Association Between Muscular Strength and Cognition in People With Major Depression or Bipolar Disorder and Healthy Controls

Joseph Firth; Josh A Firth; Brendon Stubbs; Davy Vancampfort; Felipe B Schuch; Mats Hallgren; Nicola Veronese; Alison R Yung; Jerome Sarris

doi:10.1001/jamapsychiatry.2018.0503

. 2018 Apr 18;75(7):740–746. doi: 10.1001/jamapsychiatry.2018.0503

Association Between Muscular Strength and Cognition in People With Major Depression or Bipolar Disorder and Healthy Controls

Joseph Firth ^1,^2,^✉, Josh A Firth ^3,⁴, Brendon Stubbs ^5,⁶, Davy Vancampfort ^7,⁸, Felipe B Schuch ^9,¹⁰, Mats Hallgren ¹¹, Nicola Veronese ^12,¹³, Alison R Yung ^2,¹⁴, Jerome Sarris ^1,¹⁵

¹NICM Health Research Institute, School of Science and Health, University of Western Sydney, Sydney. New South Wales, Australia

²Division of Psychology and Mental Health, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom

³Department of Zoology, Edward Grey Institute, University of Oxford, Oxford, United Kingdom

⁴Merton College, University of Oxford, Oxford, United Kingdom

⁵Physiotherapy Department, South London and Maudsley National Health Services Foundation Trust, United Kingdom

⁶Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom

⁷Katholieke Universiteit Leuven Department of Rehabilitation Sciences, Leuven, Belgium

⁸Universitair Psychiatrisch Centrum Katholieke Universiteit Leuven, Campus Kortenberg, Leuven, Belgium

⁹Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil

¹⁰Post Graduate Program in Health and Human Development, Universidade La Salle, Canoas, Brazil

¹¹Department of Public Health Sciences, Karolinksa Institute, Stockholm, Sweden

¹²Laboratory of Nutritional Biochemistry, Research Hospital, Istituto di Ricovero e cura a Carattere Scientifico “S. de Bellis,” Castellana Grotte, Bari, Italy

¹³National Research Council, Neuroscience Institute, Aging Branch, Padua, Italy

¹⁴Greater Manchester Mental Health National Health Service Foundation Trust, United Kingdom

¹⁵ARCADIA Group, Professorial Unit, The Melbourne Clinic, Department of Psychiatry, University of Melbourne, Melbourne, Australia

^✉

Corresponding Author: Joseph Firth, PhD, NICM Health Research Institute, School of Science and Health, University of Western Sydney, Campbelltown, Sydney, NSW 2560, Australia (j.firth@westernsydney.edu.au).

Accepted for Publication: February 16, 2018.

Published Online: April 18, 2018. doi:10.1001/jamapsychiatry.2018.0503

Author Contributions: Dr J. Firth had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: J. Firth, J. A. Firth, Stubbs, Yung, Sarris.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: J. Firth, J. A. Firth, Stubbs, Schuch, Veronese, Yung, Sarris.

Critical revision of the manuscript for important intellectual content: J. Firth, J. A. Firth, Stubbs, Vancampfort, Schuch, Hallgren, Yung, Sarris.

Statistical analysis: J. Firth, J. A. Firth, Veronese.

Obtained funding: J. Firth.

Administrative, technical, or material support: J. Firth, Hallgren.

Study supervision: J. Firth, Stubbs, Schuch, Yung, Sarris.

Conflict of Interest Disclosures: None reported.

Funding/Support: Dr J. Firth is supported by a Blackmores Institute Fellowship and Medical Research Council doctoral training grant P117413F07. Dr Sarris is funded by National Health and Medical Research Council Research fellowship APP1125000. Dr Stubbs is partially funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London, Maudsley National Health Service (NHS) Foundation Trust, and King’s College London, and the NIHR Collaboration for Leadership in Applied Health Research and Care South London at King’s College Hospital NHS Foundation Trust.

Role of the Funder/Sponsor: The funding organizations had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: The views expressed are those of the authors and not necessarily those of the NHS, the NIHR, or the Department of Health and Social Care.

Additional Contributions: This research was conducted using the UK Biobank Resource under application number 22125. We acknowledge the efforts of the UK Biobank research team and thank all UK Biobank participants for agreeing to volunteer in this research.

^✉

Corresponding author.

PMCID: PMC6145677 PMID: 29710135

Key Points

Question

Can handgrip strength provide an indication of cognitive functioning in people with major depression or bipolar disorder and healthy controls?

Findings

In this cross-sectional analysis of a population-scale data set of 110 067 individuals, handgrip strength was significantly associated with all 5 domains of cognition in people with major depression and in healthy controls, independently of confounding factors. Similar associations, but to a lesser extent, were observed in those with bipolar disorder.

Meaning

Handgrip strength is associated with overall cognition in individuals with and without major depression; muscular function may provide a proxy for assessing neurocognitive impairment and present a novel interventional outcome for targeting cognitive improvement.

Abstract

Importance

Objective physical fitness measures, such as handgrip strength, are associated with physical, mental, and cognitive outcomes in the general population. Although people with mental illness experience reduced physical fitness and cognitive impairment, the association between muscular strength and cognition has not been examined to date.

Objective

To determine associations between maximal handgrip strength and cognitive performance in people with major depression or bipolar disorder and in healthy controls.

Design, Setting, and Participants

In a multicenter, population-based study conducted between February 13, 2005, and October 1, 2010, in the United Kingdom, cross-sectional analysis was conducted of baseline data from 110 067 participants in the UK Biobank. Data analysis was performed between August 3 and August 18, 2017. Invitations were mailed to approximately 9.2 million UK homes, recruiting 502 664 adults, all aged 37 to 73 years. Clinically validated measures were used to identify individuals with major recurrent depression (moderate or severe) or bipolar disorder (type I or type II) and healthy controls (those with no indication of present or previous mood disorders).

Main Outcomes and Measures

Handgrip dynamometry was used to measure muscular function. Cognitive functioning was assessed using computerized tasks of reaction time, visual memory, number memory, reasoning, and prospective memory. Generalized linear mixed models assessed the association between handgrip strength and cognitive performance, controlling for age, educational level, sex, body weight, and geographic region.

Results

Of the 110 067 participants, analyses included 22 699 individuals with major depression (mean [95% range] age, 55.5 [41-68] years; 7936 [35.0%] men), 1475 with bipolar disorder (age, 54.4 [41-68] years; 748 [50.7%] men), and 85 893 healthy controls (age, 53.7 [41-69] years; 43 000 [50.0%] men). In those with major depression, significant positive associations (P < .001) between maximal handgrip strength and improved performance on all 5 cognitive tasks were found, including visual memory (coefficient, −0.146; SE, 0.014), reaction time (coefficient, −0.036; SE, 0.002), reasoning (coefficient, 0.213; SE, 0.02), number memory (coefficient, 0.160; SE, 0.023), and prospective memory (coefficient, 0.341; SE, 0.024). Similar results were found in healthy controls. Among participants with bipolar disorder, handgrip strength was positively associated with improved visual memory (coefficient, −0.129; SE, 0.052; P = .01), reaction time (coefficient, −0.047; SE, 0.007; P < .001), prospective memory (coefficient, 0.262; SE, 0.088; P = .003), and reasoning (coefficient, 0.354; SE, 0.08; P < .001).

Conclusions and Relevance

Grip strength may provide a useful indicator of cognitive impairment in people with major depression and bipolar disorder. Future research should investigate causality, assess the functional implications of handgrip strength in psychiatric populations, and examine how interventions to improve muscular fitness affect neurocognitive status and socio-occupational functioning.

This population-based study evaluates the use of handgrip strength as a measure of cognitive function in people with major depression and bipolar disorder.

Introduction

Mood disorders, such as major depression and bipolar disorder, are associated with deficits in cognition including executive functioning, memory, and attentional processing.¹ These cognitive deficits also impair social and occupational functioning,² contributing to the personal, social, and economic burden associated with mood disorders.³ Thus, novel approaches for reducing these impairments and improving cognition in this population are needed.

Although the magnitude of cognitive deficits can vary over time, impairments are often present from adolescence and young adulthood,⁴ perhaps even preceding psychiatric diagnoses.⁵ Furthermore, some degree of dysfunction persists over the course of illness despite medication or current affective status.^1,6 Increasing our understanding of the pathology and factors contributing to cognitive deficits is essential for developing novel treatment strategies.

Physical health is increasingly recognized as a determining factor of neurocognitive status in psychiatric and nonpsychiatric populations. For instance, higher body mass index is associated with poorer cognitive performance and reduced gray matter in healthy samples.^4,7 In addition, increasing cardiorespiratory fitness improves cognition and increases brain volume in people with schizophrenia.^8,9,10,11 However, the effects of exercise on brain structure and function in people with affective disorders are inconsistent and underinvestigated.¹² Nonetheless, epidemiologic studies have found that cognitive functioning in people with depression holds significant correlations with physical activity.¹³

There is increasing recognition of the importance of objective physical fitness tests as being indicators of physical,¹⁴ mental,¹⁵ and cognitive¹⁶ outcomes in the general population. Hand handgrip strength is easily assessed and provides an objective measure of muscular fitness, which is emerging as a valid indicator of overall health status.¹⁷ For example, higher maximal handgrip scores are associated with reduced all-cause and cardiovascular mortality, independent of body mass index.^14,17 Furthermore, handgrip strength in aging populations bears significant associations with cognitive health, with higher scores indicating less cognitive decline and related functional disability.^18,19 Owing to the strength of the evidence in this area, handgrip strength is now considered an easily administered and clinically useful biomarker of cognitive decline across the lifespan.^16,20

Although handgrip strength has already been shown to be an indicator of risk of developing psychiatric disorders,^15,21 the potential value of handgrip strength as a marker of cognitive status in psychiatric disorders has not been explored. If handgrip strength provides a reliable indication of overall cognitive functioning, it is an attractive measure in comparison with other neurocognitive or biological markers, being noninvasive, inexpensive, and quickly administered with relatively little training.¹⁶

The aim of this study was to use population-scale data from the UK Biobank to establish how muscular function as measured by handgrip strength relates to cognitive functioning in people with major depression or bipolar disorder and healthy controls. The findings, in turn, will increase current understanding on the use of a handgrip dynamometer as an indicator of overall cognitive status, along with providing new insights into the contributing factors and possible interventions for cognitive functioning in people with and without psychiatric conditions.

Methods

The study was performed using data collected between February 13, 2005, and October 1, 2010. The UK Biobank is a nationwide, health-oriented, cohort study conducted across 22 dedicated assessment centers throughout the United Kingdom²² investigating the association of lifestyle, environmental, and genetic factors with an array of health outcomes. Invitations to participate were mailed to approximately 9.2 million UK homes. These invitations recruited 502 664 participants, aged 37 to 73 years, who attended UK Biobank assessment centers in person. Written informed consent was obtained from participants at the assessment centers before they were led through an extensive assessment process including touchscreen questionnaires, in-person interviews, and physical health examinations. There was no financial compensation. Full details of the UK Biobank data collection procedures are available elsewhere.²² This study is covered under the generic ethical approval for the UK Biobank from the National Health Service Research Ethics Committee. The specific analysis presented in this study was separately approved by the UK Biobank research committee.

Participant Sampling

Participants were categorized into groups of those with previous or present (1) major recurrent depression or (2) bipolar disorder and (3) healthy controls (ie, no indication of present or previous affective disorders). This categorization was conducted with respect to a previous study, which systematically assessed the prevalence of mood disorders within the UK Biobank cohort.²³ The study applied a preestablished criterion to individuals’ answers to the Structured Clinical Interview for DSM-IV Axis I Disorders and Patient Health Questionnaire²³ to categorize participants as likely having a single episode of major depression, recurrent major depression (moderate or severe), previous or present bipolar type I or type II disorder, or no indicated mood disorders. Categorization of participants was subsequently validated against other demographic and clinical information available from the UK Biobank, and lifetime prevalence rates were consistent with other population-based estimates for each disorder across both sexes.²³

For our study, participants with neurologic conditions known to affect cognitive functioning and nonaffective severe mental illnesses (eg, schizophrenia and other psychotic disorders) were excluded from the analyses. The excluded neurologic and psychiatric conditions are reported in eTable 1 in the Supplement.

Cognitive Functioning

Cognitive functioning was assessed within a brief (15 minutes) computerized task battery. This battery was developed specifically for UK Biobank population-scale research designed to be delivered electronically without requiring supervision. The task battery was completed at UK Biobank assessment centers and measured 5 domains of cognition, using the following tests (detailed in full elsewhere²⁴):

Visuospatial memory: attempts required to correctly pair 6 sets of symbol cards with their matching counterpart following brief visual presentation of these stimuli;
Reaction time: response time (in milliseconds) to sequentially matching cards presented in a digital game of “snap”;
Reasoning: number of numeric and verbal logic problems correctly solved in 2 minutes;
Prospective memory: dichotomous measure, assessing if participants acted correctly or incorrectly in response to an earlier instruction following a delay/distraction period;
Numeric memory: longest string of digits recalled correctly.

Handgrip Strength Measurement

Handgrip strength was measured at UK Biobank assessment centers by a research assistant, using a Jamar J00105 hydraulic hand dynamometer, in line with standard procedures for obtaining reliable and reproducible handgrip measurements.²⁵ A single, maximum score indicating the greatest strength was obtained for each hand. The testing began by allowing participants to select the most comfortable of 5 possible handgrip positions (ranging between 3.49 and 8.57 cm). Participants sat upright, elbow adjacent to their torso, and forearm positioned on an armrest with the thumb facing upward. The score from participants’ self-reported dominant hand was used for our analyses. If participants failed to specify handedness, the value from their highest-scoring hand was used.

Confounding Variables

Age, sex, educational level, body weight, and geographic location were identified as the key confounding variables. Age, sex, and educational level information was collected from computerized questionnaires completed at UK Biobank assessment centers. Highest educational level and qualifications responses were dichotomized to categorize participants as either having or not having university/college degree–level qualifications. Body weight measurement was acquired by a research assistant on-site during the physical health assessments. Geographic location was determined from the UK Biobank assessment center, which was recorded automatically during data collection.

Statistical Analysis

We aimed to assess factors related to performance in the cognitive domains by setting each of these measures as the dependent variable in separate models within the same analytical framework. Linear mixed models (LMMs) were run for reasoning, number memory, and reaction time, which was log transformed to normalize the data. Generalized LMMs with Poisson error structure were used when assessing visuospatial memory, as this measure is essentially count data, and generalized LMMs with binomial error structure (with logit link function) were used when considering prospective memory due to this being a binomial measurement. For each cognitive measure, we ran the same structure but separate models for each of the 3 separately considered samples (bipolar disorder, major depression, and control). Within each of the models, we primarily aimed to determine the association between handgrip strength (continuous measure) and the response variable (cognitive measure) while controlling for factors that are likely to influence the cognitive measure and for which sufficient data were available. Therefore, we fit handgrip strength as a fixed effect along with age, sex, body weight, and educational status. We also fit UK Biobank testing center as a random effect to account for the nonindependence between the different testing centers and other potentially associated variables. For each of the models run, we report appropriate summary statistics regarding the sample composition (sample size, means, and errors surrounding measurements of interest), the model parameter estimates, and associated 2-tailed P values, with significance determined at P < .05. Data analysis was conducted between August 3 and August 18, 2017. R, version 3.1.2 (R Foundation) was used for analysis.

Results

Included Participants

The summary characteristics of the participants are displayed in Table 1. The final analyses included a maximum of 110 067 participants who provided sufficient data, completing mood disorders screening, handgrip strength testing, and at least 1 of the cognitive tasks (visual memory being most commonly completed). Of these, 85 893 participants had no indication of any mood disorders (healthy controls), 22 699 reported recurrent major depression, and 1475 reported bipolar disorder (type I or type II). The mean age of the healthy control, bipolar disorder, and major depression samples was 53.7 years (95% range, 41-69 years; 43 000 [50.0%] men), 54.4 years (95% range, 41-68 years; 748 [50.7%] men), and 55.5 years (95% range, 41-68 years; 7936 [35.0%] men), respectively. Only a subset of participants (32 467 [29.5%] of total) completed the number memory task, as this was administered only during the pilot phase of the UK Biobank. The raw mean scores for handgrip strength and performance in each cognitive task across the major depression, bipolar disorder, and healthy control samples are reported in eTable 2 in the Supplement.

Table 1. Characteristics of Participants.

Characteristic	Raw, Mean (95% Range of Data)
Characteristic	Healthy Controls (n = 85 893)	Major Depression (n = 22 699)	Bipolar Disorder (n = 1475)
Age, y	53.7 (41-69)	55.5 (41-68)	54.4 (41-68)
Men, No. (%)	43 000 (50.0)	7936 (35.0)	748 (50.7)
Body weight, kg	85.7 (63-118)	78.3 (53-117)	80.7 (52-120)

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Associations Between Handgrip Strength and Cognitive Functioning

Table 2 displays the results of the generalized LMMs examining associations between handgrip strength and cognition in the major depression, bipolar disorder, and control samples. As shown in the Figure, A and B, all associations were in the hypothesized direction, with any negative effects below being related to cognitive task scoring where lower scores equate to improved cognitive performance.

Table 2. Results of Linear Mixed Models Analyses Showing the Associations Between Handgrip Strength and Each Cognitive Domain.

Cognitive Task	Healthy Controls				Major Depression				Bipolar Disorder
Cognitive Task	Total No.	Coefficient (SE)	t Value	P Value	Total No.	Coefficient (SE)	t Value	P Value	Total No.	Coefficient (SE)	t Value	P Value
Visual memory^a	85 893	−0.176 (0.007)^b	−23.9	<.001	22 699	−0.146 (0.014)^b	−10.8	<.001	1475	−0.129 (0.052)^b	−2.48	.01
Reaction time^a	84 947	−0.034 (0.001)^b	−35.7	<.001	22 504	−0.036 (0.002)^b	−20.3	<.001	1458	−0.047 (0.007)^b	−6.66	<.001
Prospective memory	85 445	0.332 (0.013)^b	26.5	<.001	22 615	0.341 (0.024)^b	14.3	<.001	1467	0.262 (0.088)^b	2.98	.003
Reasoning	82 948	0.202 (0.011)^b	18.8	<.001	22 107	0.213 (0.02)^b	10.8	<.001	1419	0.354 (0.080)^b	4.43	<.001
Number memory	25 336	0.140 (0.012)^b	11.3	<.001	6748	0.160 (0.023)^b	6.89	<.001	383	0.189 (0.105)	1.80	.07

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^{^a}

For negative associations, lower scores indicate better cognitive performance.

^{^b}

Statistically significant correlation.

Figure. — A, Healthy sample. B, Individuals with major depression. C, Individuals with bipolar disorder. Blue lines show the fit of the linear mixed models (number memory, reasoning, and reaction time) and generalized linear mixed models (visual memory and prospective memory) (see Table 2 for full model details). Blue shaded area shows the 95% CI around the mean of the raw cognitive measure split into bins (dependent on total sample size) of A, 0.1%, B, 1.0%, and C, 5.0% of the data.

In people with major depression, the generalized LMMs (setting age, sex, and weight qualifications as fixed effects, and geographic location as a random effect) showed that handgrip strength was a significant predictor of better cognitive performance in all 5 domains (all P < .001) (Figure, B): visual memory (t = −10.8; coefficient, −0.146; SE, 0.014), reaction time (t = −20.3, coefficient, −0.036; SE, 0.002), reasoning (t = 10.8; coefficient, 0.213; SE = 0.02), number memory (t = 6.89; coefficient, 0.160; SE, 0.023), and prospective memory (t = 14.3; coefficient, 0.341; SE, 0.024).

Similar findings were observed in the sample of 85 895 healthy participants with no indication of affective or neuropsychiatric conditions; significant associations were noted between greater handgrip strength and increased performance across all 5 cognitive domains (all P < .001) (Table 2, Figure, A).

In the models considering people with bipolar disorder (Figure, C), we found that handgrip strength was significantly associated with visual memory (t = −2.48; coefficient, −0.129; SE, 0.052; P = .01), reaction time (t = −6.66; coefficient, −0.047; SE, 0.007; P < .001), reasoning (t = 4.43; coefficient, −0.354; SE, 0.080; P < .001), and prospective memory (t = 2.98; coefficient, 0.262; SE, 0.088; P = .003). The association with number memory remained similar when considering people with major depression or healthy controls but it fell short of significance, potentially due to reduced power from the smaller subset of participants with bipolar disorder completing this measure (n = 383; t = 1.8; coefficient, −0.189; SE, 0.105; P = .07).

To examine if significant relationships between handgrip strength and cognition persisted when also controlling for metabolic health, we conducted post hoc sensitivity analysis, also adjusting for waist circumference (a marker of obesity-related health risk)²⁶and any reported history of vascular or heart problems diagnosed by a physician (including hypertension, angina, stroke, or myocardial infarction). Controlling for these additional factors did not affect the results (eTable 3 in the Supplement) other than the association between handgrip and visual memory in the bipolar disorder sample, which was now only approaching statistical significance (P = .07). The full model outputs for all of the confounding factors controlled for in our analyses are displayed in eTable 4 in the Supplement.

Discussion

To the best of our knowledge, the present study is the first population-scale study to examine associations between muscular and cognitive functioning in people with major depression and bipolar disorder. Across 110 067 participants of the UK Biobank, we showed that maximal handgrip strength held significant associations with greater performance in tasks of reasoning, reaction time, and immediate and delayed memory measures in people with major depression, bipolar disorder, and the general population. The consistent associations between handgrip strength and reaction time could potentially be explained by the rapid motor demands of reaction time tasks intuitively relating to muscular function of the hand, thus increasing the correlation between this cognitive domain and handgrip strength. Nonetheless, given the consistent associations found for other cognitive domains, such as fluid intelligence (reasoning) and delayed recall (prospective memory), which were assessed using tasks that do not rely on hand speed or dexterity, the associations between cognition and maximal handgrip strength cannot be ascribed only to greater motor skill inflating task performance. The findings are consistent with earlier smaller studies that have shown significant associations between muscular and cognitive functioning in other samples. The majority of research in this area to date has been conducted in older adults.¹⁶ Weak handgrip strength in this group has been shown to be a valid and clinically useful marker of both cognitive decline and impaired daily functioning.¹⁶

Although handgrip is the most widely used and validated measure of muscular fitness, the association between strength and cognitive performance extends to other muscle groups. Population-scale studies have shown that maximal force outputs of various muscle groups in the upper and lower limbs indicate both global cognitive functioning and risk of cognitive impairment among healthy older adults.²⁷

The exact nature of the association between handgrip strength and cognition is unclear. For instance, some studies have shown that changes in handgrip strength precede cognitive decline¹⁶ and that high handgrip strength at baseline is protective of age-related cognitive deterioration.²⁷ However, other studies have indicated an opposite directionality of this association, showing that cognitive impairments indicate future decline in muscular fitness.²⁸ Nonetheless, a recent, longer study assessed 708 adults at 6 time points over a 20-year period and concluded that the strength and stability of the connections between handgrip and cognition indicate bidirectionality and/or third-factor causality.²⁰ One possible underlying mechanism for the association is white matter integrity, as this is implicated in physical and mental performance across a range of tasks and domains. However, recent studies have indicated that other neural mechanisms must also play a role in the association between handgrip and cognition as the decrements in handgrip and cognition that occur over time in aging adults cannot be accounted for entirely by white matter degradation.¹⁸

To our knowledge, this study is the first to identify handgrip strength as a marker of cognitive function in mood disorders. However, the cross-sectional design of this investigation means that further longitudinal and mechanistic research must be conducted to determine the causative nature of the association between handgrip strength and cognition in psychiatric populations. This work could contribute toward handgrip strength providing an easily administered and clinically useful objective tool for routine assessment of cognitive and functional status in people with mood disorders. Its clinical potential is underlined by previous findings in people with bipolar depression that showed that handgrip scores have the highest reproducibility and intraclass correlations of all physical functional assessments.²⁹

Two recent meta-analyses of cognitive effects of exercise in depressive disorders found no overall effect, although the results were based largely on interventions using aerobic training.^12,30 Only a small number of studies have examined cognitive outcomes of resistance training in bipolar or depressive disorders. First, in a small, single-arm study, Strassnig et al³¹ reported significant improvements in memory and processing speed among a mixed sample of patients with schizophrenia and bipolar disorder undertaking 8 weeks of high-intensity weight training. Second, Krogh et al³² found no difference between resistance vs aerobic vs relaxation training on cognitive outcomes in people with depression. However, strength training outperformed aerobic training and relaxation groups for occupational functional outcomes, reducing days off work by 12% (P = .009) over 12 months, whereas aerobic exercise had no significant effect. This is a notable finding since unemployment and work absence confer the majority of economic burden associated with mood disorders.³ Other clinical trials have also shown socio-occupational benefits of strength training exercise in depression,³³ with greater effects from interventions that use high-intensity rather than low-intensity weight training. This finding indicates that the benefits of resistance training interventions are tied to improvements in muscular fitness.³⁴

Limitations

A limitation of this study is that no social or occupational functioning data were available. Thus, we were unable to explore the association between handgrip strength cognition and functioning. Furthermore, the cognitive task battery used did not include any of the traditional and/or widely validated tasks for assessing social cognition, which is an important cognitive construct that may mediate the association between neurocognition and real-world functioning. Another limitation of this study is that the mean age of the participants was approximately 55 years. Thus, the findings may not generalize to younger samples. Although the association between handgrip and cognition in younger psychiatric samples has not been assessed to date, a longitudinal population-scale study of over 1 million adolescents²¹ has previously shown that weak handgrip strength in younger people is associated with a 15% to 65% increased risk for psychiatric disorders in later life, thus, implicating handgrip as an important indicator of mental health risk, even prior to illness onset.

In addition, beyond considering handgrip strength as a marker of cognitive and functional capacities, further work should investigate how increasing muscular fitness may be a therapeutic target for improving cognitive and functional outcomes of individuals with mood disorders. There is now evidence from randomized clinical trials in aging populations that strength training exercise interventions significantly improve cognitive functioning^35,36 and may be more effective than computerized cognitive training.³⁷ The beneficial effects of resistance training may be mediated through exercise-induced increases in gray matter and attenuation of aging-related white matter abnormalities.³⁷

Conclusions

Further investigation is required to assess the effects of resistance training on cognitive functioning in people with depression and bipolar disorder to determine whether muscular function provides not only a biomarker of cognition, but also potential therapeutic target for reducing the social and economic burden of these conditions.

Supplement.

eTable 1. Neurological/Psychiatric Conditions Which Excluded Participants

eTable 2. Raw Mean Scores (and 95% Range) for Measures of Interest in MDD, BPD and Healthy Control Samples

eTable 3. Results of Sensitivity Analyses, Showing Relationships Between Grip Strength and Cognitive Domains in Fully Adjusted Models

eTable 4. Full Model Outputs Showing Relationships Between Each Cognitive Domain and All of the Fixed-Effects Confounding Factors

Click here for additional data file.^{(133.1KB, pdf)}

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13.Stubbs B, Koyanagi A, Schuch FB, et al. . Physical activity and depression: a large cross-sectional, population-based study across 36 low- and middle-income countries. Acta Psychiatr Scand. 2016;134(6):546-556. [DOI] [PubMed] [Google Scholar]
14.Veronese N, Stubbs B, Fontana L, et al. . A comparison of objective physical performance tests and future mortality in the elderly people. J Gerontol A Biol Sci Med Sci. 2017;72(3):362-368. [DOI] [PubMed] [Google Scholar]
15.Veronese N, Stubbs B, Trevisan C, et al. . Poor physical performance predicts future onset of depression in elderly people: Progetto Veneto Anziani Longitudinal Study. Phys Ther. 2017;97(6):659-668. [DOI] [PubMed] [Google Scholar]
16.Fritz NE, McCarthy CJ, Adamo DE. Handgrip strength as a means of monitoring progression of cognitive decline—a scoping review. Ageing Res Rev. 2017;35:112-123. [DOI] [PubMed] [Google Scholar]
17.Leong DP, Teo KK, Rangarajan S, et al. ; Prospective Urban Rural Epidemiology (PURE) Study investigators . Prognostic value of grip strength: findings from the Prospective Urban Rural Epidemiology (PURE) study. Lancet. 2015;386(9990):266-273. [DOI] [PubMed] [Google Scholar]
18.Viscogliosi G, Di Bernardo MG, Ettorre E, Chiriac IM. Handgrip strength predicts longitudinal changes in clock drawing test performance: an observational study in a sample of older non-demented adults. J Nutr Health Aging. 2017;21(5):593-596. [DOI] [PubMed] [Google Scholar]
19.Taekema DG, Gussekloo J, Maier AB, Westendorp RG, de Craen AJ. 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):331-337. [DOI] [PubMed] [Google Scholar]
20.Sternäng O, Reynolds CA, Finkel D, Ernsth-Bravell M, Pedersen NL, Dahl Aslan AK. Grip strength and cognitive abilities: associations in old age. J Gerontol B Psychol Sci Soc Sci. 2016;71(5):841-848. [DOI] [PMC free article] [PubMed] [Google Scholar]
21.Ortega FB, Silventoinen K, Tynelius P, Rasmussen F. Muscular strength in male adolescents and premature death: cohort study of one million participants. BMJ. 2012;345:e7279. [DOI] [PMC free article] [PubMed] [Google Scholar]
22.UK Biobank Coordinating Centre UK Biobank: Protocol for a Large-Scale Prospective Epidemiological Resource. http://www.ukbiobank.ac.uk/wp-content/uploads/2011/11/UK-Biobank-Protocol.pdf. Published March 27, 2007. Accessed March 1, 2018.
23.Smith DJ, Nicholl BI, Cullen B, et al. . Prevalence and characteristics of probable major depression and bipolar disorder within UK Biobank: cross-sectional study of 172,751 participants. PLoS One. 2013;8(11):e75362. [DOI] [PMC free article] [PubMed] [Google Scholar]
24.Lyall DM, Cullen B, Allerhand M, et al. . Cognitive test scores in UK Biobank: data reduction in 480,416 participants and longitudinal stability in 20,346 participants. PLoS One. 2016;11(4):e0154222. [DOI] [PMC free article] [PubMed] [Google Scholar]
25.Roberts HC, Denison HJ, Martin HJ, et al. . A review of the measurement of grip strength in clinical and epidemiological studies: towards a standardised approach. Age Ageing. 2011;40(4):423-429. [DOI] [PubMed] [Google Scholar]
26.Janssen I, Katzmarzyk PT, Ross R. Waist circumference and not body mass index explains obesity-related health risk. Am J Clin Nutr. 2004;79(3):379-384. [DOI] [PubMed] [Google Scholar]
27.Narazaki K, Matsuo E, Honda T, Nofuji Y, Yonemoto K, Kumagai S. Physical fitness measures as potential markers of low cognitive function in Japanese community-dwelling older adults without apparent cognitive problems. J Sports Sci Med. 2014;13(3):590-596. [PMC free article] [PubMed] [Google Scholar]
28.Atkinson HH, Rapp SR, Williamson JD, et al. . The relationship between cognitive function and physical performance in older women: results from the Women’s Health Initiative Memory Study. J Gerontol A Biol Sci Med Sci. 2010;65(3):300-306. [DOI] [PMC free article] [PubMed] [Google Scholar]
29.Vancampfort D, Sienaert P, Wyckaert S, et al. . Test-retest reliability, feasibility and clinical correlates of the Eurofit test battery in people with bipolar disorder. Psychiatry Res. 2015;228(3):620-625. [DOI] [PubMed] [Google Scholar]
30.Sun M, Lanctot K, Herrmann N, Gallagher D. Exercise for cognitive symptoms in depression: a systematic review of interventional studies. Can J Psychiatry. 2018;63(2):115-128. [DOI] [PMC free article] [PubMed] [Google Scholar]
31.Strassnig M, Brar JS, Ganguli R. Body mass index and quality of life in community-dwelling patients with schizophrenia. Schizophr Res. 2003;62(1-2):73-76. [DOI] [PubMed] [Google Scholar]
32.Krogh J, Saltin B, Gluud C, Nordentoft M. The DEMO trial: a randomized, parallel-group, observer-blinded clinical trial of strength versus aerobic versus relaxation training for patients with mild to moderate depression. J Clin Psychiatry. 2009;70(6):790-800. [DOI] [PubMed] [Google Scholar]
33.Singh NA, Clements KM, Fiatarone MA. A randomized controlled trial of progressive resistance training in depressed elders. J Gerontol A Biol Sci Med Sci. 1997;52(1):M27-M35. [DOI] [PubMed] [Google Scholar]
34.Singh NA, Stavrinos TM, Scarbek Y, Galambos G, Liber C, Fiatarone Singh MA. A randomized controlled trial of high versus low intensity weight training versus general practitioner care for clinical depression in older adults. J Gerontol A Biol Sci Med Sci. 2005;60(6):768-776. [DOI] [PubMed] [Google Scholar]
35.Cassilhas RC, Viana VA, Grassmann V, et al. . The impact of resistance exercise on the cognitive function of the elderly. Med Sci Sports Exerc. 2007;39(8):1401-1407. [DOI] [PubMed] [Google Scholar]
36.Liu-Ambrose T, Nagamatsu LS, Graf P, Beattie BL, Ashe MC, Handy TC. Resistance training and executive functions: a 12-month randomized controlled trial. Arch Intern Med. 2010;170(2):170-178. [DOI] [PMC free article] [PubMed] [Google Scholar]
37.Suo C, Singh MF, Gates N, et al. . Therapeutically relevant structural and functional mechanisms triggered by physical and cognitive exercise. Mol Psychiatry. 2016;21(11):1633-1642. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplement.

eTable 1. Neurological/Psychiatric Conditions Which Excluded Participants

eTable 2. Raw Mean Scores (and 95% Range) for Measures of Interest in MDD, BPD and Healthy Control Samples

eTable 3. Results of Sensitivity Analyses, Showing Relationships Between Grip Strength and Cognitive Domains in Fully Adjusted Models

eTable 4. Full Model Outputs Showing Relationships Between Each Cognitive Domain and All of the Fixed-Effects Confounding Factors

Click here for additional data file.^{(133.1KB, pdf)}

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[yoi180016r10] 10.Kimhy D, Vakhrusheva J, Bartels MN, et al. . Aerobic fitness and body mass index in individuals with schizophrenia: implications for neurocognition and daily functioning. Psychiatry Res. 2014;220(3):784-791. [DOI] [PMC free article] [PubMed] [Google Scholar]

[yoi180016r11] 11.Kimhy D, Vakhrusheva J, Bartels MN, et al. . The impact of aerobic exercise on brain-derived neurotrophic factor and neurocognition in individuals with schizophrenia: a single-blind, randomized clinical trial. Schizophr Bull. 2015;41(4):859-868. [DOI] [PMC free article] [PubMed] [Google Scholar]

[yoi180016r12] 12.Brondino N, Rocchetti M, Fusar-Poli L, et al. . A systematic review of cognitive effects of exercise in depression. Acta Psychiatr Scand. 2017;135(4):285-295. [DOI] [PubMed] [Google Scholar]

[yoi180016r13] 13.Stubbs B, Koyanagi A, Schuch FB, et al. . Physical activity and depression: a large cross-sectional, population-based study across 36 low- and middle-income countries. Acta Psychiatr Scand. 2016;134(6):546-556. [DOI] [PubMed] [Google Scholar]

[yoi180016r14] 14.Veronese N, Stubbs B, Fontana L, et al. . A comparison of objective physical performance tests and future mortality in the elderly people. J Gerontol A Biol Sci Med Sci. 2017;72(3):362-368. [DOI] [PubMed] [Google Scholar]

[yoi180016r15] 15.Veronese N, Stubbs B, Trevisan C, et al. . Poor physical performance predicts future onset of depression in elderly people: Progetto Veneto Anziani Longitudinal Study. Phys Ther. 2017;97(6):659-668. [DOI] [PubMed] [Google Scholar]

[yoi180016r16] 16.Fritz NE, McCarthy CJ, Adamo DE. Handgrip strength as a means of monitoring progression of cognitive decline—a scoping review. Ageing Res Rev. 2017;35:112-123. [DOI] [PubMed] [Google Scholar]

[yoi180016r17] 17.Leong DP, Teo KK, Rangarajan S, et al. ; Prospective Urban Rural Epidemiology (PURE) Study investigators . Prognostic value of grip strength: findings from the Prospective Urban Rural Epidemiology (PURE) study. Lancet. 2015;386(9990):266-273. [DOI] [PubMed] [Google Scholar]

[yoi180016r18] 18.Viscogliosi G, Di Bernardo MG, Ettorre E, Chiriac IM. Handgrip strength predicts longitudinal changes in clock drawing test performance: an observational study in a sample of older non-demented adults. J Nutr Health Aging. 2017;21(5):593-596. [DOI] [PubMed] [Google Scholar]

[yoi180016r19] 19.Taekema DG, Gussekloo J, Maier AB, Westendorp RG, de Craen AJ. 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):331-337. [DOI] [PubMed] [Google Scholar]

[yoi180016r20] 20.Sternäng O, Reynolds CA, Finkel D, Ernsth-Bravell M, Pedersen NL, Dahl Aslan AK. Grip strength and cognitive abilities: associations in old age. J Gerontol B Psychol Sci Soc Sci. 2016;71(5):841-848. [DOI] [PMC free article] [PubMed] [Google Scholar]

[yoi180016r21] 21.Ortega FB, Silventoinen K, Tynelius P, Rasmussen F. Muscular strength in male adolescents and premature death: cohort study of one million participants. BMJ. 2012;345:e7279. [DOI] [PMC free article] [PubMed] [Google Scholar]

[yoi180016r22] 22.UK Biobank Coordinating Centre UK Biobank: Protocol for a Large-Scale Prospective Epidemiological Resource. http://www.ukbiobank.ac.uk/wp-content/uploads/2011/11/UK-Biobank-Protocol.pdf. Published March 27, 2007. Accessed March 1, 2018.

[yoi180016r23] 23.Smith DJ, Nicholl BI, Cullen B, et al. . Prevalence and characteristics of probable major depression and bipolar disorder within UK Biobank: cross-sectional study of 172,751 participants. PLoS One. 2013;8(11):e75362. [DOI] [PMC free article] [PubMed] [Google Scholar]

[yoi180016r24] 24.Lyall DM, Cullen B, Allerhand M, et al. . Cognitive test scores in UK Biobank: data reduction in 480,416 participants and longitudinal stability in 20,346 participants. PLoS One. 2016;11(4):e0154222. [DOI] [PMC free article] [PubMed] [Google Scholar]

[yoi180016r25] 25.Roberts HC, Denison HJ, Martin HJ, et al. . A review of the measurement of grip strength in clinical and epidemiological studies: towards a standardised approach. Age Ageing. 2011;40(4):423-429. [DOI] [PubMed] [Google Scholar]

[yoi180016r26] 26.Janssen I, Katzmarzyk PT, Ross R. Waist circumference and not body mass index explains obesity-related health risk. Am J Clin Nutr. 2004;79(3):379-384. [DOI] [PubMed] [Google Scholar]

[yoi180016r27] 27.Narazaki K, Matsuo E, Honda T, Nofuji Y, Yonemoto K, Kumagai S. Physical fitness measures as potential markers of low cognitive function in Japanese community-dwelling older adults without apparent cognitive problems. J Sports Sci Med. 2014;13(3):590-596. [PMC free article] [PubMed] [Google Scholar]

[yoi180016r28] 28.Atkinson HH, Rapp SR, Williamson JD, et al. . The relationship between cognitive function and physical performance in older women: results from the Women’s Health Initiative Memory Study. J Gerontol A Biol Sci Med Sci. 2010;65(3):300-306. [DOI] [PMC free article] [PubMed] [Google Scholar]

[yoi180016r29] 29.Vancampfort D, Sienaert P, Wyckaert S, et al. . Test-retest reliability, feasibility and clinical correlates of the Eurofit test battery in people with bipolar disorder. Psychiatry Res. 2015;228(3):620-625. [DOI] [PubMed] [Google Scholar]

[yoi180016r30] 30.Sun M, Lanctot K, Herrmann N, Gallagher D. Exercise for cognitive symptoms in depression: a systematic review of interventional studies. Can J Psychiatry. 2018;63(2):115-128. [DOI] [PMC free article] [PubMed] [Google Scholar]

[yoi180016r31] 31.Strassnig M, Brar JS, Ganguli R. Body mass index and quality of life in community-dwelling patients with schizophrenia. Schizophr Res. 2003;62(1-2):73-76. [DOI] [PubMed] [Google Scholar]

[yoi180016r32] 32.Krogh J, Saltin B, Gluud C, Nordentoft M. The DEMO trial: a randomized, parallel-group, observer-blinded clinical trial of strength versus aerobic versus relaxation training for patients with mild to moderate depression. J Clin Psychiatry. 2009;70(6):790-800. [DOI] [PubMed] [Google Scholar]

[yoi180016r33] 33.Singh NA, Clements KM, Fiatarone MA. A randomized controlled trial of progressive resistance training in depressed elders. J Gerontol A Biol Sci Med Sci. 1997;52(1):M27-M35. [DOI] [PubMed] [Google Scholar]

[yoi180016r34] 34.Singh NA, Stavrinos TM, Scarbek Y, Galambos G, Liber C, Fiatarone Singh MA. A randomized controlled trial of high versus low intensity weight training versus general practitioner care for clinical depression in older adults. J Gerontol A Biol Sci Med Sci. 2005;60(6):768-776. [DOI] [PubMed] [Google Scholar]

[yoi180016r35] 35.Cassilhas RC, Viana VA, Grassmann V, et al. . The impact of resistance exercise on the cognitive function of the elderly. Med Sci Sports Exerc. 2007;39(8):1401-1407. [DOI] [PubMed] [Google Scholar]

[yoi180016r36] 36.Liu-Ambrose T, Nagamatsu LS, Graf P, Beattie BL, Ashe MC, Handy TC. Resistance training and executive functions: a 12-month randomized controlled trial. Arch Intern Med. 2010;170(2):170-178. [DOI] [PMC free article] [PubMed] [Google Scholar]

[yoi180016r37] 37.Suo C, Singh MF, Gates N, et al. . Therapeutically relevant structural and functional mechanisms triggered by physical and cognitive exercise. Mol Psychiatry. 2016;21(11):1633-1642. [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

Association Between Muscular Strength and Cognition in People With Major Depression or Bipolar Disorder and Healthy Controls

Joseph Firth, PhD

Josh A Firth, DPhil

Brendon Stubbs, PhD

Davy Vancampfort, PhD

Felipe B Schuch, PhD

Mats Hallgren, PhD

Nicola Veronese, MD

Alison R Yung, MD

Jerome Sarris, PhD

Key Points

Question

Findings

Meaning

Abstract

Importance

Objective

Design, Setting, and Participants

Main Outcomes and Measures

Results

Conclusions and Relevance

Introduction

Methods

Participant Sampling

Cognitive Functioning

Handgrip Strength Measurement

Confounding Variables

Statistical Analysis

Results

Included Participants

Table 1. Characteristics of Participants.

Associations Between Handgrip Strength and Cognitive Functioning

Table 2. Results of Linear Mixed Models Analyses Showing the Associations Between Handgrip Strength and Each Cognitive Domain.

Figure. Association Between Handgrip Strength and Cognitive Domains.

Discussion

Limitations

Conclusions

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

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Links to NCBI Databases