Objective
The aim of this study was to investigate whether declining mobility and muscle strength predict new-onset hypertension in suburban-dwelling elderly individuals.
Methods
This study was designed as a longitudinal prospective cohort study. It was comprised of 362 individuals (mean age = 67.8 ± 6.2; 157 men) without hypertension at baseline. At baseline, all participants completed health questionnaires and underwent measurements of mobility [the Timed Up and Go test (TUGT) and 4-m walking test] and muscle strength (grip strength). At 1-year follow-up, we determined the number of participants who had developed new-onset hypertension. We then evaluated the relationship between above metrics and the development of hypertension.
Results
In the present study, 94 (26.0%) participants developed hypertension after 1 year. After adjusting for mixed factors, the TUGT scores [hazard ratio = 1.15; 95% confidence interval (CI), 1.10–1.31; P = 0.030] were positively associated with the development of hypertension, while the 4-m walking test scores (hazard ratio = 0.07; 95% CI, 0.01–0.47; P = 0.007) showed an inverse relationship with hypertension incidence. Grip strength (hazard ratio = 1.03; 95% CI, 0.99–1.06; P = 0.098) was not significantly associated with hypertension incidence.
Conclusion
Our results indicate that people with declining mobility are significantly more likely to develop hypertension. Hence, improving mobility could be protective against hypertension for elderly individuals.
Keywords: hypertension, mobility ability, muscle strength
Introduction
An estimated more than 60% adults over 60 years of age has hypertension [1], contributing to 50% of cardiovascular disease-related deaths [2]. Needless to say hypertension places a great burden on society and the economy. As the population ages, the prevalence of hypertension will increase even more [3] unless effective preventive measures for risk factors are implemented in normotensives.
On the basis of previously published longitudinal studies, it has been published that physical activity is causally related to hypertension [4]. The underlying mechanism involved in the association between physical activity and hypertension is still not explicit. There are two possible factors for this connection more directly, that is, muscle strength and mobility. They are two essential conditions for maintaining daily physical activity level [5], and their measurements are more objective and convenient relative to the way of physical activity. Epidemiological study has linked muscle strength as a predictor to impaired mobility [6]. Mobility impairments are likely to be the other risk factors for hypertension that has been recommended as an additional ‘vital sign’ [7]. Some studies have focused on the correlation between mobility [8,9]/muscle strength [10,11] and hypertension, but there is no longitudinal study using both of them as predictive indicators for considering their interaction.
In China, hypertension is even more prevalent in rural areas compared to urban areas, and the rate of poorly controlled hypertension is also higher in rural areas [12,13]. Therefore, the purpose of this study was to assess the relationship between hypertension and the above parameters among suburban-dwelling elderly Chinese individuals in order to identify individuals at high risk for hypertension before it happened, so that these individuals could promptly receive preventive interventions, possibly including physical rehabilitation.
Methods
This study was approved by ethics committee of Tianjin Medical University, and the methods were carried out in accordance with the principles of the Declaration of Helsinki. Informed consent was obtained from all subjects.
Participants
From July 2015 to July 2016 at follow-up, subjects were recruited from the pool of 813 subjects that had participated in the National Free Physical Examination Program in the Hangu Health Center of Tianjin, China. For the purposes of the present study, subjects ≥60 years of age were invited to participate in a comprehensive geriatric assessment twice by the same group of researchers in July 2015 and July 2016. People without hypertension diagnosis at baseline were included in the analysis. The exclusion criteria were as follows: (1) history of diagnosis hypertension, (2) unable to provide informed consent, (3) inability to complete study tasks (i.e. physical disability, incomprehension, or unwillingness to comply with instructions), and (4) having a diagnosis that could affect muscle strength or mobility (i.e. amyosthenia, Parkinson disease).
Baseline variables
All patients completed health questionnaires, had their height, weight, and blood pressure (BP) taken, and underwent measurements of physical performance. The questionnaires included questions about age, sex, occupation, educational level, marital status, smoking habits, drinking habits, history of illness (i.e. diabetes, hyperlipidemia, heart disease, peptic ulcer disease, stroke, osteoarthritis, cancer, kidney disease, hepatic disease, biliary tract disease, thyroid disease, amyosthenia, Parkinson disease, and anemia), and physical activity. Physical activity was assessed using the short form of the International Physical Activity Questionnaire (IPAQ), which asks participants the total minutes spent on vigorous activity, moderate-intensity activity, and walking over the previous 7 days. Total minutes for each activity intensity level were multiplied by 8.0, 4.0, and 3.3, respectively, to yield activity intensity subscores. These subscores were then added up for each participant to generate a total physical activity score.
Height and weight were recorded using a standard protocol. BMI was calculated as weight in kilograms divided by height in meters squared.
Hypertension definition
Participants were considered to be hypertensive if they reported being diagnosed by a clinician or reported taking antihypertensive medications. Office BP evaluation involved two SBP and DBP measurements, using the average of the two measurements, with a validated OMRON model PASESA AVE-2000 (Shisei Datum, Tokyo, Japan). If the individuals without history of hypertension had a measured average SBP ≥ 140 mmHg or DBP ≥ 90 mmHg, they would be advised to check with a physician within two weeks. Subsequently, this population was re-examined by professional physician according to the seventh report of the Joint National Committee (the average BPs of two or more measurements taken on different days results in a SBP ≥ 140 mmHg or DBP ≥ 90 mmHg) [14].
Mobility
Self-pace mobility was assessed using the 4-m walk test at usual speed. To perform the 4 -m walk tests, a 4-m path was marked with red tape. The first and last meters were added to the path to allow for the inevitable acceleration of walking at the beginning of the test and the inevitable deceleration of walking at the end of the test to ensure the walking speed in the intervening 4 m was not confounded by acceleration and deceleration. The time was recorded by stopwatch when the participants were verbally instructed to walk at their usual pace through the 4-m path. The participants were allowed to use a gait-assistance device. Participants completed the task twice. The average time of the two trials was used to compute walking speed.
The Timed Up and Go test (TUGT) is an indicator of mobility at a fast-paced walking speed. It measures the number of seconds needed for an individual to stand up from a chair, walk 3 m as fast as possible past a red cone on the floor, turn around, walk back to the chair, and sit down again with his/her back against the chair. The task was demonstrated before participants were asked to complete it.
Muscle strength
Grip strength was used as a measure of muscle strength and was quantified using a handheld dynamometer (GRIP-D; Takei Ltd, Niigata, Japan). Subjects stood during the task with arms relaxed at their sides unless the participant was physically limited. Participants were asked to exert their maximum effort twice using their dominant hand; the average grip strength was then calculated.
Data analysis
Statistical analysis was conducted using SPSS 19.0 statistical software (SPSS Inc, Chicago, Illinois, USA). Normally distributed continuous variables were expressed as mean ± SD, except for IPAQ variables, which were expressed as medians with 25–75th percentages; classification variables were reported as percentages. Comparisons between participants with and without hypertension were conducted using t-tests for normally distributed continuous variables, χ2 tests for categorical variables, and Kruskal–Wallis rank tests for ranked data. Simple logistic regression analyses were used to examine the independent effect of different physical performance metrics on hypertension; odds ratios and 95% confidence intervals (CIs) were computed. In addition, adjustments for potential confounders, such as age, sex, BMI (model 1), marital status and illiteracy (model 2), and comorbidity status (diabetes, hyperlipidemia, and stroke) (model 3) were performed using multiple logistic regression analyses.
Results
Baseline characteristics
Four hundred twenty-nine (52.8%) of the original 813 participants were excluded at baseline for having hypertension, 19 subjects were lost to follow-up, and 3 subjects had missing data, resulting in a final analytic sample of 362 individuals without hypertension at baseline.
Ninety-four of 362 participants (mean age = 67.8 ± 6.2; 157 men) developed new onset hypertension after 1 year (Table 1). Participants who developed hypertension were more likely to have fewer years of education and be widowed. They also had a higher BMI and higher prevalence of diabetes, hyperlipidemia, and stroke. Finally, their performances on the TUGT and 4-m walking tests were worse than those without hypertension. There was no significant difference in muscle strength between those with hypertension and those without.
Table 1.
Baseline characteristics of study participants according to the presence of hypertension at 1-year follow-up
| Characteristic | No hypertension (n = 268) | Hypertension n = 94) | P value |
|---|---|---|---|
| SBP (mmHg) | 119.3 ± 12.3 | 128.9 ± 8.50 | <0.001 |
| DBP (mmHg) | 69.3 ± 7.60 | 72.3 ± 8.20 | 0.014 |
| Sociodemographic | |||
| Age (years) | 66.3 ± 5.70 | 66.5 ± 5.86 | 0.704 |
| Female (%) | 57.1 | 55.3 | 0.766 |
| BMI (kg/m2) | 24.0 ± 3.85 | 25.1 ± 3.53 | 0.012 |
| Widowed (%) | 9.8 | 23.3 | 0.021 |
| Living alone (%) | 14.1 | 10.4 | 0.358 |
| Illiterate (%) | 23.7 | 33.7 | 0.040 |
| Farming (%) | 90.8 | 90.6 | 0.950 |
| Drinking (%) | 0.354 | ||
| Never | 67.6 | 61.5 | |
| <7 Days/week | 19.5 | 24.0 | |
| Daily | 13.0 | 14.6 | |
| Smoking (%) | 0.274 | ||
| Never | 52.3 | 50.0 | |
| Former | 15.6 | 10.4 | |
| Current | 32.1 | 39.6 | |
| Physical metrics | |||
| IPAQ (Met/week) | 2056 (1315, 6118) | 2153 (903, 4158) | 0.303 |
| Grip strength (kg) | 25.1 ± 9.30 | 25.7 ± 10.2 | 0.582 |
| TUGT(S) | 8.51 ± 1.99 | 9.20 ± 2.08 | 0.004 |
| 4-m walking test (m/s) | 1.01 ± 0.17 | 0.94 ± 0.14 | <0.001 |
| Diseases (%) | |||
| Diabetes (%) | 8.0 | 16.0 | 0.025 |
| Hyperlipidemia (%) | 24.8 | 38.0 | 0.010 |
| Heart disease (%) | 21.9 | 17.3 | 0.387 |
| Peptic ulcer (%) | 5.3 | 7.8 | 0.430 |
| Stroke (%) | 2.6 | 10.4 | 0.008 |
| Osteoarthritis (%) | 16.1 | 7.7 | 0.067 |
| Cancer (%) | 2.1 | 3.9 | 0.411 |
| Kidney disease (%) | 5.3 | 1.3 | 0.140 |
| Hepatic disease (%) | 3.7 | 0.0 | 0.089 |
| Biliary tract disease (%) | 5.3 | 3.8 | 0.624 |
| Thyroid disease (%) | 2.6 | 3.9 | 0.583 |
| Anemia (%) | 0.5 | 0.0 | 0.523 |
IPAQ, International Physical Activity Questionnaire; TUGT, Timed Up and Go test.
Risk factors for hypertension incidence
After adjustments for potential confounders in model 3 (i.e. age, sex, BMI, marital status, illiteracy, and comorbidity status), the three physical risk factors for hypertension were summarized below: grip strength (adjusted hazard ratio = 1.03; 95% CI, 0.99–1.06, P = 0.098), TUGT (adjusted hazard ratio = 1.15; 95% CI, 1.10–1.31, P = 0.030), 4-m walking test (adjusted hazard ratio = 0.07; 95% CI, 0.01–0.47, P = 0.007) (Table 2).
Table 2.
Multiple logistic regression on incidence of hypertension during baseline to 1-year (n = 362)
| Variable | Unadjusted | Model 1 | Model 2 | Model 3 | ||||
|---|---|---|---|---|---|---|---|---|
| Hazard ratio (95% CI) | P | Hazard ratio (95% CI) | P | Hazard ratio (95% CI) | P | Hazard ratio (95% CI) | P | |
| Grip strength | 1.01 (0.98–1.03) | 0.581 | 1.01 (0.98–1.03) | 0.636 | 1.01 (0.98–1.04) | 0.340 | 1.03 (0.99–1.06) | 0.098 |
| TUGT | 1.71 (1.05–1.30) | 0.005 | 1.19 (1.07–1.34) | 0.002 | 1.19 (1.07–1.34) | 0.005 | 1.15 (1.10–1.31) | 0.030 |
| 4-m walking test | 0.07 (0.02–0.31) | 0.001 | 0.06 (0.01–0.29) | <0.001 | 0.06 (0.11–0.30) | 0.001 | 0.07 (0.01–0.47) | 0.007 |
Model 1: Age, Sex, BMI; Model 2: Model 1+marital status, and illiteracy; Model 3: Model 2+ comorbidity status (diabetes, hyperlipidemia, and stroke).
IPAQ, International Physical Activity Questionnaire; TUGT, Timed Up and Go test.
Discussion
To our knowledge, this is the first prospective cohort study of suburban-dwelling elderly Chinese individuals aged 60 years and older, to simultaneously include two critical physical metrics to predict hypertension. In our study, the prevalence of hypertension was 52.8% at baseline; after 1 year 26.0% (female = 25.8%, male = 26.8%) of individuals who did not have hypertension at baseline developed new onset hypertension. These findings are consistent with previous research that reported the prevalence of hypertension among rural-dwelling elderly individuals in China to be 51.4%15 and the incidence of hypertension to be 26.9% [16]. We found that participants with worse performance on the TUGT and the 4-m walking test had a higher risk of developing hypertension, whereas grip strength performance did not impact the development of new onset hypertension.
Better 4-m walking test performance is negatively associated with hypertension
In our study, the association between the 4-m walking test and hypertension was significant. People with subnormal walking speeds had a nearly 1.5-fold risk of developing hypertension. Some cross-sectional research [8] that has reported an inverse correlation between walking speed and hypertension. The previous longitudinal study by Dumurgier et al. [17] showed that slower walking speed resulted in a three-fold increased risk of cardiovascular disease death, but not just associated with hypertension. Our study goes even further by finding that decreased walking speed is an independent risk for hypertension in the elderly. The underlying mechanisms of how decreased walking speed predicts hypertension has yet to be explained. The positive association of hypertension with cerebral small vessel disease has been well established [18]. It is possible that slower walking speed results from cerebral small vessel microbleeds and infarcts [19,20], which results in decreased cerebral blood flow to motor areas of cerebral cortex [21].
Better Timed Up and Go test performance is associated with hypertension
After adjusting for many potential confounding factors, our study found that participants with longer TUGT times had an increased risk of developing hypertension. This finding is in line with a previous cross-sectional study [9] that found a significant association between TUGT performance and hypertension. However, our study reveals that a decline in mobility may precede the development of hypertension. This decline in mobility may be secondary to cerebral small vessel disease which compromises the microstructural integrity of the white matter and consequently negatively impacts the descending cortical spinal cord fibers [22]. The same disease process may also precipitate hypertension after worse mobility has already become evident.
Muscle strength is not associated with hypertension
Declining muscle strength has been associated with cardiovascular disease and the prevalence of hypertension [23] in several studies [10,11]. The mechanism of their association is still uncertain, it can be speculated that greater smooth muscle strength provides better protection for load-bearing elastic lamina and collagen fibers that takes dominant responsibility for BP changes [24]. However, our results showed no association between grip strength and hypertension in the older patients, a finding in line with a cohort study by Maslow et al. [25]. There are two possible explanations for these discrepant results. One possibility is that the present study’s average baseline BP was lower than that of the PURE study [10], suggesting that strength can only be predictive of hypertension after a certain average BP threshold has been reached. Another explanation is that our 1-year follow-up time was not long enough to show a possible predictive relationship between grip strength and hypertension. Nevertheless, 1 year was a sufficient time for the 4-m walking test and the TUGT to show predictive value, indicating that these two metrics are more sensitive than grip strength. By the way, the predictive mechanism of physical activity on hypertension may not be mediated by the variation of muscle strength.
Comorbidity status may be related to hypertension
Participants with diabetes, hyperlipidemia and stroke at baseline were more likely to develop hypertension. Studies have found that these diseases are often associated with decreased physical performance [26], but their temporal relationship remains unclear. It is possible that these diseases impair physical performance, which in turn leads to decreased physical activity, which itself precipitates the onset of hypertension.
Limitations
This study has several limitations. First, the study may suffer from a selection bias as there were participants who were unable or unwilling to finish the physical performance tests. Second, the follow-up time was short and thus the incidence of hypertension may have been underestimated. As a large country, China has marked regional differences and different populations. The extent of the research was limited to a small part of Chinese populations and no general conclusions can therefore be drawn. Thus, large-scale, multicentered prospective trials are needed to confirm the results of this study in the future. In the next study, we will increase the sample size and the region from which the participants are recruited to reduce error and improve the reliability of our data. Lastly, we hope to conduct future research to identify clinically meaningful cutoff points on physical metrics that can be used to screen elderly individuals for hypertension.
Summary
In conclusion, mobility, but not muscle strength, is independent risk factor for hypertension in suburban-dwelling elderly individuals. This study may have crucial relevance for hypertension screening and prevention.
Acknowledgements
This work was supported by the Nanjing World Digital Guide Instrument Co., LTD. (grant numbers 20170096).
Conflicts of interest
There are no conflicts of interest.
Footnotes
Yuewen Liu contributed equally to the writing of this article.
References
- 1.Williams B, Mancia G, Spiering W, Agabiti Rosei E, Azizi M, Burnier M, et al. ; Authors/Task Force Members:. 2018 ESC/ESH Guidelines for the management of arterial hypertension: The Task Force for the management of arterial hypertension of the European Society of Cardiology and the European Society of Hypertension: The Task Force for the management of arterial hypertension of the European Society of Cardiology and the European Society of Hypertension. J Hypertens 2018; 36:1953–2041. [DOI] [PubMed] [Google Scholar]
- 2.Lacey B, Lewington S, Clarke R, Kong XL, Chen Y, Guo Y, et al. Age-specific association between blood pressure and vascular and non-vascular chronic diseases in 0.5 million adults in China: a prospective cohort study. Lancet Global Health 2018; 6:e641–e649. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Beckett NS, Peters R, Fletcher AE, Staessen JA, Liu L, Dumitrascu D, et al. ; HYVET Study Group. Treatment of hypertension in patients 80 years of age or older. N Engl J Med 2008; 358:1887–1898. [DOI] [PubMed] [Google Scholar]
- 4.Guo C, Zeng Y, Chang LY, Yu Z, Bo Y, Lin C, et al. Independent and opposing associations of habitual exercise and chronic PM2.5 exposures on hypertension incidence. Circulation 2020; 142:645–656. [DOI] [PubMed] [Google Scholar]
- 5.Nascimento CMC, Cardoso JFZ, de Jesus ITM, de Souza Orlandi F, Costa-Guarisco LP, Gomes GAO, et al. Are body fat and inflammatory markers independently associated with age-related muscle changes? Clin Nutr 2021; 40:2009–2015. [DOI] [PubMed] [Google Scholar]
- 6.Mantel A, Trapuzzano A, Chizmar S, Haffke L, Dawson N. An investigation of the predictors of comfortable and fast gait speed in community-dwelling older adults. J Geriatr Phys Ther 2019; 42:E62–E68. [DOI] [PubMed] [Google Scholar]
- 7.Montero-Odasso M, Schapira M, Soriano ER, Varela M, Kaplan R, Camera LA, Mayorga LM. Gait velocity as a single predictor of adverse events in healthy seniors aged 75 years and older. J Gerontol A Biol Sci Med Sci 2005; 60:1304–1309. [DOI] [PubMed] [Google Scholar]
- 8.Figgins E, Choi YH, Speechley M, Montero-Odasso M. Associations between potentially modifiable and non-modifiable risk factors and gait speed in middle and older-aged adults: results from the Canadian Longitudinal Study on Aging. J Gerontol A Biol Sci Med Sci 2021. doi: 10.1093/gerona/glab008 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Ibrahim A, Singh DKA, Shahar S. ‘Timed Up and Go’ test: age, gender and cognitive impairment stratified normative values of older adults. PLoS One 2017; 12:e0185641. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Leong DP, Teo KK, Rangarajan S, Lopez-Jaramillo P, Avezum A, Jr, Orlandini A, et al. ; Prospective Urban Rural Epidemiology (PURE) Study investigators. Prognostic value of grip strength: findings from the Prospective Urban Rural Epidemiology (PURE) study. Lancet 2015; 386:266–273. [DOI] [PubMed] [Google Scholar]
- 11.Celis-Morales CA, Welsh P, Lyall DM, Steell L, Petermann F, Anderson J, 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. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Wang J, Sun W, Wells GA, Li Z, Li T, Wu J, et al. Differences in prevalence of hypertension and associated risk factors in urban and rural residents of the northeastern region of the People’s Republic of China: a cross-sectional study. PLoS One 2018; 13:e0195340. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Mohamed SF, Mutua MK, Wamai R, Wekesah F, Haregu T, Juma P, et al. Prevalence, awareness, treatment and control of hypertension and their determinants: results from a national survey in Kenya. BMC Public Health 2018; 18:1219. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL, Jr, et al. ; National Heart, Lung, and Blood Institute Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure; National High Blood Pressure Education Program Coordinating Committee. The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. JAMA 2003; 289:2560–2572. [DOI] [PubMed] [Google Scholar]
- 15.Wu L, He Y, Jiang B, Liu M, Wang J, Zhang D, et al. Association between sleep duration and the prevalence of hypertension in an elderly rural population of China. Sleep Med 2016; 27–28:92–98. [DOI] [PubMed] [Google Scholar]
- 16.Dauphinot V, Roche F, Kossovsky MP, Schott AM, Pichot V, Gaspoz JM, et al. C-reactive protein implications in new-onset hypertension in a healthy population initially aged 65 years: the Proof study. J Hypertens 2009; 27:736–743. [DOI] [PubMed] [Google Scholar]
- 17.Dumurgier J, Elbaz A, Ducimetière P, Tavernier B, Alpérovitch A, Tzourio C. Slow walking speed and cardiovascular death in well functioning older adults: prospective cohort study. BMJ 2009; 339:b4460. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Vermeer SE, Longstreth WT, Jr, Koudstaal PJ. Silent brain infarcts: a systematic review. Lancet Neurol 2007; 6:611–619. [DOI] [PubMed] [Google Scholar]
- 19.Pinter D, Ritchie SJ, Doubal F, Gattringer T, Morris Z, Bastin ME, et al. Impact of small vessel disease in the brain on gait and balance. Sci Rep 2017; 7:41637. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Stijntjes M, de Craen AJ, van der Grond J, Meskers CG, Slagboom PE, Maier AB. Cerebral microbleeds and lacunar infarcts are associated with walking speed independent of cognitive performance in middle-aged to older adults. Gerontology 2016; 62:500–507. [DOI] [PubMed] [Google Scholar]
- 21.Mignini F, Vitaioli L, Sabbatini M, Tomassoni D, Amenta F. The cerebral cortex of spontaneously hypertensive rats: a quantitative microanatomical study. Clin Exp Hypertens 2004; 26:287–303. [DOI] [PubMed] [Google Scholar]
- 22.Batty NJ, Torres-Espin A, Vavrek R, Raposo P, Fouad K. Single-session cortical electrical stimulation enhances the efficacy of rehabilitative motor training after spinal cord injury in rats. Exp Neurol 2019; 324:113136. [DOI] [PubMed] [Google Scholar]
- 23.Zhang X, Huang L, Peng X, Xie Y, Bao X, Huang J, Wang P. Association of handgrip strength with hypertension among middle-aged and elderly people in Southern China: a cross-sectional study. Clin Exp Hypertens 2020; 42:190–196. [DOI] [PubMed] [Google Scholar]
- 24.Souza RR, de Franca E, Madureira D, Pontes CCR, Santana JO, Caperuto EC. Resistance training improves aortic structure in Wistar rats. Braz J Phys Ther 2017; 21:244–250. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Maslow AL, Sui X, Colabianchi N, Hussey J, Blair SN. Muscular strength and incident hypertension in normotensive and prehypertensive men. Med Sci Sports Exerc 2010; 42:288–295. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Zhang W, Yang X, Han P, Ma Y, Fu L, Jia L, et al. Risk factors for developing diabetes after 3 years among community-dwelling elderly with impaired fasting glucose. J Diabetes 2018; 11:107–114. [DOI] [PubMed] [Google Scholar]