Poorer performance on physical frailty-related parameters is associated with depression among older rural Indians

Abstract

The role of physical factors in depression is prominent but often underrecognized in the aging population. The potential relationship between physical frailty and depression among older adults has been understudied in the rural southern Indian population. We aimed to examine if there is a cross-sectional association between three objective physical frailty-related parameters (handgrip strength, HGS; timed up-and-go, TUG test; chair stand Test, CST) with depression (assessed using the Geriatric Depression Scale, GDS-30) among 4455 participants aged ≥ 55 years from a rural population in Karnataka, India. Binary logistic regression was used to test the association between each of the three frailty-related parameters and depression. Odds ratios (OR) along with 95% confidence intervals (Cl) were estimated, adjusting for covariates (age, sex, education, marital status, income, current tobacco use, current alcohol use, body mass index, number of medical comorbidities, and family history of depression). We found that for every kilogram increase in HGS and every point increase in the CST score, there was 0.97 (95% CI 0.96–0.99, p = 0.008) and 0.93 (95% CI 0.90–0.96, p < 0.001) times lower odds of depression, respectively, whereas each unit of increase in TUG time was associated with 1.05 (95% CI 1.03–1.08, p < 0.001) times higher odds of depression. We underscore the clinical importance of routine physical frailty assessments in older adults, as specific frailty-related parameters could potentially predict depression.

Introduction

Depression is a common mental health disorder that contributes substantially to the global disease burden¹. Depression is widely prevalent among older adults², and its adverse impact on this population is profound, resulting in poor quality of life, disability, and mortality³. Nevertheless, it is underdiagnosed and undertreated, resulting in substantial strain on healthcare systems and enormous economic costs.

In India, wherein the proportion of older adults is rising rapidly, geriatric depression poses a serious public health challenge⁴. Recent estimates suggest that around one-third of the older Indian population could be suffering from depression⁵. Furthermore, in a country with the highest population in the world, there is a shortage of mental health professionals⁶, and the treatment gap for mental illnesses is as high as 83%⁷. Considering the estimates of around 350 million older persons by 2050 in India, poor mental health awareness and stigma, underdiagnosis and undertreatment of depression, the growing prevalence of chronic non-communicable diseases, and the rapidly changing family systems, depression among older adults in India will be a formidable health problem to contend with in the coming years.

Depression in the older population is not merely a psychological issue but rather a complex interplay of biological, psychological, and social factors associated with aging³. Understanding these factors is essential for identifying at-risk individuals, implementing preventive measures, and providing appropriate interventions. Notably, the role of physical factors in depression is prominent but often underrecognized in the aging population. For example, physical or sensory limitations, nutritional problems, and chronic medical conditions could increase the susceptibility to depression⁸. These factors could also perpetuate depression or adversely influence its prognosis. Hence, a comprehensive physical assessment of older adults should be essential to their mental health evaluation and management.

One of the essential components of a comprehensive geriatric assessment is the assessment of physical frailty⁹. Frailty is regarded as a clinically recognizable state of increased vulnerability to stressors or diminished resilience to health insults owing to decreased physiological reserves¹⁰. Though the concept of frailty has recently been expanded to include not only the physical dimension but psychosocial and cognitive dimensions also, in this paper, we have used the term frailty to refer to physical frailty only. The necessity for prompt assessment of physical frailty among older adults stems from its association with a range of adverse health consequences, such as falls, disability, multimorbidity, hospitalizations, and mortality^11,12.

The potential relationship between physical frailty and depression among older adults is complex but holds immense clinical significance. The physical limitations entailing frailty may increase the risk for depression, worsen existing depressive symptoms, or hinder recovery. Inversely, it is possible that depression could make an individual frail, as depression often results in reduced motivation, decreased physical and social activity, or poor nutritional intake¹³. Irrespective of the mechanisms linking frailty and depression, the consequences of them existing together could be considerably unfavourable to both physical and psychological well-being and increase the likelihood of disability and mortality¹⁴.

There is no gold standard or straightforward assessment tool to measure frailty. Several assessment methods have been proposed depending on the varying operational definitions¹⁵. Some are self-reported questionnaires^16,17, while others have incorporated objective measurements such as hand grip strength and gait speed¹⁸. Among the objective parameters for physical frailty, upper limb strength (hand grip strength, HGS using hand dynamometry), lower limb strength (using the chair stand test, CST), and functional mobility (using the timed up-and-go, TUG test) have been widely used and have been shown to be reliable indicators of frailty^19–22.

Though there have been prior attempts to establish a link between physical frailty and depression, such studies have mainly been restricted to Western populations. However, the prevalence, clinical presentation, and factors associated with depression could vary tremendously from population to population. Similarly, physical frailty could be related to several population-specific factors such as ethnicity, income status, educational level, social environment, and so on^23,24. For example, a prior study²⁵ that derived normative data for frailty-related parameters (HGS and TUG time) from a rural Indian cohort revealed that reference values for this population were considerably different compared to various Western and other Asian populations. Further, frailty status and the impact of frailty on health outcomes could depend on access to healthcare and healthcare utilization²⁶. For instance, rural Indians have limited access to healthcare compared to urban or Western populations. The impact of frailty on depression could also be modified by psychosocial variables, such as perceived stress, social support, and control beliefs, which could differ considerably from population to population²⁷. In this background, this study is unique since it is conducted in a non-Caucasian, marginalized, rural-dwelling Indian population with low education and limited healthcare access. This population has been grossly underrepresented in healthcare research, and well-conducted studies to understand the potential relationship between frailty and depression in this particular population are limited.

Rural Indians have a significantly higher proportion of depression as compared to their urban counterparts^28,29. This difference further widened after the COVID-19 pandemic, indicating that these individuals are likely to be highly vulnerable to psychosocial stressors³⁰. Considering the challenges in the diagnosis and treatment of depression in this rural setting, it is critical to focus on primary prevention. So, understanding its potential causal factors is necessary to develop appropriate, community-level, primary prevention strategies.

This study aimed to examine if there was an association between specific physical frailty measures and depression among non-demented, older rural Indians. We considered three objective physical frailty-related parameters, namely hand grip strength (HGS) for measuring upper limb strength, timed up-and-go (TUG) test time for measuring functional mobility, and chair stand test (CST) score for measuring lower limb strength. We used the Geriatric Depression Scale (GDS-30) to screen for depression. We hypothesized that poorer performance on HGS, TUG test, and CST was associated with higher odds of depression in this study population.

Methods

Study design and recruitment

We used cross-sectional, baseline data of 4455 participants (2296 males and 2159 females) aged 55 years and above, derived from a prospective aging cohort study that is ongoing in rural Karnataka in India, namely the Srinivaspura NeuroSenescence and COGnition (SANSCOG) study. The SANSCOG cohort aims to recruit 10,000 individuals aged 45+ years to study the diverse patterns of cognitive aging among rural Indians, thereby identifying risk and protective factors for dementia. The detailed study protocol of the SANSCOG study has been published elsewhere³¹. The SANSCOG cohort is recruited through an area sampling strategy from the villages of Srinivaspura in the Kolar district in the southern Indian state of Karnataka. The SANSCOG field team comprising trained social workers, with the help of Accredited Social Health Activists (ASHAs, community health workers who are part of India’s National Rural Health Mission and who act as an interface between the rural community and the public health system), systematically recruits from the all the villages attached to each Primary Health Centre (PHC, the basic unit of India’s public funded healthcare system) of Srinivaspura. Awareness programs are conducted at each village through talks and audiovisual presentations to inform potential participants about the study. Following this, the SANSCOG field team conducts door-to-door visits to obtain consent from eligible individuals to enroll in the study. Once all the villages of the PHC are covered, the villages of the next PHC are targeted. Individuals with a diagnosis of dementia or terminal medical illnesses and those with severe visual or hearing impairments that could preclude the study assessments are excluded.

Study participants

SANSCOG participants are a predominantly agricultural community engaged in mango cultivation (Srinivaspura is famous for its mango plantations and is one of the largest mango producers in the country). They have low levels of formal education and limited access to advanced healthcare or modern technology. For the present analysis, we included only those SANSCOG participants aged 55 + years with complete data for the studied clinical variables.

Ethics clearance and informed consent

The SANSCOG study was cleared by the Institutional Ethics Committee of the Centre for Brain Research, Indian Institute of Science. Written, informed consent was taken from all participants before recruitment into the study. All research methods in this study were performed in accordance with the Declaration of Helsinki.

Assessments

Frailty-related parameters

We used three objective, quantifiable frailty-related parameters, namely handgrip strength (HGS), timed up-and-go (TUG) test, and chair stand test (CST). The assessment procedures of these measures are described below.

Handgrip strength (HGS)

HGS is a reliable and widely used measure of frailty and is a component of several well-validated frailty scales^18,32. It is a measure of the strength and function of the muscles in the hand and forearm. Our study assessed handgrip strength using an electronic hand dynamometer (Camry—EH101). The participant was seated in an armed chair, with the wrist held in a neutral position (thumb facing upwards) and resting just over the end of the chair’s arm. The participant was instructed to hold the instrument with the dominant hand, with the thumb around the top of the handle and the other four fingers around the bottom. The examiner’s hand gently supported the dynamometer’s base (to negate gravity’s effect) without restricting its movement. The participant was then asked to squeeze the handle as hard and as long as possible. Two such attempts were allowed, and the higher reading (in kilograms) was taken as the maximum handgrip strength.

Timed up-and-go (TUG) test

The TUG test is another reliable marker of frailty and assesses functional mobility, which, in turn, is a function of gait and balance³³. This test is simple to administer and has been found to possess good psychometric properties³⁴. The participant was seated on a stable, iron stool and then instructed to get up, walk a distance of 3 metres (at a normal pace), turn around, walk back, and be seated again. The total time taken was measured in seconds with a stopwatch.

Chair stand test (CST)

The 30-second CST is a simple marker of frailty that measures lower limb muscle strength³⁵. The participant was seated in a stable chair with the back straight, feet rested on the floor at an angle slightly behind the knees, with one foot slightly in front of the other to help maintain balance when standing; the arms must be crossed against the chest. The participant was instructed to rise to stand erect and then return to the seated position. After one practice trial, they must perform as many full stands as possible within 30 seconds and the examiner counted the total number of correctly executed stands.

Assessment of depression

Depression was measured using the Geriatric Depression Scale (GDS-30), administered in the participants’ local language. The GDS is a widely used screening instrument that was developed to assess depressive symptoms among older adults and has demonstrated good validity and reliability in various populations, including southern Indian populations^36,37. It comprises 30 simple, self-rated questions that must be answered as ‘yes’ or ‘no.’ Each question carries one point, thus yielding a maximum score of 30. A score of 10 and above is indicative of depression³⁶.

Covariates

We used socio-demographic and clinical assessment data collected from our participants as part of the SANSCOG study assessments to adjust for the below-mentioned covariates. In addition to age (years) and sex (male/female), educational level was determined according to the total years of formal education received. Individuals’ annual income was categorized as ≥ 50,000 and < 50,000 Indian Rupees. The Body Mass Index (BMI) was calculated using the standard formula of the participant’s weight (in kilograms) divided by the square of the height (in meters). Current tobacco use and current alcohol use were determined based on self-report by the participant. The number of medical comorbidities was calculated based on a self-report of hypertension, diabetes mellitus, high cholesterol, renal disease, lung disease, thyroid disease, arthritis, cardiac illness, stroke, transient ischemic attack (TIA), Parkinson’s disease, and cancer. For this analysis, participants were grouped as “no comorbidities,” “one comorbidity,” and “two or more comorbidities.” Cognitive status was determined using the Clinical Dementia Rating (CDR) scale, and participants were classified as Normal (CDR = 0) and Mild Cognitive Impairment (MCI, CDR = 0.5); participants with dementia (CDR ≥ 1) were excluded from this study. A self-reported family history of depression was also taken as a covariate.

Statistical analysis

The sample characteristics were expressed as frequencies (%) for categorical variables, and their association with depression was tested using the Chi-squared test. Continuous variables were expressed as means with standard deviations (SD) or medians with interquartile ranges (IQR), as appropriate. The Student’s t-test was used to compare the means between two normally distributed, independent continuous variables, whereas the Mann–Whitney U test, a non-parametric analog of the t-test, was used to compare the means between two normally distributed, independent ordinal variables. Multivariable logistic regression was used to examine the association between each of the three frailty-related parameters (HGS, TUG test, and CST) and depression, and odds ratios (OR) along with 95% confidence intervals (Cl) were estimated, adjusting for covariates. We fitted two models separately, wherein model 1 was unadjusted and Model 2 was adjusted for age, sex, age, education, marital status, income, current tobacco use, current alcohol use, body mass index (BMI), number of medical comorbidities, cognitive status, and family history of depression. SPSS version 25.0³⁸ was used for all statistical analyses, and a p-value of less than 0.05 was considered statistically significant.

Results

Participant characteristics

Among the 4455 participants in this study, 2296 (51.54%) were males and 2159 (48.46%) were females. The mean HGS was 21.20 (7.09) kilograms (kg), the mean TUG time was 12.10 (3.14) seconds (s), and the mean CST score was 11.09 (2.96). The prevalence of depression was 17.48%, which was significantly higher among females as compared to males. While comparing the participant characteristics between the depressed and not depressed groups, the depressed group had a significantly higher proportion of individuals who were females, less educated, having two or more comorbidities, using tobacco, and having a family history of depression. The detailed characteristics of the study participants are presented in Table 1.

Table 1.

Comparison of participant characteristics between non-depressed and depressed groups.

Characteristics	Total (n = 4455)	Not depressed (n = 3676)	Depressed (n = 779)	p-value
Age, mean (SD)	64.93 (7.15)	64.80 (7.05)	65.58 (7.55)	0.005
Sex, n (%)
Male	2296 (51.54)	2002 (54.46)	294 (37.74)
Female	2159 (48.46)	1674 (45.54)	485 (62.26)	< 0.001
Education in years, mean (SD)	3.31 (4.32)	3.54 (4.42)	2.22 (3.64)	< 0.001
Body mass index, mean (SD)	22.96 (4.12)	22.98 (4.09)	22.89 (4.28)	0.139
Marital status, n (%)
Living with partner	3442 (77.26)	2912 (79.21)	530 (68.04)
Living without partner	1013 (22.74)	764 (20.79)	249 (31.96)	< 0.001
Individual annual income, n (%)
≥ 50,000 Indian rupees	1390 (31.20)	1161 (31.59)	229 (29.40)
< 50,000 Indian rupees	3065 (68.80)	2515 (68.41)	550 (70.60)	0.124
Tobacco use status, n (%)
No current use	2771 (62.20)	2311 (62.87)	460 (59.05)
Current use	1684 (37.80)	1365 (37.13)	319 (40.95)	0.026
Alcohol use status, n (%)
No current use	4211 (94.52)	3476 (94.56)	735 (94.35)
Current use	244 (5.48)	200 (5.44)	44 (5.64)	0.436
Family history of depression, n (%)
No	4345 (97.53)	3603 (98.02)	742 (95.25)
Yes	110 (2.47)	73 (1.98)	37 (4.75)	< 0.001
Number of comorbidities, n (%)
None	2847 (63.90)	2396 (65.18)	451 (57.89)
One	1142 (25.64)	931 (25.33)	211 (27.09)
Two or more	466 (10.46)	349 (9.49)	117 (15.02)	< 0.001
Cognitive status, n (%)
CDR = 0 (Normal)	3639 (81.68)	3089 (84.03)	550 (70.60)
CDR = 0.5 (MCI)	816 (18.32)	587 (15.97)	229 (29.40)	< 0.001
HGS (kg), mean (SD)	21.20 (7.09)	21.61 (7.19)	19.24 (6.24)	< 0.001
TUG test (s), mean (SD)	12.10 (3.14)	11.92 (2.91)	12.91 (3.96)	< 0.001
CST, mean (SD)	11.09 (2.96)	11.23 (3.00)	10.44 (2.68)	< 0.001
History of psychiatric illness
No	4433 (99.51)	3664 (99.67)	769 (98.72)
Yes	22 (0.49)	12 (0.33)	10 (1.28)	0.002

SD - Standard deviation, IQR - Interquartile range, HGS - Handgrip strength, kg - kilograms, TUG - Timed up-and-go, s - seconds, CST - Chair stand test, CDR - Clinical Dementia Rating , MCI - Mild Cognitive Impairment.

Association between handgrip strength (HGS) and depression

Multivariable logistic regression results revealed that in the fully adjusted model, handgrip strength was negatively associated with depression. Each kilogram increase in handgrip strength was associated with 0.97 times lower odds of depression (95% CI 0.96–0.99, p = 0.008, Fig. 1; Table 2).

Fig. 1.

This figure is a forest plot of the Odds Ratios (95% CI) of physical frailty-related parameters, namely Handgrip Strength (HGS), Timed Up-and-Go (TUG) test, and 30-second Chair Stand Test (CST) with depression from the logistic regression analysis. Results from model 2 (adjusted for age, sex, education, marital status, income, current tobacco use, current alcohol use, body mass index, number of medical comorbidities, cognitive status, and family history of depression) are depicted.

Table 2.

Association between frailty-related parameters and depression.

Frailty parameters	Model 1, OR (95% CI)	Model 2, OR (95% CI)
HGS (kg)	0.95 (0.93,0.96)*	0.97 (0.96,0.99)*
TUG test (s)	1.09 (1.06,1.11)*	1.05 (1.03,1.08)*
CST	0.89 (0.87,0.92)*	0.93 (0.90,0.96)*

Model 1 was unadjusted; Model 2 was adjusted for age, sex, education, marital status, individual annual income, current tobacco use, current alcohol use, body mass index, number of medical comorbidities, cognitive status, and family history of depression.

OR - Odds ratio, HGS - Handgrip strength, kg - kilograms, TUG - Timed up-and-go, s - seconds, CST - Chair stand test.

*p-value < 0.05.

Association between timed-up-and-go (TUG) test and depression

We found that the TUG score was positively associated with depression after adjusting for all the covariates. Further, each unit of increase in TUG time was associated with 1.05 times higher odds of depression (95% CI 1.03–1.08, p < 0.001) (Fig. 1; Table 2).

Association between chair stand test (CST) and depression

We found that the CST score was negatively associated with depression after adjusting for all the covariates. Further, each unit increase in CST score was associated with 0.93 times lower odds of depression (95% CI 0.90–0.96, p < 0.001, Fig. 1; Table 2).

Discussion

Our study revealed that poorer performance in all the three studied frailty-related parameters, namely handgrip strength (HGS), timed up-and-go (TUG) test, and chair stand test (CST), was significantly associated with higher odds of depression in a community-based population of older adults from rural India. Our findings highlight the clinical importance of routine evaluation of physical frailty in older adults as well as the necessity of screening for depression, particularly among those with poor physical performance parameters.

Our results conform with similar studies from other parts of the world investigating the association of the above objective frailty-related parameters with depression. A large cross-sectional study with over fifty-one thousand participants from aging cohorts in the United States (US), England, Europe, Brazil, Korea, and China found that lower handgrip strength was related to an increased likelihood of having depression³⁹. Similarly, cross-sectional findings from the World Health Organization’s Study on Global Ageing and Adult Health (SAGE), conducted among older adults (≥ 50 years) from six low- and middle-income countries, including India, indicated that reduced HGS was associated with a one-and-a-half times increased odds of prevalent depression⁴⁰. Another cross-sectional study among older Iranians, both rural- and urban-dwelling, showed that weaker HGS was associated with depressive symptoms⁴¹. Similar findings were reported among community-dwelling adults ≥ 50 years from the English Longitudinal Study of Aging⁴². Recent findings from the Longitudinal Aging Study in India (LASI) among older adults (60 years and above) from rural and urban areas across several states in India also revealed a negative association between HGS and depression⁴³. However, there have been negative results also observed, as in a study among older Turkish adults, where no significant association was found between hand grip strength and depression assessed using GDS.

In line with our results, prior studies from diverse populations have shown a positive association between higher TUG time (indicating poorer performance) and depressive symptoms. A community-based study among older individuals in the US showed that higher TUG time was correlated with higher GDS scores⁴⁴. Galán-Arroyo and colleagues reported a weak correlation between TUG time and depressive symptoms on GDS in a sample of older women from Spain⁴⁵, and a similar trend was observed in a study among older Korean individuals⁴⁶. Another study on older Koreans aged 65 years and above observed that poorer physical performance in tests, including grip strength and chair stand test, was associated with greater depressive symptoms on the Geriatric Depression Scale⁴⁷. Similarly, a cross-sectional study among older Chinese adults revealed that CST performance was significantly associated with depressed mood⁴⁸. Another study among Singaporean women aged between 45 and 69 years revealed that both upper body strength (as measured by HGS) and lower body strength (as measured by CST) were significantly associated with greater depressive / anxiety symptoms⁴⁹.

Though we cannot make any causal relationships between the poorer performance in frailty-related measures and depression due to the cross-sectional nature of our study, we speculate that poorer physical functioning among older adults makes them less physically, socially, or cognitively active. Reduced physical functioning could impede their engagement in enjoyable activities and social interactions and, thereby, put these individuals at higher risk for depression. It is also possible that frail older adults could face physiological dysfunction, such as changes in the digestive system or immune system, leading to nutritional deficiencies or systemic inflammation, which, in turn, could contribute to depression⁵⁰.

On the other hand, past research has indicated that depression could hinder physical health and autonomy, reduce both life satisfaction and quality of life, and thereby contribute to frailty⁵¹. Older persons who are frailer or have poorer functional mobility could also have a fear of falls, which could increase depressive symptoms⁵². It is also quite likely that both depression and frailty in older adults are related or overlapping syndromes. This overlap could be in terms of a shared construct of symptoms, shared vulnerability, or shared biological and psychosocial risk factors^53–55. Longitudinal studies could provide insights into the temporal relationship between frailty parameters and depression and potential causality. Investigating mediating and moderating factors influencing this association could also inform targeted interventions.

Nevertheless, older adults with poorer physical performance and depression form a high-risk group, and early identification and management of both conditions are essential for improving quality of life and reducing adverse outcomes⁵⁶. In general practice or community health services, screening for physical strength or performance in older adults using quick and simple tests such as the chair stand test may be much easier than detecting depression by mental health professionals. This is particularly relevant in rural settings, where widespread community mental health services are lacking.

Even from the perspective of treating depression, assessment of frailty is crucial as it can aid in the clinician’s decision-making process. For example, antidepressant drugs need to be prescribed judiciously in frail and depressed individuals as they may be at higher risk of side effects such as falls or cognitive impairment; polypharmacy should be avoided due to the increased risk of adverse drug reactions in this high-risk population⁵⁷. Non-pharmacological interventions and social interventions could benefit in the treatment of both frailty and depression.

Our study is one of the first of its kind among aging rural Indians, a population that is grossly underrepresented in mental health and aging research. A recent meta-analysis of 23 studies conducted in rural populations that revealed a significant association between depression and frailty had only one study from a rural Indian population (which utilized a self-reported frailty index and not objective frailty parameters)⁵⁸. Thus, our study adds significantly to the existing literature by including a marginalized community from India. Our study’s emphasis on the potential role of physical functioning parameters in depression is also significant from a translational perspective in the rural Indian setting, where mental health diagnostic and treatment services are limited. In this scenario, adopting interventions to improve physical functioning, such as nutritional supplementation or exercise programs, could be a cost-effective way to prevent depression⁵⁹. The additional strengths of our study include a large sample from a relatively homogenous cohort, employing widely used objective frailty-related parameters and a well-validated depression scale. However, our study had limitations, the first being its cross-sectional design, which precludes the establishment of causal relationships. Secondly, there could be unmeasured or uncontrolled variables that confound the relationship between the frailty-related parameters and depression that our study did not account for. The third limitation has to do with the assessment tools. We have examined only specific objective measures of frailty and did not have data on the other measures, particularly to classify individuals as frail, prefrail or non-frail. Further, depression was screened using a self-reported questionnaire (GDS), which can be prone to recall bias. In conclusion, our findings underscore the importance of assessing physical strength in understanding, identifying, and potentially mitigating the risk factors associated with depression, providing impetus for more integrated and holistic approaches to mental and physical healthcare in rural areas.

Author contributions

J.S.S. and P.S. conceptualized the study. J.S.S and P.R. supervised the study and the data analysis. P.S. compiled and analyzed the data. A.H. and S.A. conducted review of literature and helped with drafting the manuscript. J.S.S. wrote the main manuscript text. All authors reviewed the manuscript.

Funding

The SANSCOG study is funded by Pratiksha Trust through the Centre for Brain Research.

Data availability

The datasets used in the current study are available from the corresponding author at reasonable request under the Centre for Brain Research’s data-sharing policy and the statutory requirements of the Government of India.

Declarations

Competing interests

The authors declare no competing interests.