Association between Cardiovascular Disease and Handgrip Strength Risk among Community-Dwelling Older Adults in India

Abstract

The literature does not adequately examine the relationship between cardiovascular disease (CVD) and risk in handgrip strength (HGS) among community-dwelling older adults in India. The study aimed to investigate this relationship, considering sociodemographic, lifestyle, and clinical variables. A cross-sectional study involving 31,001 individuals aged ≥60 assessed HGS in kilograms using a handheld Smedley Hand Dynamometer and self-reported CVD status. Participants were classified into two groups: with (n = 2291) and without CVD (n = 28,710). Multivariate logistic regression analyses revealed a significant odds ratio (OR) of HGS among older adults with CVD, adjusted for age, gender, education, marital status, place of residence (sociodemographic), alcohol consumption, smoking, activity, body mass index (lifestyle), hypertension, diabetes, and chronic bone/joint diseases (clinical) (right-handed: OR = 1.23, 95% confidence interval [CI] = 1.09–1.38; left-handed: OR = 1.16, 95% CI = 1.04–1.30). CVD is associated with an increased risk of reduced HGS in older Indians, underscoring that improving HGS may help reduce death rates in this population.

Keywords

cardiovascular disease handgrip strength older adults India

What this paper adds

• CVD is a significant cause of death in India.

• There is a lack of research on the association between CVD and HGS risk in older adults, particularly among community-dwelling older Indians.

• After analyzing data from 31,001 people ≥60 years old, we found that community-dwelling older Indians are more likely to have reduced HGS if they have CVD, especially men and those with chronic bone or joint illness, diabetes, low physical activity levels, and rural residence.

Applications of study findings

• The study findings emphasize the importance of enhancing HGS to decrease mortality rates among community-dwelling older Indians with CVD and other comorbidities.

• The study findings also emphasize the value of encouraging physical activity, particularly in older Indian people with CVD.

• Policies should consider using HGS as a vital health indicator to reduce CVD death rates in this population.

Introduction

Cardiovascular diseases (CVD) are a major cause of mortality, affecting over 30% of deaths worldwide (Roth et al., 2020). In India, its impact is particularly pronounced among older adults, who endure a rising burden of this disease (Kundu & Kundu, 2022). The CVD crisis in India is exacerbated by aging, obesity, poor diabetes management, smoking, and higher vascular susceptibility (India State-Level Disease Burden Initiative, 2018; Kalra et al., 2023; Koya et al., 2023; Kundu & Kundu, 2022). Although handgrip strength (HGS) has an inverse relationship with CVD, aging was found to be substantially linked to a higher risk of decreasing HGS, particularly among older men in India (Zhuo et al., 2022).

Evidence suggests that the prevalence of CVD increases as HGS decreases; a 5-kilogram (kg) decrease in HGS is associated with a 1.21-fold increase in CVD incidence (Wu et al., 2017). However, most of the data come from observational studies, which are limited in their ability to conclusively prove causality because of the possibility of residual confounding and reverse causation. A previous study (Xu & Hao, 2017) showed a causal connection between higher HGS and lower coronary artery disease (CAD) risk. However, the study’s findings were still limited because it solely examined the relationship between HGS and CAD and selected two single-nucleotide polymorphisms as instrumental factors. A recent study (Zhuo et al., 2022) revealed that HGS was not substantially linked with hypertension, stroke, or heart failure. However, it was associated with myocardial infarction (MI) and CAD. Additionally, studies indicate that low HGS in hypertensive individuals is linked to the highest risk of CVD, CVD mortality, and all-cause mortality (Celis-Morales et al., 2018; Leong et al., 2015; Liu et al., 2021).

Since HGS is a well-known indicator (Lee, 2021), the most direct and valid objective measure of muscle strength (Muollo et al., 2022; Rantanen et al., 2002), and health outcomes (Soysal et al., 2021), it serves as a crucial tool for assessing overall health in older adults. HGS is particularly useful in developing countries like India due to its predictive accuracy, non-invasive nature, cost-effectiveness, and portability. Moreover, HGS recently has garnered increasing attention as a useful predictor of CVD risk (Li et al., 2023; Liu et al., 2021). A recent comprehensive review also summarized that HGS could be a significant indicator of health (Vaishya et al., 2024). A recent study (Shim & Yoo, 2020) also specifically found that for every kg rise in HGS, the 10-year risk of CVD was 1.68 times lower.

However, no research has examined the relationship between the presence of CVD and HGS in older adults, specifically among community-dwelling older Indians (Ramirez-Velez et al., 2021; Soysal et al., 2021). Given this gap in the literature, the present study aimed to examine the relationship between the presence of CVD and HGS in community-dwelling older adults in India, encompassing sociodemographic, lifestyle, and clinical factors. The study hypothesized that the presence of CVD would be associated with an increased risk of reduced HGS in older Indians with CVD than those without CVD. Understanding the relationship between CVD and reduced HGS in older Indians may highlight the importance of improving HGS to reduce mortality rates in this demographic.

Methods

Data Source

Secondary data analyses were conducted using data from the 2017–2018 Longitudinal Ageing Study in India (LASI, Wave 1) (Perianayagam et al., 2022). While LASI is designed to be longitudinal, data collection for the second wave is still ongoing. Currently, only wave 1 baseline data are available. LASI is a comprehensive survey representing the entire nation, encompassing more than 72,000 individuals aged 45 and older from all states and union territories (UTs) of India. The primary aim of the LASI survey is to investigate the health and socioeconomic conditions of older Indians. The survey involved three-stage sampling in rural areas and a four-stage approach in urban areas in all states and UTs of India. Primary sampling units (PSUs) were selected in the first stage, villages and wards were chosen within the PSUs in the second stage, and households were chosen from selected villages in the third stage. However, a randomly selected census enumeration block was used to choose households from urban areas in the final stage. The survey utilized advanced technology, computer-assisted interviews, and personal biomarkers to reduce errors and improve data entry, with high response rates of 87% varying by 96% in Nagaland and 74% in Chandigarh (Basu, 2022).

Participants

In our study, we focus on older adults aged 60 years and older. Older adults were defined as aligning with India’s demographic context and policy standards (Sujaya, 2000), which differ from the Western benchmark of 65 years. Given the lower life expectancy, earlier onset of health issues, and higher chronic disease burden, as well as government policies that recognize 60 as the threshold for senior citizenship (Meenai, 2021), this definition is more appropriate for the Indian population (Mandi et al., 2023). After excluding persons under the age of 60 (n = 40,899), both dominant handedness (n = 299), and missing data (n = 81), the final sample size for this study was 31,001 persons. Participants were classified into two groups: 2291 individuals with CVD and 28,710 without CVD.

Handgrip Strength

HGS measurements were conducted utilizing Smedley’s hand dynamometer. The procedure involved adjusting the device for both the respondent’s dominant right and non-dominant left hands. Participants were positioned with their right forearm at the elbow of the upper arm, maintaining the upper arm close to the body. They were then instructed to exert firm pressure on the dynamometer three times with each hand for a brief interval. Subsequently, the highest recorded value in kgs of the six trials was selected.

Cardiovascular Diseases

The independent variable in this study indicated the presence of CVD, which includes stroke, chronic heart disease, and hypertension. Respondents self-reported CVD in response to the question, “Has any health professional ever diagnosed you with chronic conditions or diseases such as stroke, hypertension (high blood pressure), or chronic heart disease?” Chronic heart diseases also include CAD (a heart attack or MI), congestive heart failure, or other chronic heart problems. Those who reported one or more such conditions were classified as having CVD and those without any conditions comprised the reference group. Similar questionnaires were employed in recent research to evaluate the above conditions (Ahmed et al., 2023).

Covariates

Age was measured as a continuous variable. Gender was dichotomized into men and women. The level of education was classified into less than primary school (standard 1–4), primary school (standard 4–7), middle school (standard 8–9), secondary/senior secondary/diploma, and graduate/professional degree/post-graduates. Marital status was classified as married, widowed/separated/divorced, and never married. The self-reported questions were used to assess place of residence, engagement in activity, alcohol consumption, tobacco consumption, and comorbidities, such as hypertension, diabetes, and joint/bone disease status. The place of residence was categorized into rural and urban areas. An engagement in activity was classified into daily/weekly and monthly/never. BMI was measured in kg/m².

Statistical Analysis

The Shapiro-Wilk test was used to determine whether the data distribution was normal. Descriptive statistics, such as the mean and standard deviation (SD) were used for continuous data, whereas the count (%) was used for categorical variables. The significant difference between the groups was determined using an independent student t-test for mean values and a chi-square test for frequencies.

The multivariate logistic regression was used to investigate the relationship between CVD (independent categorical variable) and the likelihood of HGS risk (dependent continuous variable). The analysis was modified into two models to account for sociodemographic (such as age, gender, education, marital status, and place of residence), lifestyle (such as alcohol consumption, smoking, activity, and BMI), and clinical factors such as hypertension, diabetes, and chronic bone or joint diseases. Model 1 adjusted with sociodemographic factors. Model 2 adjusted for all sociodemographic, lifestyle, and clinical factors. The data were presented using the odds ratio (OR) and 95% confidence interval (CI). To assess multicollinearity, the variance inflation factor was employed. SAS, version 9.4 was used for all analyses (SAS Institute, Inc, Cary, NC). Each analysis was considered significant if the p-value was less than .05.

Results

The flow of the study participants through LASI has been shown in Figure 1. Of 72,250 participants, 31,001 (42.9%) individual data were used in the analysis after 41,249 (57.1%) were excluded. The data were excluded from the study due to age of less than 60, both handedness and lack of data.

Figure 1.

Flowchart of the study participants through LASI. ^λOlder adults with CVD. ^ηOlder adults without CVD.

The basic characteristics of the study participants have been presented in Table 1. While 2291 (7.4%) participants were diagnosed with CVD out of 31,001, 28,710 (92.6%) were not diagnosed with CVD. The average age of diagnosis with CVD was 60.9 years. The majority of older adults who were diagnosed with CVD have used medication (69.8%). The average age of the participants was 69.3 years, with significant differences between groups (p < .0001). Although most were older women (52%) in the sample, most men (56.8%) were in group 1. The majority in the total sample had less primary school education (28.1%), were married (63.4%), and residing in rural areas (66.1%), especially older adults in group 1 had primary school education (25.6%) and the majority were married (67%). The majority of older adults in the total sample were underweight (17.7 ± 3.6), monthly, or never engaged in activity (73.7%), especially those in group 1 (83.9%). Non-smokers (63.4%), Most participants had right-hand dominance (95.7%). The majority of older adults in group 1 were diagnosed with hypertension (67.2%). Although only 15.4% and 18.7% of the older adults in the total sample were diagnosed with diabetes and chronic bone or joint diseases, 31.3% and 23.9% of older adults in group 1 were diagnosed with those diseases, respectively. Older adults with and without CVD had almost similar average HGS of 19.4 kgs and did not significantly differ between groups (p = .74).

Table 1.

Characteristics of the Study Participants.

	Total n = 31,001	Groups		p-value
		Group 1^λ n = 2291 (7.4%)	Group 2^η n = 28,710 (92.6%)
Age in years, mean ± SD	69.3 ± 7.4	69.9 ± 7.4	68.8 ± 7.5	<.0001^¶
The average age of diagnosis	–	60.9 ± 6.3	–	–
Medication, %	–	69.8	–	–
Gender, n (%)^*				<.0001^#
Men	14,868 (48)	1301 (56.8)	13,567 (47.3)
Women	16,133 (52)	990 (43.2)	15,143 (52.7)
Highest level of education, n (%)^*				<.0001^#
Less than primary school (standard 1–4)	3741 (28.1)	292 (23.2)	3449 (28.6)
Primary school (standard 4–7)	3722 (28)	321 (25.6)	3401 (28.2)
Middle school (standard 8–9)	2192 (16.5)	211 (16.8)	1981 (16.4)
Secondary/senior secondary/diploma	3388 (25.5)	406 (32.3)	2982 (24.8)
Graduates^ψ/professional degree^δ/post-graduates^τ	253 (1.9)	26 (2.1)	227 (2)
Marital status, n (%)^*				.0007^#
Married	19,646 (63.4)	1536 (67)	18,110 (63.1)
Widow/Divorced/Separated	11,062 (35.7)	737 (32.2)	10,325 (36)
Never married	293 (0.9)	18 (0.8)	275 (0.9)
Place of residence, n (%)^*				<.0001^#
Rural	20,502 (66.1)	1186 (51.8)	19,316 (67.3)
Urban	10,499 (33.9)	1105 (48.2)	9394 (32.7)
Alcoholic beverages consumption, n (%)^*				.186^#
Consumed	5322 (17.3)	416 (18.3)	4906 (17.2)
No or never consumed	25,496 (82.7)	1860 (81.7)	23,636 (82.8)
Smoked or used smokeless tobacco, n (%)^*				.084^#
Yes	12,099 (39.3)	855 (37.6)	11,244 (39.4)
No	18,713 (60.7)	1421 (62.4)	17,292 (60.6)
Engage in activity, n (%)^*				<.0001^#
Daily/weekly	8118 (26.3)	367 (16.1)	7751 (27.2)
Monthly/never	22,688 (73.7)	1906 (83.9)	20,782 (72.8)
Body mass index in kg/m², mean ± SD	17.7 ± 3.6	18.6 ± 3.7	16.9 ± 3.7	<.0001^¶
Diagnosed with hypertension, n (%)^*				<.0001^#
Yes	10,857 (35)	1539 (67.2)	9318 (32.5)
No	20,140 (65)	752 (32.8)	19,388 (67.5)
Diagnosed with diabetes, n (%)^*				<.0001^#
Yes	4766 (15.4)	716 (31.3)	4050 (14.1)
No	26,232 (84.6)	1575 (68.7)	24,657 (85.9)
Diagnosed with chronic bone/joint diseases, n (%)^*				<.0001^#
Yes	5495 (17.7)	535 (23.3)	4960 (17.3)
No	25,506 (82.3)	1756 (76.7)	23,750 (82.7)
The average handgrip strength in kg, mean ± SD	19.4 ± 7.4	19.5 ± 7.5	19.4 ± 7.4	.74
Dominant handgrip strength, n (%)^*				<.0001^#
Right-handedness	26,562 (95.7)	1849 (93.8)	24,713 (95.8)
Left-handedness	1198 (4.3)	123 (6.2)	1075 (4.2)

SD, standard deviation; Kg, kilogram.

^λOlder adults with CVD.

^ηOlder adults without CVD.

^*Missing data of gender (n = 81), education (n = 17,786), marital status (n = 81), place of residence (n = 81), smoking (n = 270), alcohol consumption (n = 264), activity (n = 276), hypertension (n = 85), diabetes (n = 84), chronic bone/joint diseases (n = 81), and dominat handgrip strength (n = 3322).

^ψGraduates in B.A., B.Sc., or B.Com.

^τPost-graduates in M.A., M.Sc., M.Com., M.Phil, or Ph.D.

^δProfessional degree in B.Ed., BE., B.Tech., MBBS., BHMS., B.Pharm, BCS., BCA., BBA., LLB., BVSc., BArch., M.Ed., or ME.

^¶Significant difference between groups was determined using the independent student t-test.

^#Significant difference between groups was determined using the Chi-square t-test.

The association between the presence of CVD and an increasing risk of reduced HGS among Indian community-dwelling older adults has been presented in Table 2. In model 1, right- and left-handed older adults with CVD had a higher risk of reduced HGS compared to those without CVD (OR = 1.22, 95% CI = 1.09–1.37; OR = 1.23, 95% CI = 1.09–1.38, respectively) after adjusting for sociodemographic variables. In other words, there was a 22% increase in the odds of weak HGS with right-handedness and a 23% increase with left-handedness among older adults with CVD compared to those without CVD. In model 2, the odds of reduced HGS were 1.23 (95% CI = 1.09–1.38) and 1.16 (95% CI = 1.04–1.30) times higher for right- and left-handed older adults with CVD than for those without CVD, respectively, after adjusting for sociodemographic, lifestyle, and clinical factors. In other words, model 3 shows that there was a 23% increase in the odds of reduced HGS with right-handedness and a 16% increase in left-handedness among older adults with CVD compared to those without CVD.

Table 2.

Association Between the Presence of Cardiovascular Diseases and Handgrip Strength Risk.

	Right-handedness		Left-handedness
	OR (95% CI)^a	OR (95% CI)^b	OR (95% CI)^a	OR (95% CI)^b
Group 1 ^λ vs. 2 ^η	1.22 (1.09–1.37)	1.23 (1.09–1.38)	1.15 (1.02–1.28)	1.16 (1.04–1.30)

OR, odds ratio; CI, confidence interval; vs., versus

^λOlder adults with CVD.

^ηOlder adults without CVD.

^aModel 1 adjusted for sociodemographic factors, such as age, gender, education, marital status, and place of residence.

^bModel 2 adjusted for all sociodemographic, lifestyle (such as alcohol consumption, smoking, activity, and BMI), and clinical factors, such as hypertension, diabetes, and chronic bone or joint diseases.

Discussion

This study examined the association between the presence of CVD and HGS among community-dwelling older Indians. Findings showed that the presence of CVD was significantly associated with an increased risk of reduced HGS in this population, even after controlling for sociodemographic, lifestyle, and clinical factors. These findings consistently demonstrate a higher risk of reduced HGS in this population among those with CVD compared to those without it.

The association between CVD and HGS risk has not been explored in prior research, particularly among older community-dwelling Indians. Nonetheless, several studies (Ramirez-Velez et al., 2021; Shim & Yoo, 2020; Soysal et al., 2021; Vaishya et al., 2024) have examined the relationship between HGS and the onset of CVD. The current study is supported by earlier studies (Heiland et al., 2019; Jin et al., 2017), which found that leading an unhealthy lifestyle exacerbates the negative effects of CVD on physical health. It is reasonable to assume that CVD itself may directly contribute to muscle weakness, even when accounting for sociodemographic factors.

Several mechanisms support the idea that cardiovascular diseases such as atherosclerosis can lead to plaque accumulation in the arteries, narrowing and hardening them, decreasing muscle blood supply, and resulting in muscular weakening (Uchida et al., 2020). Sarcopenia, or muscular atrophy, is a condition diagnosed with HGS because of decreased physical activity and can be brought on by heart failure, stroke, or severe coronary artery disease (Coats et al., 2017; Fielding et al., 2011). Peripheral neuropathy, which results in hand weakness, tingling, or numbness, and chronic inflammation, which causes muscular weakness and loss of function, are two conditions that several CVDs can cause (Koshikawa et al., 2020; Tuttle et al., 2020). Furthermore, although older people often tolerate beta-blockers well, these drugs can occasionally cause muscle weakness or weariness (Cojocariu et al., 2021), which might further impair HGS.

Our findings showed that older adults with CVD have a higher risk of reduced HGS due to factors such as age, chronic conditions, and lifestyle challenges. Older Indians living in rural areas, smoking, and having low physical activity endured a higher HGS risk. People with diabetes and chronic bone or joint disease also reported a higher risk of reduced HGS. A possible reason for this may be that growing older is associated with decreased muscle mass and sarcopenia, which can be further exacerbated by chronic conditions such as CVD (Damluji et al., 2023). Furthermore, living in rural settings may make it more difficult to acquire services that promote health and medical care (Banerjee, 2021; Basu, 2022), which could worsen the adverse effects of CVD.

Our study is the first within the Indian context to examine the associations between the presence of CVD and HGS among community-dwelling older adults. Our findings are relevant to the practices and policies affecting Indian older people living in the community. Improved muscle strength with aging is associated with favorable changes in CVD biomarkers, such as waist circumference, high-density lipoprotein cholesterol, triglycerides, and blood pressure (Kim et al., 2020). As such, HGS has been recommended as a new vital indicator of health (Celis-Morales et al., 2018; Vaishya et al., 2024). However, its usefulness differs depending on gender and age (Taylor et al., 2024). High levels of education, physical activity, and good aging can all aid in CVD management (van Oort et al., 2021). In particular, there is a basic connection between physical activity and public health, as evidenced by its benefits for musculoskeletal health, healthy aging, the prevention of chronic diseases, and all-cause mortality (Herrmann et al., 2024; Lavie et al., 2024). These advantages emphasize the value of encouraging physical activity, particularly for older Indians who have CVD. Further research, relying on longitudinal data, is needed to understand the mechanisms underlying the link between CVD and HGS in this population, considering sociocultural, lifestyle, and clinical factors.

Limitations

First, the cross-sectional nature of our study limits the ability to conclude causality or sequencing of events. Longitudinal research is needed to track changes in HGS alongside changes in CVD status, enabling a better understanding of how these factors influence each other over time. Multiple waves of data would provide opportunities to explore the temporal relationships between CVD onset and declines in HGS, variability in their progression, and potential intervention points. Second, although HGS is commonly used to evaluate muscle strength, future research should contemplate integrating alternative measures of muscle function, like the chair rise test, to offer a more thorough assessment. Third, future research replicating our study should extend it by exploring pathways that connect CVD to HGS in Indian older adults. Lastly, the main focus of this study was on the association between CVD and HGS, but the models’ inability to account for neurological and cerebrovascular disorders may have attenuated estimates. Future studies should explore the impact of these circumstances on HGS, particularly in the Indian context. Investigating these interactions could clarify whether the associations are unique to cardiovascular health or part of a broader spectrum of age-related health outcomes, contributing to a more comprehensive understanding of HGS as a biomarker of overall health and aging.

Conclusions

Our study found that CVD is significantly associated with higher odds of low HGS among community-dwelling older adults in India. This association underscores the importance of HGS as a practical marker for physical function decline in individuals with CVD. The results are important for applied gerontology and clinical practice because they suggest that interventions that build muscle strength, like physical therapy or customized exercise programs, might help lessen the bad effects of CVD on health. Regular HGS assessments may help identify those at greater risk for physical deterioration, allowing for timely and targeted interventions to improve functional outcomes and enhance the quality of life in older adults. Further research should focus on developing strategies to enhance HGS among older adults with CVD, which could improve health outcomes and reduce mortality within this population, especially in developing countries like India.

Footnotes

Acknowledgments

The authors would like to extend their sincere appreciation to the Researchers Supporting Project Number (RSPD2024R1094), King Saud University, Riyadh, Saudi Arabia for funding this project.

Author Contributions

V.V. substantially contributed to the conceptualization, data analysis, writing – original draft preparation, and comprehensive review & editing. M.P. contributed significantly to the conceptualization, interpretation of the results, writing – original draft preparation, comprehensive review & editing. All authors have given final approval for the version to be published.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The work was supported by the Researchers Supporting Project Number (RSPD2024R1094), King Saud University, Riyadh, Saudi Arabia.

Ethical Statement

ORCID iD

Vishal Vennu

References

Ahmed

Muhammad

Maurya

Akhtar

S. N.

(2023). Prevalence and factors associated with undiagnosed and uncontrolled heart disease: A study based on self-reported chronic heart disease and symptom-based angina pectoris among middle-aged and older Indian adults. PLoS One, 18(6), Article e0287455. https://doi.org/10.1371/journal.pone.0287455

Banerjee

(2021). Determinants of rural-urban differential in healthcare utilization among the elderly population in India. BMC Public Health, 21(1), 939. https://doi.org/10.1186/s12889-021-10773-1

Basu

(2022). Research on disparities in primary health care in rural versus urban areas: Select perspectives. International Journal of Environmental Research and Public Health, 19(12), 7110. https://doi.org/10.3390/ijerph19127110

Celis-Morales

C. A.

Welsh

Lyall

D. M.

Steell

Petermann

Anderson

Iliodromiti

Sillars

Graham

Mackay

D. F.

Pell

J. P.

Gill

J. M. R.

Sattar

Gray

S. R.

(2018). Associations of grip strength with cardiovascular, respiratory, and cancer outcomes and all cause mortality: Prospective cohort study of half a million UK biobank participants. BMJ, 361(8153), k1651. https://doi.org/10.1136/bmj.k1651

Coats

A. J. S.

Forman

D. E.

Haykowsky

Kitzman

D. W.

McNeil

Campbell

T. S.

Arena

(2017). Physical function and exercise training in older patients with heart failure. Nature Reviews Cardiology, 14(9), 550–559. https://doi.org/10.1038/nrcardio.2017.70

Cojocariu

S. A.

Mastaleru

Sascau

R. A.

Statescu

Mitu

Leon-Constantin

M. M.

(2021). Neuropsychiatric consequences of lipophilic beta-blockers. Medicina (Kaunas), 57(2), 155. https://doi.org/10.3390/medicina57020155

Damluji

A. A.

Alfaraidhy

AlHajri

Rohant

N. N.

Kumar

Al Malouf

Bahrainy

Ji Kwak

Batchelor

W. B.

Forman

D. E.

Rich

M. W.

Kirkpatrick

Krishnaswami

Alexander

K. P.

Gerstenblith

Cawthon

deFilippi

C. R.

Goyal

(2023). Sarcopenia and cardiovascular diseases. Circulation, 147(20), 1534–1553. https://doi.org/10.1161/CIRCULATIONAHA.123.064071

Fielding

R. A.

Vellas

Evans

W. J.

Bhasin

Morley

J. E.

Newman

A. B.

Abellan van Kan

Andrieu

Bauer

Breuille

Cederholm

Chandler

De Meynard

Donini

Harris

Kannt

Keime Guibert

Onder

Papanicolaou

Zamboni

(2011). Sarcopenia: An undiagnosed condition in older adults. Current consensus definition: Prevalence, etiology, and consequences. International working group on sarcopenia. Journal of the American Medical Directors Association, 12(4), 249–256. https://doi.org/10.1016/j.jamda.2011.01.003

Heiland

E. G.

Welmer

A. K.

Wang

Santoni

Fratiglioni

Qiu

(2019). Cardiovascular risk factors and the risk of disability in older adults: Variation by age and functional status. Journal of the American Medical Directors Association, 20(2), 208–212.e3. https://doi.org/10.1016/j.jamda.2018.05.013

10.

Herrmann

S. D.

Conger

S. A.

Willis

E. A.

Ainsworth

B. E.

(2024). Promoting public health through the 2024 compendium of physical activities: Strategies for adults, older adults, and wheelchair users. Journal of Sport and Health Science. Advance online publication. https://doi.org/10.1016/j.jshs.2024.05.013

11.

India State-Level Disease Burden Initiative CVD Collaborators . (2018). The changing patterns of cardiovascular diseases and their risk factors in the states of India: The global burden of disease study 1990-2016. Lancet Global Health, 6(12), e1339–e1351. https://doi.org/10.1016/S2214-109X(18)30407-8

12.

Jin

Tanaka

Bandinelli

Ferrucci

Talegawkar

S. A.

(2017). Cardiovascular health is associated with physical function among older community dwelling men and women. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 72(12), 1710–1716. https://doi.org/10.1093/gerona/glw329

13.

Kalra

Jose

A. P.

Prabhakaran

Kumar

Agrawal

Roy

Bhargava

Tandon

Prabhakaran

(2023). The burgeoning cardiovascular disease epidemic in Indians - perspectives on contextual factors and potential solutions. The Lancet Regional Health – Southeast Asia, 12(2023), Article 100156. https://doi.org/10.1016/j.lansea.2023.100156

14.

Kim

Gonzales

J. U.

Reddy

P. H.

(2020). An investigation of short-term longitudinal associations between handgrip strength and cardiovascular disease biomarkers among middle-aged to older adults: A project frontier study. Journal of Aging and Physical Activity, 28(1), 9–17. https://doi.org/10.1123/japa.2018-0399

15.

Koshikawa

Harada

Noyama

Kiyono

Motoike

Nomura

Nishimura

Izawa

Watanabe

Ozaki

(2020). Association between inflammation and skeletal muscle proteolysis, skeletal mass and strength in elderly heart failure patients and their prognostic implications. BMC Cardiovascular Disorders, 20(1), 228. https://doi.org/10.1186/s12872-020-01514-0

16.

Koya

S. F.

Pilakkadavath

Chandran

Wilson

Kuriakose

Akbar

S. K.

Ali

(2023). Hypertension control rate in India: Systematic review and meta-analysis of population-level non-interventional studies, 2001-2022. The Lancet Regional Health – Southeast Asia, 9(2023), Article 100113. https://doi.org/10.1016/j.lansea.2022.100113

17.

Kundu

(2022). Cardiovascular disease (CVD) and its associated risk factors among older adults in India: Evidence from LASI wave 1. Clinical Epidemiology and Global Health, 13(2022), Article 100937. https://doi.org/10.1016/j.cegh.2021.100937

18.

Lavie

C. J.

Carbone

Slipczuk

(2024). Physical activity with or without dietary intervention for the prevention of cardiovascular diseases. Journal of Sport and Health Science. Advance online publication. https://doi.org/10.1016/j.jshs.2024.05.012

19.

Lee

S. Y.

(2021). Handgrip strength: An irreplaceable indicator of muscle function. Annals of Rehabilitation Medicine, 45(3), 167–169. https://doi.org/10.5535/arm.21106

20.

Leong

D. P.

Teo

K. K.

Rangarajan

Lopez-Jaramillo

Avezum

Jr. Orlandini

Seron

Ahmed

S. H.

Rosengren

Kelishadi

Rahman

Swaminathan

Iqbal

Gupta

Lear

S. A.

Oguz

Yusoff

Zatonska

Chifamba

Prospective Urban Rural Epidemiology (PURE) Study investigators . (2015). Prognostic value of grip strength: Findings from the prospective urban rural epidemiology (PURE) study. Lancet, 386(9990), 266–273. https://doi.org/10.1016/S0140-6736(14)62000-6

21.

Shao

Qiao

Ding

(2023). Handgrip strength is associated with risks of new-onset stroke and heart disease: Results from 3 prospective cohorts. BMC Geriatrics, 23(1), 268. https://doi.org/10.1186/s12877-023-03953-8

22.

Liu

Leong

D. P.

AhTse

Rangarajan

Wang

Yusuf

Liu

(2021). The association of grip strength with cardiovascular diseases and all-cause mortality in people with hypertension: Findings from the prospective urban rural epidemiology China study. Journal of Sport and Health Science, 10(6), 629–636. https://doi.org/10.1016/j.jshs.2020.10.005

23.

Mandi

Bansod

D. W.

Goyal

A. K.

(2023). Exploring the association of lifestyle behaviors and healthy ageing among the older adults in India: Evidence from LASI survey. BMC Geriatrics, 23(1), 675. https://doi.org/10.1186/s12877-023-04367-2

24.

Meenai

(2021). Senior citizens: Issues and perspectives. In Ageing Issues in India: Practices, Perspectives and Policies (pp. 211–230). Rawat Publications.

25.

Muollo

Tatangelo

Ghiotto

Cavedon

Milanese

Zamboni

Schena

Rossi

A. P.

(2022). Is handgrip strength a marker of muscle and physical function of the lower limbs? Sex differences in older adults with obesity. Nutrition, Metabolism, and Cardiovascular Diseases, 32(9), 2168–2176. https://doi.org/10.1016/j.numecd.2022.06.018

26.

Perianayagam

Bloom

Lee

Parasuraman

Sekher

Mohanty

S. K.

Chattopadhyay

Govil

Pedgaonkar

Gupta

Agarwal

Posture

Weerman

Pramanik

(2022). Cohort profile: The longitudinal ageing study in India (LASI). International Journal of Epidemiology, 51(4), e167–e176. https://doi.org/10.1093/ije/dyab266

27.

Ramirez-Velez

Garcia-Hermoso

Correa-Rodriguez

Lobelo

Gonzalez-Ruiz

Izquierdo

(2021). Abdominal aortic calcification is associated with decline in handgrip strength in the U.S. adult population ≥40 years of age. Nutrition, Metabolism, and Cardiovascular Diseases, 31(4), 1035–1043. https://doi.org/10.1016/j.numecd.2020.11.003

28.

Rantanen

Avlund

Suominen

Schroll

Frandin

Pertti

(2002). Muscle strength as a predictor of onset of adl dependence in people aged 75 years. Aging Clinical and Experimental Research, 14(3 Suppl), 10–15.

29.

Roth

G. A.

Mensah

G. A.

Johnson

C. O.

Addolorato

Ammirati

Baddour

L. M.

Barengo

N. C.

Beaton

A. Z.

Benjamin

E. J.

Benziger

C. P.

Bonny

Brauer

Brodmann

Cahill

T. J.

Carapetis

Catapano

A. L.

Chugh

S. S.

Cooper

L. T.

Coresh

GBD-NHLBI-JACC Global Burden of Cardiovascular Diseases Writing Group . (2020). Global burden of cardiovascular diseases and risk factors, 1990-2019: Update from the gbd 2019 study. Journal of the American College of Cardiology, 76(25), 2982–3021. https://doi.org/10.1016/j.jacc.2020.11.010

30.

Shim

Yoo

H. J.

(2020). Effects of handgrip strength on 10-year cardiovascular risk among the Korean middle-aged population: The Korea national health and nutrition examination survey 2014. Healthcare (Basel), 8(4), 458. https://doi.org/10.3390/healthcare8040458

31.

Soysal

Hurst

Demurtas

Firth

Howden

Yang

Tully

M. A.

Koyanagi

Ilie

P. C.

Lopez-Sanchez

G. F.

Schwingshackl

Veronese

Smith

(2021). Handgrip strength and health outcomes: Umbrella review of systematic reviews with meta-analyses of observational studies. Journal of Sport and Health Science, 10(3), 290–295. https://doi.org/10.1016/j.jshs.2020.06.009

32.

Sujaya

C. P.

(2000). National policy for older persons. Retrieved from: https://www.india-seminar.com/2000/488/488sujaya.htm

33.

Taylor

K. A.

Carroll

M. K.

Short

S. A.

Goode

A. P.

(2024). Identifying characteristics and clinical conditions associated with hand grip strength in adults: The project baseline health study. Scientific Reports, 14(1), 8937. https://doi.org/10.1038/s41598-024-55978-7

34.

Tuttle

C. S. L.

Thang

L. A. N.

Maier

A. B.

(2020). Markers of inflammation and their association with muscle strength and mass: A systematic review and meta-analysis. Ageing Research Reviews, 64(2020), Article 101185. https://doi.org/10.1016/j.arr.2020.101185

35.

Uchida

Kamiya

Hamazaki

Matsuzawa

Nozaki

Ichikawa

Suzuki

Nakamura

Yamashita

Kariya

Maekawa

Yamaoka-Tojo

Matsunaga

Ako

(2020). Association between sarcopenia and atherosclerosis in elderly patients with ischemic heart disease. Heart and Vessels, 35(6), 769–775. https://doi.org/10.1007/s00380-020-01554-8

36.

Vaishya

Misra

Vaish

Ursino

D'Ambrosi

(2024). Hand grip strength as a proposed new vital sign of health: A narrative review of evidences. Journal of Health, Population and Nutrition, 43(1), 7. https://doi.org/10.1186/s41043-024-00500-y

37.

van Oort

Beulens

J. W. J.

van Ballegooijen

A. J.

Burgess

Larsson

S. C.

(2021). Cardiovascular risk factors and lifestyle behaviours in relation to longevity: A mendelian randomization study. Journal of Internal Medicine, 289(2), 232–243. https://doi.org/10.1111/joim.13196

38.

Wang

Liu

Zhang

(2017). Association of grip strength with risk of all-cause mortality, cardiovascular diseases, and cancer in community-dwelling populations: A meta-analysis of prospective cohort studies. Journal of the American Medical Directors Association, 18(6), 551.e17–551.e35. https://doi.org/10.1016/j.jamda.2017.03.011

39.

Hao

Y. T.

(2017). Effect of handgrip on coronary artery disease and myocardial infarction: A mendelian randomization study. Scientific Reports, 7(1), 954. https://doi.org/10.1038/s41598-017-01073-z

40.

Zhuo

Zhao

Wang

Lin

Cai

Pan

Chen

Jin

Tao

(2022). Assessment of causal associations between handgrip strength and cardiovascular diseases: A two sample Mendelian randomization study. Front Cardiovasc Med, 9(2022), Article 930077. https://doi.org/10.3389/fcvm.2022.930077