Abstract
The triglyceride-glucose (TyG) index represents a pioneering approach to assessing insulin resistance. The objective of this study was to investigate the potential association between the TyG index and muscle strength in a Chinese middle-aged and older adults without comorbid chronic diseases. A total of 2,086 participants were identified in the China Health and Retirement Longitudinal Study (CHARLS). Muscle strength was assessed using two methods: absolute handgrip strength (HGS) and relative HGS, which was normalised by body weight or BMI. To evaluate the correlation between the TyG index and muscle strength, a range of analytical techniques was employed, including linear regression models, logistic regression models, and restricted cubic spline (RCS) analyses. A reduction in relative HGS was observed in the high TyG population compared to the low TyG population, whereas no such reduction was observed for absolute HGS. Regression analyses revealed a significant negative correlation between TyG and relative HGS, after controlling for a range of potential confounding variables. Conversely, no such relationship was observed between TyG and absolute HGS. The RCS results indicated that no nonlinear relationship existed between TyG and absolute HGS. In Chinese middle-aged and older adults, a negative correlation was observed between the TyG index and relative HGS, but not absolute HGS, in individuals without comorbid chronic diseases.
Keywords: Handgrip strength, Triglyceride-glucose index, Insulin resistance, Aging
Subject terms: Endocrinology, Health care
Introduction
China is the most populous country in the world and is also one of the countries with the fastest ageing population. The process of ageing is currently one of the most significant public health concerns in China, with the country’s older adults exceeding the combined adult population of all European countries1. As the proportion of the population comprising middle-aged and older adults increases, so too does the incidence of diseases associated with this demographic, including osteoporosis, fractures and falls. This represents a significant public health concern, particularly given the potential for these conditions to impair the health and well-being of middle-aged and older adults. The pervasive occurrence of nutritional deficiencies, including low body weight, anaemia and nutrient deficiencies , among the older adults is associated with an increased risk of frailty and falls. Furthermore, the decline in muscle strength that occurs during the aging process has been linked to an increased risk of developing frailty, experiencing functional decline, and ultimately dying from any cause2,3.
Handgrip strength (HGS) is a well-established physical fitness parameter and is regarded as an accessible predictor of health outcomes4. It has been demonstrated that diminished HGS is associated with an elevated risk of mortality, and can be utilized as an independent predictor of mortality risk5,6. A substantial body of recent research has demonstrated a robust correlation between low HGS and cognitive decline, as well as the onset of depression7–9. Among the numerous factors influencing HGS, metabolic syndrome represents a significant and noteworthy element. A number of recent studies have demonstrated an association between reduced HGS and an increased incidence of metabolic syndrome10–12. Insulin resistance (IR) is a pivotal factor in the development of the metabolic syndrome, as muscle function is contingent upon glucose metabolism. Consequently, IR impairs the ability of muscles to process glucose, leading to diminished muscle strength and reduced HGS13,14.
The triglyceride glucose (TyG) index is now acknowledged as a reliable and straightforward indicator of insulin resistance. Previous studies have demonstrated an inverse relationship between the TyG index and handgrip strength, as well as a positive correlation with sarcopenia, in middle-aged and older adults13,15,16. It has been established that a variety of chronic diseases have the capacity to influence muscular strength. This is the case with pathologies including, but not limited to, diabetes and cerebrovascular accidents. Previous studies, however, have failed to entirely rule out the impact of these underlying chronic diseases on muscle strength. Furthermore, the presence of reduced muscle strength in middle-aged and older adults has been identified as a significant risk factor for the occurrence of falls. Consequently, it is imperative to investigate potential risk factors for diminished muscle strength in middle-aged and elderly populations without chronic diseases. Further investigation is required to elucidate the relationship between the TyG index and handgrip strength in middle-aged and older adults without chronic diseases, and to ascertain its potential as a predictor of reduced handgrip strength. Accordingly, the present study included middle-aged and older adults without chronic diseases with the objective of exploring the relationship between the TyG index and handgrip strength, as well as providing feasible clinical ideas for the health status of this population.
Materials and methods
Study population
The data for this study were derived from the China Health and Retirement Longitudinal Study (CHARLS), a nationally representative survey conducted by the National Development Research Institute of Peking University. CHARLS employs a multi-stage probability sampling methodology to obtain a representative sample from a large population. In this study, the results of the 2015 survey were utilised. Among the population aged 45 and above, 2086 participants free of comorbid chronic diseases were ultimately included in the subsequent analysis, in accordance with the nadir exclusion criteria. These exclusion criteria encompassed the following: (1) comorbidities of various chronic diseases, including but not limited to heart disease, hypertension, and diabetes; (2) the absence of the primary study variables; and (3) the lack of grip strength data.
Baseline data collection
Information pertaining to demographic characteristics, encompassing gender, age, educational attainment, smoking habits and alcohol consumption, was collated. A range of physical measurements was also obtained, including systolic blood pressure (SBP), diastolic blood pressure (DBP), pulse rate, body weight, waist circumference (WC) and body mass index (BMI). Furthermore, a series of haematological parameters were evaluated, including fasting blood glucose (FBG), serum creatinine (SCr), total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and glycated haemoglobin (HbA1c), as well as uric acid (UA). The TyG index is calculated using serum TG and FBG levels.
Handgrip strength
The assessment of left-handed handgrip strength (LHGS) and right-handed handgrip strength (RHGS) was conducted utilising a hydraulic grip strength gauge. Each subject’s hands were measured on two occasions, and the largest value was used for the final analysis. Considering the effect of body weight on HGS, we calculated relative HGS, both the ratio of HGS to body weight and the ratio of HGS to BMI. LHGS per weight (LHGS/W) is calculated as LHGS/W = LHGS (kg)/weight (kg). RHGS per weight (RHGS/W) is calculated as RHGS/W = RHGS (kg)/weight (kg). LHGS per BMI (LHGS/BMI) is calculated as LHGS/BMI = LHGS (kg)/BMI (kg/m2). RHGS per BMI (RHGS/BMI) is calculated as RHGS/BMI = RHGS (kg)/BMI (kg/m2).
Statistical analysis
All data were subjected to statistical analysis using the R 4.2 software. Continuous variables are expressed as mean ± standard deviation or median (interquartile range). Categorical variables are expressed as a percentage. Comparisons between two groups were made using the appropriate statistical test, namely the t-test, Mann–Whitney U-test, or chi-square test, in order to determine between-group variability, depending on the data. Univariate and multivariate binary logistic regression and linear regression models were employed to investigate potential correlations between different variables. A restricted cubic spline (RCS) was employed to evaluate the existence of non-linear relationships between variables.
Results
Basic clinical characteristics of all populations
In accordance with the study design, the study population comprised 2086 participants who did not have chronic diseases (Fig. 1). The total population was comprised of 59.72% males and the mean age was 59.2 years. The remaining basic clinical data and handgrip strength information are presented in the table (Table 1).
Fig. 1.
Flowchart of the population included in our study. TyG index: triglyceride-glucose; BMI, body mass index.
Table 1.
Baseline characteristics of study populations. TyG index Triglyceride-glucose index; SBP Systolic blood pressure; DBP Diastolic blood pressure; WC Waist circumference; BMI Body mass index; BUN Urea nitrogen; FBG Fasting blood glucose; Scr Scrum creatinine; LDL-C Low-density lipoprotein cholesterol; TG Triglyceride; HDL-C High-density lipoprotein cholesterol; TC Total cholesterol; UA Uric acid; LHGS Left-handed handgrip strength; LHGS/W Left-handed handgrip strength/Weight; RHGS Right-handed handgrip strength; RHGS/W Right-handed handgrip strength/Weight.
| Variables | Total (n = 2086) | Low TyG (n = 1043) | High TyG (n = 1043) | P |
|---|---|---|---|---|
| Male (%) | 1058 (50.72) | 486 (46.60) | 572 (54.84) | < 0.001 |
| Age (y) | 59.20 ± 9.58 | 59.77 ± 10.05 | 58.63 ± 9.04 | 0.007 |
| Drinking (%) | 966 (46.46) | 509 (48.94) | 457 (43.98) | 0.023 |
| Smoking (%) | 905 (43.41) | 490 (47.02) | 415 (39.79) | < 0.001 |
| SBP (mmHg) | 124.34 ± 18.05 | 122.68 ± 17.94 | 126.00 ± 18.03 | < 0.001 |
| DBP (mmHg) | 74.33 ± 11.30 | 73.10 ± 10.82 | 75.57 ± 11.64 | < 0.001 |
| Pulse (/min) | 73.52 ± 10.00 | 72.00 ± 9.79 | 75.05 ± 9.98 | < 0.001 |
| Weight (KG) | 59.01 ± 10.20 | 56.69 ± 9.00 | 61.33 ± 10.79 | < 0.001 |
| WC (cm) | 84.25 ± 11.30 | 81.16 ± 10.85 | 87.33 ± 10.89 | < 0.001 |
| BMI (kg/m2) | 23.39 ± 3.25 | 22.47 ± 2.98 | 24.32 ± 3.25 | < 0.001 |
| BUN (mg/dl) | 15.44 ± 4.57 | 15.81 ± 4.80 | 15.07 ± 4.30 | < 0.001 |
| FBG (mg/dl) | 98.94 ± 24.80 | 91.04 ± 11.58 | 106.85 ± 31.17 | < 0.001 |
| Scr (mg/dl) | 0.78 ± 0.21 | 0.79 ± 0.20 | 0.78 ± 0.22 | 0.283 |
| TC (mg/dl) | 182.16 ± 35.33 | 172.65 ± 31.31 | 191.68 ± 36.56 | < 0.001 |
| TG (mg/dl) | 131.39 ± 85.05 | 78.02 ± 19.12 | 184.76 ± 91.70 | < 0.001 |
| HDL-C (mg/dl) | 52.22 ± 11.50 | 55.49 ± 12.13 | 48.96 ± 9.81 | < 0.001 |
| LDL-C (mg/dl) | 101.61 ± 28.28 | 97.77 ± 25.99 | 105.46 ± 29.92 | < 0.001 |
| HbA1c (%) | 5.82 ± 0.71 | 5.70 ± 0.43 | 5.93 ± 0.89 | < 0.001 |
| UA (mg/dl) | 4.79 ± 1.34 | 4.60 ± 1.28 | 4.97 ± 1.38 | < 0.001 |
| Aducation (%) | 0.428 | |||
| Illiterate | 846 (40.56) | 431 (41.32) | 415 (39.79) | |
| Primary School | 459 (22.00) | 225 (21.57) | 234 (22.44) | |
| Middle school | 521 (24.98) | 268 (25.70) | 253 (24.26) | |
| High school and above | 260 (12.46) | 119 (11.41) | 141 (13.52) | |
| LHGS | 30.31 ± 9.04 | 30.50 ± 8.73 | 30.12 ± 9.34 | 0.342 |
| LHGS/BMI | 1.31 ± 0.41 | 1.37 ± 0.42 | 1.25 ± 0.40 | < 0.001 |
| LHGS/W | 0.52 ± 0.14 | 0.54 ± 0.14 | 0.49 ± 0.13 | < 0.001 |
| RHGS | 31.74 ± 9.50 | 31.78 ± 9.14 | 31.70 ± 9.85 | 0.849 |
| RHGS/BMI | 1.38 ± 0.43 | 1.43 ± 0.43 | 1.32 ± 0.42 | < 0.001 |
| RHGS/W | 0.54 ± 0.14 | 0.56 ± 0.14 | 0.52 ± 0.14 | < 0.001 |
Comparison of basic clinical characteristics and handgrip strength between low TyG and high TyG groups
The TyG index was employed to categorise all participants, yielding a high TyG group and a low TyG group comprising 1,043 individuals each. The median TyG value was used as a reference point for this division. A comparison of the two groups revealed that participants in the high TyG group exhibited a higher proportion of males, elevated blood pressure, heart rate, weight, WC and BMI, in addition to elevated FBG, HbA1c and UA (Table 1). With regard to lipid indices, the high TyG group exhibited elevated levels of LDL-C, TG and TC, while the low TyG group demonstrated lower levels of HDL-C (Table 1). Nevertheless, certain indicators are elevated in the low TyG cohort relative to the high TyG cohort, including age, the prevalence of smoking, the prevalence of alcohol consumption, and BUN (Table 1). No significant difference was observed between the two groups with regard to handgrip strength whether measured in a left-handed or right-handed manner (Table 1). However, when adjusted for weight or BMI, the high TyG group exhibited significantly reduced handgrip strength (Table 1).
Multivariate linear regression analysis between TyG index and handgrip strength
To further examine the independent correlation between the TyG index and handgrip strength, a multivariate regression analysis was conducted. The results of the study demonstrated that the inverse correlations between the TyG index and the LHGS/BMI, LHGS/W, RHGS/BMI, and RHGS/W indices persisted in Models 1–3, even after correction for several confounding variables (Table 2).
Table 2.
Multivariate linear regression analyses of TyG index in all populations.
| Model 1 | Model 2 | Model 3 | |||||||
|---|---|---|---|---|---|---|---|---|---|
| P | β (95%CI) | R2 | P | β (95%CI) | R2 | P | β (95%CI) | R2 | |
| LHGS/BMI | < 0.001 | − 0.08 | 0.82 | < 0.001 | − 0.11 | 0.80 | < 0.001 | − 0.10 | 0.83 |
| ( − 0.11 to − 0.05) | ( − 0.14 to − 0.08) | ( − 0.13 to − 0.06) | |||||||
| LHGS/W | < 0.001 | − 0.03 | 0.85 | < 0.001 | − 0.04 | 0.92 | < 0.001 | − 0.04 | 0.91 |
| ( − 0.04 to − 0.02) | ( − 0.05 to − 0.03) | ( − 0.05 to − 0.02) | |||||||
| RHGS/BMI | < 0.001 | − 0.07 | 0.86 | < 0.001 | − 0.10 | 0.76 | < 0.001 | − 0.07 | 0.79 |
| ( − 0.10 to − 0.04) | ( − 0.13 to − 0.07) | ( − 0.11 to − 0.03) | |||||||
| RHGS/W | < 0.001 | − 0.03 | 0.82 | < 0.001 | − 0.04 | 0.89 | < 0.001 | − 0.03 | 0.85 |
| ( − 0.04 to − 0.02) | ( − 0.05 to − 0.03) | ( − 0.04 to − 0.01) | |||||||
Model 1: Crude.
Model 2: Adjusted for age, SBP, DBP, Pulse.
Model 3: Model 2 + adjustment for BUN, Scr, TC, HDL-C, LDL-C, UA, Sex, Smoking, Drinking, Aducation.
TyG index Triglyceride-glucose index; BMI Body mass index; SBP Systolic blood pressure; DBP Diastolic blood pressure; BUN Urea nitrogen; Scr Scrum creatinine; LDL-C low-density lipoprotein cholesterol; HDL-C High-density lipoprotein cholesterol; TC Total cholesterol; UA Uric acid; LHGS Left-handed handgrip strength; LHGS/W Left-handed handgrip strength/Weight; RHGS Right-handed handgrip strength; RHGS/W Right-handed handgrip strength/Weight.
Subgroup analysis between TyG index and handgrip strength
Subgroup analyses were conducted to gain a deeper understanding of the independent correlation between the TyG index and grip strength. The relationship between TyG index and muscle strength between different subgroups was explored by subgrouping the median LHGS/BMI, LHGS/W, RHGS/BMI and RHGS/W. The relationship between TyG index and muscle strength between different subgroups was investigated in a univariate subgroup analysis. In univariate subgroup analyses, no significant correlations were found between the variables of gender, smoking, alcohol consumption and education and the dependent variables LHGS/BMI, LHGS/W and RHGS/W, nor were there any correlations after applying multiple confounders in the corrected model (Figs. 2 and 3). As for RHGS/BMI, the relationship between TyG index and RHGS/BMI was stronger in males and non-smokers (Figs. 2 and 3).
Fig. 2.
Univariate subgroup analysis between TyG index and handgrip strength. (A) LHGS/BMI. (B) LHGS/W. (C) RHGS/BMI. (D) RHGS/W. Educational attainment levels 1, 2, 3 and 4 represent Illiterate, Primary School, Middle school and High school and above respectively. Abbreviations: TyG index: triglyceride-glucose index; BMI, body mass index; LHGS: Left-handed handgrip strength; LHGS/W: Left-handed handgrip strength/Weight; RHGS: Right-handed handgrip strength; RHGS/W: Right-handed handgrip strength/Weight.
Fig. 3.
Multivariate subgroup analysis between TyG index and handgrip strength. (A) LHGS/BMI. (B) LHGS/W. (C) RHGS/BMI. (D) RHGS/W. Educational attainment levels 1, 2, 3 and 4 represent Illiterate, Primary School, Middle school and High school and above respectively.: TyG index Triglyceride-glucose index; BMI Body mass index; LHGS Left-handed handgrip strength; LHGS/W Left-handed handgrip strength/Weight; RHGS Right-handed handgrip strength; RHGS/W Right-handed handgrip strength/Weight.
Multivariate logistic regression analysis of TyG index and handgrip strength
In multivariate logistic regression analyses, LHGS/BMI median, LHGS/W median, RHGS/BMI median, and RHGS /W median were grouped according to and were used as dependent variables, while TyG index was used as a linear independent variable. The results showed that a significant negative association was observed between TyG index and LHGS/BMI, LHGS/W, RHGS/BMI and RHGS /W, despite correction for potential confounders such as age, SBP, DBP, pulse, BUN, Scr, TC, HDL-C, LDL-C, UA, sex, smoking, alcohol consumption and education (Table 3).
Table 3.
Multivariate logistic regression analyses of TyG index in all populations.
| Model 1 | Model 2 | Model 3 | ||||
|---|---|---|---|---|---|---|
| P | OR (95% CI) | P | OR (95% CI) | P | OR (95% CI) | |
| LHGS/BMI | < 0.001 | 0.75 (0.65–0.87) | < 0.001 | 0.67 (0.57–0.78) | < 0.001 | 0.46 (0.33–0.65) |
| LHGS/W | < 0.001 | 0.67 (0.58–0.78) | < 0.001 | 0.61 (0.52–0.72) | < 0.001 | 0.52 (0.39–0.70) |
| RHGS/BMI | < 0.001 | 0.76 (0.66–0.88) | < 0.001 | 0.69 (0.59–0.80) | 0.013 | 0.66 (0.47–0.92) |
| RHGS/W | < 0.001 | 0.72 (0.62–0.84) | < 0.001 | 0.66 (0.56–0.77) | 0.001 | 0.61 (0.46–0.82) |
Model 1: Crude.
Model 2: Adjusted for age, SBP, DBP, Pulse.
Model 3: Model 2 + adjustment for BUN, Scr, TC, HDL-C, LDL-C, UA, Sex, Smoking, Drinking, Aducation.
TyG index: Triglyceride-glucose index; BMI Body mass index; SBP Systolic blood pressure; DBP Diastolic blood pressure; BUN Urea nitrogen; Scr Scrum creatinine; LDL-C Low-density lipoprotein cholesterol; HDL-C High-density lipoprotein cholesterol; TC Total cholesterol; UA Uric acid; LHGS Left-handed handgrip strength; LHGS/W Left-handed handgrip strength/Weight; RHGS Right-handed handgrip strength; RHGS/W Right-handed handgrip strength/Weight.
Nonlinear relationship analysis between TyG index and handgrip strength
Given the absence of a correlation between the TyG index and both the LHGS and RHGS in the linear regression analyses, it is evident that further investigation into the potential existence of a non-linear relationship is warranted. In the restricted cubic spline analysis, a nonlinear relationship was observed between TyG and LHGS and RHGS at the univariate level in both linear and logistic regression models (Figs. 4 and 5). However, this nonlinear correlation was not evident in the multivariate analysis (Figs. 4 and 5).
Fig. 4.
Non-linear correlation analysis between LHGS and TyG index. (A) Univariate non-linear correlation analysis based on linear regression between LHGS and TyG index. (B) Multivariate non-linear correlation analysis based on linear regression between LHGS and TyG index. (C) Univariate non-linear correlation analysis based on logistic regression between LHGS and TyG index. (D) Multivariate non-linear correlation analysis based on logistic regression between LHGS and TyG index. TyG index Triglyceride-glucose index; LHGS Left-handed handgrip strength.
Fig. 5.
Non-linear correlation analysis between RHGS and TyG index. (A) Univariate non-linear correlation analysis based on linear regression between RHGS and TyG index. (B) Multivariate non-linear correlation analysis based on linear regression between RHGS and TyG index. (C) Univariate non-linear correlation analysis based on logistic regression between RHGS and TyG index. (D) Multivariate non-linear correlation analysis based on logistic regression between RHGS and TyG index. TyG index Triglyceride-glucose index; RHGS Right-handed handgrip strength.
Discussion
This study was the inaugural investigation into the relationship between the TyG index and HGS in a Chinese middle-aged and older adults devoid of chronic diseases. The findings of the study demonstrated the absence of a statistically significant linear and non-linear correlation between the TyG index and absolute HGS. However, a notable negative correlation was observed between the TyG index and relative HGS, with the inclusion of body weight and BMI as confounding variables.
HGS is a commonly used measure of muscle strength. It is a non-invasive method that is relatively inexpensive, indicates overall muscle strength, and is a reliable indicator of neuromuscular integrity and muscle function. A reduction in HGS is associated with a range of adverse health outcomes, including chronic disease, functional impairment, falls, fractures, cognitive decline and all-cause mortality17–20. Furthermore, greater discrepancies in two-handed HGS have been demonstrated to be linked to a range of adverse health outcomes, including depression, anxiety, and cognitive impairment21,22. The present study did not find a significant correlation between the TyG index and either LHGS or RHGS. However, a weak non-linear correlation was identified in the RCS analyses, which disappeared after correction for several confounders. It is evident that although this correlation was not observed in the present study, previous studies have demonstrated that a high insulin resistance status is strongly associated with reduced HGS23. This result may be attributed to the fact that the population included in this study was a relatively healthy middle-aged and older adults, free of various chronic diseases. It has been demonstrated that lower levels of insulin resistance are associated with this type of population.
Prior research has demonstrated that body weight is the primary determinant of HGS. Furthermore, studies have indicated that relative HGS, adjusted for body weight or BMI, is more strongly associated with adverse health outcomes than absolute HGS, which is the actual strength of the handgrip muscles24,25. The utilisation of absolute HGS may introduce a potential bias in comparison to relative HGS, which takes into account weight-related confounding factors. It is therefore recommended that the associated health status be predicted by assessing relative HGS rather than absolute HGS in Chinese middle-aged and older adults. After correcting for body weight or BMI, the present study found that LHGS/BMI, LHGS/W, RHGS/BMI, and RHGS/W were significantly lower in the high-TyG index population, suggesting a decrease in muscle strength in the high-TyG population. After correction for multiple confounding variables, the correlations between the TyG index and LHGS/BMI, LHGS/W, RHGS/BMI, and RHGS/W remained, whereas the correlations with LHGS and RHGS were no longer statistically significant.
It has been demonstrated that IR is associated with reduced skeletal muscle strength, and that resistance training can enhance IR levels26,27. A reduction in HGS in non-diabetic populations has been linked to elevated IR levels. This association has also been observed in adolescent populations28,29. Nevertheless, the question of whether there is an association between HGS and IR in middle-aged and older adults without chronic diseases remains unanswered. The TyG index, which has been the subject of extensive recent research as an indicator of IR, is more suitable for clinical practice due to its simplicity. Furthermore, the correlation between the TyG index and HGS has not been reported in any relevant studies. The aim of this study was to explore the relationship between the TyG index and both absolute and relative HGS. Although no significant correlation was observed between the TyG index and LHGS and RGHS, this may be attributed to the fact that the population included in the present study did not have comorbid chronic diseases. However, a significant negative correlation was found between the TyG index and LHGS/BMI, LHGS/W, RHGS/BMI, and RHGS/W, which remained significant after adjusting for numerous potential confounding factors.
The reduced grip strength to BMI ratio is indicative of insufficient muscle mass or excess fat, which can trigger insulin resistance through multiple mechanisms30–32. Firstly, muscle, as a major organ of glucose metabolism, decreases glucose uptake and oxidation, and secondly, intramuscular lipid deposition inhibits insulin signalling. Thirdly, visceral fat accumulation accompanied by elevated BMI releases pro-inflammatory factors and free fatty acids, which trigger lipotoxicity and inhibit insulin sensitivity. Finally, chronic inflammation and oxidative stress also interfere with insulin signalling pathways. Furthermore, the presence of chronic inflammation and oxidative stress has been demonstrated to interfere with the insulin signalling pathway. In addition, the vicious circle of hormonal regulation, such as reduced lipocalin secretion and reduced physical activity, has been shown to exacerbate systemic insulin resistance. Consequently, the aforementioned findings can elucidate the correlation between TyG index and grip strength in this study.
The present study is characterised by a number of key strengths. Firstly, the data presented in this study are derived from a large sample size, obtained from a national longitudinal survey involving middle-aged and older Chinese individuals. Secondly, this is the inaugural study to investigate the correlation between the TyG index and relative HGS in middle-aged and older adults without concomitant chronic illnesses. Ultimately, the findings indicate that relative HGS is a more clinically significant measure than absolute HGS in this population. These findings have significant implications for the screening and early identification of high-risk groups. It is essential to consider the constraints of the study design when analysing the findings of our study. Firstly, as this was a cross-sectional study, it was not possible to determine the direction of causal relationships between variables. Secondly, the study was conducted with a sample of Chinese participants only, and thus the findings may not be generalisable to other ethnic populations. Ultimately, despite the consideration of a multitude of potential influencing factors, it is important to acknowledge that dietary habits, exercise status, and medications also have an impact on HGS. However, these factors were not excluded from the study.
Conclusion
In conclusion, the present study, which used data from CHARLS, explored the existence of a negative correlation between the TyG index and relative HGS in a middle-aged and older population without comorbid chronic diseases. However, no such correlation was identified in absolute HGS. Therefore, for this population, the calculation of a simple TyG index is beneficial for the early detection of declining muscle strength, thus enabling the implementation of appropriate interventions to prevent multiple complications and promote healthy ageing.
Acknowledgements
We thank all participants of the CHARLS in this study.
Author contributions
All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by X.P., X.Z., A.G., and X.H. The first draft of the manuscript was written by X.P. Writing (review and editing) was performed by T.P.; all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
Funding
This work was supported by Clinical and Translational Research Project of Anhui Province (S202427b10025004).
Data availability
No datasets were generated or analysed during the current study.
Declarations
Competing interests
The authors declare no competing interests.
Ethics approval
The original survey protocol was approved by the Institutional Review Board of the National Center of Heath Statistics. All participants signed informed consent forms. The present study was deemed exempt by the Institutional Review Board of our center.
Consent for publication
All authors read the manuscript and agreed toits publication.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
No datasets were generated or analysed during the current study.