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Gripping insights: prevalence of hypertension and its association with relative muscle strength—a cross-sectional study in an adult Indian population

Journal of Health, Population and Nutrition volume 43, Article number: 215 (2024) Cite this article

Abstract

Background

Hypertension and muscle strength are known to be associated; however, identifying simple clinical indicators of this relationship is challenging. Relative muscle strength (RMS), defined as strength per unit muscle mass, has been proposed as a potential indicator, but its association with hypertension is unclear. This study aimed to estimate the prevalence of hypertension and determine its association with RMS in an adult Indian population attending a tertiary care center in Gujarat.

Methods

This hospital-based cross-sectional study included 430 adults aged 18 years and older who were admitted to outpatient medicine clinics between January and October 2023. Grip strength and appendicular lean muscle mass (ALM), estimated using a validated formula, were measured. The RMS was calculated as grip strength/ALM. Hypertension was defined using standard criteria. Logistic regression was used to analyze the association between RMS (analyzed continuously and categorically in tertiles) and hypertension, adjusting for confounders. A p value of < 0.05 was considered significant.

Results

The prevalence of prehypertension and hypertension was 187 (43%) and 96 (23%), respectively. Compared to participants in the low RMS tertile (0.00–2.45 kg/kg ALM), those in the high tertile (3.79–6.12 kg/kg ALM) had 26% lower odds of hypertension (OR 0.74, 95% CI 0.59–0.89) and 33% lower odds of prehypertension (OR 0.67, 95% CI 0.49–0.91) after adjusting for confounders. The RMS also showed strong negative correlations with systolic and diastolic blood pressure (r = − 0.559 and − 0.418, respectively; p < 0.001).

Conclusion

Increased RMS was significantly protective against prehypertension and hypertension. These findings highlight the potential importance of muscle quality, beyond muscle mass, in blood pressure regulation.

Introduction

Hypertension, a leading contributor to cardiovascular morbidity and mortality worldwide, has reached epidemic proportions, with an estimated 1.28 billion adults affected globally [1, 2]. This escalating burden disproportionately impacts low- and middle-income countries [3]. In India, more than 30% of adults have hypertension, and its incidence nearly doubled between 1990 and 2016, highlighting the urgency for robust prevention measures [4,5,6].

Epidemiological research has identified muscle strength as a potential protective factor against hypertension [7,8,9]. This relationship is supported by several physiological mechanisms. The proposed pathways associated with greater muscle strength include decreased arterial stiffness, enhanced vasodilation, and improved metabolic health. These mechanisms collectively contribute to improved blood pressure regulation [10,11,12].

A systematic review and meta-analysis by García-Hermoso et al. (2018) revealed that greater muscle strength was consistently associated with a lower risk of hypertension across diverse populations. This review included both cross-sectional and longitudinal studies, providing robust evidence for the protective role of muscle strength against hypertension development [13].

While absolute muscle strength shows an inverse association with hypertension, recent studies have indicated that muscle quality, defined as muscle strength normalized to muscle mass, may be a more precise predictor of hypertension risk [14,15,16]. Muscle quality captures the neurological capacity and functional ability conferred by a given muscle mass, providing a more comprehensive assessment of muscular health [17]. Higher relative muscle strength or muscle quality is more strongly inversely correlated with blood pressure and more accurately predicts incident hypertension than are absolute strength measures across diverse populations [18,19,20].

Grip strength normalized to appendicular lean mass, obtained from DXA assessments, provides a simple clinical marker of overall muscle quality [21, 22].

India is undergoing a nutritional transition with rising rates of obesity, metabolic syndrome, diabetes, and sarcopenic obesity, the latter potentially linking declines in muscle quality to increased hypertension risk [23,24,25,26,27]. However, data on the relationship between muscle quality and hypertension in Indian populations are limited.

Therefore, the primary objective of this study was to estimate the prevalence of hypertension and prehypertension in the study population. The secondary objectives included examining the association between relative muscle strength, assessed by grip strength normalized to appendicular lean mass, and the risk of hypertension and prehypertension in an adult Indian population.

Confirming this protective relationship would highlight the importance of maintaining muscle strength and attenuating sarcopenic obesity to reduce India's escalating hypertension burden. These findings will help guide clinical and public health strategies for hypertension control by helping individuals build on emerging evidence linking muscle strength and cardiovascular health.

Methodology

Study design

This was a hospital-based cross-sectional study.

Setting

This study was conducted at the Medicine OPD of the tertiary Care Center in Gujarat from January 2023 to October 2023.

Study population

The study population consisted of adult patients attending the Medicine outpatient department at the hospital during the study period.

Eligibility Criteria: Inclusion Criteria:

  • Patients aged 18 years or older

  • Willing to provide informed consent

Exclusion criteria:

  • Conditions impairing the measurement of grip strength (e.g., recent surgery involving the upper limbs)

  • Any illness causing muscle wasting, such as advanced cancer"

Sample size calculation and sampling technique

The sample size was calculated using the following formula for estimating a population proportion:

$${\text{n }} = {\text{ Z}}_{\gamma /2}^{2} * {\text{p}}\left( {1 - {\text{p}}} \right)/{\text{d}}^{2}$$

The study had a power of 80%, an acceptable error of 5%, and an anticipated prevalence of hypertension of 30.7% based on a previous nationwide study [28]. Using these parameters: n = (1.96)2 * 0.307(1–0.307)/(0.05)2 = 326. To account for potential nonresponse and to ensure adequate power for subgroup analyses, we increased this by 10%, resulting in a sample size of 358.6. To ensure robustness and account for potential stratified analyses, we further increased this number to 430 participants. The study employed stratified random sampling, categorizing individuals based on sex (male/female) and age (18–30, 31–50, 51–65, > 65 years). Participants were randomly selected from each stratum in proportion to the distribution of the medical OPD. (Fig. 1).

Fig. 1
figure 1

Participant Flow and Sample Selection

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Measurement of variables and data collection

Diagnosis of hypertension

Hypertension status was assessed using a calibrated OMRON HEM-7121 digital sphygmomanometer. Two readings were taken 5 min apart, and the average was used for analysis. Hypertension was defined as systolic BP ≥ 140 mmHg and/or diastolic BP ≥ 90 mmHg or current use of antihypertensive medication [29].

Assessment of relative muscle strength

Relative muscle strength (RMS) was calculated using grip strength measured by a Jamar hydraulic hand dynamometer (model J00105, resolution 2 kg), and the appendicular lean mass (ALM) was estimated using a validated equation for Indian adults. Two measurements were taken for each hand, and the maximum value was used for analysis. The RMS was then calculated as the grip strength (kg) divided by the ALM (kg). (Roberts et al. 2011) (Figure given in supplementary file-1) [30]. Appendicular lean mass was estimated from height, weight, age, and sex using validated predictive equations developed specifically for the Indian population. Only the lean mass from the arms was used to calculate relative grip strength [31].

We used normalized grip strength to estimate appendicular lean mass as a measure of relative muscle strength. While this approach uses a simple ratio, we acknowledge that more complex allometric scaling methods may provide better size-independent measures of strength. A supplementary analysis was conducted to examine the effectiveness of this normalization in removing the influence of body size.

Anthropometric measurements included height, measured to the nearest 0.1 cm using a stadiometer, and weight, measured to the nearest 0.1 kg using a digital scale. BMI was calculated as weight (kg) divided by height (m) squared. Sociodemographic and lifestyle factors, including age, sex, education level, physical activity (assessed using the Global Physical Activity Questionnaire), smoking status, and alcohol consumption, were self-reported by participants. Medical history, including diabetes and dyslipidemia status, was extracted from medical records with participant consent.

The data were collected during a single visit to the outpatient department. Participants were interviewed using a structured questionnaire for sociodemographic and lifestyle information. Anthropometric measurements were taken by trained research assistants, while blood pressure and grip strength were measured by trained medical staff. All measurements and data collection procedures were standardized to ensure consistency across all participants.

Statistical analysis

Statistical analysis was performed using STATA version 16.0 (StataCorp, College Station, TX). Descriptive statistics were calculated for all variables, with continuous variables presented as the mean ± standard deviation and categorical variables as frequencies and percentages. Differences in continuous variables across hypertension statuses were assessed using one-way ANOVA, while differences in categorical variables were evaluated using the chi-square test. Pearson's correlation coefficient was used to assess relationships between continuous variables. Nonnormally distributed variables were log-transformed before analysis.

Two types of regression analyses were conducted. Logistic regression was used with hypertension status as the binary outcome and RMS as the main predictor, both as continuous variables. For the analysis of RMS as a continuous variable, we employed linear regression models. To ensure the validity of these models, we assessed the distributional assumptions of the residuals. Normality of residuals: We created a histogram of the residuals and a quantile‒quantile (Q‒Q) plot to visually assess whether the normality assumption was satisfied. Additionally, we conducted a Shapiro‒Wilk test to statistically evaluate the normality of residuals and homoscedasticity. We plotted the residuals against the predicted values to check for constant variance across the range of predictions. Linearity: We examined partial regression plots to ensure a linear relationship between RMS and blood pressure measures. Independence: We used the Durbin–Watson test to check for autocorrelation in the residuals and for categorical variables. RMSs were categorized into tertiles based on the distribution in our study population. The tertiles were defined as follows:

1st tertile (low): 0.00–2.45 kg/kg ALM, 2nd tertile (medium): 2.46–3.78 kg/kg ALM, 3rd tertile (high): 3.79–6.12 kg/kg ALM.

These cutoff points represent the 33rd and 66th percentiles of the RMS distribution in our sample. Linear regression was performed with systolic and diastolic BP as continuous outcomes and RMS as the main predictor. Both regression analyses included age, sex, BMI, physical activity, smoking status, alcohol use status, diabetes status, dyslipidemia status, and hip and waist circumference as covariates. For logistic regression, both unadjusted and fully adjusted models were used, and the results are presented as odds ratios (ORs) with 95% confidence intervals (CIs). For linear regression, the results are presented as β coefficients with 95% CIs.

Model diagnostics were performed for both regression types. For logistic regression, the Hosmer‒Lemeshow goodness-of-fit test was used, and variance inflation factors were calculated to check for multicollinearity. For linear regression, R-squared values were calculated, residual plots were examined, and tests for heteroscedasticity were conducted. A p value < 0.05 was considered to indicate statistical significance for all analyses.

Model assumptions

Hypertension Analysis: Logistic Regression: The Box-Tidwell test showed no significant deviation from the linearity of the logit (p > 0.05 for all continuous predictors). The VIFs were all below 2.5, indicating no problematic multicollinearity.

Linear Regression: Residuals were approximately normally distributed for both the systolic (Shapiro–Wilk test, p = 0.18) and diastolic (p = 0.22) blood pressure models. No significant heteroscedasticity was observed in the residual plots. The Durbin-Watson test (systolic: 2.03, diastolic: 1.98) indicated no significant autocorrelation.

Prehypertension Analysis: Logistic Regression: The Box-Tidwell test showed no significant deviation from linearity of the logit (p > 0.05 for all continuous predictors). The VIFs were all below 2.3.

Linear Regression: Residuals were approximately normally distributed for both the systolic (Shapiro–Wilk test, p = 0.20) and diastolic (p = 0.25) blood pressure models. No significant heteroscedasticity was observed. The Durbin-Watson test (systolic: 2.01, diastolic: 1.97) indicated no significant autocorrelation (Table 1).

Table 1 Study variables
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Ethical considerations

Ethical approval was obtained from Shri MP Shah Govt Medical College & GG Hospital (ref No: 40/01/2023). All participants provided written informed consent before participation. The study was conducted in accordance with the Declaration of Helsinki (2008).

Results

Table 2 shows the characteristics of the 430 study participants categorized by blood pressure status: normotensive, prehypertensive, and hypertensive. There were no significant differences between the groups in weight or BMI. However, significant differences were observed in waist circumference (p = 0.049) and hip circumference (p = 0.01) across the blood pressure categories.

Table 2 Anthropometric characteristics of the study participants in the normotensive, prehypertensive, and hypertensive groups (n = 430)
Full size table

Relative muscle strength, assessed by grip strength/appendicular lean mass, was significantly lower in the hypertensive group (2.47 ± 1.37) than in the normotensive group (3.43 ± 2.12), with a p value of 0.002. These findings indicate that those with hypertension had poorer muscle quality.

Physical activity levels were also lower among hypertensive patients (1245 ± 641 MET-minutes/week) than among normotensive patients (1853 ± 789 MET-minutes/week), with a p value of 0.02. The prevalence of diabetes (19% vs. 9%, p = 0.03) and dyslipidemia (30% vs. 21%, p = 0.04) was greater in hypertensive patients.

Table 3 shows the correlation analyses between the anthropometric factors and systolic and diastolic blood pressure in the total study population (n = 430). Compared with BMI and hip circumference, relative muscle strength demonstrated the strongest negative correlation with both systolic (r = − 0.559, p = 0.001) and diastolic (r = − 0.418, p = 0.001) blood pressure.

Table 3 Correlations between anthropometric factors and blood pressure
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Table 4 presents the results of the analyses examining the association between relative muscle strength (RMS) and hypertension risk. In the adjusted analysis (Model 1), which accounted for age, physical activity, diabetes status, dyslipidemia status, and hip and waist circumference, we found that for each 1-unit increase in relative muscle strength, the odds of hypertension decreased by 37% (OR 0.63, 95% CI 0.54–0.68, p < 0.001).

Table 4 Association between relative muscle strength and prehypertension
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The unadjusted analysis (Model 2) showed a slightly weaker association, with a 20% decrease in the odds of hypertension for each 1-unit increase in RMS (OR 0.80, 95% CI 0.62–0.89, p < 0.001).

According to the categorical analysis, compared to those in the low muscle strength tertile, the odds of hypertension were 31% (OR 0.69, 95% CI 0.54–0.86, p < 0.001) and 26% (OR 0.74, 95% CI 0.59–0.89, p < 0.001) lower in the medium and high tertiles, respectively, after adjustment for confounders. This dose‒response relationship persisted in both the adjusted and unadjusted models.

Table 5 presents the results of the analyses examining the association between relative muscle strength and hypertension risk. Analysis of RMS as a continuous variable revealed that for each 1-unit increase in relative muscle strength, the adjusted odds of hypertension decreased by 37% (OR 0.63, 95% CI 0.54–0.68; p < 0.001). The categorical analysis demonstrated that, compared to those in the low muscle strength tertile, the odds of hypertension were 31% (OR 0.69, 95% CI 0.54–0.86) and 26% (OR 0.74, 95% CI 0.59–0.89) lower in the medium and high tertiles, respectively.

Table 5 Association between relative muscle strength and hypertension
Full size table

In Fig. 2, the bar graph illustrates the prevalence of hypertension across increasing relative muscle strength tertiles, showing a clear decrease in hypertension prevalence as muscle strength increases from low to high tertiles. (1st tertile-(55%), 2nd tertile- (35%), 3rd tertile-(20%) (Fig. 2).

Fig. 2
figure 2

Bar graph showing that the prevalence of hypertension decreased across increasing relative muscle strength tertiles

Full size image

Supplementary Table 1: Correlations between grip strength, anthropometric measures, and blood pressure before and after normalization to appendicular lean mass. The data analysis revealed that, before normalization, grip strength had moderate positive correlations with BMI, body weight, and height, indicating that grip strength is confounded by body size. However, after normalizing grip strength to appendicular lean mass (grip strength/lean mass), the correlations with BMI, weight, and height became nonsignificant (r = 0.05, 0.12, and − 0.07, respectively).

This suggests that normalizing for appendicular lean mass removes the influence of overall body size on the grip strength measure.

The strong negative correlations between grip strength/lean mass and systolic and diastolic BP persist even after normalization, indicating that this measure of relative muscle strength is associated with blood pressure independent of body size. (r = − 0.56 and − 0.43).

This supplementary table provides evidence that the normalization approach used in the study accounts for body size confounding when assessing the relationship between muscle strength and hypertension risk. This analysis also suggested that the normalization approach reduced, but did not eliminate, the influence of body size on strength.

Supplementary Tables 2 and 3 provide a comprehensive view of the relationship between absolute handgrip strength and hypertension/prehypertension risk. They allow for comparison with the main analysis using relative muscle strength, potentially offering insights into whether absolute or relative strength is a better predictor of hypertension risk in this population.

In summary, higher relative muscle strength showed a significant inverse dose‒response relationship with the odds of hypertension and prehypertension, independent of potential confounding factors.

Discussion

This cross-sectional study revealed a 23% prevalence of hypertension and 43% prevalence of prehypertension in the adult population attending our tertiary care center. These findings are comparable to recent national estimates but show some variation from other regional studies. The National Family Health Survey-5 (2019–21) reported a hypertension prevalence of 21.3% in adults aged 15–49 years in Gujarat [33]. However, a community-based study in rural Gujarat by Bhagyalaxmi et al. reported a prevalence of hypertension of 30%, with 40% prehypertension [34]. Our results fall between these estimates, possibly reflecting differences in study settings and population characteristics. A meta-analysis by Anchala et al. estimated the overall prevalence of hypertension in India to be 29.8%, with significant regional variations [35]. Our slightly lower hypertension prevalence might be due to increased awareness and treatment in our hospital-based setting. The high prevalence of prehypertension in our study population (43%) is particularly concerning, as it represents a significant at-risk group for future hypertension and cardiovascular complications. This finding underscores the importance of early intervention strategies targeting this pre-disease state.

This cross-sectional study also revealed a significant inverse association between relative muscle strength, measured by grip strength normalized to appendicular lean mass, and the risk of hypertension in an adult Indian population. Participants in the high tertile of relative muscle strength had 26% (odds ratio (OR) 0.74, 95% CI 0.59–0.89) lower odds of hypertension than those in the low tertile after adjusting for potential confounders.

The protective association we observed between greater relative muscle strength and reduced hypertension risk aligns with proposed physiological mechanisms linking muscle strength to cardiovascular health. Increased muscle strength is linked to decreased arterial stiffness, an established contributor to age-related systolic hypertension [10]. Resistance training promotes favorable structural remodeling of arteries, enhancing elasticity and compliance [11]. Additionally, acute muscle contractions during strength exertions stimulate nitric oxide release, inducing vasodilation [12]. Over time, this augments endothelial function and decreases peripheral resistance. Furthermore, greater muscle strength is associated with improved insulin sensitivity, conferring metabolic benefits that may lower hypertension risk [13]. Our study revealed a significant inverse association between relative muscle strength and hypertension risk. This finding is consistent with previous research by Polo et al. [36], who reported that grip strength was inversely associated with blood pressure and hypertension across multiple populations. The key role of relative muscle strength is underscored by studies showing that the ratio of strength to muscle mass is a stronger predictor of hypertension risk than grip strength alone [37,38,39,40]. A recent review article also reported that resistance exercise significantly lowered systolic and diastolic blood pressure in adults with normal blood pressure and prehypertension [41]. This highlights the potential for targeted strengthening programs to improve blood pressure control. Jung et al. reported that skeletal muscle quality was a stronger predictor of mortality than muscle mass alone in older adults [42]. This emphasizes the importance of assessing relative muscle strength, not just absolute mass or size.

A greater relative muscle strength was associated with a significantly lower likelihood of prehypertension after adjustment for confounders. This inverse association is consistent with previous studies demonstrating that greater muscle strength or quality predicts a lower risk of developing hypertension over time. This finding aligns with previous research suggesting that better muscle strength protects against the development of hypertension [43].

Similarly, another study conducted by Luo et al. suggested that higher RMS is an independent protective factor against hypertension, and efforts to promote RMS may be beneficial for the prevention and management of hypertension [44].

The inverse dose–response relationship between higher relative muscle strength and lower prehypertension risk was notable. This suggests that preserving muscle quality may delay or prevent the progression from normotension to hypertension. Prior studies have reported that relative muscle strength predicts future hypertension prevalence better than absolute strength measures [18, 19, 43, 44].

The strengths of this study include robust hypertension assessment per the ACC/AHA 2017 guidelines, grip strength measurement using a calibrated dynamometer, and using a previously validated equation for estimating appendicular lean mass in Indian adults.

Limitations

The cross-sectional design limits the ability to determine the causality or directionality of associations. A single-center study may affect the generalizability of the findings, self-reported data on lifestyle factors are prone to recall bias, dietary factors are not assessed, or medication use may confound relationships. Our use of a simple ratio (grip strength/appendicular lean mass) to assess relative muscle strength may not fully account for the allometric relationship between strength and body size. Future studies should consider more sophisticated scaling methods, as recommended by Nevill et al. [45], and the sample size should be relatively small. Furthermore, the relationship between RMS and endothelial function could be explored. However, our study design does not allow us to distinguish between the relative contributions of systolic and diastolic blood pressure to this association. Future research using continuous blood pressure measures as outcomes could provide more nuanced insights into these relationships.

Recommendations

Larger multicenter longitudinal studies are needed to establish a temporal relationship between relative muscle strength and hypertension. Studies on whether resistance exercise interventions improve muscle quality and reduce blood pressure are warranted. Research on the influence of diet, micronutrients, and physical activity on muscle quality is needed. To examine whether poor muscle quality mediates nutritional/lifestyle transitions and rising hypertension in India. Assess whether relative muscle strength predicts hard outcomes such as cardiovascular events and mortality.

In summary, this study demonstrated that greater relative muscle strength, reflecting greater muscle quality, is associated with significantly reduced odds of hypertension and prehypertension in Indian adults. Maintaining muscle strength and attenuating age-related decreases in muscle quality may represent an important strategy for optimal blood pressure regulation and hypertension prevention.

Conclusions

This cross-sectional study revealed that increased relative muscle strength, assessed by grip strength normalized to appendicular lean mass, was associated with a significantly decreased likelihood of hypertension and prehypertension in Indian adults. Participants in the top tertile of relative strength had 26% and 33% lower odds of having hypertension and prehypertension, respectively, than did those in the bottom tertile after adjusting for confounders. These findings highlight the potential importance of muscle quality, beyond muscle mass, in blood pressure regulation. Although our study does not provide evidence on the effects of any specific type of exercise, it does suggest that maintaining higher muscle quality may be beneficial for blood pressure regulation. Future longitudinal and interventional studies are needed to establish causality and to investigate whether improving relative muscle strength through various forms of exercise could be an effective strategy for hypertension prevention and management.

Availability of data and materials

The datasets generated and/or analyzed during the current study are not publicly available to protect the privacy of the study participants but are available from the corresponding author upon reasonable request.

Abbreviations

BMI:

Body mass index

RMS:

Relative muscle strength

References

  1. GBD 2017 Risk Factor Collaborators. Global, regional, and national comparative risk assessment of 84 behavioral, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2018;392(10159):1923–1994. https://doi.org/10.1016/S0140-6736(18)32225-6

  2. Mills KT, Bundy JD, Kelly TN, Reed JE, Kearney PM, Reynolds K, Chen J, He J. Global disparities of hypertension prevalence and control: a systematic analysis of population-based studies from 90 countries. Circulation. 2016;134(6):441–50. https://doi.org/10.1161/CIRCULATIONAHA.115.018912.

    Article  PubMed  PubMed Central  Google Scholar 

  3. NCD Risk Factor Collaboration (NCD-RisC). Worldwide trends in blood pressure from 1975 to 2015: a pooled analysis of 1479 population-based measurement studies with 19·1 million participants [published correction appears in Lancet. 2020 Sep 26;396(10255):886. https://doi.org/10.1016/S0140-6736(20)31972-3]. Lancet. 2017;389(10064):37–55. https://doi.org/10.1016/S0140-6736(16)31919-5

  4. Gupta R, et al. Recent studies on hypertension prevalence and control in India 2023. Hypertens Res. 2024;47(6):1445–56. https://doi.org/10.1038/s41440-024-01585-y.

    Article  PubMed  Google Scholar 

  5. Collaborators I-L. Nations within a nation: variations in epidemiological transition across the states of India, 1990–2016 in the global burden of disease study. Lancet. 2017;390(10111):2437–60. https://doi.org/10.1016/S0140-6736(17)32804-0.

    Article  Google Scholar 

  6. Deepa M, Anjana RM, Manjula D, Narayan KM, Mohan V. Convergence of prevalence rates of diabetes and cardiometabolic risk factors in middle and low-income groups in urban India: 10-year follow-up of the Chennai urban population study. J Diabetes Sci Technol. 2011;5(4):918–27. https://doi.org/10.1177/193229681100500415.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Celis-Morales CA, Petermann F, Hui L, et al. Associations between diabetes and both cardiovascular disease and all-cause mortality are modified by grip strength: evidence from UK Biobank, a prospective population-based cohort study. Diabetes Care. 2018;41(8):1710–8. https://doi.org/10.2337/dc18-0266.

    Article  Google Scholar 

  8. Celis-Morales CA, Welsh P, Lyall DM, et al. 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. 2018;361:k1651. https://doi.org/10.1136/bmj.k1651.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Jeong W, Moon JY, Kim JH. Association of absolute and relative hand grip strength with all-cause mortality among middle-aged and old-aged people. BMC Geriatr. 2023;23(1):321. https://doi.org/10.1186/s12877-023-04008-8.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Quan Y, Wang C, Wang L, Li G. Geriatric sarcopenia is associated with hypertension: a systematic review and meta-analysis. J Clin Hypertens (Greenwich). 2023;25(9):808–16. https://doi.org/10.1111/jch.14714.

    Article  PubMed  Google Scholar 

  11. Miyachi M. Effects of resistance training on arterial stiffness: a meta-analysis. Br J Sports Med. 2013;47(6):393–6. https://doi.org/10.1136/bjsports-2012-090488.

    Article  PubMed  Google Scholar 

  12. Maiorana A, O’Driscoll G, Cheetham C, et al. The effect of combined aerobic and resistance exercise training on vascular function in type 2 diabetes. J Am Coll Cardiol. 2001;38(3):860–6. https://doi.org/10.1016/S0735-1097(01)01439-5.

    Article  CAS  PubMed  Google Scholar 

  13. García-Hermoso A, Cavero-Redondo I, Ramírez-Vélez R, Ruiz JR, Ortega FB, Lee DC, Martínez-Vizcaíno V. Muscular strength as a predictor of all-cause mortality in an apparently healthy population: a systematic review and meta-analysis of data from approximately 2 million men and women. Arch Phys Med Rehabil. 2018;99(10):2100-2113.e5. https://doi.org/10.1016/j.apmr.2018.01.008.

    Article  PubMed  Google Scholar 

  14. Sui SX, Holloway-Kew KL, Hyde NK, et al. Handgrip strength and muscle quality in Australian women: cross-sectional data from the geelong osteoporosis study. J Cachexia Sarcopenia Muscle. 2020;11(3):690–7. https://doi.org/10.1002/jcsm.12544.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Naimo MA, Varanoske AN, Hughes JM, Pasiakos SM. Skeletal muscle quality: a biomarker for assessing physical performance capabilities in young populations. Front Physiol. 2021;12:706699. https://doi.org/10.3389/fphys.2021.706699.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Kuschel LB, Sonnenburg D, Engel T. Factors of muscle quality and determinants of muscle strength: a systematic literature review. Healthcare (Basel). 2022;10(10):1937. https://doi.org/10.3390/healthcare10101937.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Cruz-Jentoft AJ, Bahat G, Bauer J, et al. Sarcopenia: revised European consensus on definition and diagnosis. Age Aging. 2019;48(1):16–31. https://doi.org/10.1093/aging/afy169.

    Article  Google Scholar 

  18. Yang S, Li T, Yang H, et al. Association between muscle strength and health-related quality of life in a Chinese rural elderly population: a cross-sectional study. BMJ Open. 2020;10(1):e026560. https://doi.org/10.1136/bmjopen-2018-026560.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Bai X, Zhao J, Shi S, Zhu C, Wang Y. Muscle quality is negatively related to hypertension prevalence in adults: results from NHANES 2011–2014. J Clin Hypertens (Greenwich). 2023;25(11):1027–35. https://doi.org/10.1111/jch.14734.

    Article  CAS  PubMed  Google Scholar 

  20. Liu P, Ma F, Lou H, Liu Y. The utility of fat mass index vs. body mass index and percentage of body fat in the screening of metabolic syndrome. BMC Public Health. 2013;13:629. https://doi.org/10.1186/1471-2458-13-629.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Cesari M, Araujo de Carvalho I, Amuthavalli Thiyagarajan J, et al. Evidence for the domains supporting the construct of intrinsic capacity. J Gerontol A Biol Sci Med Sci. 2018;73(12):1653–60. https://doi.org/10.1093/gerona/gly011.

    Article  PubMed  Google Scholar 

  22. Madden AM, Smith S. Body composition and morphological assessment of nutritional status in adults: a review of anthropometric variables. J Hum Nutr Diet. 2016;29(1):7–25. https://doi.org/10.1111/jhn.12278.

    Article  CAS  PubMed  Google Scholar 

  23. Tripathy JP, Thakur JS, Jeet G, Chawla S, Jain S, Prasad R. Urban rural differences in diet, physical activity and obesity in India: are we witnessing the great Indian equalization? Results from a cross-sectional STEPS survey. BMC Public Health. 2016;16(1):816. https://doi.org/10.1186/s12889-016-3489-8.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Kumar V, Selby A, Rankin D, et al. Age-related differences in the dose-response relationship of muscle protein synthesis to resistance exercise in young and old men. J Physiol. 2009;587(1):211–7. https://doi.org/10.1113/jphysiol.2008.164483.

    Article  CAS  PubMed  Google Scholar 

  25. Baumgartner RN. Body composition in healthy aging. Ann N Y Acad Sci. 2000;904:437–48. https://doi.org/10.1111/j.1749-6632.2000.tb06498.x.

    Article  CAS  PubMed  Google Scholar 

  26. Lau EM, Lynn HS, Woo JW, Kwok TC, Melton LJ 3rd. Prevalence of and risk factors for sarcopenia in elderly Chinese men and women. J Gerontol A Biol Sci Med Sci. 2005;60(2):213–6. https://doi.org/10.1093/gerona/60.2.213.

    Article  PubMed  Google Scholar 

  27. Morris MS, Jacques PF. Total protein, animal protein and physical activity in relation to muscle mass in middle-aged and older Americans. Br J Nutr. 2013;109(7):1294–303. https://doi.org/10.1017/S0007114512003133.

    Article  CAS  PubMed  Google Scholar 

  28. Ramakrishnan S, Zachariah G, Gupta K, et al. Prevalence of hypertension among Indian adults: results from the great India blood pressure survey. Indian Heart J. 2019;71(4):309–13. https://doi.org/10.1016/j.ihj.2019.09.012.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Whelton PK, Carey RM, Aronow WS, et al. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA guideline for the prevention, detection, evaluation, and management of high blood pressure in adults: executive summary: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Hypertension. 2018;71(6):1269–324. https://doi.org/10.1161/hyp.0000000000000066.

    Article  CAS  PubMed  Google Scholar 

  30. Roberts HC, Denison HJ, Martin HJ, Patel HP, Syddall H, Cooper C, Sayer AA. A review of the measurement of grip strength in clinical and epidemiological studies: toward a standardized approach. Age Aging. 2011;40(4):423–9. https://doi.org/10.1093/ageing/afr051.

    Article  Google Scholar 

  31. Rathnayake N, Alwis G, Lenora J, Lekamwasam S. Development & cross-validation of anthropometric predictive models to estimate the appendicular skeletal muscle mass in middle-aged women in Sri Lanka. Indian J Med Res. 2019;150(3):297–305. https://doi.org/10.4103/ijmr.IJMR_1961_17.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Cleland CL, Hunter RF, Kee F, Cupples ME, Sallis JF, Tully MA. Validity of the global physical activity questionnaire (GPAQ) in assessing levels and change in moderate-vigorous physical activity and sedentary behavior. BMC Public Health. 2014;14:1255. https://doi.org/10.1186/1471-2458-14-1255.

    Article  PubMed  PubMed Central  Google Scholar 

  33. International Institute for Population Sciences (IIPS) and ICF. National Family Health Survey (NFHS-5), India, 2019–21: Gujarat. Mumbai: IIPS; 2021.

  34. Bhagyalaxmi A, Atul T, Shikha J. Prevalence of risk factors for noncommunicable diseases in a District of Gujarat. India J Health Popul Nutr. 2013;31(1):78–85. https://doi.org/10.3329/jhpn.v31i1.14752.

    Article  PubMed  Google Scholar 

  35. Anchala R, Kannuri NK, Pant H, et al. Hypertension in India: a systematic review and meta-analysis of prevalence, awareness, and control of hypertension. J Hypertens. 2014;32(6):1170–7. https://doi.org/10.1097/HJH.0000000000000146.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Polo-López A, Calatayud J, Núñez-Cortés R, Andersen LL, Moya-Ramón M, López-Bueno R. Dose-response association between handgrip strength and hypertension: a longitudinal study of 76,503 European older adults. Curr Probl Cardiol. 2023;48(9): 101813. https://doi.org/10.1016/j.cpcardiol.2023.101813.

    Article  PubMed  Google Scholar 

  37. Leong DP, Teo KK, Rangarajan S, Lopez-Jaramillo P, Avezum A, Orlandini A, Seron P, Ahmed SH, Rosengren A, Kelishadi R, Rahman O, Swaminathan S, Iqbal R, Gupta R, Lear SA, Oguz A, Yusoff K, Zatonska K, Yusuf S. Prognostic value of grip strength: findings from the prospective urban rural epidemiology (PURE) study. Lancet (London, England). 2015;386(9990):266–73. https://doi.org/10.1016/S0140-6736(14)62000-6.

    Article  PubMed  Google Scholar 

  38. Feng Q, Jiang C, Wang M, et al. Association between relative handgrip strength and hypertension in Chinese adults: an analysis of four successive national surveys with 712,442 individuals (2000–2014). PLoS ONE. 2021;16(10):e0258763. https://doi.org/10.1371/journal.pone.0258763.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Bai T, Fang F, Li F, Ren Y, Hu J, Cao J. Sarcopenia is associated with hypertension in older adults: a systematic review and meta-analysis. BMC Geriatr. 2020;20(1):279. https://doi.org/10.1186/s12877-020-01672-y.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Gu Y, Dong J, Meng G, et al. Handgrip strength as a predictor of incident hypertension in the middle-aged and older population: the TCLSIH cohort study. Maturitas. 2021;150:7–13. https://doi.org/10.1016/j.maturitas.2021.06.002.

    Article  PubMed  Google Scholar 

  41. Paluch A, Boyer W, Franklin B, Laddu D, Lobelo F, Lee D, et al. Resistance exercise training in individuals with and without cardiovascular disease: 2023 update: a scientific statement from the American heart association. Circulation. 2024. https://doi.org/10.1161/cir.0000000000001189.

    Article  PubMed  Google Scholar 

  42. Jung J, Lee J, Lim JH, et al. The effects of muscle mass and quality on mortality of patients with acute kidney injury requiring continuous renal replacement therapy. Sci Rep. 2023;13(1):7311. https://doi.org/10.1038/s41598-023-33716-9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Ji C, Zheng L, Zhang R, Wu Q, Zhao Y. Handgrip strength is positively related to blood pressure and hypertension risk: results from the national health and nutrition examination survey. Lipids Health Dis. 2018;17(1):86. https://doi.org/10.1186/s12944-018-0734-4.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Luo JH, Zhang TM, Yang LL, Cai YY, Yang Y. Association between relative muscle strength and hypertension in middle-aged and older Chinese adults. BMC Public Health. 2023;23(1):2087. https://doi.org/10.1186/s12889-023-17007-6.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Nevill AM, Holder RL. Scaling, normalizing, and per ratio standards: an allometric modeling approach. J Appl Physiol (1985). 1995;79(3):1027–31. https://doi.org/10.1152/jappl.1995.79.3.1027.

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

We acknowledge and are grateful to all the patients who contributed to the collection of the data for this study. We are also thankful to Dr. Nandini Desai (Dean and Chairperson of MDRU), Dr. Dipesh Parmar (Professor and Head, of the Department of Community Medicine), and Shri M P Shah Government Medical College, Jamnagar, India.

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None.

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Authors and Affiliations

  1. Department of Community Medicine, Shri M P Shah Government Medical College, New PG Hostel, Shri MP Shah Medical College Campus, GG Hospital, Patel Colony Post, Jamnagar, Gujarat, 361008, India

    M. Yogesh & Jay Nagda

  2. Shri M P Shah Government Medical College, Jamnagar, Gujarat, India

    Nirmalkumar Shaileshbhai Patel & Jay Varu

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  1. M. Yogesh
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  2. Jay Nagda
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  3. Nirmalkumar Shaileshbhai Patel
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Contributions

YM contributed to the conceptualization, data curation, formal analysis, investigation, methodology, resources, supervision, validation, writing (original draft), and writing (review and editing). YM, JN, JV and NP contributed to conceptualization, data curation, formal analysis, investigation, writing (original draft), and writing (review and editing). YM, JN, JV and NP contributed to the methodology, resources, supervision, validation, and writing (review and editing). YM, JN, JV and NP contributed to the formal analysis, investigation, writing (original draft), and writing (review and editing). All the authors read and approved the final manuscript.

Corresponding author

Correspondence to M. Yogesh.

Ethics declarations

Ethics approval and consent to participate

Good clinical care guidelines were followed, and the guidelines were established as per the Helsinki Declaration 2008. All the participants were given clear instructions about the study before the start of the study. Written informed consent was obtained from the patients in their vernacular language for study participation, and no identifying information or images were included in the original article, which was submitted for publication in an online open-access publication. The entire methodology and protocol were approved by the Institutional Ethical Committee of Shri M P Shah Government Medical College, Jamnagar, Gujarat, India.

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Not Applicable.

Competing interests

The authors declare no competing interests.

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Yogesh, M., Nagda, J., Patel, N.S. et al. Gripping insights: prevalence of hypertension and its association with relative muscle strength—a cross-sectional study in an adult Indian population. J Health Popul Nutr 43, 215 (2024). https://doi.org/10.1186/s41043-024-00707-z

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Keywords

Journal of Health, Population and Nutrition

ISSN: 2072-1315

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