The Mediating Role of Cognitive Function in the Association between Grip Strength and Depression among Chinese middle-aged and elderly adults: A Cross-Sectional Study

The Mediating Role of Cognitive Function in the Association between Grip Strength and Depression among Chinese middle-aged and elderly adults: A Cross-Sectional Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Mediating Role of Cognitive Function in the Association between Grip Strength and Depression among Chinese middle-aged and elderly adults: A Cross-Sectional Study Xinzheng Wang, Guohao Yi, Lifei Wu, Huifen Zhou, Jiandong He This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4207923/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective This study investigates the associations and mediating pathways between grip strength, cognitive function, and depression in middle-aged and elderly individuals in China. Methods Utilizing data from the 2011 China Health and Retirement Longitudinal Study (CHARLS), we employed logistic regression and mediation analysis to examine the relationships and mediating factors between grip strength, cognitive function, and depression, while adjusting for potential confounders. Results The study included 6,841 participants, of whom 1,734 (25.35%) exhibited symptoms of depression. Our findings indicate that weak grip strength is significantly associated with an increased risk of depression (OR: 1.57, 95% CI: 1.32–1.87) among the middle-aged and elderly population. Conversely, good cognitive function was found to be protective against depression (OR: 0.94, 95% CI: 0.93–0.95). The analysis revealed that grip strength indirectly affects depression through cognitive function, accounting for 9.4% of the total effect (OR: −0.008, 95% CI: -0.013, − 0.004). Specifically, cognitive abilities such as calculation, memory, and orientation were identified as significant mediators in the relationship between grip strength and depression. Conclusion This study highlights that adequate cognitive function can mitigate the association between weak grip strength and an increased risk of depression among middle-aged and elderly individuals in China. These insights provide valuable guidance for clinical practitioners in the diagnosis and management of depression, emphasizing the importance of assessing grip strength and cognitive function. Grip Strength Cognitive Function Depression Mediation analysis Figures Figure 1 Introduction Depression is a significant mental health concern and is increasingly recognized as a leading cause of disabling mental disorders worldwide [ 1 ]. The World Health Organization has predicted that by 2030, depression will become one of the most impactful global health issues [ 2 ]. In China, which is undergoing rapid population aging, more than 54 million individuals are affected by depression, as reported by the World Health Organization [ 3 ]. The prevalence of depression is particularly high among the middle-aged and elderly, those aged 45 and above [ 4 ], with a detection rate of 20.6% in the population over 60 years old [ 5 ]. Moreover, the incidence of depression increases with age [ 6 ]. Depression not only significantly impairs the quality of life of affected individuals [ 7 ] but also increases the risks of suicide [ 8 ], type 2 diabetes [ 9 ], cardiovascular diseases, and overall mortality [ 10 ]. Therefore, understanding the etiology and pathophysiology of depression, particularly in the middle-aged and elderly population in China, is of great public health importance. However, our understanding of depression is still incomplete, and more effective treatment methods are needed [ 11 ]. Identifying risk factors for depression and implementing effective interventions and management strategies are therefore crucial. Among various factors associated with depression, the impact of weak grip strength on depressive symptoms has recently gained attention ([ 12 ][ 13 ][ 14 ]). However, research data on the correlation between grip strength and depression in elderly populations are limited, and the nature of this association remains unclear. Studies by Zhang F[ 15 ] and Brooks JM[ 16 ], using data from the China Health and Retirement Longitudinal Study (CHARLS) and the National Health and Nutrition Examination Survey (NHANES), suggest a negative correlation between grip strength and depression, after adjusting for confounding factors. Conversely, Zhang XM[ 17 ] found in a cross-sectional study that the risk of depression decreased with increasing grip strength, but the association was not significant when handgrip strength (HGS) exceeded 36.5 kg. In contrast, studies by Stessman J[ 18 ] and Taekema DG[ 19 ] observed a weak or non-existent predictive role of declining grip strength in the onset of depression in older adults. This suggests that the relationship between muscle strength and depression may be influenced by the psychological adaptation process during aging. It is therefore essential to understand the association between grip strength levels and depression among middle-aged and elderly individuals in China to inform the development of intervention measures. Additionally, recent evidence suggests a strong association between cognitive function and depressive symptoms, with better cognitive states in older individuals linked to good emotional states ([ 20 ][ 21 ]). Studies by Ferri F[ 22 ] and Christensen GT[ 23 ] have shown that cognitive impairments in executive function, memory, and attention are common in individuals with depression, and that alleviating these cognitive deficits can contribute to improving depression symptoms. Moreover, research has shown a connection between grip strength and cognitive function [ 24 ]. A study in rural China found that lower handgrip strength (HGS) and HGS asymmetry are independently associated with lower cognitive function [ 25 ], and studies by Firth J[ 26 ] indicate a significant correlation between higher grip strength in older individuals and better cognitive performance [ 27 ]. However, the association between grip strength and cognitive function in the elderly has not reached a consensus. Cui M[ 28 ] reported that in older adults, grip strength is positively correlated with recall and memory performance but not with general cognitive function. In contrast, some studies have found no relationship between grip strength and cognitive dysfunction ([ 29 ][ 30 ]). This discrepancy may be due to the complexity of motor function and needs further investigation. Our study aims to explore the potential mediating pathways between grip strength, cognitive function, and depression in middle-aged and elderly Chinese adults using data from the China Health and Retirement Longitudinal Study (CHARLS). Materials and Methods Data Source This study is based on data from the China Health and Retirement Longitudinal Survey (CHARLS). CHARLS conducted a comprehensive baseline survey across the nation utilizing a probability-proportional-to-size (PPS) sampling method. This extensive survey gathered a wide array of information, including respondents' basic demographic details, their family's data, and insights into their education, employment, income, marital status, and health status. In addition, CHARLS incorporated an extensive set of 13 physical measurements and also undertook blood sample collection. Each stage of this survey was subject to stringent quality control measures, establishing CHARLS as a vital and authoritative source for investigating the array of health issues facing China's elderly population. The data from this extensive survey is publicly available and can be accessed at http://charls.pku.edu.cn . The CHARLS project was conducted with full approval from the Peking University Biomedical Ethics Committee (IRB0000001052-11015), ensuring ethical compliance, and informed consent was duly obtained from all individuals who participated in the survey [ 31 ]. For this particular study, we used the data from the 2011 CHARLS survey, which originally consisted of 17,708 participants. We had to exclude some participants from our analysis due to missing data in key areas such as grip strength, cognitive function (which included aspects like orientation, memory, calculation abilities, and drawing skills), and depression scores. Additionally, we also excluded participants who had missing values in covariate data crucial for our sample analysis. After applying these exclusion criteria, our study eventually included data from 6,841 participants, which was sufficient for a robust analysis (Fig. 1 ). Variable Selection Demographic Characteristics The demographic characteristics of the survey participants were meticulously extracted from two specific modules of the CHARLS follow-up questionnaire: the "Basic Information" module and the "Family" module. This extraction process yielded vital information such as the participants' gender, age, marital status, and their level of educational attainment. Grip Strength The measurement of grip strength was conducted using a specialized isometric dynamometer (YuejianTM WL-1000, Nantong, China) [ 32 ]. Participants were instructed to perform this test while standing, using either their dominant or non-dominant hand, based on their preference. They were required to keep their elbow positioned at a precise right angle (90°) and then exert force by squeezing the handle of the dynamometer for several seconds. This process was repeated to allow two measurements for both the right and left hands, and the highest value recorded in kilograms was used for analysis. We then categorized grip strength based on gender and body mass index [ 33 ], employing a binary scale where 0 indicated a normal grip strength level, and 1 indicated a comparatively weak grip strength, as detailed in Supplementary File 2: Table S1 . Cognitive Function Cognitive function was evaluated based on the methodology employed in the American Health and Retirement Study (HRS) [ 34 ]. This comprehensive assessment involved evaluating four key dimensions of cognitive function: orientation, calculation, memory, and drawing ability. The orientation assessment involved questions about the current year, month, day, day of the week, and the season, with each correct answer scoring 1 point, making a total possible score of 5 points. The calculation dimension required participants to perform serial subtractions, starting from 100 and subtracting 7 each time, up to five iterations. Each successful subtraction earned them 1 point. The memory assessment involved presenting ten random words to each participant, with their immediate recall capacity being evaluated based on the number of words they could immediately recollect. Following this, the participants completed the depression scale survey, after which their calculation and drawing abilities were tested. An assessment of delayed word recall was then conducted. The total memory score was a combination of both immediate and delayed word recall, with each correctly recalled word earning 1 point. The drawing test involved presenting participants with a picture of two overlapping pentagons, which they were then asked to replicate accurately. Successful replication earned the participant 1 point. The total score for cognitive function was thus calculated as the sum of scores from these four dimensions: orientation (5 points), calculation (5 points), memory (20 points), and drawing (1 point), giving a total possible score of 31 points. The scoring criteria followed for this assessment were aligned with the methodology used in the American Health and Retirement Study [ 35 ]. Depression The assessment of depression was carried out using the 10-item Center for Epidemiologic Studies Depression Scale (CES-D). Each item on this scale was rated on a frequency scale ranging from 0 to 3 [ 36 ]. The scale's specifics were as follows: 0 was used to indicate rare or no occurrence of a symptom (less than 1 day per week), 1 indicated the symptom occurred some or a little of the time (1–2 days per week), 2 was used for occasions or a moderate amount of the time (3–4 days per week), and 3 indicated the symptom was present all of the time (5–7 days per week). On this scale, the occurrence of positive emotions or behaviors was scored in a reverse manner. The scores of all 10 items were summed to obtain a total score, which ranged from 0 to 30, with higher scores indicating more severe symptoms of depression. Individuals who had a CES-D score of 10 or higher were considered to be participants with depressive symptoms. Covariates This study included a range of additional covariates, such as age, follow-up time, education level, smoking habits, alcohol consumption, body mass index (BMI), hypertension, fall-related injuries, lipid abnormalities, diabetes or elevated blood sugar, cancer or malignant tumors, heart disease, stroke, nearsightedness and farsightedness, injuries, hearing issues, memory-related disorders, etc. Categories like hearing, vision, and life satisfaction were divided into three levels: "poor, moderate, good." Marital status was categorized as married (living with a spouse) or unmarried (separated, divorced, widowed, or never married). Permanent residence was classified as urban or rural. Other variables were dichotomized into a simple "yes or no" format. Statistical Analysis The characteristics of the sample were thoroughly measured and subjected to a descriptive analysis. To identify differences between groups with and without depressive symptoms at baseline, variance t-tests were employed for numerical variables, and chi-square tests were used for categorical variables. The variables are presented in different formats for clarity: continuous variables are shown as medians, with the interquartile range (25%-75%) in parentheses, while categorical variables are expressed as counts (percentages). To determine the associations between grip strength groups, cognitive function, and depressive symptoms, both binary logistic regression and multiple linear regression analyses were employed. These analyses produced effect estimates and 95% confidence intervals (CI). Three distinct models were introduced for this purpose: Model 1, which was unadjusted; Model 2, which was adjusted for Gender, Age, BMI; and Model 3, which was adjusted for the variables in Model 2, as well as additional factors like Education, Permanent address, Marital status, Hypertension, Dyslipidemia, Diabetes, Psychiatric problems, Smoking, and Alcohol consumption. Additionally, Pearson correlation analysis was conducted to examine the relationships between the variables involved in this study. Mediation analysis was a significant component of this module, and it was performed using the Mediation package available in R. The bootstrap method was employed to estimate confidence intervals for the mediation effects. The significance of these mediation effects was determined based on whether the confidence interval included 0 (indicating non-significance) or did not include 0 (indicating significance). Furthermore, to assess the stability of results and examine gender and age differences in the associations between grip strength, cognitive function, and depressive symptoms, subgroup analyses of the binary logistic regression models were conducted, with these analyses being segmented by gender (male and female) and age groups (< 60 and ≥ 60). For all analyses conducted in this study, a significance level of P < 0.05 was considered statistically significant. The analytical processes were carried out using two software programs: SPSS 26.0 and R (version 4.2.2). Results Baseline Characteristics Analysis of the Sample Table 1 showcases the baseline characteristics of the participants from the China Health and Retirement Longitudinal Study (CHARLS) database. Among the 6,841 subjects included in this analysis, 1,734 individuals (25.35%) exhibited depressive symptoms. A total of 6,077 (88.8%) participants were classified in the normal grip strength group, while 764 (11.2%) fell into the weak grip strength group. The analysis revealed that participants who were female, lived in urban areas, were unmarried (widowed/separated/single), had lower educational levels, poor hearing, and poor vision, and belonged to the weak grip strength group, had a heightened risk of developing depressive symptoms (P < 0.001). Moreover, individuals with hypertension, diabetes, chronic lung diseases, kidney disease, digestive disease, and psychiatric problems also displayed an increased risk of depression (P < 0.05). Table 1 Characteristics of study participants stratified by depressive symptoms Variables Total NO-Depression Depression p N = 6841 N = 5107 N = 1734 Age 59.00 [52.00, 65.00] 59.00 [52.00, 65.00] 58.50 [51.00, 65.00] 0.545 Gender (%) < 0.001 Male 3682 (53.8) 2961 (58.0) 721 (41.6) Female 3159 (46.2) 2146 (42.0) 1013 (58.4) Grip strength (%) < 0.001 Normal 6077 (88.8) 4585 (89.8) 1492 (86.0) Weak 764 (11.2) 522 (10.2) 242 (14.0) Education (%) < 0.001 Junior high and below 5791 (84.7) 4246 ( 83.1) 1545 ( 89.1) high school and above 1050 (15.3) 861 ( 16.9) 189 ( 10.9) Permanent address (%) < 0.001 Urban 5073 (74.2) 3724 (72.9) 1349 (77.8) Rural 1768 (25.8) 1383 (27.1) 385 (22.2) Marital status (%) < 0.001 Married 721 (10.5) 468 (9.2) 253 (14.6) Unmarried 6120 (89.5) 4639 (90.8) 1481 (85.4) Smoking (%) < 0.001 NO 3842 (56.2) 2757 (54.0) 1085 (62.6) YES 2999 (43.8) 2350 (46.0) 649 (37.4) Alcohol consumption (%) < 0.001 NO 4363 (63.8) 3152 (61.7) 1211 (69.8) YES 2478 (36.2) 1955 (38.3) 523 (30.2) Hypertension (%) 1694 (24.8) 1215 (23.8) 479 (27.6) 0.002 Dyslipidemia (%) 706 (10.3) 519 (10.2) 187 (10.8) 0.49 Diabetes (%) 417 (6.1) 287 (5.6) 130 (7.5) 0.006 Cancer (%) 60 (0.9) 40 (0.8) 20 (1.2) 0.2 Chronic lung diseases (%) 676 (9.9) 441 (8.6) 235 (13.6) < 0.001 Liver disease (%) 280 (4.1) 193 (3.8) 87 (5.0) 0.029 Kidney disease (%) 417 (6.1) 273 (5.4) 144 (8.3) < 0.001 Digestive disease (%) 1478 (21.6) 971 (19.0) 507 (29.3) < 0.001 Psychiatric problems (%) 65 (1.0) 30 (0.6) 35 (2.0) < 0.001 Memory related disease (%) 69 (1.0) 43 (0.8) 26 (1.5) 0.026 Arthritis or rheumatism (%) 2115 (30.9) 1387 (27.2) 728 (42.0) < 0.001 Asthma (%) 253 (3.7) 156 (3.1) 97 (5.6) < 0.001 Nighttime sleep duration 6.00 [5.00, 7.50] 6.00 [5.00, 7.50] 6.00 [5.00, 7.00] 0.14 Poor sleep quality (%) < 0.001 Rarely or none of the time 3597 (52.6) 3247 (63.6) 350 (20.2) Some or a little of the time 1145 (16.7) 885 (17.3) 260 (15.0) Occasionally or a moderate amount of the time 917 (13.4) 506 (9.9) 411 (23.7) Most or all of the time 1182 (17.3) 469 (9.2) 713 (41.1) Hearing (%) < 0.001 Good 3292 (48.1) 2605 (51.0) 687 (39.6) Fair 2871 (42.0) 2083 (40.8) 788 (45.4) Poor 678 (9.9) 419 (8.2) 259 (14.9) Life satisfaction (%) < 0.001 Good 5872 (85.8) 4568 (89.4) 1304 (75.2) Fair 836 (12.2) 482 (9.4) 354 (20.4) Poor 133 (1.9) 57 (1.1) 76 (4.4) waistline 85.30 [78.40, 92.20] 86.00 [78.60, 92.60] 84.60 [78.00, 92.00] 0.003 BMI (median [IQR]) 23.44 [21.15, 25.99] 23.46 [21.20, 26.03] 23.32 [20.96, 25.89] 0.089 memory (median [IQR]) 8.00 [5.00, 10.00] 8.00 [5.00, 10.00] 7.00 [5.00, 9.00] < 0.001 orientation (median [IQR]) 5.00 [4.00, 5.00] 5.00 [4.00, 5.00] 4.00 [3.00, 5.00] < 0.001 computation (median [IQR]) 5.00 [1.00, 5.00] 5.00 [2.00, 5.00] 3.00 [1.00, 5.00] < 0.001 drawing (%) < 0.001 0 points 1683 (24.6) 1140 (22.3) 543 (31.3) 1 point 5158 (75.4) 3967 (77.7) 1191 (68.7) Vision (%) < 0.001 Good 3588 (52.7) 2815 (55.4) 773 (44.7) Fair 2693 (39.5) 1973 (38.8) 720 (41.6) Poor 529 (7.8) 292 (5.7) 237 (13.7) Cognitive function (median [IQR]) 16.00 [13.00, 19.00] 17.00 [13.00, 20.00] 15.00 [12.00, 18.00] < 0.001 Associations of Grip Strength and Cognitive Function with Depression Table 2 delineates the relationship between grip strength levels, cognitive function, and depression. After adjusting for various confounders, it was found that older adults in the weak grip strength group were more likely to develop depressive symptoms compared to those in the normal grip strength group (OR: 1.57, 95% CI: 1.32–1.87). Enhanced cognitive function (OR: 0.94, 95% CI: 0.93–0.95), along with better orientation (OR: 0.87, 95% CI: 0.83–0.93), memory (OR: 0.94, 95% CI: 0.92–0.95), computation (OR: 0.90, 95% CI: 0.87–0.93), and drawing abilities (OR: 0.93, 95% CI: 0.92–0.94), were identified as protective factors against depression. Table 2 Associations of grip strength and cognitive function with depression Variables Model1 Model2 Model3 P-value Grip strength <0.001 Normal 1 1 1 Weak 1.42(1.21–1.68) 1.61(1.35–1.91) 1.57(1.32–1.87) Cognitive Function 0.93(0.92–0.94) 0.93(0.92–0.94) 0.94(0.93–0.95) <0.001 Orientation 0.84(0.56–0.86) 0.85(0.81–0.90) 0.87(0.83–0.93) <0.001 Memory 0.93(0.92–0.94) 0.93(0.91–0.94) 0.94(0.92–0.95) <0.001 Computation 0.87(0.84–0.89) 0.89(0.86–0.91) 0.90(0.87–0.93) <0.001 Drawing <0.001 0 points 1 1 1 1 point 0.63(0.55–0.71) 0.68(0.60–0.77) 0.93(0.92–0.94) Model 1, unadjusted; Model 2, adjusted for Gender, Age, BMI; Model 3, adjusted for variables in Model 2 as well as Education, Permanent address, Marital status, Hypertension, Dyslipidemia, Diabetes, Psychiatric problems, Smoking, Alcohol consumption. The Bivariate Correlations for All Variables Table 3 presents the bivariate correlations for all variables. It was observed that grip strength and cognitive function (including memory, drawing, orientation, computation) were negatively associated with depression. On the other hand, grip strength showed a positive association with depression, justifying further moderated mediation analysis. Table 3 Correlation for the main variables Variable 1 2 3 4 5 6 7 1.Grip strength - 2.Depression -0.148 *** - 3.Cognitive function 0.220 *** -0.133 *** - 4.Memory 0.148 *** -0.091 *** 0.874 *** - 5.Drawing 0.194 *** -0.073 *** 0.422 *** 0.239 *** - 6.Orientation 0.161 *** -0.085 *** 0.555 *** 0.297 *** 0.310 *** - 7.Computation 0.175 *** -0.120 *** 0.628 *** 0.247 *** 0.269 *** 0.280 *** - *** P<0.001 Mediating Effects of Cognitive Function in the Association between Grip Strength and Depression The results illustrated the impact of grip strength on depression through cognitive function, while controlling for 11 covariates potentially associated with the study variables (Table 4 ). Grip strength level was a significant negative predictor of depression (β = -0.088, p < 0.001), and a significant positive predictor of cognitive function (β = 0.220, p < 0.001). Additionally, a negative correlation was found between cognitive function and depression (β = -0.133, p < 0.001). The indirect influence of grip strength on depression through cognitive function was also revealed (β = -0.008, 95% CI [-0.013, -0.004]), accounting for 9.4% of the effect. Table 4 The moderated mediating effect of grip strength class on depression by cognitive function. Independent variable Mediator Total effect Indirect effect Direct effect Proportion mediated, % (95% CI) Coefficient (95% CI) P value Coefficient (95% CI) P value Coefficient (95% CI) P value Grip strength class Drawing -0.087 (-0.126, -0.053) < 0.001 -0.000 (-0.004, 0.001) 0.376 -0.086 (-0.125, -0.052) < 0.001 0.3 (-1.3, 4.4) Memory -0.088 (-0.127, -0.054) < 0.001 -0.005 (-0.008, -0.002) < 0.001 -0.083 (-0.121, -0.050) < 0.001 5.6 (1.9, 11.6) orientation -0.087 (-0.126, -0.053) < 0.001 -0.003 (-0.006, -0.001) 0.004 -0.084 (-0.123, -0.051) < 0.001 3.6 (1.2, 7.7) computation -0.087 (-0.126, -0.053) < 0.001 -0.004 (-0.007, -0.001) 0.020 -0.084 (-0.123, -0.050) < 0.001 4.2 (0.9, 8.9) Cognitive function -0.088 (-0.127, -0.054) < 0.001 -0.008 (-0.013, -0.004) < 0.001 -0.080 (-0.118, -0.046) < 0.001 9.4 (4.6, 17.4) The mediation analyses were adjusted for Age, BMI, Gender, Education, Permanent address, Marital status, Hypertension, Dyslipidemia, Diabetes, Smoking and Alcohol consumption, p:P value; CI: Confidence interval Sensitivity and Subgroup Analyses The sensitivity analysis was enhanced by conducting subgroup analyses stratified by gender and age. These analyses disclosed no significant age or gender differences in the relationship between weak grip strength, cognitive function, and the incidence of depression. This finding emphasizes the consistency and robustness of our results (Supplementary File 2: Table S2 ). Discussion This study represents a pioneering exploration into the mediating role of cognitive function in the relationship between grip strength and the incidence of depression among middle-aged and elderly individuals in China. Our research findings underscore that weak grip strength, after accounting for potential confounding factors, is a notable risk factor for depression within this demographic group (OR: 1.57, 95% CI: 1.32–1.87). In contrast, an elevated level of cognitive function (OR: 0.94, 95% CI: 0.93–0.95) emerges as a protective factor against depression among the middle-aged and elderly population in China. Interestingly, our results indicate that cognitive function partially mediates the relationship between grip strength and the incidence of depression. The utility of grip strength as a straightforward, economical risk stratification tool is well-recognized, particularly in clinical settings. Its simplicity, portability, and low cost make it an attractive tool for assessing individual health risks ([ 38 ]). Previous research into grip strength and depression has indicated that weak grip strength might be a risk factor for depression in middle-aged and elderly individuals [ 39 – 40 ]. These studies have suggested a dose-response relationship between grip strength and depression risk, highlighting a negative correlation between grip strength and the risk of depression. Our study aligns with these findings, as we discovered that individuals with weaker grip strength, after adjusting for potential confounding factors, have a 1.45 times higher odds of developing depression [ 41 ]. Elderly individuals in the lowest quartile of muscle strength are more prone to experiencing symptoms of depression and suicidal thoughts [ 42 ]. Our study extends these insights by stratifying grip strength based on body mass index (BMI) and identifying weak grip strength levels under different BMI conditions [ 33 ]. We delved into analyzing the relationship between the weak grip strength group and the incidence of depression, suggesting that weak grip strength levels can be a useful indicator for monitoring depression in the middle-aged and elderly population. Our findings advocate for primary healthcare providers to regularly assess grip strength levels in this demographic, especially those with weak grip strength, and to implement appropriate interventions, such as scientific physical exercise or resistance training, to alleviate depression. The association between cognition and grip strength is also a critical aspect of our findings. Epidemiological studies have established that weaker grip strength is linked to cognitive decline, an increased risk of mental illnesses, and dementia. For example, an analysis involving 190,406 adult participants from the UK Biobank revealed a correlation between hand grip strength and measures of neurocognitive health in both males and females [ 44 ]. In populations with depression, cognitive tasks like reaction time and working memory have shown associations with maximum grip strength, influencing the risk of dementia [ 26 ]. The reciprocal relationship between grip strength and cognition is also evident in some studies suggesting that muscle strength deficits lead to cognitive decline [ 19 ][ 45 ]. However, this perspective is challenged by conflicting findings in other studies [ 46 , 47 , 48 ] that propose individuals with better cognitive abilities exhibit superior handgrip strength (HGS) values compared to those with poorer cognitive abilities. There is significant evidence indicating an association between cognitive changes and reduced grip strength (HGS) [ 49 ]. Cognitive impairments affect the muscle strength of older individuals, influencing their functional capacity and subsequent dependency. A decline in inhibitory function and grip strength is evident in middle-aged individuals, showing a significant correlation [ 50 ]. A recent study involving 5995 Korean participants confirmed a bidirectional relationship between grip strength and cognitive function, suggesting a common pathway between these two structures [ 51 ]. This suggests that grip strength can be a supplementary measure for assessing cognitive abilities in older adults. Furthermore, our study indicates an increase in the likelihood of depression with cognitive decline, with individuals experiencing cognitive decline at an elevated risk of progressing to mild cognitive impairment (MCI) and dementia [ 52 ]. Numerous longitudinal studies have identified a decline in cognitive abilities among elderly individuals with symptoms of depression or diagnosed depression [ 53 , 54 ]. The level of cognitive functioning not only influences the severity of depressive symptoms but also impacts the types of symptoms reported [ 55 ]. Research exploring broader cognitive indicators has encompassed areas such as memory, executive function, reasoning, and processing speed [ 56 ]. The severity of depressive symptoms is often associated with poorer cognitive performance in neuropsychological tests, revealing specific domain deficits in memory, attention, executive function, and processing speed [ 57 ]. The relationship between depression, brain abnormalities, and cognitive decline is dynamic over time, necessitating an analysis of cognitive decline across various domains to investigate subtle early changes related to mental states. These factors may be intricately linked to the complexity of neural and motor functions. Importantly, our study indicates that cognitive function acts as an intermediary in the relationship between weak grip strength and the likelihood of depression. In our analysis, mediation analysis revealed a significant pathway involving grip strength levels, cognitive function, and depressive status. Further subdivision of cognitive function indicators for mediation analysis revealed that, apart from drawing ability, memory, orientation, and calculation – three cognitive abilities – demonstrated significant mediation effects on the relationship between grip strength and depressive symptoms in middle-aged and elderly individuals (P < 0.001). This finding offers new evidence in the existing literature, suggesting that grip strength may positively impact subsequent depression through the cognitive abilities of older adults, including memory, orientation, and calculation. Although the mechanisms supporting the impact of cognitive function on the association between grip strength and depressive symptoms are not yet fully understood, several hypotheses have been proposed, both biologically and psychologically. One plausible mechanism linking grip strength to depression involves low-grade inflammation, a condition prevalent in approximately one-fourth of individuals with depression, with over half of these individuals exhibiting mild elevations in C-reactive protein levels [ 58 , 59 ]. In a study, inflammatory factors (plasma interleukin (IL)-6 and C-reactive protein (CRP)) were shown to be associated with midlife cognition through changes in brain morphology [ 60 ]. Physical exercise or resistance training, known to increase muscle strength and reduce systemic inflammation, can also improve cognitive function, thereby contributing to the alleviation of depressive symptoms [ 61 ]. Another crucial factor that may influence the relationship between depression and cognition is age-related structural changes in the brain, particularly hippocampal volume loss. Older individuals with depression and reduced hippocampal volume are at a greater risk of cognitive decline [ 62 ]. Brain-derived neurotrophic factor (BDNF) plays a role in regulating hippocampal plasticity, and its deficiency is implicated in the pathophysiology of depression. BDNF is considered essential for maintaining hippocampal integrity and cognition [ 63 ]. Depression is associated with low levels of brain-derived neurotrophic factor (BDNF), which is crucial for emotional processing, memory, and learning [ 64 ]. Evidence suggests that the lack of BDNF plays a significant role in the pathophysiology of depression, and exercise-induced increases in BDNF can improve hippocampal atrophy, consequently enhancing cognitive functions such as memory [ 65 ], thus supporting the notion of reducing depression. Beyond the impact of exercise on improving inflammation and neurotrophic factors, in psychological terms, exercise may contribute to a sense of mental well-being. Various psychosocial factors may also influence susceptibility to illness. For instance, a robust physique may be associated with reduced psychological distress (i.e., stress and negative impacts) and better mental health (i.e., optimism and self-esteem) [ 66 ]. Individuals engaged in regular exercise are more likely to foster supportive social relationships, potentially reducing the severity of depression [ 67 ]. Therefore, comprehensive research is needed in the future to understand how different factors mediate the relationship between grip strength and depression. Our research findings may have potential theoretical implications for attenuating and improving depressive symptoms in middle-aged and elderly individuals. Weak grip strength levels can serve as an indicator for monitoring depression susceptibility in this population. Primary healthcare practitioners should regularly assess grip strength levels in middle-aged and elderly individuals, with particular attention to those with weak grip strength. Grip strength can be enhanced through physical exercise or resistance training [ 68 ]. Simultaneously, cognitive functions can be improved through activities such as exercise games [ 69 ], meditation [ 70 ], music [ 71 ], and dance therapy [ 72 ]. These interventions aim to mitigate the relationship between low grip strength levels and the risk of depression. Limitations While this study draws on a nationally representative sample of middle-aged and elderly individuals in China, providing novel insights into the moderating role of cognitive function in the relationship between grip strength and depressive symptoms, it is not without its limitations. Firstly, the cross-sectional nature of this study precludes the ability to infer causal or bidirectional relationships among grip strength, cognition, and depression. This limitation is significant as it restricts the understanding of the temporal sequence of these associations. Secondly, the reliance on self-reported data for many variables, including sociodemographic and health-related factors, introduces the potential for recall bias. Participants' recollections may not always be accurate, which could affect the reliability of the findings. Lastly, while the study made efforts to adjust for various potential confounders, there remains the possibility that other unmeasured factors, such as dietary patterns [ 73 ], levels of inflammation [ 74 ], and additional indicators, might have influenced the results. Future research endeavors should consider a more comprehensive approach, possibly incorporating longitudinal designs, to better understand the intricate relationships between depression and its related risk factors. Conclusion This cross-sectional study, utilizing data from the China Health and Retirement Longitudinal Study (CHARLS), reveals that weak grip strength is significantly associated with an increased risk of depressive symptoms among middle-aged and elderly individuals. Importantly, the study also finds that elevated cognitive function appears to mitigate this association. These findings underscore the importance of considering grip strength as a potential indicator of depression risk in this demographic. In future research and clinical practice, identifying individuals with weak grip strength could be key in recognizing those at higher risk for depression. Targeted interventions, possibly focusing on enhancing grip strength and cognitive function, could be beneficial in reducing the risk and severity of depressive symptoms in middle-aged and elderly populations. Declarations Author contribution Conceptualization and methodology: Xinzheng Wang，Huifen Zhou，Jiandong He Data curation, formal analysis, and visualization: Xinzheng Wang， Guohao Yi Writing—original draft: Xinzheng Wang, Lifei Wu Writing—review and editing: Xinzheng Wang, Guohao Yi, Lifei Wu, Huifen Zhou，Jiandong He All authors read and approved the final manuscript. Funding No Data Availability The data provided in this article are available in a public, open access repository, and can be accessed at China Health and Retirement Longitudinal Study (CHARLS) https://charls.pku.edu.cn/en/ Conflict of interest The authors declare no competing interests References GBD 2019 Diseases and Injuries Collaborators. Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet. 2020;396(10258):1204–1222. doi: 10.1016/S0140-6736(20)30925-9. Erratum in: Lancet. 2020;396(10262):1562. PMID: 33069326; PMCID: PMC7567026.). Dwyer JB, Aftab A, Radhakrishnan R, et al. Hormonal treatments for major depressive disorder: state of the art. Am J Psychiatry. 2020;177:686–705. World Health Organization. Depression and other common mental disorders, World Health Organization. 2017 Jan. URL: https://www.who.int/publications/i/item/depression-global-health-estimates [accessed 2022-01-04]. Lei X, Sun X, Strauss J, Zhang P, Zhao Y. Depressive symptoms and SES among the mid-aged and elderly in China: evidence from the China Health and Retirement Longitudinal Study national baseline. Soc Sci Med. 2014;120:224–32. Wang Y, Chen Q, Liu. Lurong. Meta-analysis of Depression Detection Rate and Influencing Factors in Chinese Elderly Population[J]. Chin J Gen Pract. 2023;26(34):4329–35. Yang Y. Is old age depressing? Growth trajectories and cohort variations in late-life depression. J Health Soc Behav. 2007;48(1):16–32. 10.1177/002214650704800102 . Ji Y, Chen H, Yang Y, Zhou Y, Li H, Jin H, Xie J, Shen B. Health-related quality of life and survival outcomes for patients with major depressive disorder and anxiety: A longitudinal study in pancreatic ductal adenocarcinoma. Cancer Med. 2023;12(19):20070–80. Epub 2023 Sep 25. PMID: 37746894; PMCID: PMC10587956. Ruggieri V. Autismo, depresión y riesgo de suicidio [Autism, depression and risk of suicide]. Med (B Aires). 2020;80(Suppl 2):12–6. Spanish. PMID: 32150706. Semenkovich K, Brown ME, Svrakic DM, Lustman PJ. Depression in type 2 diabetes mellitus: prevalence, impact, and treatment. Drugs. 2015;75(6):577 – 87. 10.1007/s40265-015-0347-4 . PMID: 25851098. Krittanawong C, Maitra NS, Qadeer YK, Wang Z, Fogg S, Storch EA, Celano CM, Huffman JC, Jha M, Charney DS, Lavie CJ. Association of Depression and Cardiovascular Disease. Am J Med. 2023;136(9):881–95. Epub 2023 May 27. PMID: 37247751. Malhi GS, Mann JJ. Depress Lancet. 2018;392(10161):2299–312. Fukumori N. Yamamoto Y.Takegami M.Association between hand-grip strength and depressive symptoms: Locomotive Syndrome and Health Outcomes in Aizu Cohort Study (LOHAS).Age Ageing. 2015; 44: 592–8. Lee MR. Y.B.The association between muscular strength and depression in Korean adults: a cross-sectional analysis of the sixth Korea National Health and Nutrition Examination Survey (KNHANES VI) 2014. BMC Public Health. 2018;18:1123. Marques A, Gaspar de Matos M, Henriques-Neto D, Peralta M, Gouveia ÉR, Tesler R, Martins J, Gomez-Baya D. Grip Strength and Depression Symptoms Among Middle-Age and Older Adults. Mayo Clin Proc. 2020;95(10):2134–2143. 10.1016/j.mayocp.2020.02.035 . PMID: 33012344. Zhang F, Yu Y, Wang H, Zhang Y, Bai Y, Huang L, Zhang H. Association between handgrip strength and depression among Chinese older adults: a cross-sectional study from the China Health and Retirement Longitudinal Study. BMC Geriatr. 2023;23(1):299. 10.1186/s12877-023-04034-6 . PMID: 37193949; PMCID: PMC10190059. Brooks JM, Titus AJ, Bruce ML, Orzechowski NM, Mackenzie TA, Bartels SJ, Batsis JA. Depression and Handgrip Strength Among U.S. Adults Aged 60 Years and Older from NHANES 2011–2014. J Nutr Health Aging. 2018;22(8):938–43. PMID: 30272097; PMCID: PMC6168750. Zhang XM, Jiao J, Cao J, Guo N, Zhu C, Li Z, Wu X, Xu T. Handgrip Strength and Depression Among Older Chinese Inpatients: A Cross-Sectional Study. Neuropsychiatr Dis Treat. 2021;17:1267–77. https://doi.org/10.2147/ndt.S301064 . Stessman J, Rottenberg Y, Fischer M, Hammerman-Rozenberg A, Jacobs JM. Handgrip strength in old and very old adults: mood, cognition, function, and mortality. J Am Geriatr Soc. 2017;65:526–32. Taekema DG, Gussekloo J, Maier AB, Westendorp RGJ, de Craen AJM. Handgrip strength as a predictor of functional, psychological and social health. A prospective population-based study among the oldest old. Age Ageing. 2010;39(3):331–7. Kaczorowska A, Kaczorowska A, Kowalska J. Associations Between Physical Fitness, Cognitive Function, and Depression in Nursing Homes Residents Between 60–100 Years of Age in South-Western Poland. Med Sci Monit. 2024;30:e942729. 10.12659/MSM.942729 . PMID: 38185903. Rock PL, Roiser JP, Riedel WJ, Blackwell AD. Cognitive impairment in depression: a systematic review and meta-analysis. Psychol Med. 2014;44(10):2029-40. 10.1017/S0033291713002535 . Epub 2013 Oct 29. PMID: 24168753. Ferri F, Deschênes SS, Power N, Schmitz N. Associations between cognitive function, metabolic factors and depression: A prospective study in Quebec, Canada. J Affect Disord. 2021;283:77–83. 10.1016/j.jad.2021.01.039 . Epub 2021 Jan 14. PMID: 33524662. Christensen GT, Rozing MP, Mortensen EL, Christensen K, Osler M. Young adult cognitive ability and subsequent major depression in a cohort of 666,804 Danish men. J Affect Disord. 2018;235:162–167. 10.1016/j.jad.2018.04.035 . Epub 2018 Apr 5. PMID: 29656261. Yang J, Deng Y, Yan H, Li B, Wang Z, Liao J, Cai X, Zhou L, Tan W, Rong S. Association Between Grip Strength and Cognitive Function in US Older Adults of NHANES 2011–2014. J Alzheimers Dis. 2022;89(2):427–436. 10.3233/JAD-215454 . PMID: 35871326. Feng W, Ma M, Gao H, Yuan W, Li R, Guo H, Gu C, Sun Z, Zhang Y, Zheng L. Association between handgrip strength asymmetry and cognitive function across ethnicity in rural China: a cross-sectional study. Front Aging Neurosci. 2023;15:1191197. 10.3389/fnagi.2023.1191197 . PMID: 37273648; PMCID: PMC10235480. Firth J, Stubbs B, Vancampfort D, Firth J, Large M, Rosenbaum S, et al. Grip strength is associated with cognitive performance in schizophrenia and the general population: a UK biobank study of 476559 participants. Schizop Bull. 2018;44:728–36. 10.1093/schbul/sby034 . Jin Y, Xu L, Jiang C, Zhang W, Pan J, Zhu F, et al. Association of hand grip strength with mild cognitive impairment in middle-aged and older people in guangzhou biobank cohort study. Int J Environ Res Public Health. 2022;19:11. 10.3390/ijerph19116464 . Cui M, Zhang S, Liu Y, Gang X, Wang G. Grip Strength and the risk of cognitive decline and dementia: a systematic review and meta-analysis of longitudinal cohort studies. Front Aging Neurosci. 2021;13:625551. 10.3389/fnagi.2021.625551 . Sibbett RA, Russ TC, Allerhand M, Deary IJ, Starr JM. Physical fitness and dementia risk in the very old: a study of the Lothian Birth Cohort 1921. BMC Psychiatry. 2018;18:285. 10.1186/s12888-018-1851-3 . Doi T, Tsutsumimoto K, Nakakubo S, Kim MJ, Kurita S, Hotta R, et al. Physical performance predictors for incident dementia among japanese community-dwelling older adults. Phys Therapy. 2019;99:1132–40. 10.1093/ptj/pzz077 . Zhao Y, Hu Y, Smith JP, Strauss J, Yang G. Cohort profile: the China Health and Retirement Longitudinal Study (CHARLS). Int J Epidemiol. 2014;43(1):61–8. 10.1093/ije/dys203 . Epub 2012 Dec 12. PMID: 23243115; PMCID: PMC3937970. Bao M, Chao J, Sheng M, Cai R, Zhang N, Chen H. Longitudinal association between muscle strength and depression in middle-aged and older adults: A 7-year prospective cohort study in China. J Affect Disord. 2022;301:81–6. 10.1016/j.jad.2022.01.036 . Mak JKL, Kuja-Halkola R, Wang Y, Hägg S, Jylhävä J. Can frailty scores predict the incidence of cancer? Results from two large population-based studies. Geroscience. 2023;45(3):2051–64. 10.1007/s11357-023-00783-9 . Epub 2023 Mar 30. PMID: 36997701; PMCID: PMC10400738. Crimmins EM, Kim JK, Langa KM, Weir DR. Assessment of cognition using surveys and neuropsychological assessment: the Health and Retirement Study and the Aging, Demographics, and Memory Study. J Gerontol B Psychol Sci Soc Sci. 2011;66:i162–71. Cao L, Zhao Z, Ji C, Xia Y. Association between solid fuel use and cognitive impairment: A cross-sectional and follow-up study in a middle-aged and older Chinese population. Environ Int. 2021;146:106251. Gabriel A, Zare H, Jones W, Yang M, Ibe CA, Cao Y, et al. Evaluating depressive symptoms among low-socioeconomic-status African American women aged 40 to 75 years with uncontrolled hypertension: a secondary analysis of a randomized clinical trial. JAMA Psychiatry. 2021;78:426–32. https://doi.org/10.1001/jamapsychiatry.2020.4622 . World Health Organization. Ageing and health. 2018. . Zare S, Hasani M, Estêvão MD, Tahmasebi R, Azadbakht L, Shidfar F, Heshmati J, Ziaei S. Muscle Strength and Biochemical Markers as Predictors of Depression in Hemodialysis Patients: A Cross-Sectional Study. Clin Nutr Res. 2023;12(4):293–303. 10.7762/cnr.2023.12.4.293 . PMID: 37969939; PMCID: PMC10641328. Muhammad T, Maurya P. Relationship between handgrip strength, depression and cognitive functioning among older adults: Evidence from longitudinal ageing study in India. Int J Geriatr Psychiatry. 2022;37(8). 10.1002/gps.5776 . PMID: 35785433. López-Bueno R, Calatayud J, Andersen LL, Casaña J, Koyanagi A, Del Pozo Cruz B, Smith L. Dose-response association of handgrip strength and risk of depression: a longitudinal study of 115 601 older adults from 24 countries. Br J Psychiatry. 2023;222(3):135–42. 10.1192/bjp.2022.178 . PMID: 36464972; PMCID: PMC9929711. Ashdown-Franks G, Stubbs B, Koyanagi A, Schuch F, Firth J, Veronese N, et al. Handgrip strength and depression among 34,129 adults aged 50 years and older in six low- and middle-income countries. J Affect Disord. 2019;243:448–54. Kyu-Man H, Jisoon C, Ho-Kyoung Y, Young-Hoon K, Byung-Joo H, Yong-Ku K, et al. Relationships between hand-grip strength, socioeconomic status, and depressive symptoms in community-dwelling older adults. J Affect Disord. 2019;252:263–70. Zasadzka E, Pieczynska A, Trzmiel T, Kleka P, Pawlaczyk M. Correlation between Handgrip Strength and Depression in older Adults-A systematic review and a Meta-analysis. Int J Environ Res Public Health 2021,18(9). Duchowny KA, Ackley SF, Brenowitz WD, Wang J, Zimmerman SC, Caunca MR, Glymour MM. Associations between Handgrip Strength and Dementia Risk, Cognition, and neuroimaging outcomes in the UK Biobank Cohort Study. JAMA Netw Open. 2022;5(6):e2218314. McGough EL, Cochrane BB, Pike KC, Logsdon RG, McCurry SM, Teri L. Dimensions of physical frailty and cognitive function in older adults with amnestic mild cognitive impairment. Ann Phys Rehabil Med. 2013;56(5):329–41. Kan GA, Cesari M, Gillette-Guyonnet S, Dupuy C, Nourhashémi F, Schott AM, Beauchet O, Annweiler C, Vellas B, Rolland Y. Sarcopenia and cognitive impairment in elderly women: results from the EPIDOS cohort. Age Ageing. 2013;42(2):196–202. Ukegbu U, Maselko J, Malhotra R, Perera B, Østbye T. Correlates of Handgrip Strength and activities of daily living in elderly Sri Lankans. J Am Geriatr Soc. 2014;62(9):1800–1. allucci M, Mazzuco S, Ongaro F, Di Giorgi E, Mecocci P, Cesari M, Albani D, Forloni GL, Durante E, Gajo GB, Zanardo A, Siculi M, Caberlotto L, Regini C. Body mass index, lifestyles, physical performance and cognitive decline: the Treviso Longeva (TRELONG) study. J Nutr Health Aging. 2013;17(4):378–84. Silva N, Menezes TN. Associação entre cognição e força de preensão manual em idosos: revisão integrativa [The association between cognition and handgrip strength among the elderly: an integrative review]. Cien Saude Colet. 2016;21(11):3611–3620. Portuguese. 10.1590/1413-812320152111.22872015 . PMID: 27828593. Adamo DE, Anderson T, Koochaki M, et al. Declines in grip strength may indicate early changes in cognition in healthy middle-aged adults. PLoS ONE. 2020;15(4):e0232021. Kim GR, Sun J, Han M, Nam CM, Park S. Evaluation of the directional relationship between handgrip strength and cognitive function: the Korean Longitudinal Study of Ageing. Age Ageing. 2019;48(3):426–32. Shimada H, Park H, Makizako H, Doi T, Lee S, Suzuki T. Depressive symptoms and cognitive performance in older adults. J Psychiatr Res. 2014;57:149 – 56. 10.1016/j.jpsychires.2014.06.004 . Epub 2014 Jun 24. PMID: 25023083. Guan Q, Hu X, Ma N, He H, Duan F, Li X, Luo Y, Zhang H. Sleep Quality, Depression, and Cognitive Function in Non-Demented Older Adults. J Alzheimers Dis. 2020;76(4):1637–1650. 10.3233/JAD-190990 . PMID: 32675408. Dotson VM, McClintock SM, Verhaeghen P, Kim JU, Draheim AA, Syzmkowicz SM, Gradone AM, Bogoian HR, Wit L. Depression and Cognitive Control across the Lifespan: a Systematic Review and Meta-Analysis. Neuropsychol Rev. 2020;30(4):461–76. 10.1007/s11065-020-09436-6 . Epub 2020 May 8. PMID: 32385756; PMCID: PMC9637269. Brailean A, Comijs HC, Aartsen MJ, Prince M, Prina AM, Beekman A, Huisman M. Late-life depression symptom dimensions and cognitive functioning in the Longitudinal Aging Study Amsterdam (LASA). J Affect Disord. 2016;201:171–8. 10.1016/j.jad.2016.05.027 . Epub 2016 May 19. PMID: 27235820; PMCID: PMC4914607. Jiang R, Westwater ML, Noble S, Rosenblatt M, Dai W, Qi S, Sui J, Calhoun VD, Scheinost D. Associations between grip strength, brain structure, and mental health in > 40,000 participants from the UK Biobank. BMC Med. 2022;20(1):286. 10.1186/s12916-022-02490-2 . PMID: 36076200; PMCID: PMC9461129. Jamieson A, Goodwill AM, Termine M, Campbell S, Szoeke C. Depression related cerebral pathology and its relationship with cognitive functioning: A systematic review. J Affect Disord. 2019;250:410–8. 10.1016/j.jad.2019.03.042 . Epub 2019 Mar 6. PMID: 30878653. Osimo EF, Baxter LJ, Lewis G, Jones PB, Khandaker GM. Prevalence of low-grade inflammation in depression: a systematic review and meta-analysis of CRP levels. Psychol Med. 2019;49(12):1958–70. Epub 2019 Jul 1. PMID: 31258105; PMCID: PMC6712955. Kunutsor SK, Isiozor NM, Voutilainen A, Laukkanen JA. Handgrip strength and risk of cognitive outcomes: new prospective study and meta-analysis of 16 observational cohort studies. Geroscience. 2022;44(4):2007–24. 10.1007/s11357-022-00514-6 . Epub 2022 Jan 10. PMID: 35013908; PMCID: PMC9616970. Marsland AL, Gianaros PJ, Kuan DC, Sheu LK, Krajina K, Manuck SB. Brain morphology links systemic inflammation to cognitive function in midlife adults. Brain Behav Immun. 2015;48:195–204. 10.1016/j.bbi.2015.03.015 . Epub 2015 Apr 14. PMID: 25882911; PMCID: PMC4508197. Verhoeven F, Tordi N, Prati C, Demougeot C, Mougin F, Wendling D. Physical activity in patients with rheumatoid arthritis. Jt Bone Spine. 2016;83:265–70. https://doi.org/10.1016/j.jbspin.2015.10.002 . Baksh RA, Ritchie CW, Terrera GM, Norton J, Raymont V, Ritchie K. The association between anxiety disorders and hippocampal volume in older adults. Psychol Aging. 2021;36(2):288–97. 10.1037/pag0000597 . Epub 2021 Mar 4. PMID: 33661669. Kanellopoulos D, Gunning FM, Morimoto SS, Hoptman MJ, Murphy CF, Kelly RE, Glatt C, Lim KO, Alexopoulos GS. Hippocampal volumes and the brain-derived neurotrophic factor val66met polymorphism in geriatric major depression. Am J Geriatr Psychiatry. 2011;19(1):13–22. 10.1097/jgp.0b013e3181f61d62 . PMID: 21218562; PMCID: PMC3058412. Brunoni, 。Brunoni AR, Lopes M, Fregni F et al. 2008. A systematic review and meta-analysis of clinical studies on major depression and BDNF levels: implications for the role of neuroplasticity in depression. Int. J. Neuropsychopharmacol. 11, 1169–1180. https://doi.org/10.1017/S1461145708009309 . Erickson KI, Miller DL, Roecklein KA. The aging hippocampus: interactions between exercise, depression, and BDNF. Neuroscientist. 2012;18(1):82–97. doi: 10.1177/1073858410397054. Epub 2011 Apr 29. PMID: 21531985; PMCID: PMC3575139. Rodriguez-Ayllon M, Cadenas-Sanchez C, Esteban-Cornejo I, Migueles JH, Mora-Gonzalez J, Henriksson P, Martín-Matillas M, Mena-Molina A, Molina-García P, Estévez-López F, Enriquez GM, Perales JC, Ruiz JR, Catena A, Ortega FB. Physical fitness and psychological health in overweight/obese children: A cross-sectional study from the ActiveBrains project. J Sci Med Sport. 2018;21(2):179–184. doi: 10.1016/j.jsams.2017.09.019. Epub 2017 Oct 4. PMID: 29031643. Hallgren M, Lundin A, Tee FY, Burström B, Forsell Y. Somebody to lean on: Social relationships predict post-treatment depression severity in adults. Psychiatry Res. 2017;249:261–7. 10.1016/j.psychres.2016.12.060 . Epub 2017 Jan 17. PMID: 28131948. Khodadad Kashi S, Mirzazadeh ZS, Saatchian VA, Systematic Review. Meta-Analysis of Resistance Training on Quality of Life, Depression, Muscle Strength, and Functional Exercise Capacity in Older Adults Aged 60 Years or More. Biol Res Nurs. 2023;25(1):88–106. Epub 2022 Aug 13. PMID: 35968662. Rosenberg D, Depp CA, Vahia IV, Reichstadt J, Palmer BW, et al. Exergames for subsyndromal depression in older adults: a pilot study of a novel intervention. Am J Geriatr Psychiatry. 2010;18:221–26. Nash JD, Newberg A. Toward a unifying taxonomy and definition for meditation. Front Psychol. 2013;4:806. Hars M, Herrmann FR, Gold G, Rizzoli R, Trombetti A. Effect of music-based multitask training on cognition and mood in older adults. Age Ageing. 2014;43:196–200. Murrock CJ, Graor CH. The effects of dance on depression, physical function, and disability in underserved adults. J Aging Phys Act. 2014;22(3):380–85. Marx W, Lane M, Hockey M, et al. Diet and depression: exploring the biological mechanisms of action. Mol Psychiatry. 2021;26:134–50. https://doi.org/10.1038/s41380-020-00925-x . Verhoeven F, Tordi N, Prati C, Demougeot C, Mougin F, Wendling D. Physical activity in patients with rheumatoid arthritis. Jt Bone Spine. 2016;83:265–70. https://doi.org/10.1016/j.jbspin.2015.10.002 . Additional Declarations No competing interests reported. Supplementary Files TableS1.docx TableS2.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4207923","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":288396323,"identity":"07af4f31-4de4-4510-af63-82ef6643c971","order_by":0,"name":"Xinzheng Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAwElEQVRIiWNgGAWjYBACfvbmAwc+VNjI8bM3EKlFsudY4sMZZ9KMJXsOEKnF4IaPsTFv26HEDTcSiNbCYyY548wBxpkzH2+8wVBjE03YYbfbyiQ+VNxh5pdOK7ZgOJaW20BIC9+dw9uAtjxjk5ydYybB2HCYsBaGGwlm0rxth3kMbp4hUovAjRSQ9w9LgDxFnBZYIBtI9gD9kkCMX2BRWd/PfnjjjQ81NkT4BQkYSCSQohyihVQdo2AUjIJRMDIAAB3sSYvOSeFsAAAAAElFTkSuQmCC","orcid":"","institution":"Zhejiang Chinese Medical University","correspondingAuthor":true,"prefix":"","firstName":"Xinzheng","middleName":"","lastName":"Wang","suffix":""},{"id":288396324,"identity":"8f296fc6-615e-4589-9ddd-1cd91e643a7f","order_by":1,"name":"Guohao Yi","email":"","orcid":"","institution":"Zhejiang Chinese Medical University","correspondingAuthor":false,"prefix":"","firstName":"Guohao","middleName":"","lastName":"Yi","suffix":""},{"id":288396325,"identity":"3bfc3952-2c74-4645-b54f-69c2b4e711f8","order_by":2,"name":"Lifei Wu","email":"","orcid":"","institution":"Zhejiang Chinese Medical University","correspondingAuthor":false,"prefix":"","firstName":"Lifei","middleName":"","lastName":"Wu","suffix":""},{"id":288396326,"identity":"902463f1-22d6-4517-96eb-72ce42126133","order_by":3,"name":"Huifen Zhou","email":"","orcid":"","institution":"Zhejiang Chinese Medical University","correspondingAuthor":false,"prefix":"","firstName":"Huifen","middleName":"","lastName":"Zhou","suffix":""},{"id":288396327,"identity":"e70af5cd-4f63-4439-b20c-fe97afa85025","order_by":4,"name":"Jiandong He","email":"","orcid":"","institution":"Zhejiang Chinese Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jiandong","middleName":"","lastName":"He","suffix":""}],"badges":[],"createdAt":"2024-04-02 16:09:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4207923/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4207923/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":54321310,"identity":"1eb3feaa-be50-41d6-8593-e4ac639c0157","added_by":"auto","created_at":"2024-04-08 19:27:23","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":67814,"visible":true,"origin":"","legend":"\u003cp\u003eFlow chart of the selection of study participants.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4207923/v1/2332709f1cddf1f7dc059ffc.png"},{"id":55516395,"identity":"9a9709d9-9bfc-4523-9722-eb80df1923be","added_by":"auto","created_at":"2024-04-29 13:15:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":951782,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4207923/v1/891e2d07-e2fd-4a8d-bdf2-bfe004ee77dc.pdf"},{"id":54321309,"identity":"6df54e85-3c54-4f87-9b8e-66de924e569d","added_by":"auto","created_at":"2024-04-08 19:27:23","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":15323,"visible":true,"origin":"","legend":"","description":"","filename":"TableS1.docx","url":"https://assets-eu.researchsquare.com/files/rs-4207923/v1/70b706bf07c947179532a2d8.docx"},{"id":54321311,"identity":"4495ec56-8168-4efd-9e9f-8ec74d81c898","added_by":"auto","created_at":"2024-04-08 19:27:23","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":16505,"visible":true,"origin":"","legend":"","description":"","filename":"TableS2.docx","url":"https://assets-eu.researchsquare.com/files/rs-4207923/v1/972f58a290885659116ef46b.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Mediating Role of Cognitive Function in the Association between Grip Strength and Depression among Chinese middle-aged and elderly adults: A Cross-Sectional Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDepression is a significant mental health concern and is increasingly recognized as a leading cause of disabling mental disorders worldwide [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The World Health Organization has predicted that by 2030, depression will become one of the most impactful global health issues [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In China, which is undergoing rapid population aging, more than 54\u0026nbsp;million individuals are affected by depression, as reported by the World Health Organization [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The prevalence of depression is particularly high among the middle-aged and elderly, those aged 45 and above [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], with a detection rate of 20.6% in the population over 60 years old [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Moreover, the incidence of depression increases with age [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Depression not only significantly impairs the quality of life of affected individuals [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] but also increases the risks of suicide [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], type 2 diabetes [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], cardiovascular diseases, and overall mortality [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Therefore, understanding the etiology and pathophysiology of depression, particularly in the middle-aged and elderly population in China, is of great public health importance. However, our understanding of depression is still incomplete, and more effective treatment methods are needed [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Identifying risk factors for depression and implementing effective interventions and management strategies are therefore crucial.\u003c/p\u003e \u003cp\u003eAmong various factors associated with depression, the impact of weak grip strength on depressive symptoms has recently gained attention ([\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e][\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e][\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]). However, research data on the correlation between grip strength and depression in elderly populations are limited, and the nature of this association remains unclear. Studies by Zhang F[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] and Brooks JM[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], using data from the China Health and Retirement Longitudinal Study (CHARLS) and the National Health and Nutrition Examination Survey (NHANES), suggest a negative correlation between grip strength and depression, after adjusting for confounding factors. Conversely, Zhang XM[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] found in a cross-sectional study that the risk of depression decreased with increasing grip strength, but the association was not significant when handgrip strength (HGS) exceeded 36.5 kg. In contrast, studies by Stessman J[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] and Taekema DG[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] observed a weak or non-existent predictive role of declining grip strength in the onset of depression in older adults. This suggests that the relationship between muscle strength and depression may be influenced by the psychological adaptation process during aging. It is therefore essential to understand the association between grip strength levels and depression among middle-aged and elderly individuals in China to inform the development of intervention measures.\u003c/p\u003e \u003cp\u003eAdditionally, recent evidence suggests a strong association between cognitive function and depressive symptoms, with better cognitive states in older individuals linked to good emotional states ([\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e][\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]). Studies by Ferri F[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] and Christensen GT[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] have shown that cognitive impairments in executive function, memory, and attention are common in individuals with depression, and that alleviating these cognitive deficits can contribute to improving depression symptoms. Moreover, research has shown a connection between grip strength and cognitive function [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. A study in rural China found that lower handgrip strength (HGS) and HGS asymmetry are independently associated with lower cognitive function [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], and studies by Firth J[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] indicate a significant correlation between higher grip strength in older individuals and better cognitive performance [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. However, the association between grip strength and cognitive function in the elderly has not reached a consensus. Cui M[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] reported that in older adults, grip strength is positively correlated with recall and memory performance but not with general cognitive function. In contrast, some studies have found no relationship between grip strength and cognitive dysfunction ([\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e][\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]). This discrepancy may be due to the complexity of motor function and needs further investigation. Our study aims to explore the potential mediating pathways between grip strength, cognitive function, and depression in middle-aged and elderly Chinese adults using data from the China Health and Retirement Longitudinal Study (CHARLS).\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData Source\u003c/h2\u003e \u003cp\u003eThis study is based on data from the China Health and Retirement Longitudinal Survey (CHARLS). CHARLS conducted a comprehensive baseline survey across the nation utilizing a probability-proportional-to-size (PPS) sampling method. This extensive survey gathered a wide array of information, including respondents' basic demographic details, their family's data, and insights into their education, employment, income, marital status, and health status. In addition, CHARLS incorporated an extensive set of 13 physical measurements and also undertook blood sample collection. Each stage of this survey was subject to stringent quality control measures, establishing CHARLS as a vital and authoritative source for investigating the array of health issues facing China's elderly population. The data from this extensive survey is publicly available and can be accessed at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://charls.pku.edu.cn\u003c/span\u003e\u003cspan address=\"http://charls.pku.edu.cn\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. The CHARLS project was conducted with full approval from the Peking University Biomedical Ethics Committee (IRB0000001052-11015), ensuring ethical compliance, and informed consent was duly obtained from all individuals who participated in the survey [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFor this particular study, we used the data from the 2011 CHARLS survey, which originally consisted of 17,708 participants. We had to exclude some participants from our analysis due to missing data in key areas such as grip strength, cognitive function (which included aspects like orientation, memory, calculation abilities, and drawing skills), and depression scores. Additionally, we also excluded participants who had missing values in covariate data crucial for our sample analysis. After applying these exclusion criteria, our study eventually included data from 6,841 participants, which was sufficient for a robust analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eVariable Selection\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003eDemographic Characteristics\u003c/h2\u003e \u003cp\u003eThe demographic characteristics of the survey participants were meticulously extracted from two specific modules of the CHARLS follow-up questionnaire: the \"Basic Information\" module and the \"Family\" module. This extraction process yielded vital information such as the participants' gender, age, marital status, and their level of educational attainment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003eGrip Strength\u003c/h2\u003e \u003cp\u003eThe measurement of grip strength was conducted using a specialized isometric dynamometer (YuejianTM WL-1000, Nantong, China) [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Participants were instructed to perform this test while standing, using either their dominant or non-dominant hand, based on their preference. They were required to keep their elbow positioned at a precise right angle (90\u0026deg;) and then exert force by squeezing the handle of the dynamometer for several seconds. This process was repeated to allow two measurements for both the right and left hands, and the highest value recorded in kilograms was used for analysis. We then categorized grip strength based on gender and body mass index [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], employing a binary scale where 0 indicated a normal grip strength level, and 1 indicated a comparatively weak grip strength, as detailed in Supplementary File 2: Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eCognitive Function\u003c/h2\u003e \u003cp\u003eCognitive function was evaluated based on the methodology employed in the American Health and Retirement Study (HRS) [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. This comprehensive assessment involved evaluating four key dimensions of cognitive function: orientation, calculation, memory, and drawing ability. The orientation assessment involved questions about the current year, month, day, day of the week, and the season, with each correct answer scoring 1 point, making a total possible score of 5 points. The calculation dimension required participants to perform serial subtractions, starting from 100 and subtracting 7 each time, up to five iterations. Each successful subtraction earned them 1 point. The memory assessment involved presenting ten random words to each participant, with their immediate recall capacity being evaluated based on the number of words they could immediately recollect. Following this, the participants completed the depression scale survey, after which their calculation and drawing abilities were tested. An assessment of delayed word recall was then conducted. The total memory score was a combination of both immediate and delayed word recall, with each correctly recalled word earning 1 point. The drawing test involved presenting participants with a picture of two overlapping pentagons, which they were then asked to replicate accurately. Successful replication earned the participant 1 point. The total score for cognitive function was thus calculated as the sum of scores from these four dimensions: orientation (5 points), calculation (5 points), memory (20 points), and drawing (1 point), giving a total possible score of 31 points. The scoring criteria followed for this assessment were aligned with the methodology used in the American Health and Retirement Study [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eDepression\u003c/h2\u003e \u003cp\u003eThe assessment of depression was carried out using the 10-item Center for Epidemiologic Studies Depression Scale (CES-D). Each item on this scale was rated on a frequency scale ranging from 0 to 3 [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. The scale's specifics were as follows: 0 was used to indicate rare or no occurrence of a symptom (less than 1 day per week), 1 indicated the symptom occurred some or a little of the time (1\u0026ndash;2 days per week), 2 was used for occasions or a moderate amount of the time (3\u0026ndash;4 days per week), and 3 indicated the symptom was present all of the time (5\u0026ndash;7 days per week). On this scale, the occurrence of positive emotions or behaviors was scored in a reverse manner. The scores of all 10 items were summed to obtain a total score, which ranged from 0 to 30, with higher scores indicating more severe symptoms of depression. Individuals who had a CES-D score of 10 or higher were considered to be participants with depressive symptoms.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eCovariates\u003c/h2\u003e \u003cp\u003eThis study included a range of additional covariates, such as age, follow-up time, education level, smoking habits, alcohol consumption, body mass index (BMI), hypertension, fall-related injuries, lipid abnormalities, diabetes or elevated blood sugar, cancer or malignant tumors, heart disease, stroke, nearsightedness and farsightedness, injuries, hearing issues, memory-related disorders, etc. Categories like hearing, vision, and life satisfaction were divided into three levels: \"poor, moderate, good.\" Marital status was categorized as married (living with a spouse) or unmarried (separated, divorced, widowed, or never married). Permanent residence was classified as urban or rural. Other variables were dichotomized into a simple \"yes or no\" format.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eThe characteristics of the sample were thoroughly measured and subjected to a descriptive analysis. To identify differences between groups with and without depressive symptoms at baseline, variance t-tests were employed for numerical variables, and chi-square tests were used for categorical variables. The variables are presented in different formats for clarity: continuous variables are shown as medians, with the interquartile range (25%-75%) in parentheses, while categorical variables are expressed as counts (percentages). To determine the associations between grip strength groups, cognitive function, and depressive symptoms, both binary logistic regression and multiple linear regression analyses were employed. These analyses produced effect estimates and 95% confidence intervals (CI). Three distinct models were introduced for this purpose: Model 1, which was unadjusted; Model 2, which was adjusted for Gender, Age, BMI; and Model 3, which was adjusted for the variables in Model 2, as well as additional factors like Education, Permanent address, Marital status, Hypertension, Dyslipidemia, Diabetes, Psychiatric problems, Smoking, and Alcohol consumption. Additionally, Pearson correlation analysis was conducted to examine the relationships between the variables involved in this study.\u003c/p\u003e \u003cp\u003eMediation analysis was a significant component of this module, and it was performed using the Mediation package available in R. The bootstrap method was employed to estimate confidence intervals for the mediation effects. The significance of these mediation effects was determined based on whether the confidence interval included 0 (indicating non-significance) or did not include 0 (indicating significance). Furthermore, to assess the stability of results and examine gender and age differences in the associations between grip strength, cognitive function, and depressive symptoms, subgroup analyses of the binary logistic regression models were conducted, with these analyses being segmented by gender (male and female) and age groups (\u0026lt;\u0026thinsp;60 and \u0026ge;\u0026thinsp;60). For all analyses conducted in this study, a significance level of P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. The analytical processes were carried out using two software programs: SPSS 26.0 and R (version 4.2.2).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eBaseline Characteristics Analysis of the Sample\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e showcases the baseline characteristics of the participants from the China Health and Retirement Longitudinal Study (CHARLS) database. Among the 6,841 subjects included in this analysis, 1,734 individuals (25.35%) exhibited depressive symptoms. A total of 6,077 (88.8%) participants were classified in the normal grip strength group, while 764 (11.2%) fell into the weak grip strength group. The analysis revealed that participants who were female, lived in urban areas, were unmarried (widowed/separated/single), had lower educational levels, poor hearing, and poor vision, and belonged to the weak grip strength group, had a heightened risk of developing depressive symptoms (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Moreover, individuals with hypertension, diabetes, chronic lung diseases, kidney disease, digestive disease, and psychiatric problems also displayed an increased risk of depression (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of study participants stratified by depressive symptoms\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNO-Depression\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDepression\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;6841\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;5107\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;1734\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e59.00 [52.00, 65.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e59.00 [52.00, 65.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e58.50 [51.00, 65.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.545\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3682 (53.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2961 (58.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e721 (41.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3159 (46.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2146 (42.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1013 (58.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrip strength (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6077 (88.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4585 (89.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1492 (86.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeak\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e764 (11.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e522 (10.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e242 (14.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJunior high and below\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5791 (84.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4246 ( 83.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1545 ( 89.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ehigh school and above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1050 (15.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e861 ( 16.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e189 ( 10.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePermanent address (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5073 (74.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3724 (72.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1349 (77.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1768 (25.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1383 (27.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e385 (22.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e721 (10.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e468 (9.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e253 (14.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnmarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6120 (89.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4639 (90.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1481 (85.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3842 (56.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2757 (54.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1085 (62.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2999 (43.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2350 (46.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e649 (37.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcohol consumption (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4363 (63.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3152 (61.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1211 (69.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2478 (36.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1955 (38.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e523 (30.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1694 (24.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1215 (23.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e479 (27.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyslipidemia (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e706 (10.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e519 (10.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e187 (10.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e417 (6.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e287 (5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e130 (7.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCancer (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40 (0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20 (1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic lung diseases (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e676 (9.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e441 (8.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e235 (13.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver disease (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e280 (4.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e193 (3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e87 (5.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKidney disease (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e417 (6.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e273 (5.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e144 (8.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDigestive disease (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1478 (21.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e971 (19.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e507 (29.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePsychiatric problems (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e65 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35 (2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMemory related disease (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e69 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43 (0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26 (1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArthritis or rheumatism (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2115 (30.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1387 (27.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e728 (42.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsthma (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e253 (3.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e156 (3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e97 (5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNighttime sleep duration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.00 [5.00, 7.50]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.00 [5.00, 7.50]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.00 [5.00, 7.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor sleep quality (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRarely or none of the time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3597 (52.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3247 (63.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e350 (20.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSome or a little of the time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1145 (16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e885 (17.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e260 (15.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOccasionally or a moderate amount of the time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e917 (13.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e506 (9.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e411 (23.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMost or all of the time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1182 (17.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e469 (9.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e713 (41.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHearing (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3292 (48.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2605 (51.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e687 (39.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFair\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2871 (42.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2083 (40.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e788 (45.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e678 (9.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e419 (8.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e259 (14.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLife satisfaction (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5872 (85.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4568 (89.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1304 (75.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFair\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e836 (12.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e482 (9.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e354 (20.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e133 (1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57 (1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e76 (4.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ewaistline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e85.30 [78.40, 92.20]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e86.00 [78.60, 92.60]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e84.60 [78.00, 92.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (median [IQR])\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23.44 [21.15, 25.99]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23.46 [21.20, 26.03]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23.32 [20.96, 25.89]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.089\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ememory (median [IQR])\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.00 [5.00, 10.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.00 [5.00, 10.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.00 [5.00, 9.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eorientation (median [IQR])\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.00 [4.00, 5.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.00 [4.00, 5.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.00 [3.00, 5.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ecomputation (median [IQR])\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.00 [1.00, 5.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.00 [2.00, 5.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.00 [1.00, 5.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edrawing (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1683 (24.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1140 (22.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e543 (31.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1 point\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5158 (75.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3967 (77.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1191 (68.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVision (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3588 (52.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2815 (55.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e773 (44.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFair\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2693 (39.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1973 (38.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e720 (41.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e529 (7.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e292 (5.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e237 (13.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCognitive function (median [IQR])\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16.00 [13.00, 19.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.00 [13.00, 20.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15.00 [12.00, 18.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eAssociations of Grip Strength and Cognitive Function with Depression\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e delineates the relationship between grip strength levels, cognitive function, and depression. After adjusting for various confounders, it was found that older adults in the weak grip strength group were more likely to develop depressive symptoms compared to those in the normal grip strength group (OR: 1.57, 95% CI: 1.32\u0026ndash;1.87). Enhanced cognitive function (OR: 0.94, 95% CI: 0.93\u0026ndash;0.95), along with better orientation (OR: 0.87, 95% CI: 0.83\u0026ndash;0.93), memory (OR: 0.94, 95% CI: 0.92\u0026ndash;0.95), computation (OR: 0.90, 95% CI: 0.87\u0026ndash;0.93), and drawing abilities (OR: 0.93, 95% CI: 0.92\u0026ndash;0.94), were identified as protective factors against depression.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociations of grip strength and cognitive function with depression\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModel1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModel2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModel3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrip strength\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeak\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.42(1.21\u0026ndash;1.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.61(1.35\u0026ndash;1.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.57(1.32\u0026ndash;1.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCognitive Function\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.93(0.92\u0026ndash;0.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.93(0.92\u0026ndash;0.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.94(0.93\u0026ndash;0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrientation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.84(0.56\u0026ndash;0.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.85(0.81\u0026ndash;0.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.87(0.83\u0026ndash;0.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMemory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.93(0.92\u0026ndash;0.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.93(0.91\u0026ndash;0.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.94(0.92\u0026ndash;0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComputation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.87(0.84\u0026ndash;0.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.89(0.86\u0026ndash;0.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.90(0.87\u0026ndash;0.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrawing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1 point\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.63(0.55\u0026ndash;0.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.68(0.60\u0026ndash;0.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.93(0.92\u0026ndash;0.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eModel 1, unadjusted; Model 2, adjusted for Gender, Age, BMI; Model 3, adjusted for variables in Model 2 as well as Education, Permanent address, Marital status, Hypertension, Dyslipidemia, Diabetes, Psychiatric problems, Smoking, Alcohol consumption.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eThe Bivariate Correlations for All Variables\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the bivariate correlations for all variables. It was observed that grip strength and cognitive function (including memory, drawing, orientation, computation) were negatively associated with depression. On the other hand, grip strength showed a positive association with depression, justifying further moderated mediation analysis.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation for the main variables\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1.Grip strength\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2.Depression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.148\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3.Cognitive function\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.220\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.133\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4.Memory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.148\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.091\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.874\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5.Drawing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.194\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.073\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.422\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.239\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6.Orientation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.161\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.085\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.555\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.297\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.310\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7.Computation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.175\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.120\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.628\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.247\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.269\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.280\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003csup\u003e***\u003c/sup\u003eP\u0026lt;0.001\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eMediating Effects of Cognitive Function in the Association between Grip Strength and Depression\u003c/h2\u003e \u003cp\u003eThe results illustrated the impact of grip strength on depression through cognitive function, while controlling for 11 covariates potentially associated with the study variables (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Grip strength level was a significant negative predictor of depression (β = -0.088, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and a significant positive predictor of cognitive function (β\u0026thinsp;=\u0026thinsp;0.220, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Additionally, a negative correlation was found between cognitive function and depression (β = -0.133, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The indirect influence of grip strength on depression through cognitive function was also revealed (β = -0.008, 95% CI [-0.013, -0.004]), accounting for 9.4% of the effect.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe moderated mediating effect of grip strength class on depression by cognitive function.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIndependent variable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMediator\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eTotal effect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eIndirect effect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eDirect effect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eProportion mediated, % (95% CI)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCoefficient (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCoefficient (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCoefficient (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eGrip strength class\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDrawing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.087 (-0.126, -0.053)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.000 (-0.004, 0.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.376\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.086 (-0.125, -0.052)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.3 (-1.3, 4.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMemory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.088 (-0.127, -0.054)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.005 (-0.008, -0.002)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.083 (-0.121, -0.050)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.6 (1.9, 11.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eorientation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.087 (-0.126, -0.053)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.003 (-0.006, -0.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.084 (-0.123, -0.051)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3.6 (1.2, 7.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ecomputation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.087 (-0.126, -0.053)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.004 (-0.007, -0.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.084 (-0.123, -0.050)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4.2 (0.9, 8.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCognitive function\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.088 (-0.127, -0.054)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.008 (-0.013, -0.004)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.080 (-0.118, -0.046)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e9.4 (4.6, 17.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eThe mediation analyses were adjusted for Age, BMI, Gender, Education, Permanent address, Marital status, Hypertension, Dyslipidemia, Diabetes, Smoking and Alcohol consumption, p:P value; CI: Confidence interval\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eSensitivity and Subgroup Analyses\u003c/h2\u003e \u003cp\u003eThe sensitivity analysis was enhanced by conducting subgroup analyses stratified by gender and age. These analyses disclosed no significant age or gender differences in the relationship between weak grip strength, cognitive function, and the incidence of depression. This finding emphasizes the consistency and robustness of our results (Supplementary File 2: Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study represents a pioneering exploration into the mediating role of cognitive function in the relationship between grip strength and the incidence of depression among middle-aged and elderly individuals in China. Our research findings underscore that weak grip strength, after accounting for potential confounding factors, is a notable risk factor for depression within this demographic group (OR: 1.57, 95% CI: 1.32\u0026ndash;1.87). In contrast, an elevated level of cognitive function (OR: 0.94, 95% CI: 0.93\u0026ndash;0.95) emerges as a protective factor against depression among the middle-aged and elderly population in China. Interestingly, our results indicate that cognitive function partially mediates the relationship between grip strength and the incidence of depression.\u003c/p\u003e \u003cp\u003eThe utility of grip strength as a straightforward, economical risk stratification tool is well-recognized, particularly in clinical settings. Its simplicity, portability, and low cost make it an attractive tool for assessing individual health risks ([\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]). Previous research into grip strength and depression has indicated that weak grip strength might be a risk factor for depression in middle-aged and elderly individuals [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. These studies have suggested a dose-response relationship between grip strength and depression risk, highlighting a negative correlation between grip strength and the risk of depression. Our study aligns with these findings, as we discovered that individuals with weaker grip strength, after adjusting for potential confounding factors, have a 1.45 times higher odds of developing depression [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Elderly individuals in the lowest quartile of muscle strength are more prone to experiencing symptoms of depression and suicidal thoughts [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Our study extends these insights by stratifying grip strength based on body mass index (BMI) and identifying weak grip strength levels under different BMI conditions [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. We delved into analyzing the relationship between the weak grip strength group and the incidence of depression, suggesting that weak grip strength levels can be a useful indicator for monitoring depression in the middle-aged and elderly population. Our findings advocate for primary healthcare providers to regularly assess grip strength levels in this demographic, especially those with weak grip strength, and to implement appropriate interventions, such as scientific physical exercise or resistance training, to alleviate depression.\u003c/p\u003e \u003cp\u003eThe association between cognition and grip strength is also a critical aspect of our findings. Epidemiological studies have established that weaker grip strength is linked to cognitive decline, an increased risk of mental illnesses, and dementia. For example, an analysis involving 190,406 adult participants from the UK Biobank revealed a correlation between hand grip strength and measures of neurocognitive health in both males and females [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. In populations with depression, cognitive tasks like reaction time and working memory have shown associations with maximum grip strength, influencing the risk of dementia [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The reciprocal relationship between grip strength and cognition is also evident in some studies suggesting that muscle strength deficits lead to cognitive decline [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e][\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. However, this perspective is challenged by conflicting findings in other studies [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e] that propose individuals with better cognitive abilities exhibit superior handgrip strength (HGS) values compared to those with poorer cognitive abilities. There is significant evidence indicating an association between cognitive changes and reduced grip strength (HGS) [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Cognitive impairments affect the muscle strength of older individuals, influencing their functional capacity and subsequent dependency. A decline in inhibitory function and grip strength is evident in middle-aged individuals, showing a significant correlation [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. A recent study involving 5995 Korean participants confirmed a bidirectional relationship between grip strength and cognitive function, suggesting a common pathway between these two structures [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. This suggests that grip strength can be a supplementary measure for assessing cognitive abilities in older adults.\u003c/p\u003e \u003cp\u003eFurthermore, our study indicates an increase in the likelihood of depression with cognitive decline, with individuals experiencing cognitive decline at an elevated risk of progressing to mild cognitive impairment (MCI) and dementia [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Numerous longitudinal studies have identified a decline in cognitive abilities among elderly individuals with symptoms of depression or diagnosed depression [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. The level of cognitive functioning not only influences the severity of depressive symptoms but also impacts the types of symptoms reported [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. Research exploring broader cognitive indicators has encompassed areas such as memory, executive function, reasoning, and processing speed [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. The severity of depressive symptoms is often associated with poorer cognitive performance in neuropsychological tests, revealing specific domain deficits in memory, attention, executive function, and processing speed [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. The relationship between depression, brain abnormalities, and cognitive decline is dynamic over time, necessitating an analysis of cognitive decline across various domains to investigate subtle early changes related to mental states. These factors may be intricately linked to the complexity of neural and motor functions.\u003c/p\u003e \u003cp\u003eImportantly, our study indicates that cognitive function acts as an intermediary in the relationship between weak grip strength and the likelihood of depression. In our analysis, mediation analysis revealed a significant pathway involving grip strength levels, cognitive function, and depressive status. Further subdivision of cognitive function indicators for mediation analysis revealed that, apart from drawing ability, memory, orientation, and calculation \u0026ndash; three cognitive abilities \u0026ndash; demonstrated significant mediation effects on the relationship between grip strength and depressive symptoms in middle-aged and elderly individuals (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This finding offers new evidence in the existing literature, suggesting that grip strength may positively impact subsequent depression through the cognitive abilities of older adults, including memory, orientation, and calculation. Although the mechanisms supporting the impact of cognitive function on the association between grip strength and depressive symptoms are not yet fully understood, several hypotheses have been proposed, both biologically and psychologically. One plausible mechanism linking grip strength to depression involves low-grade inflammation, a condition prevalent in approximately one-fourth of individuals with depression, with over half of these individuals exhibiting mild elevations in C-reactive protein levels [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. In a study, inflammatory factors (plasma interleukin (IL)-6 and C-reactive protein (CRP)) were shown to be associated with midlife cognition through changes in brain morphology [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. Physical exercise or resistance training, known to increase muscle strength and reduce systemic inflammation, can also improve cognitive function, thereby contributing to the alleviation of depressive symptoms [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. Another crucial factor that may influence the relationship between depression and cognition is age-related structural changes in the brain, particularly hippocampal volume loss. Older individuals with depression and reduced hippocampal volume are at a greater risk of cognitive decline [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. Brain-derived neurotrophic factor (BDNF) plays a role in regulating hippocampal plasticity, and its deficiency is implicated in the pathophysiology of depression. BDNF is considered essential for maintaining hippocampal integrity and cognition [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. Depression is associated with low levels of brain-derived neurotrophic factor (BDNF), which is crucial for emotional processing, memory, and learning [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. Evidence suggests that the lack of BDNF plays a significant role in the pathophysiology of depression, and exercise-induced increases in BDNF can improve hippocampal atrophy, consequently enhancing cognitive functions such as memory [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e], thus supporting the notion of reducing depression. Beyond the impact of exercise on improving inflammation and neurotrophic factors, in psychological terms, exercise may contribute to a sense of mental well-being. Various psychosocial factors may also influence susceptibility to illness. For instance, a robust physique may be associated with reduced psychological distress (i.e., stress and negative impacts) and better mental health (i.e., optimism and self-esteem) [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. Individuals engaged in regular exercise are more likely to foster supportive social relationships, potentially reducing the severity of depression [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. Therefore, comprehensive research is needed in the future to understand how different factors mediate the relationship between grip strength and depression.\u003c/p\u003e \u003cp\u003eOur research findings may have potential theoretical implications for attenuating and improving depressive symptoms in middle-aged and elderly individuals. Weak grip strength levels can serve as an indicator for monitoring depression susceptibility in this population. Primary healthcare practitioners should regularly assess grip strength levels in middle-aged and elderly individuals, with particular attention to those with weak grip strength. Grip strength can be enhanced through physical exercise or resistance training [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e]. Simultaneously, cognitive functions can be improved through activities such as exercise games [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e], meditation [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e], music [\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e], and dance therapy [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. These interventions aim to mitigate the relationship between low grip strength levels and the risk of depression.\u003c/p\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eWhile this study draws on a nationally representative sample of middle-aged and elderly individuals in China, providing novel insights into the moderating role of cognitive function in the relationship between grip strength and depressive symptoms, it is not without its limitations. Firstly, the cross-sectional nature of this study precludes the ability to infer causal or bidirectional relationships among grip strength, cognition, and depression. This limitation is significant as it restricts the understanding of the temporal sequence of these associations. Secondly, the reliance on self-reported data for many variables, including sociodemographic and health-related factors, introduces the potential for recall bias. Participants' recollections may not always be accurate, which could affect the reliability of the findings. Lastly, while the study made efforts to adjust for various potential confounders, there remains the possibility that other unmeasured factors, such as dietary patterns [\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e], levels of inflammation [\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e], and additional indicators, might have influenced the results. Future research endeavors should consider a more comprehensive approach, possibly incorporating longitudinal designs, to better understand the intricate relationships between depression and its related risk factors.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis cross-sectional study, utilizing data from the China Health and Retirement Longitudinal Study (CHARLS), reveals that weak grip strength is significantly associated with an increased risk of depressive symptoms among middle-aged and elderly individuals. Importantly, the study also finds that elevated cognitive function appears to mitigate this association. These findings underscore the importance of considering grip strength as a potential indicator of depression risk in this demographic. In future research and clinical practice, identifying individuals with weak grip strength could be key in recognizing those at higher risk for depression. Targeted interventions, possibly focusing on enhancing grip strength and cognitive function, could be beneficial in reducing the risk and severity of depressive symptoms in middle-aged and elderly populations.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contribution\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConceptualization and methodology:\u003c/strong\u003e Xinzheng Wang，Huifen Zhou，Jiandong He\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData curation, formal analysis, and visualization:\u0026nbsp;\u003c/strong\u003eXinzheng Wang， Guohao Yi\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWriting\u0026mdash;original draft:\u0026nbsp;\u003c/strong\u003eXinzheng Wang, Lifei Wu\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWriting\u0026mdash;review and editing:\u0026nbsp;\u003c/strong\u003eXinzheng Wang, Guohao Yi, Lifei Wu, Huifen Zhou，Jiandong He\u003c/p\u003e\n\u003cp\u003eAll authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data provided in this article are available in a\u003c/p\u003e\n\u003cp\u003epublic, open access repository, and can be accessed at China Health and Retirement Longitudinal Study (CHARLS) \u0026nbsp; https://charls.pku.edu.cn/en/ \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGBD 2019 Diseases and Injuries Collaborators. Global burden of 369 diseases and injuries in 204 countries and territories, 1990\u0026ndash;2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet. 2020;396(10258):1204\u0026ndash;1222. doi: 10.1016/S0140-6736(20)30925-9. Erratum in: Lancet. 2020;396(10262):1562. PMID: 33069326; PMCID: PMC7567026.).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDwyer JB, Aftab A, Radhakrishnan R, et al. Hormonal treatments for major depressive disorder: state of the art. Am J Psychiatry. 2020;177:686\u0026ndash;705.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization. Depression and other common mental disorders, World Health Organization. 2017 Jan. URL: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/publications/i/item/depression-global-health-estimates\u003c/span\u003e\u003cspan address=\"https://www.who.int/publications/i/item/depression-global-health-estimates\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e [accessed 2022-01-04].\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLei X, Sun X, Strauss J, Zhang P, Zhao Y. Depressive symptoms and SES among the mid-aged and elderly in China: evidence from the China Health and Retirement Longitudinal Study national baseline. Soc Sci Med. 2014;120:224\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang Y, Chen Q, Liu. Lurong. Meta-analysis of Depression Detection Rate and Influencing Factors in Chinese Elderly Population[J]. Chin J Gen Pract. 2023;26(34):4329\u0026ndash;35.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang Y. Is old age depressing? Growth trajectories and cohort variations in late-life depression. J Health Soc Behav. 2007;48(1):16\u0026ndash;32. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/002214650704800102\u003c/span\u003e\u003cspan address=\"10.1177/002214650704800102\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJi Y, Chen H, Yang Y, Zhou Y, Li H, Jin H, Xie J, Shen B. Health-related quality of life and survival outcomes for patients with major depressive disorder and anxiety: A longitudinal study in pancreatic ductal adenocarcinoma. Cancer Med. 2023;12(19):20070\u0026ndash;80. Epub 2023 Sep 25. PMID: 37746894; PMCID: PMC10587956.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRuggieri V. Autismo, depresi\u0026oacute;n y riesgo de suicidio [Autism, depression and risk of suicide]. Med (B Aires). 2020;80(Suppl 2):12\u0026ndash;6. Spanish. PMID: 32150706.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSemenkovich K, Brown ME, Svrakic DM, Lustman PJ. Depression in type 2 diabetes mellitus: prevalence, impact, and treatment. Drugs. 2015;75(6):577\u0026thinsp;\u0026ndash;\u0026thinsp;87. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s40265-015-0347-4\u003c/span\u003e\u003cspan address=\"10.1007/s40265-015-0347-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 25851098.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKrittanawong C, Maitra NS, Qadeer YK, Wang Z, Fogg S, Storch EA, Celano CM, Huffman JC, Jha M, Charney DS, Lavie CJ. Association of Depression and Cardiovascular Disease. Am J Med. 2023;136(9):881\u0026ndash;95. Epub 2023 May 27. PMID: 37247751.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMalhi GS, Mann JJ. Depress Lancet. 2018;392(10161):2299\u0026ndash;312.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFukumori N. Yamamoto Y.Takegami M.Association between hand-grip strength and depressive symptoms: Locomotive Syndrome and Health Outcomes in Aizu Cohort Study (LOHAS).Age Ageing. 2015; 44: 592\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee MR. Y.B.The association between muscular strength and depression in Korean adults: a cross-sectional analysis of the sixth Korea National Health and Nutrition Examination Survey (KNHANES VI) 2014. BMC Public Health. 2018;18:1123.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarques A, Gaspar de Matos M, Henriques-Neto D, Peralta M, Gouveia \u0026Eacute;R, Tesler R, Martins J, Gomez-Baya D. Grip Strength and Depression Symptoms Among Middle-Age and Older Adults. Mayo Clin Proc. 2020;95(10):2134\u0026ndash;2143. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.mayocp.2020.02.035\u003c/span\u003e\u003cspan address=\"10.1016/j.mayocp.2020.02.035\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 33012344.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang F, Yu Y, Wang H, Zhang Y, Bai Y, Huang L, Zhang H. Association between handgrip strength and depression among Chinese older adults: a cross-sectional study from the China Health and Retirement Longitudinal Study. BMC Geriatr. 2023;23(1):299. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12877-023-04034-6\u003c/span\u003e\u003cspan address=\"10.1186/s12877-023-04034-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 37193949; PMCID: PMC10190059.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrooks JM, Titus AJ, Bruce ML, Orzechowski NM, Mackenzie TA, Bartels SJ, Batsis JA. Depression and Handgrip Strength Among U.S. Adults Aged 60 Years and Older from NHANES 2011\u0026ndash;2014. J Nutr Health Aging. 2018;22(8):938\u0026ndash;43. PMID: 30272097; PMCID: PMC6168750.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang XM, Jiao J, Cao J, Guo N, Zhu C, Li Z, Wu X, Xu T. Handgrip Strength and Depression Among Older Chinese Inpatients: A Cross-Sectional Study. Neuropsychiatr Dis Treat. 2021;17:1267\u0026ndash;77. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2147/ndt.S301064\u003c/span\u003e\u003cspan address=\"10.2147/ndt.S301064\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStessman J, Rottenberg Y, Fischer M, Hammerman-Rozenberg A, Jacobs JM. Handgrip strength in old and very old adults: mood, cognition, function, and mortality. J Am Geriatr Soc. 2017;65:526\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTaekema DG, Gussekloo J, Maier AB, Westendorp RGJ, de Craen AJM. Handgrip strength as a predictor of functional, psychological and social health. A prospective population-based study among the oldest old. Age Ageing. 2010;39(3):331\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKaczorowska A, Kaczorowska A, Kowalska J. Associations Between Physical Fitness, Cognitive Function, and Depression in Nursing Homes Residents Between 60\u0026ndash;100 Years of Age in South-Western Poland. Med Sci Monit. 2024;30:e942729. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.12659/MSM.942729\u003c/span\u003e\u003cspan address=\"10.12659/MSM.942729\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 38185903.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRock PL, Roiser JP, Riedel WJ, Blackwell AD. Cognitive impairment in depression: a systematic review and meta-analysis. Psychol Med. 2014;44(10):2029-40. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1017/S0033291713002535\u003c/span\u003e\u003cspan address=\"10.1017/S0033291713002535\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2013 Oct 29. PMID: 24168753.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFerri F, Desch\u0026ecirc;nes SS, Power N, Schmitz N. Associations between cognitive function, metabolic factors and depression: A prospective study in Quebec, Canada. J Affect Disord. 2021;283:77\u0026ndash;83. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2021.01.039\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2021.01.039\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2021 Jan 14. PMID: 33524662.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChristensen GT, Rozing MP, Mortensen EL, Christensen K, Osler M. Young adult cognitive ability and subsequent major depression in a cohort of 666,804 Danish men. J Affect Disord. 2018;235:162\u0026ndash;167. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2018.04.035\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2018.04.035\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2018 Apr 5. PMID: 29656261.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang J, Deng Y, Yan H, Li B, Wang Z, Liao J, Cai X, Zhou L, Tan W, Rong S. Association Between Grip Strength and Cognitive Function in US Older Adults of NHANES 2011\u0026ndash;2014. J Alzheimers Dis. 2022;89(2):427\u0026ndash;436. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3233/JAD-215454\u003c/span\u003e\u003cspan address=\"10.3233/JAD-215454\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 35871326.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFeng W, Ma M, Gao H, Yuan W, Li R, Guo H, Gu C, Sun Z, Zhang Y, Zheng L. Association between handgrip strength asymmetry and cognitive function across ethnicity in rural China: a cross-sectional study. Front Aging Neurosci. 2023;15:1191197. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fnagi.2023.1191197\u003c/span\u003e\u003cspan address=\"10.3389/fnagi.2023.1191197\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 37273648; PMCID: PMC10235480.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFirth J, Stubbs B, Vancampfort D, Firth J, Large M, Rosenbaum S, et al. Grip strength is associated with cognitive performance in schizophrenia and the general population: a UK biobank study of 476559 participants. Schizop Bull. 2018;44:728\u0026ndash;36. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/schbul/sby034\u003c/span\u003e\u003cspan address=\"10.1093/schbul/sby034\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJin Y, Xu L, Jiang C, Zhang W, Pan J, Zhu F, et al. Association of hand grip strength with mild cognitive impairment in middle-aged and older people in guangzhou biobank cohort study. Int J Environ Res Public Health. 2022;19:11. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijerph19116464\u003c/span\u003e\u003cspan address=\"10.3390/ijerph19116464\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCui M, Zhang S, Liu Y, Gang X, Wang G. Grip Strength and the risk of cognitive decline and dementia: a systematic review and meta-analysis of longitudinal cohort studies. Front Aging Neurosci. 2021;13:625551. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fnagi.2021.625551\u003c/span\u003e\u003cspan address=\"10.3389/fnagi.2021.625551\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSibbett RA, Russ TC, Allerhand M, Deary IJ, Starr JM. Physical fitness and dementia risk in the very old: a study of the Lothian Birth Cohort 1921. BMC Psychiatry. 2018;18:285. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12888-018-1851-3\u003c/span\u003e\u003cspan address=\"10.1186/s12888-018-1851-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDoi T, Tsutsumimoto K, Nakakubo S, Kim MJ, Kurita S, Hotta R, et al. Physical performance predictors for incident dementia among japanese community-dwelling older adults. Phys Therapy. 2019;99:1132\u0026ndash;40. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/ptj/pzz077\u003c/span\u003e\u003cspan address=\"10.1093/ptj/pzz077\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhao Y, Hu Y, Smith JP, Strauss J, Yang G. Cohort profile: the China Health and Retirement Longitudinal Study (CHARLS). Int J Epidemiol. 2014;43(1):61\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/ije/dys203\u003c/span\u003e\u003cspan address=\"10.1093/ije/dys203\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2012 Dec 12. PMID: 23243115; PMCID: PMC3937970.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBao M, Chao J, Sheng M, Cai R, Zhang N, Chen H. Longitudinal association between muscle strength and depression in middle-aged and older adults: A 7-year prospective cohort study in China. J Affect Disord. 2022;301:81\u0026ndash;6. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2022.01.036\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2022.01.036\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMak JKL, Kuja-Halkola R, Wang Y, H\u0026auml;gg S, Jylh\u0026auml;v\u0026auml; J. Can frailty scores predict the incidence of cancer? Results from two large population-based studies. Geroscience. 2023;45(3):2051\u0026ndash;64. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11357-023-00783-9\u003c/span\u003e\u003cspan address=\"10.1007/s11357-023-00783-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2023 Mar 30. PMID: 36997701; PMCID: PMC10400738.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCrimmins EM, Kim JK, Langa KM, Weir DR. Assessment of cognition using surveys and neuropsychological assessment: the Health and Retirement Study and the Aging, Demographics, and Memory Study. J Gerontol B Psychol Sci Soc Sci. 2011;66:i162\u0026ndash;71.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCao L, Zhao Z, Ji C, Xia Y. Association between solid fuel use and cognitive impairment: A cross-sectional and follow-up study in a middle-aged and older Chinese population. Environ Int. 2021;146:106251.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGabriel A, Zare H, Jones W, Yang M, Ibe CA, Cao Y, et al. Evaluating depressive symptoms among low-socioeconomic-status African American women aged 40 to 75 years with uncontrolled hypertension: a secondary analysis of a randomized clinical trial. JAMA Psychiatry. 2021;78:426\u0026ndash;32. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1001/jamapsychiatry.2020.4622\u003c/span\u003e\u003cspan address=\"10.1001/jamapsychiatry.2020.4622\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization. Ageing and health. 2018. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003c/span\u003e\u003cspan address=\"http://www.who.int/news-room/fact-sheets/detail/ageing-and-health\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZare S, Hasani M, Est\u0026ecirc;v\u0026atilde;o MD, Tahmasebi R, Azadbakht L, Shidfar F, Heshmati J, Ziaei S. Muscle Strength and Biochemical Markers as Predictors of Depression in Hemodialysis Patients: A Cross-Sectional Study. Clin Nutr Res. 2023;12(4):293\u0026ndash;303. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.7762/cnr.2023.12.4.293\u003c/span\u003e\u003cspan address=\"10.7762/cnr.2023.12.4.293\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 37969939; PMCID: PMC10641328.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMuhammad T, Maurya P. Relationship between handgrip strength, depression and cognitive functioning among older adults: Evidence from longitudinal ageing study in India. Int J Geriatr Psychiatry. 2022;37(8). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/gps.5776\u003c/span\u003e\u003cspan address=\"10.1002/gps.5776\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 35785433.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eL\u0026oacute;pez-Bueno R, Calatayud J, Andersen LL, Casa\u0026ntilde;a J, Koyanagi A, Del Pozo Cruz B, Smith L. Dose-response association of handgrip strength and risk of depression: a longitudinal study of 115 601 older adults from 24 countries. Br J Psychiatry. 2023;222(3):135\u0026ndash;42. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1192/bjp.2022.178\u003c/span\u003e\u003cspan address=\"10.1192/bjp.2022.178\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 36464972; PMCID: PMC9929711.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAshdown-Franks G, Stubbs B, Koyanagi A, Schuch F, Firth J, Veronese N, et al. Handgrip strength and depression among 34,129 adults aged 50 years and older in six low- and middle-income countries. J Affect Disord. 2019;243:448\u0026ndash;54.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKyu-Man H, Jisoon C, Ho-Kyoung Y, Young-Hoon K, Byung-Joo H, Yong-Ku K, et al. Relationships between hand-grip strength, socioeconomic status, and depressive symptoms in community-dwelling older adults. J Affect Disord. 2019;252:263\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZasadzka E, Pieczynska A, Trzmiel T, Kleka P, Pawlaczyk M. Correlation between Handgrip Strength and Depression in older Adults-A systematic review and a Meta-analysis. Int J Environ Res Public Health 2021,18(9).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDuchowny KA, Ackley SF, Brenowitz WD, Wang J, Zimmerman SC, Caunca MR, Glymour MM. Associations between Handgrip Strength and Dementia Risk, Cognition, and neuroimaging outcomes in the UK Biobank Cohort Study. JAMA Netw Open. 2022;5(6):e2218314.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcGough EL, Cochrane BB, Pike KC, Logsdon RG, McCurry SM, Teri L. Dimensions of physical frailty and cognitive function in older adults with amnestic mild cognitive impairment. Ann Phys Rehabil Med. 2013;56(5):329\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKan GA, Cesari M, Gillette-Guyonnet S, Dupuy C, Nourhash\u0026eacute;mi F, Schott AM, Beauchet O, Annweiler C, Vellas B, Rolland Y. Sarcopenia and cognitive impairment in elderly women: results from the EPIDOS cohort. Age Ageing. 2013;42(2):196\u0026ndash;202.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUkegbu U, Maselko J, Malhotra R, Perera B, \u0026Oslash;stbye T. Correlates of Handgrip Strength and activities of daily living in elderly Sri Lankans. J Am Geriatr Soc. 2014;62(9):1800\u0026ndash;1.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eallucci M, Mazzuco S, Ongaro F, Di Giorgi E, Mecocci P, Cesari M, Albani D, Forloni GL, Durante E, Gajo GB, Zanardo A, Siculi M, Caberlotto L, Regini C. Body mass index, lifestyles, physical performance and cognitive decline: the Treviso Longeva (TRELONG) study. J Nutr Health Aging. 2013;17(4):378\u0026ndash;84.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSilva N, Menezes TN. Associa\u0026ccedil;\u0026atilde;o entre cogni\u0026ccedil;\u0026atilde;o e for\u0026ccedil;a de preens\u0026atilde;o manual em idosos: revis\u0026atilde;o integrativa [The association between cognition and handgrip strength among the elderly: an integrative review]. Cien Saude Colet. 2016;21(11):3611\u0026ndash;3620. Portuguese. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1590/1413-812320152111.22872015\u003c/span\u003e\u003cspan address=\"10.1590/1413-812320152111.22872015\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 27828593.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAdamo DE, Anderson T, Koochaki M, et al. Declines in grip strength may indicate early changes in cognition in healthy middle-aged adults. PLoS ONE. 2020;15(4):e0232021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim GR, Sun J, Han M, Nam CM, Park S. Evaluation of the directional relationship between handgrip strength and cognitive function: the Korean Longitudinal Study of Ageing. Age Ageing. 2019;48(3):426\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShimada H, Park H, Makizako H, Doi T, Lee S, Suzuki T. Depressive symptoms and cognitive performance in older adults. J Psychiatr Res. 2014;57:149\u0026thinsp;\u0026ndash;\u0026thinsp;56. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jpsychires.2014.06.004\u003c/span\u003e\u003cspan address=\"10.1016/j.jpsychires.2014.06.004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2014 Jun 24. PMID: 25023083.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGuan Q, Hu X, Ma N, He H, Duan F, Li X, Luo Y, Zhang H. Sleep Quality, Depression, and Cognitive Function in Non-Demented Older Adults. J Alzheimers Dis. 2020;76(4):1637\u0026ndash;1650. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3233/JAD-190990\u003c/span\u003e\u003cspan address=\"10.3233/JAD-190990\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 32675408.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDotson VM, McClintock SM, Verhaeghen P, Kim JU, Draheim AA, Syzmkowicz SM, Gradone AM, Bogoian HR, Wit L. Depression and Cognitive Control across the Lifespan: a Systematic Review and Meta-Analysis. Neuropsychol Rev. 2020;30(4):461\u0026ndash;76. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11065-020-09436-6\u003c/span\u003e\u003cspan address=\"10.1007/s11065-020-09436-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2020 May 8. PMID: 32385756; PMCID: PMC9637269.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrailean A, Comijs HC, Aartsen MJ, Prince M, Prina AM, Beekman A, Huisman M. Late-life depression symptom dimensions and cognitive functioning in the Longitudinal Aging Study Amsterdam (LASA). J Affect Disord. 2016;201:171\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2016.05.027\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2016.05.027\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2016 May 19. PMID: 27235820; PMCID: PMC4914607.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJiang R, Westwater ML, Noble S, Rosenblatt M, Dai W, Qi S, Sui J, Calhoun VD, Scheinost D. Associations between grip strength, brain structure, and mental health in \u0026gt;\u0026thinsp;40,000 participants from the UK Biobank. BMC Med. 2022;20(1):286. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12916-022-02490-2\u003c/span\u003e\u003cspan address=\"10.1186/s12916-022-02490-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 36076200; PMCID: PMC9461129.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJamieson A, Goodwill AM, Termine M, Campbell S, Szoeke C. Depression related cerebral pathology and its relationship with cognitive functioning: A systematic review. J Affect Disord. 2019;250:410\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2019.03.042\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2019.03.042\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2019 Mar 6. PMID: 30878653.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOsimo EF, Baxter LJ, Lewis G, Jones PB, Khandaker GM. Prevalence of low-grade inflammation in depression: a systematic review and meta-analysis of CRP levels. Psychol Med. 2019;49(12):1958\u0026ndash;70. Epub 2019 Jul 1. PMID: 31258105; PMCID: PMC6712955.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKunutsor SK, Isiozor NM, Voutilainen A, Laukkanen JA. Handgrip strength and risk of cognitive outcomes: new prospective study and meta-analysis of 16 observational cohort studies. Geroscience. 2022;44(4):2007\u0026ndash;24. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11357-022-00514-6\u003c/span\u003e\u003cspan address=\"10.1007/s11357-022-00514-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2022 Jan 10. PMID: 35013908; PMCID: PMC9616970.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarsland AL, Gianaros PJ, Kuan DC, Sheu LK, Krajina K, Manuck SB. Brain morphology links systemic inflammation to cognitive function in midlife adults. Brain Behav Immun. 2015;48:195\u0026ndash;204. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.bbi.2015.03.015\u003c/span\u003e\u003cspan address=\"10.1016/j.bbi.2015.03.015\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2015 Apr 14. PMID: 25882911; PMCID: PMC4508197.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVerhoeven F, Tordi N, Prati C, Demougeot C, Mougin F, Wendling D. Physical activity in patients with rheumatoid arthritis. Jt Bone Spine. 2016;83:265\u0026ndash;70. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jbspin.2015.10.002\u003c/span\u003e\u003cspan address=\"10.1016/j.jbspin.2015.10.002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBaksh RA, Ritchie CW, Terrera GM, Norton J, Raymont V, Ritchie K. The association between anxiety disorders and hippocampal volume in older adults. Psychol Aging. 2021;36(2):288\u0026ndash;97. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1037/pag0000597\u003c/span\u003e\u003cspan address=\"10.1037/pag0000597\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2021 Mar 4. PMID: 33661669.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKanellopoulos D, Gunning FM, Morimoto SS, Hoptman MJ, Murphy CF, Kelly RE, Glatt C, Lim KO, Alexopoulos GS. Hippocampal volumes and the brain-derived neurotrophic factor val66met polymorphism in geriatric major depression. Am J Geriatr Psychiatry. 2011;19(1):13\u0026ndash;22. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/jgp.0b013e3181f61d62\u003c/span\u003e\u003cspan address=\"10.1097/jgp.0b013e3181f61d62\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 21218562; PMCID: PMC3058412.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrunoni, 。Brunoni AR, Lopes M, Fregni F et al. 2008. A systematic review and meta-analysis of clinical studies on major depression and BDNF levels: implications for the role of neuroplasticity in depression. Int. J. Neuropsychopharmacol. 11, 1169\u0026ndash;1180. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1017/S1461145708009309\u003c/span\u003e\u003cspan address=\"10.1017/S1461145708009309\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eErickson KI, Miller DL, Roecklein KA. The aging hippocampus: interactions between exercise, depression, and BDNF. Neuroscientist. 2012;18(1):82\u0026ndash;97. doi: 10.1177/1073858410397054. Epub 2011 Apr 29. PMID: 21531985; PMCID: PMC3575139.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRodriguez-Ayllon M, Cadenas-Sanchez C, Esteban-Cornejo I, Migueles JH, Mora-Gonzalez J, Henriksson P, Mart\u0026iacute;n-Matillas M, Mena-Molina A, Molina-Garc\u0026iacute;a P, Est\u0026eacute;vez-L\u0026oacute;pez F, Enriquez GM, Perales JC, Ruiz JR, Catena A, Ortega FB. Physical fitness and psychological health in overweight/obese children: A cross-sectional study from the ActiveBrains project. J Sci Med Sport. 2018;21(2):179\u0026ndash;184. doi: 10.1016/j.jsams.2017.09.019. Epub 2017 Oct 4. PMID: 29031643.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHallgren M, Lundin A, Tee FY, Burstr\u0026ouml;m B, Forsell Y. Somebody to lean on: Social relationships predict post-treatment depression severity in adults. Psychiatry Res. 2017;249:261\u0026ndash;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.psychres.2016.12.060\u003c/span\u003e\u003cspan address=\"10.1016/j.psychres.2016.12.060\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2017 Jan 17. PMID: 28131948.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhodadad Kashi S, Mirzazadeh ZS, Saatchian VA, Systematic Review. Meta-Analysis of Resistance Training on Quality of Life, Depression, Muscle Strength, and Functional Exercise Capacity in Older Adults Aged 60 Years or More. Biol Res Nurs. 2023;25(1):88\u0026ndash;106. Epub 2022 Aug 13. PMID: 35968662.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRosenberg D, Depp CA, Vahia IV, Reichstadt J, Palmer BW, et al. Exergames for subsyndromal depression in older adults: a pilot study of a novel intervention. Am J Geriatr Psychiatry. 2010;18:221\u0026ndash;26.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNash JD, Newberg A. Toward a unifying taxonomy and definition for meditation. Front Psychol. 2013;4:806.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHars M, Herrmann FR, Gold G, Rizzoli R, Trombetti A. Effect of music-based multitask training on cognition and mood in older adults. Age Ageing. 2014;43:196\u0026ndash;200.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMurrock CJ, Graor CH. The effects of dance on depression, physical function, and disability in underserved adults. J Aging Phys Act. 2014;22(3):380\u0026ndash;85.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarx W, Lane M, Hockey M, et al. Diet and depression: exploring the biological mechanisms of action. Mol Psychiatry. 2021;26:134\u0026ndash;50. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41380-020-00925-x\u003c/span\u003e\u003cspan address=\"10.1038/s41380-020-00925-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVerhoeven F, Tordi N, Prati C, Demougeot C, Mougin F, Wendling D. Physical activity in patients with rheumatoid arthritis. Jt Bone Spine. 2016;83:265\u0026ndash;70. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jbspin.2015.10.002\u003c/span\u003e\u003cspan address=\"10.1016/j.jbspin.2015.10.002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Grip Strength, Cognitive Function, Depression, Mediation analysis","lastPublishedDoi":"10.21203/rs.3.rs-4207923/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4207923/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eThis study investigates the associations and mediating pathways between grip strength, cognitive function, and depression in middle-aged and elderly individuals in China.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eUtilizing data from the 2011 China Health and Retirement Longitudinal Study (CHARLS), we employed logistic regression and mediation analysis to examine the relationships and mediating factors between grip strength, cognitive function, and depression, while adjusting for potential confounders.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe study included 6,841 participants, of whom 1,734 (25.35%) exhibited symptoms of depression. Our findings indicate that weak grip strength is significantly associated with an increased risk of depression (OR: 1.57, 95% CI: 1.32\u0026ndash;1.87) among the middle-aged and elderly population. Conversely, good cognitive function was found to be protective against depression (OR: 0.94, 95% CI: 0.93\u0026ndash;0.95). The analysis revealed that grip strength indirectly affects depression through cognitive function, accounting for 9.4% of the total effect (OR: \u0026minus;0.008, 95% CI: -0.013, \u0026minus;\u0026thinsp;0.004). Specifically, cognitive abilities such as calculation, memory, and orientation were identified as significant mediators in the relationship between grip strength and depression.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThis study highlights that adequate cognitive function can mitigate the association between weak grip strength and an increased risk of depression among middle-aged and elderly individuals in China. These insights provide valuable guidance for clinical practitioners in the diagnosis and management of depression, emphasizing the importance of assessing grip strength and cognitive function.\u003c/p\u003e","manuscriptTitle":"The Mediating Role of Cognitive Function in the Association between Grip Strength and Depression among Chinese middle-aged and elderly adults: A Cross-Sectional Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-08 19:27:19","doi":"10.21203/rs.3.rs-4207923/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"564d5971-1501-4ff0-b25b-4470f4ae74cf","owner":[],"postedDate":"April 8th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-04-29T11:50:27+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-08 19:27:19","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4207923","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4207923","identity":"rs-4207923","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}