Longitudinal associations of depression, mild cognitive impairment, and quality of life with handgrip strength

doi:10.21203/rs.3.rs-3582657/v1

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Longitudinal associations of depression, mild cognitive impairment, and quality of life with handgrip strength

https://doi.org/10.21203/rs.3.rs-3582657/v1

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Background. Mental health and quality of life (QoL) are key components of healthy aging, and their deterioration may lead to a loss of health, dependence, and mortality among older adults. Handgrip strength (HGS) has been widely used given its practicality and reliability as an indicator of general health status and physical functioning and even as a biomarker of aging. This study aimed to estimate the longitudinal associations of handgrip strength (HGS) with depression, mild cognitive impairment (MCI), and quality of life (QoL).

Methods. Data come from the first three wave of the Study on Global Aging and Adult Health in Mexico (2009, 2014, 2017). 2,943 older adults aged 50 years or older were included. HGS was measured using a handheld dynamometer. We used the Composite International Diagnostic Interview for the diagnosis of depression based on DSM‐IV criteria. MCI was determined according to the recommendations of the National Institute on Aging and the Alzheimer's Association of the United States. Quality of life was assessed using the WHOQOL (WHO Quality of Life) instrument. HGS was considered as a time-varying exposure and the between- and within-person effects were disaggregated using the hybrid models with random intercept.

Results. Higher HGS values were significantly associated with the three outcomes, decreasing the probability of depression (OR=0.98, p=0.02) and MCI (OR=0.97, p<0.01), and increasing quality of life levels (β=0.10, p<0.01). Likewise, those with weak grip strength had a higher probability of depression (OR=1.36, 95% CI 1.01;1.82), MCI (OR=1.32, 95% CI 1.03;1.68) and lower quality of life (β= -1.21 95% CI -1.95;-0.47). a higher proportion of this association will be better explained by between-person differences than within-person differences. A predominance of between-person effects over within-person effects was observed.

Conclusion. Given the explanatory power of HGS, routine use of its measurement should be implemented, both in the community and in clinical settings, to identify older adults at risk for adverse health outcomes.

depression

mild cognitive impairment

quality of life

handgrip strength

between-person effects

within-person effects

Mental health and quality of life (QoL) are key components of healthy aging, and their deterioration may lead to a loss of health, dependence, and mortality among older adults (1). These declines in mental health are often accompanied by social and psychological effects like isolation, loneliness, and distress, carrying a significant community-wide economic and social burden, especially in low- and middle-income countries where aging populations are growing at an accelerated rate (2).

Depression and alterations of cognitive function, like dementia or mild cognitive impairment (MCI), have received particular attention due to the growing proportion of people expected to live with those conditions. In 2015, the World Health Organization (WHO) estimated that 350 million individuals were currently living with depression, with a higher prevalence observed in the older adult population (3). In addition to the burden of depression, 50 million people have dementia, and the incidence is expected to increase substantially (4). Both mental disorders have been associated with a greater risk of adverse health outcomes like cardiovascular disease, disability, and mortality (5, 6).

A change in physical function is a gradual process in older adults, mainly due to the loss of muscle and bone mass and the deterioration of musculoskeletal and neuromotor functions (7). These changes in physical function also are associated with increased morbidity and mortality, poor mental health, and decreased quality of life (8). Although several objective measures of physical function have been proposed, such as gait speed, grip strength, the balance test, sit-to-stand test, and the short physical performance battery (9), handgrip strength (HGS) has been widely used given its practicality and reliability as an indicator of general health status and physical functioning (10). HGS has also been considered as a biomarker of aging (11).

Previous studies have identified specific associations of HGS with depression, cognitive impairment, and quality of life. A recent review and meta-analysis found that higher muscular strength reduced the probability of depression (12). Twenty one of the 24 analyzed studies analyzed muscular strength using the HGS. Regarding MCI, lower HGS was identified as a predictor of future cognitive loss (13). Meanwhile, one longitudinal study found that a 5kg increase in HGS was associated with reduced risk of MCI in a large sample of older adults living in the U.S.A (14). As for the association between HGS and QoL, the evidence is mixed. Some studies have reported significant associations (15, 16), while others did not (17).

Even with the mounting evidence of the association between HGS with depression, MCI, and QoL, there are still some gaps. First, most of the studies have analyzed these three outcomes in isolation. Second, most of the longitudinal studies have analyzed the HGS as a time-constant exposure (12–14). Given that aging is variable among individuals, muscle strength must also be measured as dynamic and changing over time between and amongst individuals. Therefore, a more appropriate analytical methodology must be used to account for the potential dynamic association between HGS and the analyzed outcomes. This study aimed to estimate the longitudinal associations of HGS with depression, MCI, and QoL, considering HGS as a time-varying exposure. We hypothesize that older adults with weak HGS will have a higher probability of depression and MCI, and lower QoL. We also hypothesize that a higher proportion of this association will be better explained by between-person differences than within-person differences.

Study design and participants

Dynamic cohort design (with rolling admissions and follow-up individuals) using data from the World Health Organization (WHO) Study on global AGEing and adult health (SAGE) in Mexico. SAGE comprises nationally representative samples of individuals ≥ 50 years from six countries: China, Ghana, India, Mexico, Russia, and South Africa. Details of the study design have been published elsewhere (18). We used data from the three first waves of the SAGE-Mexico. Wave 1 (baseline: July-September 2009) collected information from 2,404 participants. Wave 2 (July-October 2014) adding new 618 individuals. Wave 3 (August-November 2017) gathered information from 2,318 participants, with 610 new interviews. In total, 3,277 individuals were interviewed in the three waves. The analytical sample comprised a total of 2,943 participants with complete information which represents an 89% overall response rate (Fig. 1). Baseline differences between the final sample and excluded participants with respect to several analytical variables were observed. The latter were older and had a higher prevalence of frailty and multimorbidity (p < 0.05)

Definition of variables

Outcomes

Depression. We assessed depression through a set of symptomatic questions based on the World Mental Health Survey version of the Composite International Diagnostic Interview (Kessler et al., 2004). Diagnosis of a major depressive episode was assessed based on severity of reported symptoms of depression during the past 12 months (20). The detailed symptomatic questions and algorithm have been provided in previous research using the SAGE dataset (21).

Mild cognitive impairment (MCI). The recommendations from the National Institute of Aging-Alzheimer’s Association (22) and the information from previous analysis of SAGE-Mexico (23) were applied to identify participants with MCI. Specifically, the following criteria were considered: a) evidence of concern about a change in cognition. Interviewers asked to the participants "how would you best describe your memory at present?” and/or “compared to 12 months ago, would you say your memory is now better, the same or worse than it was then?”. A concern about a change in cognition was identified if the individuals answered “bad” or “very bad” and “worse to the previous questions; b) impairment in one or more cognitive domains, assessed with immediate and delayed verbal recall, forward and backward digit span and verbal fluency tests. Older adults with < − 1.5 SD cut-off after adjustment for level of education and age, were considered with impairment; c) preservation of independence in functional abilities, evaluated with Katz scale for basic activities of the daily life (BADL); and d) who were unable to complete the survey due to significant cognitive impairment. Participants who met all criteria were considered to have MCI.

Quality of life (QoL). We assessed this variable using the WHOQOL (WHO Quality of Life) instrument. This eight-item questionnaire covers the following core domains (two items per domain): physical, psychological, social, and environmental. The results of the eight items were summed for an overall score ranging from 0 to 100. The higher the score, the higher quality of life (24).

Main exposure

Handgrip strength. Grip strength was measured twice for both hands using a hand dynamometer (Baseline Electronic Smedley Hand Dynamometer, Fabrication Enterprises, White Plains, NY, USA). Once the dynamometer was fitted to the respondent's hand, the interviewees were instructed to keep their arms close to their body with their elbows at a 90° angle in seated position and to push the dynamometer as hard that they could. The average value, in kilograms, of the two handgrip measurements of the dominant hand was obtained. Weak grip strength (WGS) was defined as < 27 kg for men and < 16 kg for women (25).

Covariates

Covariates were categorized as follows: sex (1 = female), age, number of years of formal education, marital status (married = 1), having a paid job, and health insurance (yes = 1). Socioeconomic status (SES) of the household was derived using the WHO standard approach to estimate permanent income from household ownership of durable goods, dwelling characteristics (type of floors, walls, and cooking stove), and access to services such as water, sanitation, and electricity (26). SES was included as a continuous variable, with higher values indicating better SES. Multimorbidity was included as a dichotomous variable defined as the presence of two or more chronic non-communicable conditions from the list of nine chronic diseases included in the SAGE study. The operational definitions of these diseases have been published elsewhere (21). Unintended weight loss was determined according to the self-reported reduction of five kilograms or more in the past 12 months. Functionality was evaluated with the following two variables: limitations in activities of daily living (ADL) and instrumental activities of daily living (IADL). Ten questions from the World Health Organization Disability Assessment Schedule (WHODAS) II questionnaire were used for assessing any difficulties in performing ADL, such as dressing (including putting on shoes and socks), eating (such as cutting up your food), using the toilet (including getting up and down), bathing and showering, and getting in and out of bed. The WHODAS II questionnaire was also used to assess IADL, such as preparing a hot meal, shopping for groceries, making telephone calls, taking medications, and managing money (such as paying your bills and keeping track of expenses) in the preceding 30 days. Respondents were considered to be “with limitation” if they reported any difficulties in performing at least one of the five daily activities listed above for ADL or IADL. Physical activity was assessed with the Global Physical Activity Questionnaire (GPAQ), which classified older adults in three categories -- low, moderate, and high physical activity -- based on reported time spent in moderate or vigorous activities during work, recreational/leisure time, and transportation (27). Tobacco use (never; ever smoked, no longer; current smoker, not daily; current smoker, daily), and alcohol consumption (never; ever drinker, no longer; current drinker, low risk; current drinker, high risk) were self-reported.

Statistical analysis

Baseline characteristics are presented in percentages and means (with standard deviation) as appropriate. Health and sociodemographic characteristics according to the presence of weak grip strength (WGS) were compared using Chi-square or t-tests.

We analyzed the association of HGS and WGS with depression, MCI, and QoL using logistic and linear mixed-effects regression models. Given that the Mexico-SAGE study included multiple members from within the same household and had repeated measurements from the same individual, our data had a three-level hierarchical structure, with measurement occasions at level 1, individuals at level 2, and households at level 3. We then fitted random intercept models including the subject and household IDs as random effects for depression, MCI, and QoL outcomes.

Additionally, to consider HGS and WGS as time-varying exposures, we disaggregated the between- and within-person effects in the random intercept models using the so-called hybrid models (28, 29). In this method, the association of outcome and time-varying covariate is disaggregated according to the between- and within-person effects. For longitudinal data, the person-mean centered time-varying covariate serves as a within-person predictor, representing the amount by which a person deviates from his or her own average at each time point (within-person effect) at level one. At level two, the associated mean of the person serves as a between-person predictor, representing each person’s pooled average over all time points (between-person effect).

All models were adjusted using follow-up time and the covariates described above. Regression coefficients, odds ratios, and 95% confidence intervals were reported. We used Stata 17.0 to conduct all the analyses.

Table 1 shows the baseline socio-demographic and health characteristics of participants by WGS status. WGS was present in 25% of participants. In comparison to individuals without WGS, those with WGS had a higher proportion of depression (p < 0.01), MCI (p = 0.05) and lower QoL (p < 0.01). Those with WGS also had a higher proportion of multimorbidity (p < 0.01) and functional limitations (ADL p < 0.01; IADL p < 0.01), were older (p < 0.01), mostly women (p < 0.01), and had fewer years of formal education (p < 0.01). They also displayed a higher proportion of low physical activity (p < 0.01).

Table 1

Baseline sociodemographic and health characteristics according to presence of weak grip strength
	Normal grip strength	Weak grip strength	p-value^a
	n = 2203 (75%)	n = 740 (25%)	p-value^a
Outcomes
Depression	7.5	11.1	< 0.01
Mild cognitive impairment	11.0	13.9	0.05
Quality of life	65.9 (13.4)	62.0 (14.1)	< 0.01
Sociodemographics
Sex (female = 1)	58.2	65.3	< 0.01
Age	65.1 (9.2)	69.6 (11.2)	< 0.01
Years of formal education	5.0 (4.5)	4.6 (4.4)	0.04
Marital status (with couple = 1)	64.9	59.7	0.01
Paid job	32.0	22.5	< 0.01
Health insurance	79.0	81.1	0.30
Socioeconomic status (assets index)	-0.06 (1.2)	-0.09 (1.2)	0.53
Health
Unintentional weight loss	14.5	17.3	0.07
Multimorbidity	56.3	62.2	< 0.01
ADL limitation	33.6	48.8	< 0.01
IADL limitation	7.1	17.7	< 0.01
Lifestyle behaviors
Physical activity
Low	43.1	51.0
Moderate	25.7	23.7
High	31.2	25.3	< 0.01
Tobacco
Never	65.7	70.0
Ever smoker, no longer	17.6	16.9
Current smoker, not daily	4.9	5.4
Current smoker, daily	11.8	7.8	< 0.01
Alcohol consumption
Never	44.5	53.7
Ever drinker, no longer	43.0	38.9
Current drinker (low risk)	8.8	5.6
Current drinker (high risk)	3.6	1.8	< 0.01
Cells are means (std. dev.) or percentages
^ap-value for t or chi-square tests

The results of the mixed regression models treating HGS and WGS as time-varying exposures are shown in Table 2. Overall, HGS was significantly associated with all the three outcomes, including decreased probability of depression (OR = 0.98, p = 0.02) and MCI (OR = 0.97, p < 0.01), and increased levels of QoL (β = 0.10, p < 0.01). WGS was also associated with greater odds of depression (OR = 1.36, p = 0.04), MCI (OR = 1.32, p = 0.03), and lower levels of QoL (β=-1.21, p < 0.01).

Table 2

Longitudinal associations of depression, mild cognitive impairment, quality of life, and grip strength considered as time-varying exposure
	Depression			Mild cognitive impairment			Quality of life
	OR^a	CI 95%	p-value	OR	CI 95%	p-value	β	CI 95%	p-value
Handgrip strength (kg)
Overall	0.98	0.96 ; 0.99	0.02	0.97	0.96 ; 0.99	< 0.01	0.10	0.06 ; 0.15	< 0.01
Between-person	0.95	0.93 ; 0.98	< 0.01	0.98	0.95 ; 0.99	0.03	0.14	0.08 ; 0.20	< 0.01
Within-person	1.00	0.98 ; 1.03	0.80	0.97	0.95 ; 0.99	< 0.01	0.06	0.01 ; 0.12	0.05
Weak grip strength
Overall	1.36	1.01 ; 1.82	0.04	1.32	1.03 ; 1.68	0.03	-1.21	-1.95 ; -0.47	< 0.01
Between-person	1.85	1.20 ; 2.85	< 0.01	1.05	0.74 ; 1.48	0.80	-2.34	-3.44 ; -1.25	< 0.01
Within-person	1.04	0.70 ; 1.56	0.83	1.65	1.17 ; 2.33	< 0.01	-0.29	-1.28 ; 0.70	0.57
Three-level logistic and linear models adjusted for follow-up time and covariates shown in Table 1
^aOdds ratio

The results of the mixed regression models treating HGS and WGS as time-varying exposures are shown in Table 2. Overall, HGS was significantly associated with all the three outcomes, including decreased probability of depression (OR = 0.98, p = 0.02) and MCI (OR = 0.97, p < 0.01), and increased levels of QoL (β = 0.10, p < 0.01). Additional WGS was also associated with greater odds of depression (OR = 1.36, p = 0.04), MCI (OR = 1.32, p = 0.03), and lower levels of QoL (β=-1.21, p < 0.01).

Our findings show that handgrip strength is longitudinally associated with depression, MCI, and QoL in Mexico's nationally representative sample of older adults. Overall, higher levels of HGS associated with lower odds of depression and MCI, and better QoL. We also found that a higher proportion of this association could be attributed to between-person differences rather than within-person.

Our results pointing to the association between HGS and depression are similar to those reported in several previous longitudinal studies. Kandola et al. (30) identified that a 5kg increase in HGS was associated with reduced odds of depression in OLDER ADULTS age 65 or more (OR = 0.727; 95% CI: 0.623, 0.850), assessing depression with the Patient Health Questionnaire-9 in a large sample from the UK Biobank. A recent systematic review and meta-analysis reported that muscle strength (MS) was inversely associated with depression/depressive symptoms (OR = 0.85 CI95% 0.80, 0.89) in older adults, with most of the studies assessing MS using HGS (12).

The findings of the longitudinal association between HGS and MCI have also been documented previously in Kim et al.’s (31) analysis with participants from the Korean Longitudinal Study of Aging. Those with lower HGS quintiles –as compared to the 5th quintile (higher HGS) as reference– had an augmented probability of experiencing cognitive decline and lower scores in the Korean Mini-Mental State Examination (OR per quintile for cognitive decline: Q1 = 4.99 Q2 = 2.57, Q3 = 1.93, Q4 = 1.41, p < 0.01). Similarly, a study with a sample of more than 14,000 participants > 50y found that a 5kg increase in HGS was associated with a reduced probability of cognitive impairment (OR = 0.97 CI95% 0.93, 0.99). The trends were in the same direction even after categorizing by weak (reference) and normal HGS (OR = 0.54 CI95% 0.43, 0.69) (14).

QoL has often been studied in relation to specific health events such as epilepsy (32) and cancer (33). However, evidence about the maintenance or increase of QoL in older adults has been growing over the last several years. The evidence for the association between HGS and QoL has been mixed. One study found that a 1kg increase in HGS was associated with a higher score of QoL, using the Control, Autonomy, Self-realization, and Pleasure-16 test (β = 0.24 CI95% 0.11, 0.37 in women, and β = 0.18 CI95% 0.06, 0.30 in men) (15). Another study also found that higher values of HGS were associated with an increased probability of better physical and mental component scores (above the median) using the Medical Outcomes Study Short Form-12 (SF-12) (OR = 1.05 CI95% 1.01, 1.10, and OR = 1.05 CI95% 1.01, 1.10, respectively) (16). On the contrary, Gopinath et al., 2007, used the extended version of the SF-12 did, not find significant associations (17). The evaluation of QoL is complex; in fact, several tools have been developed to capture some or all the domains of this concept (health status, psycho-social status, and other aspects of life) (34). Differences in the assessment of QoL and study design (cross-sectional or longitudinal) could partially explain the mixed results among these studies.

Muscle strength and HGS decline with age (35). Nonetheless, we know that this process is dynamic rather than static over time (36). Despite the above, most longitudinal studies have incorporated HGS as a time-constant exposure in their analysis. In this study, we considered HGS and WGS as time-varying exposures to further explore their relationship with depression, MCI, and QoL. Our results are consistent with two previous studies that analyzed HGS as a variable that changes over time. One study revealed that negative changes in HGS (a 1SD decrease) increase the odds of depressive symptoms after one year of follow-up in a sample of American older adults (OR = 1.13; CI95%: 1.01–1.27) (37). Another study, using a similar analytical approach to ours, found significant associations of HGS and several indicators of cognitive function (fluid reasoning, working memory, episodic memory, semantic memory, and crystallized ability). Specifically, the authors reported that higher levels of HGS attenuate the decline of fluid reasoning (7.5%) and semantic memory (19%) for within-person effects. For the rest of the indicators, the between-person effects were predominant (38).

Our results add to the available evidence in several ways. First, we have estimated the association of HGS with three of the most critical outcomes for older adults: depression, MCI, and QoL. Second, we have considered the dynamic nature of HGS in our estimates. Third, to the best of our knowledge, there are no studies that have looked at the association between HGS and QoL considering HGS as a time-varying exposure.

The results of the disaggregation analysis (between- and within-person) showed that between-person effects were statistically significant across all associations, for both HGS and WGS, except for in the case of MCI. Meanwhile, significant associations were observed for the within-person effects for MCI and partially with QoL, but not for depression. The predominance of between-person effects has already been reported in longitudinal studies with older adults (39). We hypothesize that this focus on between-person effects is likely because within-person effects may require more extended periods to observe significant changes in the outcomes analyzed. It has also previously been thought that between-person differences with respect to modifiable risk factors may have more substantial influence on outcomes like MCI and QoL than intra-individual differences. However, more longitudinal studies are required that disaggregate between- and within-person effects to confirm or dismiss these hypotheses.

The hand has been recognized as one of the most evolved structures of the human body (40). Consequently, HGS is a complex mechanism that requires strict control of the central nervous system for neuromuscular activation through motor unit organization and coordination to achieve the highly demanded task (41). The integrity of brain processes essential for optimal and efficient muscular coordination is reflected in HGS (42). Thus, changes in neurological processes may be responsible for the variations in grip strength and its associations with cognitive function.

The mechanisms driving the association between HGS, depression, and QoL are likely related to lifestyle factors, such as a decreased in physical function and activity (43, 44), and specific responses like oxidative stress and inflammation (45). For example, cytokines released in inflammation response trigger changes in the metabolism of neurotransmitters like serotonin, dopamine and glutamate that may lead to depression and other psychological disorders (46). Also, chronic inflammation appears to have a minor but constant effect on people's overall happiness as well as their contentment in intimate relationships, all of which are conditions associated with QoL in OLDER ADULTS (47). More evidence is needed to clarify the multiple processes linking HGS with these outcomes.

The results of our study should be interpreted within the context of its strengths and limitations. A major strength in this study was the large community-dwelling sample of OLDER ADULTS and the prospective design of the study. Also, all outcomes were measured through previously validated tests. There were also several potential limitations of our study. Although there was an acceptable response rate, included participants overall had healthier baseline characteristics than excluded OLDER ADULTS, leading to a likely sub-estimation of the observed associations. Even so, significant associations between HGS and the outcomes of interest were found. Additionally, even though we included a variety of potential confounders, there could have been residual confounding from variables such as drug use, inflammatory biomarkers, and food intake.

In this study, we found that higher HGS was associated with lower rates of depression and MCI and better QoL in a nationally Mexican sample of community-dwelling older adults. These results have important implications in both clinical and research settings. HGS tests should be promoted and normalized by health care professionals who work with the geriatric population to screen for muscle strength and to identify older adults whose healthy aging could be compromised. Moreover, HGS should be measured continuously given the temporal variations within individuals. Finally, given the explanatory strength of HGS, intervention studies must be conducted to determine the impact of increasing/maintaining muscular strength on mental health and QoL among the older adult population.

ADL

Activities of daily living

DSM-IV

Diagnostic and Statistical Manual of Mental Disorders, 4th Edition

GPAQ

Global physical activity questionnaire

HGS

Hand grip strength

IADL

Instrumental activities of daily living

MCI

Mild cognitive impairment

Muscle strength

Odds ratio

QoL

Quality of life

SAGE

Study on Global AGEing and adult health

SES

Socioeconomic status

USA

United States of America

United Kingdom

WGS

Weak grip strength

WHO

World Health Organization

WHODAS

WHO Disability assessment schedule

WHOQOL

WHO Quality of life questionnaire

Acknowledgements

Not applicable.

Authors contributions

Conceptualization: ASR, BME. Methodology: ASR, BME, RPG. Formal analysis: ASR, RPG. Investigation: RPG, ASR. Writing – original draft: RPG, ASR. Writing – Review & Editing: all authors. Supervision: ASR.

Funding

SAGE is supported by WHO and the US National Institute on Aging through Interagency Agreements (OGHA04034785, YA1323-08-CN-0020, and Y1-AG-1005-01) and competitive grant: R01AG034479.

Availability of data and materials

The datasets analyzed during the current study are available in the WHO repository, https://www.who.int/data/data-collection-tools/study-on-global-ageing-and-adult-health/sage-waves

Ethics approval and consent to participate

This study was performed in accordance with the declaration of Helsinki principles. The study was approved by the Ethics Research Committee of the National Institute of Public Health, Cuernavaca, Mexico (CI/2013/550). All participants gave a written informed consent..

Consent for publication

Not applicable.

Competing interest

The authors declare that they have no competing interests.

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No competing interests reported.

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Longitudinal associations of depression, mild cognitive impairment, and quality of life with handgrip strength

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