG-BMI, TyG-WC and TyG-WHtR all played significant mediating roles between PA and cognitive function, and TyG-WHtR plays the strongest mediating role in the association. The TyG-obesity combined indexes provide basis for formulating cognitive function protection strategies for individuals with metabolic abnormalities..
Triglyceride-glucose index-waist-to-height ratio / Physical activity / Cognitive function
| [1] |
|
| [2] |
|
| [3] |
|
| [4] |
Currently, obesity has become a global health issue and is referred to as an epidemic. Dysfunctional obese adipose tissue plays a pivotal role in the development of insulin resistance. However, the mechanism of how dysfunctional obese-adipose tissue develops insulin-resistant circumstances remains poorly understood. Therefore, this review attempts to highlight the potential mechanisms behind obesity-associated insulin resistance. Multiple risk factors are directly or indirectly associated with the increased risk of obesity; among them, environmental factors, genetics, aging, gut microbiota, and diets are prominent. Once an individual becomes obese, adipocytes increase in their size; therefore, adipose tissues become larger and dysfunctional, recruit macrophages, and then these polarize to pro-inflammatory states. Enlarged adipose tissues release excess free fatty acids (FFAs), reactive oxygen species (ROS), and pro-inflammatory cytokines. Excess systemic FFAs and dietary lipids enter inside the cells of non-adipose organs such as the liver, muscle, and pancreas, and are deposited as ectopic fat, generating lipotoxicity. Toxic lipids dysregulate cellular organelles, e.g., mitochondria, endoplasmic reticulum, and lysosomes. Dysregulated organelles release excess ROS and pro-inflammation, resulting in systemic inflammation. Long term low-grade systemic inflammation prevents insulin from its action in the insulin signaling pathway, disrupts glucose homeostasis, and results in systemic dysregulation. Overall, long-term obesity and overnutrition develop into insulin resistance and chronic low-grade systemic inflammation through lipotoxicity, creating the circumstances to develop clinical conditions. This review also shows that the liver is the most sensitive organ undergoing insulin impairment faster than other organs, and thus, hepatic insulin resistance is the primary event that leads to the subsequent development of peripheral tissue insulin resistance.Copyright © 2021 The Authors. Published by Elsevier Masson SAS.. All rights reserved.
|
| [5] |
|
| [6] |
Insulin resistance (IR) increases Alzheimer's disease (AD) risk. IR is related to greater amyloid burden post-mortem and increased deposition within areas affected by early AD. No studies have examined if IR is associated with an in vivo index of amyloid in the human brain in late middle-aged participants at risk for AD.Asymptomatic, late middle-aged adults (N = 186) from the Wisconsin Registry for Alzheimer's Prevention underwent [C-11]Pittsburgh compound B (PiB) positron emission tomography. The cross-sectional design tested the interaction between insulin resistance and glycemic status on PiB distribution volume ratio in three regions of interest (frontal, parietal, and temporal).In participants with normoglycemia but not hyperglycemia, higher insulin resistance corresponded to higher PiB uptake in frontal and temporal areas, reflecting increased amyloid deposition.This is the first human study to demonstrate that insulin resistance may contribute to amyloid deposition in brain regions affected by AD.Copyright © 2015 The Alzheimer's Association. All rights reserved.
|
| [7] |
|
| [8] |
|
| [9] |
|
| [10] |
Obesity and diabetes have been associated with depressive symptoms. The aim of this systematic review and meta-analysis was to evaluate the association between the triglyceride glucose index (TyG index) a novel indicator of insulin resistance (IR) and depression in the adult population.
|
| [11] |
|
| [12] |
|
| [13] |
|
| [14] |
The relationship between obesity and cognitive impairment is important given the globally ageing population in whom cognitive decline and neurodegenerative disorders will carry grave individual, societal and financial burdens. This review examines the evidence for the link between obesity and cognitive function in terms of both the immediate effects on cognitive performance, and effects on the trajectory of cognitive ageing and likelihood of dementia. In mid-life, there is a strong association between obesity and impaired cognitive function. Anthropometric measures of obesity are also associated with reduced neural integrity (e.g. grey and white matter atrophy). Increasing age coupled with the negative metabolic consequences of obesity (e.g. type 2 diabetes mellitus) are likely to significantly contribute to cognitive decline and incidence of dementia. Stress is identified as a potential risk factor promoting abdominal obesity and contributing to impaired cognitive function. However, the potentially protective effects of obesity against cognitive decline in older age require further examination. Finally, surgical and whole diet interventions, which address obesity may improve cognitive capacity and confer some protection against later cognitive decline. In conclusion, obesity and its comorbidities are associated with impaired cognitive performance, accelerated cognitive decline and neurodegenerative pathologies such as dementia in later life. Interventions targeting mid-life obesity may prove beneficial in reducing the cognitive risks associated with obesity.
|
| [15] |
|
| [16] |
|
| [17] |
Because the insulin test is expensive and is not available in most laboratories in the cities of undeveloped countries, we tested whether the product of fasting triglycerides and glucose levels (TyG) is a surrogate for estimating insulin resistance compared with the homeostasis model assessment of insulin resistance (HOMA-IR) index.We performed a population-based cross-sectional study. Sampling strategy was based on a randomized two-stage cluster sampling procedure. Only apparently healthy subjects, men and nonpregnant women aged 18-65 years, with newly diagnosed impaired fasting glucose (IFG), impaired glucose tolerance (IGT), or IFG + IGT were enrolled. Renal disease, malignancy, and diabetes were exclusion criteria. Sensitivity, specificity, predictive values, and the probability of disease given a positive test were calculated. The optimal TyG index for estimating insulin resistance was established using a receiver operating characteristic scatter plot analysis.A total of 748 apparently healthy subjects aged 41.4 +/- 11.2 years were enrolled. Insulin resistance was identified in 241 (32.2%) subjects (HOMA-IR index 4.4 +/- 1.6). New diagnoses of IFG, IGT, and IFG + IGT were established in 145 (19.4%), 54 (7.2%), and 75 (10.0%) individuals. respectively. The best TyG index for diagnosis of insulin resistance was Ln 4.65, which showed the highest sensitivity (84.0%) and specificity (45.0%) values. The positive and negative predictive values were 81.1% and 84.8%, and the probability of disease, given a positive test, was 60.5%.The TyG index could be useful as surrogate to identify insulin resistance in apparently healthy subjects.
|
| [18] |
|
| [19] |
The triglyceride-glucose index (TyG), and TyG-driven parameters incorporating TyG and obesity indices have been proposed as reliable indicators of insulin resistance and its related comorbidities. This study evaluated the effectiveness of these indices in identifying hepatic steatosis in individuals with Type 2 diabetes (T2DM).This was a cross-sectional study consisting of 175 patients with T2DM (122 with and 53 without NAFLD). TyG index, triglyceride glucose-body mass index (TyG-BMI), triglyceride glucose-waist circumference (TyG-WC), and triglyceride glucose-waist-to-height ratio (TyG-WHtR) were determined using standard formulas. Controlled attenuation parameter (CAP) was measured by transient elastography (FibroScan).Among obesity parameters, CAP showed the strongest correlation with WHtR, followed by BMI and WC (all P < 0.001). Regression analyses demonstrated TyG-WHtR as a significant predictor of NAFLD with the highest odds ratio, reaching 10.69 (95% CI: 1.68-68.22) for the top quartile (Q4) compared to the first quartile (P = 0.01), followed by TyG-BMI (Q4: 6.75; 95% CI: 1.49-30.67) and TyG-WC (Q4: 5.90; 95% CI: 0.99-35.18). Moreover, TyG-WHtR presented the largest AUC for detection of NAFLD (0.783, P < 0.001) in ROC analysis, followed by TyG-BMI (AUC: 0.751, P < 0.001), TyG-WC (AUC: 0.751, P < 0.001), and TyG (AUC: 0.647, P = 0.002). TyG-WHtR value of 5.58 (sensitivity: 79%, specificity: 68%, P < 0.001) was the best cut-off point to identify hepatic steatosis in this population.This study confirmed that the TyG-related indices comprising TyG and obesity parameters can identify hepatic steatosis more successfully than TyG alone. Furthermore, our results highlighted TyG-WHtR as a simple and effective marker for screening fatty liver in patients with T2DM, which may be used practically in clinical setting.© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
|
| [20] |
Triglyceride-glucose (TyG) is correlated with cardiovascular events caused by insulin resistance (IR). The aim of this study was to analyze the relationship between TyG and its related indicators and IR among US adults from 2007 to 2018 in the National Health and Nutrition Examination Survey (NHANES) database so as to identify more accurate and reliable predictors of IR.This is a cross-sectional study including 9884 participants (2255 with IR and 7629 without IR). TyG, TyG-body mass index (TyG-BMI), TyG waist circumference (TyG-WC), and TyG waist-to-height ratio (TyG-WtHR) were measured using standard formulas.TyG, TyG-BMI, TyG-WC, and TyG-WtHR were significantly correlated with IR in the general population, with TyG-WC being the most strongly correlated, with an odds ratio of 8.00 (95% confidence interval 5.05-12.67) for the fourth quartile of TyG-WC compared with the first quartile in the adjusted model. Receiver operating characteristic (ROC) analysis of the participants showed that the maximum area under the TyG-WC curve was 0.8491, which was significantly higher than that of the other three indicators. Moreover, this trend was stable both among people of both genders and among patients with coronary heart disease (CHD), hypertension, and diabetes.The present study confirms that the TyG-WC index is more successful than TyG alone in identifying IR. In addition, our findings demonstrate that TyG-WC is a simple and effective marker for screening the general US adult population and those with CHD, hypertension, and diabetes and can be effectively used in clinical practice.© 2023. The Author(s), under exclusive licence to Hellenic Endocrine Society.
|
| [21] |
The anthropometric indices (body mass index [BMI], waist circumference [WC] and waist-to-height ratio [WHtR]), triglyceride-glucose (TyG) index and TyG-related indicators (TyG-WHtR, TyG-BMI, TyG-WC) have been well documented to be highly correlated with insulin resistance (IR) and type 2 diabetes mellitus (T2DM). However, it was not immediately obvious which indicator would be optimal for screening people at risk of T2DM. Hence, this study intended to compare the predictive effects of the aforementioned markers on T2DM and to investigate the relation between baseline TyG-WHtR and incident T2DM.
|
| [22] |
|
| [23] |
|
| [24] |
|
| [25] |
|
| [26] |
|
| [27] |
|
| [28] |
|
| [29] |
|
| [30] |
Insulin resistance is a determining factor in the pathophysiology of type 2 diabetes mellitus (T2DM). Exercise is known to improve insulin resistance, but a systematic review of the literature is lacking.This systematic review and meta-analysis focused on identifying evidence for the effectiveness of a structured exercise intervention program for insulin resistance in T2DM.We searched MEDLINE via PubMed, CINHAL, Scopus and Web of Science, and the Cochrane Central Register of Controlled Trials for reports of studies on fasting insulin, homeostatic model assessment for insulin resistance (Homa-IR), fasting blood sugar, glycated hemoglobin and body mass index in patients with T2DM and healthy controls that were published between 1990 and 2017. Data are reported as the standardized mean difference or mean difference with 95% confidence intervals (CIs).Among 2242 records retrieved, only 11 full-text articles were available for meta-analysis. Data for 846 participants were analyzed, 440 in the intervention group, and 406 in the control group. The mean difference for fasting insulin level was-1.64 (95% CI; -3.38 to 0.10), Homa-Ir 0.14 (-1.48 to 1.76), fasting blood sugar-5.12 (-7.78 to-2.45), hemoglobin A1c 0.63 (-0.82 to 2.08) and body mass index-0.36 (-1.51 to 0.79).The evidence highlights the effectiveness of a structured exercise intervention program for insulin resistance in T2DM with a moderate level 2 of evidence.Copyright © 2018 Elsevier Masson SAS. All rights reserved.
|
| [31] |
|
| [32] |
|
| [33] |
Neurodegenerative diseases are debilitating nervous system disorders attributed to various conditions such as body aging, gene mutations, genetic factors, and immune system disorders. Prominent neurodegenerative diseases include Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, amyotrophic lateral sclerosis, and multiple sclerosis. Insulin resistance refers to the inability of the peripheral and central tissues of the body to respond to insulin and effectively regulate blood sugar levels. Insulin resistance has been observed in various neurodegenerative diseases and has been suggested to induce the occurrence, development, and exacerbation of neurodegenerative diseases. Furthermore, an increasing number of studies have suggested that reversing insulin resistance may be a critical intervention for the treatment of neurodegenerative diseases. Among the numerous measures available to improve insulin sensitivity, exercise is a widely accepted strategy due to its convenience, affordability, and significant impact on increasing insulin sensitivity. This review examines the association between neurodegenerative diseases and insulin resistance and highlights the molecular mechanisms by which exercise can reverse insulin resistance under these conditions. The focus was on regulating insulin resistance through exercise and providing practical ideas and suggestions for future research focused on exercise-induced insulin sensitivity in the context of neurodegenerative diseases.
|
| [34] |
|
/
| 〈 |
|
〉 |
