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Association between change in handgrip strength and cognitive function in Korean adults: a longitudinal panel study

Abstract

Background

Muscular function, such as handgrip strength, has been suggested as an associated factor for cognitive impairment. This study investigated the association between temporal change in handgrip strength and cognitive function using longitudinal, nationwide data from Korean older adults.

Methods

Our study used data from the Korean Longitudinal Study of Aging (KLoSA). The analysis covered 6696 participants who had taken the handgrip strength test and Mini-Mental State Examination (MMSE) from 2006 to 2018. We adopted general estimating equations to assess the temporal effect of handgrip strength change on cognitive function.

Results

After adjusting for covariates, we observed an association between handgrip strength and low MMSE scores (β = − 0.3142 in men, β = − 0.2685 in women). Handgrip strength as a continuous variable was positively correlated with MMSE scores after adjustment (β = 0.0293 in men, β = 0.0347 in women). The group with decreased handgrip strength over time also showed greater odds for mild cognitive impairment (OR = 1.23, 95%CI = 1.05–1.27 in men, OR = 1.15, 95%CI = 1.05–1.27 in women) and dementia (OR = 1.393, 95%CI = 1.18–1.65 in men, OR = 1.19, 95%CI = 1.08–1.32 in women).

Conclusions

This study identified the relationship between handgrip strength change and cognitive function among South Korean adults. According to our large, longitudinal sample, decreasing handgrip strength was associated with decline in cognitive function.

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Background

As aging progresses, impairment in cognitive function may arise, and its intensified form, dementia, is considered a major health problem worldwide [1]. Cognitive impairment induces socio-economic burden by causing poor quality of life, hospitalization, increased mortality, and poverty [2,3,4,5]. However, cognitive decline generally occurs gradually. Its onset or early phase is not easy to detect, with patients remaining undiagnosed until they display some functional impairment. Progression is likewise difficult to stop because cognitive impairment is a degenerative disease. Therefore, many studies have focused on methods to prevent cognitive impairment, including early detection and intervention, for example, by prescribing drugs such as donepezil, which is now widely used in clinical settings [6, 7].

Studies have suggested the various factors associated with cognitive impairment and the ways to prevent decline based on those factors. The patient’s neuropsychiatric condition, including depression, insomnia, or drug use [8,9,10,11,12,13], or chronic disease, such as hypertension or diabetes [14, 15], have been associated with cognitive decline. Other studies have pointed to several modifiable health behaviors including exercise, and body conditions, such as body mass index (BMI) and muscle mass, as being associated with dementia [16]. Among these, the relationship between handgrip strength, which can be easily measured, and cognitive impairment is becoming increasingly apparent [17].

A longitudinal study conducted in the United States positively linked handgrip strength with cognitive function, and a cohort study on Mexican Americans showed the association between baseline handgrip strength and Mini-Mental State Examination (MMSE) scores [18, 19]. A recent study using a longitudinal panel also showed that lower handgrip strength was associated with a higher odds ratio for cognitive impairment in aging Americans [20]. Similarly, a longitudinal study conducted in South Korea indicated the association between greater handgrip strength and a lower odds ratio of cognitive impairment [13]. However, few studies have investigated the association between changes in handgrip strength and cognitive impairment [17]. The confirmation of such an association in a large sample and through longitudinal design study would be useful as a basis for preventing cognitive decline by modulating handgrip strength via strength exercises. Therefore, we aimed to investigate the association between changes in handgrip strength and cognitive function in the Korean adult population based on a panel study, after adjusting for covariates that were assumed to affect cognitive function.

Methods

Study population and data

The data analyzed in this study were taken from the Korean Longitudinal Study of Aging database (KLoSA). The KLoSA is a longitudinal panel survey of nationally representative samples of community-dwelling adults aged above 45 years, and has been conducted every 2 years since 2006 [21]. The baseline data, gathered in 2006, include 10,254 Korean adults who have been interviewed by trained interviewers. The survey gathers information on respondents’ family background, demographics, family composition, health, employment, income, assets, subjective expectations, and subjective quality of life. The seventh wave of KLoSA, conducted in 2018, covered an effective sample of 6136 from the original panels and 804 newly included panels. In the present study, we employed survey data from 2006 to 2018, for a total of seven datasets. After deleting data with missing values for variables, we analyzed data from 6696 participants, including 2999 men and 3697 women. For statistical analysis, each change in handgrip strength from 2006 to 2018 was treated as an individual case rather than the population number itself. As KLoSA provides data in de-identified form which is open data for academic use, the need for informed consent was waived by the Institutional Review Board of Yonsei University’s Health System (4–2021-0307).

Measures

Mini-mental state examination

To measure the cognitive function of the participants, we referred to their MMSE scores. The MMSE is a widely used tool for measuring cognitive function and screening for cognitive impairment in older adults [22, 23]. The validity of the Korean version of the MMSE (k-MMSE) has been established for its usefulness in screening for cognitive impairment [24]. With a total score of 30, the MMSE’s cut-off level for mild cognitive impairment is 23 and that for dementia is 19 [25]. We used total scores for analysis to reveal detailed results regarding the association.

Handgrip strength

The KLoSA measures handgrip strength in kilograms using a handgrip dynamometer (Hand Grip Meter 6103, Tanita, Tokyo, Japan). Participants are asked to squeeze the dynamometer twice for each hand, and the mean value among four trials is recorded. Our data analysis excluded participants who declined to perform the test owing to physical problems. To analyze the association between changes in handgrip strength and cognitive function, we calculated the differences in reported values per wave. Handgrip strength was considered as both a categorized and a continuous variable in the analysis. As handgrip strength has been found to be significantly different between men and women in previous studies, we analyzed the data with stratification by sex [26, 27]. We also standardized the handgrip strength change by calculating the percentage change in handgrip strength from the handgrip strength of the original wave. The asymmetry in handgrip strength was calculated by subtracting the lower value from the higher value of handgrip strength. The change of the asymmetry per wave was then divided into two groups: 1) decreased, 2) same or increased.

Covariates

We considered demographic and health-related factors as covariates in the analysis. Demographic characteristics included age, educational level, residential region, working status, household income, participation in social activities, and number of cohabiting generations. Health-related factors included smoking/alcohol use status, number of chronic medical conditions, BMI, and perceived health status. All the multivariable models controlled for all covariates unless stated otherwise.

Statistical analysis

All statistical analyses were performed separately for men and women to rule out the effect of sex in terms of the difference in handgrip strength on cognitive function. We employed analysis of variance to investigate and compare the general characteristics of the study population. We also constructed a generalized estimating equation model for regression analysis between MMSE scores and change in handgrip and other covariates. The analysis was conducted twice using the different variable types of change in handgrip strength: the two categorical groups of change in handgrip strength and the continuous variable of the same. The results were presented as regression coefficients (β) and 95% confidence intervals (95%CI). We performed subgroup analyses for a detailed study of the interaction between change in handgrip strength and other variables associated with MMSE scores. All analyses were carried out using SAS Version 9.4 (SAS Institute, Cary, North Carolina, USA). The results were considered statistically significant at p < 0.05.

Results

Table 1 gives the baseline characteristics of the study population stratified by sex. The unadjusted comparison showed no statistical difference in MMSE scores between the two groups of handgrip strength change in both sexes. Other covariates, such as age, educational level, region of residence, working status, household income, participation in social activities, BMI, and perceived health status, showed significant differences in MMSE scores for both sexes. The comparison of mean MMSE scores between two groups in Wave 2 and Wave 7 are presented in Supplementary Table 1. Both groups showed no statistically significant differences in mean MMSE scores for both Waves 2 and 7.

Table 1 Baseline characteristics of the study population according to Mini-Mental State Examination scores

Table 2 shows the multiple regression analysis results for associations between MMSE scores and handgrip strength change groups after adjusting for covariates. Compared with the same or increased handgrip strength group, the decreased handgrip strength group showed highly significant regression coefficients (− 0.3142 in men and − 0.2685 in women). Decreased handgrip strength was associated with decreased MMSE scores in both sexes. The results of other covariates are also shown in Table 2. Higher age showed a significant association with decreased MMSE scores, albeit with smaller regression coefficients. The decreased handgrip strength group also showed statistically significant odds ratios for mild cognitive impairment (OR = 1.23 in men, OR = 1.15 in women) and dementia (OR = 1.39 in men, OR = 1.19 in women), as illustrated in Table 3.

Table 2 Results of the GEE analysis of handgrip strength change in two groups and Mini-Mental State Examination scores
Table 3 Results of the GEE analysis of handgrip strength change and mild cognitive impairment/dementia

Table 4 shows the results of the multiple regression analysis between MMSE scores and handgrip strength change in continuous values with the same covariates in Table 2. The regression coefficients were 0.0293 in men and 0.0347 in women, indicating a high level of statistical significance. The results affirm the positive association between change in handgrip strength and MMSE total scores in both sexes. The decrease in handgrip strength asymmetry was associated with lower MMSE scores (β = − 0.1476 in men and β = − 0.1755 in women) as shown in Table 5.

Table 4 Results of the GEE analysis of handgrip strength change in continuous variables and Mini-Mental State Examination scores
Table 5 Results of the GEE analysis of handgrip strength asymmetry change and Mini-Mental State Examination scores

Discussion

In this study, we identified that change in handgrip strength is associated with cognitive function in community-dwelling South Korean adults. The group with decreased handgrip strength was associated with low cognitive function when compared with the group with the same or increased handgrip strength. Furthermore, the value of the handgrip strength change was positively correlated with the MMSE scores in the study population.

Our results were generally consistent with previous studies on the relationship between change in handgrip strength and cognitive function in different populations. Previous studies showed that low baseline handgrip strength was associated with cognitive decline [28]. Christensen et al. reported that handgrip strength change, rather than initial strength, predicts changes in memory task performance [29]. MacDonald et al. suggested that biological changes, including grip strength change, share significant time-varying associations with change in cognitive function; handgrip strength decline is associated with cognitive function decline [29]. Several studies reported that physical frailty, including grip strength, was associated with cognition, suggesting that they might share common pathology [30, 31]. Compared with previous works, our results newly established that handgrip strength change is associated with cognitive function in older adults.

In our study, a decreased handgrip strength asymmetry was associated with a lower MMSE score, as shown in Table 5. Mcgrath et al. showed that handgrip strength asymmetry was associated with lower cognitive functioning [32]. The change in handgrip strength through aging or exercise could be different, resulting in a stronger or a weaker hand; thus, the change in asymmetry showed different patterns related to the asymmetry itself, with respect to association with cognitive function.

The etiology of the association between change in handgrip strength and cognitive function has not been established, although several possible explanations have been suggested. One is that physical activity increases the size of the prefrontal and hippocampal brain areas, thereby reducing cognitive decline [33,34,35]. Changes in handgrip strength can reflect the changes in the physical activity of individuals; thus, decreased handgrip might reflect reduced cognitive function. The frailty concept could be one explanation of the relationship between handgrip and reduced cognitive function. Handgrip strength decline could be an early and readily detectible indicator of frailty, which includes consequent decline of cognitive function in older adults. Previous studies showed that physical frailty, including being underweight, having weaker grip strength, and having a poor performance on the chair stand test was associated with cognitive decline [36, 37]. Another explanation is that cognitive function and handgrip strength might share a common domain of the brain, such as the frontal executive function area; decreased handgrip strength and cognitive decline might occur simultaneously.

Meanwhile, decreased cognitive function might also induce the change in handgrip strength. A study on the direction of the relationship between strength and cognitive function showed a significant bi-directional relationship [13]. Thus, muscular strength and cognitive function might share common causes of change. In our study, we could not exclude the possibility that participants with low cognitive function might have had difficulty in maintaining physical activity, including strength exercises, which could lead to the decrease in their handgrip strength. Further research should be performed to test the directionality or causality of the two variables.

This study has several limitations. First, as the data were collected via a survey, the results might be biased. Second, we excluded the data of those who did not answer the important covariate questions, which may have induced the underestimation of cognitive decline in the participants. Third, we could not include biological risk factors, which could have led us to overlook some important confounding variables. Several biological factors have been established as risk factors of cognitive impairment in adults, and future studies should include these in regression model analyses [38]. Fourth, as we used brief measurements for cognitive function, the impact of handgrip strength changes on different neurocognitive domains could not be analyzed in this study. Previous studies showed that grip strength had different effects on cognitive domains [39, 40]. Further research using a comprehensive neurocognitive test would refine our study results. Finally, cause and effect could not be established because our study did not use a prospective design, which could be used to assess the causality of change in handgrip strength vis-à-vis change in cognitive function.

Nonetheless, the strengths of our study include the relatively large sample size and longitudinal design. Our results can be representative of the Korean adult population. Another strength is that this study used standardized tools to measure muscle strength and cognitive function; therefore, the results are readily applicable for further study. Moreover, given our use of the change in handgrip strength rather than baseline strength, the present results can be referenced when introducing lifestyle modifications, such as strength exercises, for older adults to help them maintain or increase their handgrip strength, which can prevent cognitive function decline.

In conclusion, this study identified the relationship between changes in handgrip strength and cognitive function among South Korean adults. Decreased handgrip strength was associated with cognitive decline in our longitudinal, large-sample study. Further studies exploring the underlying mechanisms of the association between handgrip strength and cognitive impairment, as well as the preventive effect of increasing the former, could provide valuable strategies for treating and preventing cognitive impairment in clinical settings.

Availability of data and materials

The datasets analyzed during the current study are available in the KLoSA repository, https://survey.keis.or.kr/eng/klosa/databoard/List.jsp

References

  1. 1.

    Livingston G, Sommerlad A, Orgeta V, Costafreda SG, Huntley J, Ames D, et al. Dementia prevention, intervention, and care. Lancet. 2017;390(10113):2673–734.

    Article  Google Scholar 

  2. 2.

    Freedberg DE, Dave J, Kurth T, Gaziano JM, Bludau JH. Cognitive impairment over the age of 85: hospitalization and mortality. Arch Gerontol Geriatr. 2008;46(2):137–45.

    Article  Google Scholar 

  3. 3.

    Hussenoeder FS, Conrad I, Roehr S, Fuchs A, Pentzek M, Bickel H, et al. Mild cognitive impairment and quality of life in the oldest old: a closer look. Qual Life Res. 2020;29(6):1675–83.

    Article  Google Scholar 

  4. 4.

    Pan CW, Wang X, Ma Q, Sun HP, Xu Y, Wang P. Cognitive dysfunction and health-related quality of life among older Chinese. Sci Rep. 2015;5:17301.

    Article  Google Scholar 

  5. 5.

    Ton TGN, DeLeire T, May SG, Hou N, Tebeka MG, Chen E, et al. The financial burden and health care utilization patterns associated with amnestic mild cognitive impairment. Alzheimers Dement. 2017;13(3):217–24.

    Article  Google Scholar 

  6. 6.

    Barnett JH, Lewis L, Blackwell AD, Taylor M. Early intervention in Alzheimer's disease: a health economic study of the effects of diagnostic timing. BMC Neurol. 2014;14:101.

    Article  Google Scholar 

  7. 7.

    Petersen RC, Thomas RG, Grundman M, Bennett D, Doody R, Ferris S, et al. Vitamin E and donepezil for the treatment of mild cognitive impairment. N Engl J Med. 2005;352(23):2379–88.

    CAS  Article  Google Scholar 

  8. 8.

    Ahern E, Semkovska M. Cognitive functioning in the first-episode of major depressive disorder: a systematic review and meta-analysis. Neuropsychology. 2017;31(1):52–72.

    Article  Google Scholar 

  9. 9.

    Fortier-Brochu E, Morin CM. Cognitive impairment in individuals with insomnia: clinical significance and correlates. Sleep. 2014;37(11):1787–98.

    Article  Google Scholar 

  10. 10.

    Lagnaoui R, Tournier M, Moride Y, Wolfson C, Ducruet T, Bégaud B, et al. The risk of cognitive impairment in older community-dwelling women after benzodiazepine use. Age Ageing. 2009;38(2):226–8.

    Article  Google Scholar 

  11. 11.

    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.

    CAS  Article  Google Scholar 

  12. 12.

    Snyder HR. Major depressive disorder is associated with broad impairments on neuropsychological measures of executive function: a meta-analysis and review. Psychol Bull. 2013;139(1):81–132.

    Article  Google Scholar 

  13. 13.

    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.

    Article  Google Scholar 

  14. 14.

    Cheng G, Huang C, Deng H, Wang H. Diabetes as a risk factor for dementia and mild cognitive impairment: a meta-analysis of longitudinal studies. Intern Med J. 2012;42(5):484–91.

    CAS  Article  Google Scholar 

  15. 15.

    Reitz C, Tang MX, Manly J, Mayeux R, Luchsinger JA. Hypertension and the risk of mild cognitive impairment. Arch Neurol. 2007;64(12):1734–40.

    Article  Google Scholar 

  16. 16.

    Karlsson IK, Lehto K, Gatz M, Reynolds CA, Dahl Aslan AK. Age-dependent effects of body mass index across the adult life span on the risk of dementia: a cohort study with a genetic approach. BMC Med. 2020;18(1):131.

    CAS  Article  Google Scholar 

  17. 17.

    Zammit AR, Robitaille A, Piccinin AM, Muniz-Terrera G, Hofer SM. Associations between aging-related changes in grip strength and cognitive function in older adults: a systematic review. J Gerontol A Biol Sci Med Sci. 2019;74(4):519–27.

    Article  Google Scholar 

  18. 18.

    Alfaro-Acha A, Al Snih S, Raji MA, Kuo YF, Markides KS, Ottenbacher KJ. Handgrip strength and cognitive decline in older Mexican Americans. J Gerontol A Biol Sci Med Sci. 2006;61(8):859–65.

    Article  Google Scholar 

  19. 19.

    McGrath R, Vincent BM, Hackney KJ, Robinson-Lane SG, Downer B, Clark BC. The Longitudinal Associations of Handgrip Strength and Cognitive Function in Aging Americans. J Am Med Dir Assoc. 2020;21(5):634–9 e631.

    Article  Google Scholar 

  20. 20.

    McGrath R, Robinson-Lane SG, Cook S, Clark BC, Herrmann S, O’Connor ML, et al. Handgrip strength is associated with poorer cognitive functioning in aging Americans. J Alzheimers Dis. 2019;70:1187–96.

    CAS  Article  Google Scholar 

  21. 21.

    Jang S-N: Korean Longitudinal Study of Ageing (KLoSA): Overview of Research Design and Contents. 2015:1–9.

  22. 22.

    Mitchell AJ. A meta-analysis of the accuracy of the mini-mental state examination in the detection of dementia and mild cognitive impairment. J Psychiatr Res. 2009;43(4):411–31.

    Article  Google Scholar 

  23. 23.

    Tombaugh TN, McIntyre NJ. The mini-mental state examination: a comprehensive review. J Am Geriatr Soc. 1992;40(9):922–35.

    CAS  Article  Google Scholar 

  24. 24.

    Kang YW, Na DL, Hahn SH. A validity study on the korean mini-mental state examination (K-MMSE) in dementia patients. J Korean Neurol Assoc. 1997;15(2):300–8.

    Google Scholar 

  25. 25.

    Park JH, Kwon YC. Standardization of Korean version of Mini-mental state examination (MMSE-K) for use in the elderly. Part II. Diagnostic validity. J Korean Neuropsychiatr Assoc. 1989;28(3):508–13.

    Google Scholar 

  26. 26.

    Sevene TG, Berning J, Harris C, Climstein M, Adams KJ, DeBeliso M. Hand grip strength and gender: Allometric normalization in older adults and implications for the NIOSH lifting equation. J Lifestyle Med. 2017;7(2):63–8.

    Article  Google Scholar 

  27. 27.

    Leyk D, Gorges W, Ridder D, Wunderlich M, Rüther T, Sievert A, et al. Hand-grip strength of young men, women and highly trained female athletes. Eur J Appl Physiol. 2007;99(4):415–21.

    CAS  Article  Google Scholar 

  28. 28.

    Fritz NE, McCarthy CJ, Adamo DE. Handgrip strength as a means of monitoring progression of cognitive decline – a scoping review. Ageing Res Rev. 2017;35:112–23.

    Article  Google Scholar 

  29. 29.

    Christensen H, Korten AE, Mackinnon AJ, Jorm AF, Henderson AS, Rodgers B. Are changes in sensory disability, reaction time, and grip strength associated with changes in memory and crystallized intelligence? A longitudinal analysis in an elderly community sample. Gerontology. 2000;46(5):276–92.

    CAS  Article  Google Scholar 

  30. 30.

    Buchman AS, Yu L, Wilson RS, Boyle PA, Schneider JA, Bennett DA. Brain pathology contributes to simultaneous change in physical frailty and cognition in old age. J Gerontol A Biol Sci Med Sci. 2014;69(12):1536–44.

    CAS  Article  Google Scholar 

  31. 31.

    Boyle PA, Buchman AS, Wilson RS, Leurgans SE, Bennett DA. Physical frailty is associated with incident mild cognitive impairment in community-based older persons. J Am Geriatr Soc. 2010;58(2):248–55.

    Article  Google Scholar 

  32. 32.

    McGrath R, Cawthon PM, Cesari M, Al Snih S, Clark BC. Handgrip strength asymmetry and weakness are associated with lower cognitive function: a panel study. J Am Geriatr Soc. 2020;68(9):2051–8.

    Article  Google Scholar 

  33. 33.

    Erickson KI, Raji CA, Lopez OL, Becker JT, Rosano C, Newman AB, et al. Physical activity predicts gray matter volume in late adulthood: the cardiovascular health study. Neurology. 2010;75(16):1415–22.

    CAS  Article  Google Scholar 

  34. 34.

    Erickson KI, Weinstein AM, Lopez OL. Physical activity, brain plasticity, and Alzheimer's disease. Arch Med Res. 2012;43(8):615–21.

    Article  Google Scholar 

  35. 35.

    Rovio S, Spulber G, Nieminen LJ, Niskanen E, Winblad B, Tuomilehto J, et al. The effect of midlife physical activity on structural brain changes in the elderly. Neurobiol Aging. 2010;31(11):1927–36.

    Article  Google Scholar 

  36. 36.

    Auyeung TW, Lee JSW, Kwok T, Woo J. Physical frailty predicts future cognitive decline — a four-year prospective study in 2737 cognitively normal older adults. J Nutr Health Aging. 2011;15(8):690–4.

    CAS  Article  Google Scholar 

  37. 37.

    Samper-Ternent R, Al Snih S, Raji MA, Markides KS, Ottenbacher KJ. Relationship between frailty and cognitive decline in older Mexican Americans. J Am Geriatr Soc. 2008;56(10):1845–52.

    Article  Google Scholar 

  38. 38.

    Horvat P, Kubinova R, Pajak A, Tamosiunas A, Schöttker B, Pikhart H, et al. Blood-based oxidative stress markers and cognitive performance in early old age: the HAPIEE study. Dement Geriatr Cogn Disord. 2016;42(5–6):297–309.

    CAS  Article  Google Scholar 

  39. 39.

    Sternäng O, Reynolds CA, Finkel D, Ernsth-Bravell M, Pedersen NL, Dahl Aslan AK. Grip strength and cognitive abilities: associations in old age. The Journals of Gerontology: Series B. 2015;71(5):841–8.

    Article  Google Scholar 

  40. 40.

    Adamo DE, Anderson T, Koochaki M, Fritz NE. Declines in grip strength may indicate early changes in cognition in healthy middle-aged adults. PLoS One. 2020;15(4):e0232021–1.

    CAS  Article  Google Scholar 

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HK, SHK and WJ had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Concept and design: HK, YK. Acquisition, analysis, or interpretation of data: HK, WJ. Drafting of the manuscript: HK. Critical revision of the manuscript for important intellectual content: ECP, SIJ, YK. Statistical analysis: HK, WJ, SHK. Supervision: YK. All authors read and approved the manuscript.

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Correspondence to Youseok Kim.

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The KLoSA study was approved by the Statistics Korea of Korean Government (Approval number: 33602) and Institutional Review Board of Korea National Institute for Ethics Policy (P01–201909–22-002). The survey was conducted after acquiring verbal consent of the participants by the trained study interviewer. This study was exempted from approval by the Institutional Review Board of Yonsei University’s Health System (4–2021-0307), adhering to the principles of the Declaration of Helsinki.

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Kim, H., Kim, S.H., Jeong, W. et al. Association between change in handgrip strength and cognitive function in Korean adults: a longitudinal panel study. BMC Geriatr 21, 671 (2021). https://doi.org/10.1186/s12877-021-02610-2

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Keywords

  • Handgrip strength
  • Cognitive impairment
  • Cognitive function
  • Aging
  • Korean longitudinal study of aging