Abstract
Background
Upper and lower extremity muscle strength can be used to predict health outcomes. However, the difference between the relation of upper extremity muscle and of lower extremity muscle with physiological factors is unclear. This study aimed to evaluate the association between physiological data and muscle strength, measured using grip and leg extension strength, among Japanese adults.
Methods
We conducted a cross-sectional study of 2,861 men and 6,717 women aged ≥ 20 years living in Miyagi Prefecture, Japan. Grip strength was measured using a dynamometer. Leg extension strength was measured using a hydraulic isokinetic leg press machine. Anthropometry and physiological data, including blood pressure, calcaneal ultrasound bone status, pulmonary function, carotid echography, and blood information, were assessed. We used a general linear model adjusted for age, body composition, and smoking status to evaluate the association between muscle strength and physiological factors.
Results
Grip and leg extension strength were positively associated with bone area ratio, vital capacity, forced vital capacity, forced expiratory volume in one second, and estimated glomerular filtration rate, and negatively associated with waist circumference and percentage body fat mass in both the sexes. Diastolic blood pressure was positively associated with grip strength in both the sexes and leg extension strength in men, but not women. High-density lipoprotein cholesterol and red blood cell counts were positively associated with grip and leg extension strength in women, but not men. In both the sexes, pulse rate, total cholesterol, and uric acid were consistently associated with only leg extension strength, but not grip strength. In women, glycated hemoglobin demonstrated negative and positive associations with grip and leg extension strength, respectively.
Conclusions
Grip and leg extension strength demonstrated similar associations with anthropometry, pulmonary function, and estimated glomerular filtration rate, but the associations with the other factors were not always consistent.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12889-024-18244-z.
Keywords: General population, Grip strength, Leg extension strength, Muscle strength, Physiological data
Background
Low muscle strength is associated with successful aging [1], mortality [2–7],and diseases, such as cancer [2, 3], cardiovascular disease [2, 3], respiratory disease [2]. However, the reason for this association remains unclear. The causal association between low muscle strength and health outcomes necessitates the investigation of the underlying factors. Moreover, a meta-analysis (comprising 38 studies with 1,907,580 participants) published in 2018 indicated that upper and lower limb muscular strength was associated with the risk of mortality in adults, regardless of age or follow-up period [8]. Moreover, Sanderson et al. reported that combined measures of grip strength and lower limb indicators better predict survival than grip strength alone [5]. Therefore, mechanisms affecting the association between low muscle strength and health outcomes might differ between the upper and lower extremity muscle strength.
Studies have reported on associations between muscle strength and physiological parameters in large populations [9–17]. A large population-based cross-sectional study in Switzerland showed an association between muscle strength and cardiovascular risk markers such as waist circumference (WC) and fat mass [9]. Moreover, muscle strength was associated with cardiovascular risk factors, including blood pressure [10, 13], diabetes [10, 11, 16], lipid makers [10, 13], and atherosclerosis [14, 15]. Furthermore, besides cardiovascular risk factors, muscle strength is also associated with anemia [12] and pulmonary function [17].
However, most studies have only emphasized grip strength as a measure of muscle strength. Furthermore, the association between physiological data and muscle strength, as measured using grip and leg extension strength, has not been widely investigated in the general population. To investigate complementary mechanisms underlying the association between muscle strength and health outcomes, it is necessary to clarify the differences in the associations among upper and lower extremity muscle strength and physiological data. Therefore, clarifying the significance of each muscle strength may indicate mortality and disease development and help decide appropriate interventions.
Thus, this study aimed to assess the association between physiological data and muscle strength, measured using grip and leg extension strength, in a large community-based sample aged 20–89 years.
Methods
Participants
This cross-sectional study used data from the Tohoku Medical Megabank Community-Based Cohort Study, a population-based prospective cohort study of individuals aged ≥ 20 years in Miyagi and Iwate Prefectures, Japan [18–36]. Details of recruitment have been described previously [18]. Participants underwent several physiological measurements, such as grip and leg extension strength. Moreover, we considered it appropriate to use blood data collected at the same time. Therefore, we used participants from a type 2 survey performed in Miyagi.
We excluded 13,855 participants in the type 2 survey who withdrew consent or failed to return the self-reported questionnaire (N = 196). Considering the impact of the association between muscle strength and physiological data, participants with a self-reported history of cancer (N = 1,032), diabetes mellitus (N = 482), dementia (N = 20), neurological disorder (N = 14), stroke (N = 188), heart disease (N = 270), heart failure (N = 15), chronic obstructive pulmonary disease (N = 28), muscle/connective tissue disease (N = 737), hemodialysis (N = 2), or congenital disease (N = 142) were excluded. Furthermore, participants without information on height (N = 78), weight (N = 8), grip strength (N = 71), or leg extension strength (N = 994) were excluded. Finally, data from 9,578 participants were analyzed (Fig. 1).
Fig. 1.
Flowchart of participant selection
Muscle strength measurement
Grip strength was measured using a dynamometer (YD 110 kg; Tsutsumi Co., Ltd., Tokyo, Japan). The participants were instructed to stand with their arms down along their body and hold the dynamometer. Then, they squeezed the handle of the dynamometer as hard as possible. The participants performed the test twice for each hand alternately, and the highest value was used [6, 14]. We measured leg extension strength using a hydraulic isokinetic leg-press machine (T.K.K.1865; Takei Scientific Instruments Co., Ltd., Niigata, Japan). The participants sat on the seat of the leg-press machine in a 90° knee joint position and had belts fixed on their legs and waist. Subsequently, we instructed them to grip the bars and kick as fast as possible from the 90° knee joint position while keeping their legs extended. More than one measurement (up to five) was performed, and the maximum value was used for the analysis.
Other data
We assessed several physiological data such as cardiovascular risk factors, pulmonary function, and renal function. Alcohol drinking, smoking, and educational status were assessed using a self-administered questionnaire. Alcohol drinking status was classified as “never-drinker” (those who selected “little or no drinking” or “constitutionally unable to drink”), “ex-drinker (those who selected “no longer”), “current-drinker” (those who selected “drinking”), or “unknown” (those who did not respond to the question). Smoking status was classified as “never-smoker” (those who smoked < 100 cigarettes in their lifetime), “ex-smoker” (those who smoked ≥ 100 cigarettes in their lifetime, but answered “current non-smoker” in the questionnaire), “current-smoker” (those who smoked ≥ 100 cigarettes in their lifetime and answered “current smoker” in the questionnaire), or “unknown” (those who did not answer the question). Education status was classified as “<12 years” (those who selected “elementary school or junior high school”), “12 years” (those who selected “high school”), “>12 years” (those who selected “vocational school,” “junior college or technical college,” “university,” or “graduate school”), “others” (those who selected “other”), or “unknown” (those who did not answer the question).
Participant height was measured to the nearest 0.1 cm using a stadiometer (AD-6400; A&D Co., Ltd.). Weight and percentage of body fat mass were measured using a body composition analyzer (InBody720; Biospace Co., Ltd., Seoul, Korea). The weight was measured in increments of 0.1 kg, and 1.0 kg was subtracted to account for the weight of the participant’s clothing. Body mass index (BMI) was calculated as the weight divided by the height squared. WC was measured at the level of the umbilicus using a tape measure.
Blood pressure and pulse rate were measured twice in the right upper arm using a digital automatic blood pressure monitor (HEM-9000AI; Omron Healthcare Co., Ltd., Kyoto, Japan) after the participants rested in a sitting position for ≥ 2 min, and the average value was used. The number of steps per day was counted using a pedometer (HJ-205IT; Omron Healthcare Co., Ltd., Kyoto, Japan). Participants were instructed to wear a pedometer throughout the day for 2 weeks, except while bathing and sleeping. Bone area ratio was assessed only once in the sitting position using an ultrasound bone densitometer (UBM-3000; Ishikawa Seisakusho, Ltd., Ishikawa, Japan) on the right calcaneus and was used as an indicator of the bone status [37, 38]. Pulmonary functions, such as vital capacity (VC), forced vital capacity (FVC), forced expiratory volume in 1 s (FEV1), and forced expiratory volume in 1 s as a percentage of the forced vital capacity (FEV1/FVC), were measured in the sitting position using a spirometer (HI-801; Chest M.I., Inc., Tokyo, Japan). Carotid intima-media thickness (CIMT) was measured using ultrasonography (GM-72P00A; Panasonic Healthcare Co., Ltd., Tokyo, Japan) and calculated as the CIMT measurement with the carotid plaque excluded. We used the mean right CIMT values for the analysis employing a software program that provides the mean thickness of the IMT complex on the common carotid artery [39].
Blood samples were collected under non-fasting conditions. The details of the measurement methods have been described previously [18]. We estimated the glomerular filtration rate (eGFR) from the serum cystatin C levels using the following equation developed for the Japanese population [40, 41]:
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Statistical analysis
Grip and leg extension strength were divided into quartiles, and participant characteristics were compared using analysis of variance (ANOVA) for continuous variables and chi-square test for categorical variables. We used a general linear model to evaluate whether the muscle strength, as measured using the grip or leg extension strength, was associated with the physiological data. The results are expressed as multivariate-adjusted coefficients. General linear models were adjusted for age (continuous), smoking status (never smoker/ex-smoker/current smoker/unknown), and BMI. Weight (continuous) was used as an adjustment factor instead of the BMI [9] when using WC as the explanatory variable. Similarly, considering that pulmonary function is affected by age and height [42], the height (continuous) was used as an adjustment factor instead of the BMI, when using the VC, FVC, FEV1, and FEV1/FVC as the explanatory variables. We also performed subgroup analysis according to age (< 65, 65–74, and > 74 years).
The associations between grip strength and physiological data and leg strength and physiological data were consistent when the coefficients for the grip and leg extension strength were significantly positive or negative. A statistically significant association with grip or leg extension strength, but not with the other factors, was defined as a different association. Furthermore, if one of the regression coefficients for grip and leg extension strength was significantly positive and the other was significantly negative, the associations between the grip or leg extension strength and physiological data were different. Statistical significance was set at p < 0.05. All analyses were performed using the Statistical Analysis System software, version 9.4 for Windows (SAS Inc., Cary, NC, USA).
Results
Figure 2 depicts the age-dependent changes in muscle strength measured using grip or leg extension strength. Age was inversely associated with grip and leg extension strength. Men had higher grip and leg extension strength than women; however, the difference decreased after 50 years of age.
Fig. 2.
Age-dependent changes in the (a) grip strength, (b) leg extension strength and (c) step count. Error bar plot of grip and leg extension strength by sex. Error bars represent 95% confidence intervals for the means
Association between grip strength and physiological data
Table 1 summarizes the participant characteristics according to the grip strength quartiles. In men, physiological data, excluding pulse rate, showed differences between the grip strength quartile groups. In women, physiological data, excluding diastolic blood pressure and high-density lipoprotein (HDL) cholesterol, showed differences between the grip strength quartile groups.
Table 1.
Characteristics of the participants according to the quartile of relative grip strength
| Quartile of grip strength (MEN) | Quartile of grip strength (WOMEN) | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Q1 < 37 kg |
Q2 37–41 kg |
Q3 42–47 kg |
Q4 > 47 kg |
p-value | Q1 < 23 kg |
Q2 23–26 kg |
Q3 27–29 kg |
Q4 > 29 kg |
p-value | |
| Age, years | 64.2 (14.0) | 60.1 (13.4) | 55.5 (13.1) | 48.9 (13.0) | < 0.0001 | 59.0 (13.3) | 54.7 (13.2) | 51.7 (12.9) | 47.3 (12.9) | < 0.0001 |
| LES, W |
411.3 (149.9) |
491.9 (153.2) |
569.2 (163.2) | 677.9 (201.1) | < 0.0001 | 241.3 (84.3) | 274.9 (87.9) | 302.7 (96.2) | 339.6 (109.5) | < 0.0001 |
| Alcohol drinking status, n (%) | 0.5614 | < 0.0001 | ||||||||
| Current-drinker | 649 (77.5) | 481 (80.3) | 604 (80.2) | 544 (81.0) | 922 (44.1) | 835 (48.4) | 727 (49.6) | 760 (53.0) | ||
| Ex-drinker | 30 (3.6) | 16 (2.7) | 16 (2.1) | 16 (2.4) | 31 (1.5) | 21 (1.2) | 33 (2.3) | 19 (1.3) | ||
| Never-drinker | 157 (18.8) | 102 (17.0) | 133 (17.7) | 112 (16.7) | 1138(54.4) | 868 (50.3) | 706 (48.2) | 653 (45.6) | ||
| Unknown | 1 (0.1) | 0 (0.0) | 0 (0.0) | 0 (0.0) | 2 (0.1) | 1 (0.1) | 0 (0.0) | 1 (0.1) | ||
| Smoking status, n (%) | < 0.0001 | < 0.0001 | ||||||||
| Current-smoker | 158 (18.9) | 110 (18.4) | 176 (23.4) | 231 (34.4) | 150 (7.2) | 111 (6.4) | 146 (10.0) | 148 (10.3) | ||
| Ex-smoker | 387 (46.2) | 323 (53.9) | 383 (50.9) | 266 (39.6) | 246 (11.8) | 225 (13.0) | 204 (13.9) | 282 (19.7) | ||
| Never-smoker | 290 (34.6) | 166 (27.7) | 193 (25.6) | 174 (25.9) | 1691(80.8) | 1387(80.4) | 1112(75.9) | 1001 (69.9) | ||
| Unknown | 2 (0.2) | 0 (0.0) | 1 (0.1) | 1 (0.1) | 6 (0.3) | 2 (0.1) | 4 (0.3) | 2 (0.1) | ||
| Education status, n (%) | 0.0002 | < 0.0001 | ||||||||
| <12 years | 94 (11.2) | 45 (7.5) | 55 (7.3) | 45 (6.7) | 155 (7.4) | 83 (4.8) | 53 (3.6) | 32 (2.2) | ||
| 12 years | 396 (47.3) | 243 (40.6) | 343 (45.6) | 344 (51.2) | 1084 (51.8) | 874 (50.7) | 669 (45.6) | 638 (44.5) | ||
| >12 years | 332 (39.7) | 297 (49.6) | 349 (46.3) | 276 (41.1) | 837 (40.0) | 757 (43.9) | 731 (49.9) | 750 (52.3) | ||
| Others | 6 (0.7) | 5 (0.8) | 3 (0.4) | 2 (0.3) | 6 (0.3) | 4 (0.2) | 5 (0.3) | 4 (0.3) | ||
| Unknown | 9 (1.1) | 9 (1.5) | 3 (0.4) | 5 (0.7) | 11 (0.5) | 7 (0.4) | 8 (0.5) | 9 (0.6) | ||
| Anthropometry | ||||||||||
| Height, cm | 164.7 (6.0) | 167.4 (5.6) | 169.2 (5.9) | 171.9 (5.6) | < 0.0001 | 153.3 (5.4) | 156.0 (5.1) | 157.4 (5.0) | 159.8 (5.1) | < 0.0001 |
| Weight, kg | 62.7 (9.0) | 65.2 (8.5) | 68.4 (9.5) | 73.5 (11.5) | < 0.0001 | 51.2 (7.7) | 53.6 (7.8) | 54.8 (8.4) | 58.0 (9.9) | < 0.0001 |
| BMI, kg/cm2 | 23.1 (2.9) | 23.3 (2.8) | 23.9 (3) | 24.9 (3.6) | < 0.0001 | 21.8 (3.2) | 22.0 (3.2) | 22.1 (3.4) | 22.7 (3.8) | < 0.0001 |
| WC, cm | 84.9 (8.3) | 85.1 (7.9) | 86.1 (8.4) | 88.2 (9.6) | < 0.0001 | 80.6 (9.2) | 81.1 (9.1) | 80.6 (9.3) | 82.0 (10.1) | < 0.0001 |
| %BFM, % | 24.7 (6.2) | 23.1 (5.8) | 22.9 (6.2) | 22.4 (6.4) | < 0.0001 | 31.2 (7.0) | 30.5 (7.0) | 29.5 (7.0) | 29.2 (7.5) | < 0.0001 |
| Bone area ratio, % | 28.0 (3.8) | 28.3 (3.6) | 28.9 (3.6) | 29.3 (3.7) | < 0.0001 | 27.4 (4.0) | 28.2 (4.1) | 28.7 (4.2) | 29.8 (4.4) | < 0.0001 |
| Pulmonary function | ||||||||||
| VC, L | 3.7 (0.6) | 4.0 (0.6) | 4.2 (0.6) | 4.5 (0.7) | < 0.0001 | 2.7 (0.4) | 2.9 (0.4) | 3.0 (0.4) | 3.3 (0.5) | < 0.0001 |
| FVC, L | 3.5 (0.7) | 3.8 (0.6) | 4.0 (0.6) | 4.4 (0.7) | < 0.0001 | 2.6 (0.5) | 2.8 (0.5) | 3.0 (0.4) | 3.2 (0.5) | < 0.0001 |
| FEV1, L | 2.8 (0.6) | 3.0 (0.6) | 3.2 (0.6) | 3.5 (0.6) | < 0.0001 | 2.1 (0.4) | 2.3 (0.4) | 2.4 (0.4) | 2.6 (0.4) | < 0.0001 |
| FEV1/FVC, % | 78.4 (7.5) | 79.2 (7.3) | 79.3 (6.4) | 81 (5.7) | < 0.0001 | 81.1 (6.0) | 82.6 (5.8) | 81.9 (5.8) | 82.6 (5.7) | < 0.0001 |
| Blood pressure | ||||||||||
| SBP, mmHg | 137.2 (17.7) | 134.7 (17.7) | 133.9 (16.7) | 132.2 (15.3) | < 0.0001 | 127.6 (18.8) | 126.4 (18.8) | 124.2 (18.1) | 122.7 (17.4) | < 0.0001 |
| DBP, mmHg | 80.6 (10.8) | 81.8 (11.2) | 82.9 (10.8) | 83.2 (11.3) | < 0.0001 | 76.8 (10.5) | 77.2 (11.0) | 76.4 (10.6) | 77.0 (11.1) | 0.2382 |
| Pulse rate, beat/min | 65.3 (11.3) | 64.7 (10.2) | 64.6 (9.8) | 65.8 (9.8) | 0.1357 | 67.0 (9.5) | 66.2 (9.1) | 66.7 (9.4) | 67.2 (9.8) | 0.0092 |
| CIMT, mm | 0.7 (0.2) | 0.6 (0.1) | 0.6 (0.1) | 0.6 (0.1) | < 0.0001 | 0.6 (0.1) | 0.6 (0.1) | 0.6 (0.1) | 0.5 (0.1) | < 0.0001 |
| Lipid markers | ||||||||||
| TC, mg/dL | 201.6 (33.3) | 203.0 (33.6) | 206.7 (37.6) | 203.2 (34.4) | 0.0065 | 215.0 (34.5) | 215.0 (37.1) | 211.4 (36.4) | 205.9 (35.3) | < 0.0001 |
| Triglycerides, mg/dL | 114.1 (72.1) | 123.2 (100.5) | 128.8 (126.8) | 140.8 (105.5) | < 0.0001 | 96.0 (58.5) | 92.0 (72.1) | 92.6 (71.1) | 86.7 (56.4) | 0.0005 |
| HDL-C, mg/dL | 58.0 (15.6) | 57.9 (14.5) | 57.6 (15.2) | 55.1 (14.1) | 0.0005 | 67.6 (15.8) | 68.5 (15.7) | 67.8 (16.4) | 67.5 (16.6) | 0.3437 |
| Glucometabolic markers | ||||||||||
| HbA1c, % | 5.6 (0.5) | 5.5 (0.5) | 5.5 (0.4) | 5.4 (0.5) | < 0.0001 | 5.5 (0.4) | 5.4 (0.4) | 5.4 (0.4) | 5.4 (0.4) | < 0.0001 |
| Glucose, mg/dL | 91.8 (17.6) | 90.5 (13.9) | 89.2 (15.6) | 89.3 (14.7) | 0.0030 | 86.7 (12.9) | 85.5 (11.7) | 85.0 (12.2) | 84.6 (11.1) | < 0.0001 |
| eGFR, ml/min/1.73 m2 | 91.4 (21.7) | 97.4 (19.2) | 102.9 (19.7) | 108.5 (19.8) | < 0.0001 | 102.2 (21.8) | 107.1 (22.6) | 111.3 (22.8) | 115.9 (22.5) | < 0.0001 |
| Uric acid, mg/dL | 5.8 (1.2) | 5.9 (1.2) | 5.9 (1.2) | 6.2 (1.3) | < 0.0001 | 4.5 (1.0) | 4.5 (1.0) | 4.4 (1.0) | 4.4 (1.0) | 0.0552 |
| Red blood cells count, 104/µL | 470.8 (42.1) | 474.5 (40.8) | 482.1 (38.7) | 491.8 (36.1) | < 0.0001 | 439.8 (32.6) | 442.8 (31.9) | 441.6 (32.6) | 445.2 (32.1) | < 0.0001 |
| Hemoglobin, g/dL | 14.8 (1.3) | 14.9 (1.1) | 15.0 (1.1) | 15.3 (1.0) | < 0.0001 | 13.3 (1.1) | 13.3 (1.0) | 13.2 (1.1) | 13.2 (1.2) | 0.0017 |
| Hematocrit, % | 44.4 (3.4) | 44.7 (3.1) | 45.1 (3.0) | 45.7 (2.7) | < 0.0001 | 40.7 (2.9) | 40.8 (2.7) | 40.5 (3.0) | 40.5 (3.0) | 0.0028 |
Data are expressed as mean (standard deviation) for continuous variables and number (percentage) for categorical variables
LES: leg extension strength; BMI: body mass index; WC: waist circumference; %BFM; percentage body fat mass VC: vital capacity; FVC: forced vital capacity; FEV1: forced expiratory volume in 1 s; SBP: systolic blood pressure; DBP: diastolic blood pressure; TC: total cholesterol; CIMT: carotid intima-media thickness; HDL-C: high-density lipoprotein cholesterol; HbA1c: hemoglobin A1c; eGFR: estimated glomerular filtration rate; and Q: quartile
The p-value was obtained using ANOVA for continuous variables and chi-square for categorical variables of proportion
After adjusting for age, body composition, and smoking status, grip strength was positively associated with bone area ratio, VC, FVC, FEV1, diastolic blood pressure, and eGFR, and negatively associated with WC, percentage body fat mass, and hemoglobinA1c (HbA1c) in both the sexes (Table 2). In men, grip strength was negatively associated with CIMT. In women, it was positively associated with systolic blood pressure, high-density lipoprotein cholesterol levels, and red blood cell count.
Table 2.
Association between grip strength and physiological data adjusted for age, body composition, and smoking
| Men | Women | |||||
|---|---|---|---|---|---|---|
| N | β | p-value | N | β | p-value | |
| Anthropometry | ||||||
| WCa, cm | 2855 | –0.407 | < 0.0001 | 6701 | –0.157 | < 0.0001 |
| %BFM, % | 2851 | –0.770 | < 0.0001 | 6704 | –0.391 | < 0.0001 |
| Bone area ratio, % | 2858 | 0.121 | 0.0007 | 6713 | 0.092 | < 0.0001 |
| Pulmonary function | ||||||
| VCb, L | 2716 | 2.668 | < 0.0001 | 6375 | 2.535 | < 0.0001 |
| FVCb, L | 2708 | 2.345 | < 0.0001 | 6350 | 2.513 | < 0.0001 |
| FEV1b, L | 2708 | 2.665 | < 0.0001 | 6350 | 2.705 | < 0.0001 |
| FEV1/FVCb, % | 2708 | 0.033 | 0.1078 | 6350 | 0.000 | 0.9851 |
| Blood pressure | ||||||
| SBP, mmHg | 2857 | 0.011 | 0.1738 | 6705 | 0.013 | 0.0001 |
| DBP, mmHg | 2857 | 0.053 | < 0.0001 | 6705 | 0.019 | 0.0003 |
| Pulse rate, beat/min | 2857 | –0.023 | 0.0666 | 6705 | –0.005 | 0.4072 |
| CIMT, mm | 2845 | –2.401 | 0.0216 | 6677 | 0.655 | 0.2269 |
| Lipid markers | ||||||
| TC, mg/dL | 2858 | 0.004 | 0.3362 | 6710 | 0.003 | 0.0832 |
| Triglycerides, mg/dL | 2858 | 0.001 | 0.4133 | 6710 | –0.002 | 0.0545 |
| HDL-C, mg/dL | 2858 | 0.015 | 0.0911 | 6710 | 0.009 | 0.0123 |
| Glucometabolic markers | ||||||
| HbA1c, % | 2856 | –0.730 | 0.0099 | 6701 | –0.385 | 0.0095 |
| Glucose, mg/dL | 2856 | –0.004 | 0.6317 | 6701 | –0.001 | 0.8268 |
| eGFR, ml/min/1.73 m2 | 2858 | 0.044 | < 0.0001 | 6710 | 0.009 | 0.0085 |
| Uric acid, mg/dL | 2858 | 0.118 | 0.2730 | 6709 | –0.054 | 0.3447 |
| Red blood cell count, 104/µL | 2858 | 0.001 | 0.7214 | 6708 | 0.004 | 0.0224 |
| Hemoglobin, g/dL | 2858 | 0.078 | 0.5088 | 6708 | 0.052 | 0.2927 |
| Hematocrit, % | 2858 | 0.046 | 0.2957 | 6708 | 0.030 | 0.1103 |
The general linear model was adjusted for age, smoking status, and body mass index
aAdjusted for weight instead of body mass index
bAdjusted for height instead of body mass index
WC: waist circumference; %BFM: percentage body fat mass; VC: vital capacity; FVC: forced vital capacity; FEV1: forced expiratory volume in 1 s; SBP: systolic blood pressure; DBP: diastolic blood pressure; CIMT: carotid intima-media thickness; TC: total cholesterol; HDL-C: high-density lipoprotein cholesterol; HbA1c: hemoglobin A1c; and eGFR: estimated glomerular filtration rate
Association between leg extension strength and physiological data
Table 3 summarizes the participant characteristics according to the quartiles of the leg extension strength. In men, physiological data, excluding WC and HDL cholesterol, showed differences between the leg extension strength quartile groups. In women, physiological data, excluding diastolic blood pressure, uric acid, hemoglobin, and hematocrit, showed differences between the leg extension strength quartiles groups.
Table 3.
Characteristics of the participants according to the quartile of relative leg extension strength
| Quartile of leg extension strength (MEN) | Quartile of leg extension strength (WOMEN) | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Q1 < 393 W |
Q2 394–509 W |
Q3 510–639 W |
Q4 > 640 W |
p-value | Q1 < 214 W |
Q2 215–276 W |
Q3 277–347 W |
Q4 > 348 W |
p-value | |
| Age, years | 65.7 (12.9) | 61.4 (12.5) | 55.9 (13.1) | 46.6 (12.4) | < 0.0001 | 56.6 (14.8) | 55.5 (13.4) | 53.8 (12.7) | 49.3 (12.2) | < 0.0001 |
| GS, kg | 36.7 (6.7) | 40.6 (6.5) | 43.2 (6.2) | 47.6 (7.5) | < 0.0001 | 23.8 (4.3) | 25.2 (4.3) | 26.1 (4.2) | 28.3 (4.5) | < 0.0001 |
| Alcohol drinking status, n (%) | 0.0036 | < 0.0001 | ||||||||
| Current-drinker | 540 (75.4) | 570 (79.4) | 582 (81.4) | 586 (82.3) | 719 (42.5) | 771 (45.5) | 834 (50.2) | 920 (55.0) | ||
| Ex-drinker | 32 (4.5) | 16 (2.2) | 21 (2.9) | 9 (1.3) | 27 (1.6) | 24 (1.4) | 21 (1.3) | 32 (1.9) | ||
| Never-drinker | 143 (20.0) | 132 (18.4) | 112 (15.7) | 117 (16.4) | 944 (55.8) | 896 (52.9) | 805 (48.5) | 720 (43.1) | ||
| Unknown | 1 (0.1) | 0 (0) | 0 (0) | 0 (0) | 1 (0.1) | 2 (0.1) | 1 (0.1) | 0 (0) | ||
| Smoking status, n (%) | < 0.0001 | < 0.0001 | ||||||||
| Current-smoker | 128 (17.9) | 147 (20.5) | 177 (24.8) | 223 (31.3) | 139 (8.2) | 123 (7.3) | 127 (7.6) | 166 (9.9) | ||
| Ex-smoker | 349 (48.7) | 358 (49.9) | 364 (50.9) | 288 (40.4) | 184 (10.9) | 212 (12.5) | 262 (15.8) | 299 (17.9) | ||
| Never-smoker | 237 (33.1) | 211 (29.4) | 174 (24.3) | 201 (28.2) | 1364 (80.7) | 1355 (80.0) | 1270 (76.5) | 1202 (71.9) | ||
| Unknown | 2 (0.3) | 2 (0.3) | 0 (0) | 0 (0) | 4 (0.2) | 3 (0.2) | 2 (0.1) | 5 (0.3) | ||
| Education status, n (%) | < 0.0001 | < 0.0001 | ||||||||
| <12 years | 111 (15.5) | 54 (7.5) | 45 (6.3) | 29 (4.1) | 150 (8.9) | 83 (4.9) | 57 (3.4) | 33 (2) | ||
| 12 years | 362 (50.6) | 354 (49.3) | 321 (44.9) | 289 (40.6) | 867 (51.3) | 846 (50.0) | 787 (47.4) | 765 (45.8) | ||
| >12 years | 229 (32.0) | 299 (41.6) | 335 (46.9) | 391 (54.9) | 653 (38.6) | 751 (44.4) | 809 (48.7) | 862 (51.6) | ||
| Others | 5 (0.7) | 3 (0.4) | 7 (1.0) | 1 (0.1) | 7 (0.4) | 2 (0.1) | 5 (0.3) | 5 (0.3) | ||
| Unknown | 9 (1.3) | 8 (1.1) | 7 (1.0) | 2 (0.3) | 14 (0.8) | 11 (0.6) | 3 (0.2) | 7 (0.4) | ||
| Anthropometry | ||||||||||
| Height, cm | 164.8 (6) | 166.8 (5.8) | 168.8 (5.7) | 172.1 (5.6) | < 0.0001 | 154.2 (5.8) | 155.6 (5.4) | 156.6 (5.3) | 158.6 (5.3) | < 0.0001 |
| Weight, kg | 63.6 (10.5) | 65.6 (9.8) | 67.8 (9.4) | 72.1 (10.4) | < 0.0001 | 53.0 (9.0) | 53.5 (8.7) | 53.8 (8.4) | 55.9 (8.5) | < 0.0001 |
| BMI, kg/cm2 | 23.4 (3.4) | 23.5 (3.0) | 23.8 (3.0) | 24.3 (3.1) | < 0.0001 | 22.3 (3.6) | 22.1 (3.4) | 21.9 (3.3) | 22.2 (3.2) | 0.0018 |
| WC, cm | 85.6 (9.3) | 85.6 (8.3) | 86.1 (8.2) | 86.7 (8.7) | 0.0660 | 81.4 (9.8) | 81.1 (9.3) | 80.6 (9.3) | 80.9 (9.1) | 0.0297 |
| %BFM, % | 24.9 (6.4) | 23.4 (6.0) | 23.2 (6.1) | 21.9 (6.1) | < 0.0001 | 31.2 (7.4) | 30.6 (7.1) | 29.8 (7.1) | 29.3 (6.9) | < 0.0001 |
| Bone area ratio, % | 27.7 (3.6) | 28.2 (3.7) | 28.7 (3.7) | 29.7 (3.9) | < 0.0001 | 27.8 (4.2) | 28.0 (4.2) | 28.4 (4.1) | 29.4 (4.3) | < 0.0001 |
| Pulmonary function | ||||||||||
| VC, L | 3.6 (0.6) | 3.9 (0.6) | 4.1 (0.6) | 4.6 (0.6) | < 0.0001 | 2.7 (0.5) | 2.9 (0.5) | 3.0 (0.5) | 3.2 (0.5) | < 0.0001 |
| FVC, L | 3.4 (0.6) | 3.8 (0.6) | 4.0 (0.6) | 4.4 (0.6) | < 0.0001 | 2.7 (0.5) | 2.8 (0.5) | 2.9 (0.5) | 3.1 (0.5) | < 0.0001 |
| FEV1, L | 2.7 (0.6) | 3.0 (0.6) | 3.2 (0.6) | 3.6 (0.6) | < 0.0001 | 2.2 (0.5) | 2.3 (0.4) | 2.4 (0.4) | 2.5 (0.5) | < 0.0001 |
| FEV1/FVC, % | 78.5 (7.5) | 78.6 (7.6) | 79.8 (6.4) | 80.8 (5.7) | < 0.0001 | 81.4 (6.2) | 81.7 (5.9) | 81.6 (5.7) | 82.2 (5.8) | 0.0018 |
| Blood pressure | ||||||||||
| SBP, mmHg | 138.6 (18.2) | 135.3 (16.7) | 134.1 (16.9) | 130.6 (15.0) | < 0.0001 | 127.4 (18.7) | 127.2 (18.5) | 125.1 (18.3) | 122.3 (17.9) | < 0.0001 |
| DBP, mmHg | 80.7 (11.1) | 81.8 (10.9) | 83.3 (11.1) | 82.4 (11.0) | 0.0003 | 77.0 (10.6) | 77.1 (10.6) | 77.0 (10.8) | 76.3 (11.1) | 0.0740 |
| Pulse rate, beat/min | 65.8 (11.2) | 64.0 (10.1) | 65.4 (10.2) | 65.3 (9.9) | 0.0064 | 67.5 (9.5) | 66.7 (9.3) | 66.6 (9.4) | 66.4 (9.5) | 0.0047 |
| CIMT, mm | 0.7 (0.2) | 0.7 (0.1) | 0.6 (0.1) | 0.6 (0.1) | < 0.0001 | 0.6 (0.1) | 0.6 (0.1) | 0.6 (0.1) | 0.5 (0.1) | < 0.0001 |
| Lipid markers | ||||||||||
| TC, mg/dL | 199.5 (32.5) | 203.9 (33.6) | 206.8 (36.8) | 205.0 (36.0) | 0.0007 | 211.4 (35.3) | 213.3 (35.9) | 214.8 (35.9) | 209.6 (36.5) | 0.0004 |
| Triglycerides, mg/dL | 117.3 (81.0) | 123.2 (91.6) | 128.3 (116.7) | 135.9 (116.5) | 0.0027 | 95.0 (55.6) | 95.2 (59.2) | 92.1 (83.4) | 86.7 (56.6) | 0.0002 |
| HDL-C, mg/dL | 57.6 (15.3) | 57.7 (15.5) | 56.9 (14.1) | 56.7 (15.0) | 0.4408 | 66.3 (15.9) | 67.4 (15.6) | 69.0 (16.1) | 68.8 (16.5) | < 0.0001 |
| Glucometabolic markers | ||||||||||
| HbA1c, % | 5.6 (0.5) | 5.5 (0.5) | 5.5 (0.5) | 5.4 (0.4) | < 0.0001 | 5.4 (0.4) | 5.4 (0.4) | 5.4 (0.4) | 5.4 (0.3) | < 0.0001 |
| Glucose, mg/dL | 92.9 (18.5) | 90.6 (14.7) | 89.9 (16.0) | 87.8 (12.7) | < 0.0001 | 87.3 (14.0) | 85.7 (12.2) | 85.2 (11.3) | 84.0 (10.2) | < 0.0001 |
| eGFR, ml/min/1.73 m2 | 90 (21.3) | 95.6 (19.6) | 102.6 (19.7) | 110.8 (18.3) | < 0.0001 | 103.9 (24.0) | 106.7 (22.4) | 108.6 (21.9) | 114.3 (22.2) | < 0.0001 |
| Uric acid, mg/dL | 5.7 (1.3) | 5.9 (1.2) | 6 (1.2) | 6.1 (1.2) | < 0.0001 | 4.4 (1.0) | 4.5 (1.0) | 4.5 (1.0) | 4.4 (1.0) | 0.3058 |
| Red blood cells count, 104/µL | 468.1 (43.1) | 475.7 (38.6) | 482.8 (38.3) | 491.4 (37.6) | < 0.0001 | 440.3 (33.2) | 441.6 (33.0) | 442.9 (31.6) | 443.7 (31.7) | 0.0095 |
| Hemoglobin, g/dL | 14.7 (1.3) | 14.9 (1.1) | 15.1 (1.1) | 15.2 (1.0) | < 0.0001 | 13.2 (1.1) | 13.2 (1.1) | 13.3 (1.0) | 13.2 (1.1) | 0.6817 |
| Hematocrit, % | 44.2 (3.5) | 44.8 (3.0) | 45.3 (3.0) | 45.5 (2.8) | < 0.0001 | 40.6 (3) | 40.6 (3.0) | 40.8 (2.8) | 40.6 (2.9) | 0.3917 |
Data are expressed as mean (standard deviation) for continuous variables and number (percentage) for categorical variables
GS: grip strength; BMI: body mass index; WC: waist circumference; %BFM; percentage body fat mass VC: vital capacity; FVC: forced vital capacity; FEV1: forced expiratory volume in 1 s; SBP: systolic blood pressure; DBP: diastolic blood pressure; TC: total cholesterol; CIMT: carotid intima-media thickness; HDL-C: high-density lipoprotein cholesterol; HbA1c: hemoglobin A1c; and eGFR: estimated glomerular filtration rate; Q: quartile
The p-value was obtained using ANOVA for continuous variables and chi-square for categorical variables of proportion
After adjusting for age, body composition, and smoking status, leg extension strength was positively associated with bone area ratio, VC, FVC, FEV1, total cholesterol, eGFR, and uric acid, and negatively associated with WC, percentage body fat mass, and pulse rate in both the sexes (Table 4). In men, leg extension strength was positively associated with diastolic blood pressure. In women, it was positively associated with HDL cholesterol, HbA1c, red blood cell count, hemoglobin, and hematocrit, and negatively associated with glucose.
Table 4.
Association between leg extension strength and physiological data adjusted for age, body composition, and smoking
| Men | Women | |||||
|---|---|---|---|---|---|---|
| N | β | p-value | N | β | p-value | |
| Anthropometry | ||||||
| WCa, cm | 2855 | –9.733 | < 0.0001 | 6701 | –2.484 | < 0.0001 |
| %BFM, % | 2851 | –12.951 | < 0.0001 | 6704 | –3.846 | < 0.0001 |
| Bone area ratio, % | 2858 | 4.681 | < 0.0001 | 6713 | 1.572 | < 0.0001 |
| Pulmonary function | ||||||
| VCb, L | 2716 | 71.791 | < 0.0001 | 6375 | 43.397 | < 0.0001 |
| FVCb, L | 2708 | 57.465 | < 0.0001 | 6350 | 37.576 | < 0.0001 |
| FEV1b, L | 2708 | 50.820 | < 0.0001 | 6350 | 38.616 | < 0.0001 |
| FEV1/FVCb, % | 2708 | –0.801 | 0.0957 | 6350 | –0.256 | 0.2473 |
| Blood pressure | ||||||
| SBP, mmHg | 2857 | –0.069 | 0.7291 | 6705 | –0.775 | 0.3084 |
| DBP, mmHg | 2857 | 0.895 | 0.0019 | 6705 | 0.122 | 0.2940 |
| Pulse rate, beat/min | 2857 | –1.028 | 0.0007 | 6705 | –0.461 | 0.0003 |
| CIMT, mm | 2845 | –18.792 | 0.4605 | 6677 | 5.352 | 0.6621 |
| Lipid markers | ||||||
| TC, mg/dL | 2858 | 0.332 | 0.0002 | 6710 | 0.175 | < 0.0001 |
| Triglycerides, mg/dL | 2858 | 0.042 | 0.1840 | 6710 | –0.023 | 0.2465 |
| HDL-C, mg/dL | 2858 | 0.402 | 0.0684 | 6710 | 0.409 | < 0.0001 |
| Glucometabolic markers | ||||||
| HbA1c, % | 2856 | –6.626 | 0.3348 | 6701 | 8.550 | 0.0110 |
| Glucose, mg/dL | 2856 | –0.315 | 0.1233 | 6701 | –0.417 | < 0.0001 |
| eGFR, ml/min/1.73 m2 | 2858 | 0.870 | < 0.0001 | 6710 | 0.214 | 0.0043 |
| Uric acid, mg/dL | 2858 | 5.641 | 0.0308 | 6709 | 2.879 | 0.0260 |
| Red blood cells count, 104/µL | 2858 | 0.020 | 0.8124 | 6708 | 0.097 | 0.0099 |
| Hemoglobin, g/dL | 2858 | 3.066 | 0.2846 | 6708 | 3.529 | 0.0017 |
| Hematocrit, % | 2858 | 0.786 | 0.4581 | 6708 | 1.131 | 0.0072 |
The general linear model was adjusted for age, smoking status, and body mass index
aAdjusted for weight instead of body mass index
bAdjusted for height instead of body mass index
WC: waist circumference; %BFM: percentage body fat mass; VC: vital capacity; FVC: forced vital capacity; FEV1: forced expiratory volume in 1 s; SBP: systolic blood pressure; DBP: diastolic blood pressure; CIMT: carotid intima-media thickness; TC: total cholesterol; HDL-C: high-density lipoprotein cholesterol; HbA1c: hemoglobin A1c; and eGFR: estimated glomerular filtration rate
In the subgroup analysis according to age (< 65, 65–74, > 74 years), pulse rate for < 65-year-old men, CIMT for < 65-year-old women, triglycerides for > 74-year-old men, hemoglobin for > 74-year-old women, and hematocrit for > 74-year-old women showed a new significant association with grip strength; and FEV1/FVC for < 65-year-old men and HbA1c for 65–74-year-old men showed a new significant association with leg extension strength. Although several physiological factors were no longer significantly associated with grip or leg extension strength, no major changes were observed in the associations between physiological data and grip or leg extension strength (Supplementary Table 1, Supplementary Table 2).
For clarity regarding the associations between the physiological data and muscle strength, Table 5 summarizes the results of Tables 2 and 4. Furthermore, Table 6 summarizes the differences in the association of physiological data between grip and leg extension strength.
Table 5.
| Men | Women | |||
|---|---|---|---|---|
| GS | LS | GS | LS | |
| Anthropometry | ||||
| WCa, cm | ↓ | ↓ | ↓ | ↓ |
| %BFM, % | ↓ | ↓ | ↓ | ↓ |
| Bone area ratio, % | ↑ | ↑ | ↑ | ↑ |
| Pulmonary function | ||||
| VCb, L | ↑ | ↑ | ↑ | ↑ |
| FVCb, L | ↑ | ↑ | ↑ | ↑ |
| FEV1b, L | ↑ | ↑ | ↑ | ↑ |
| FEV1/FVCb, % | - | - | - | - |
| Blood pressure | ||||
| SBP, mmHg | - | - | ↑ | - |
| DBP, mmHg | ↑ | ↑ | ↑ | - |
| Pulse rate, beat/min | - | ↓ | - | ↓ |
| CIMT, mm | ↓ | - | - | - |
| Lipid markers | ||||
| TC, mg/dL | - | ↑ | - | ↑ |
| Triglycerides, mg/dL | - | - | - | - |
| HDL-C, mg/dL | - | - | ↑ | ↑ |
| Glucometabolic markers | ||||
| HbA1c, % | ↓ | - | ↓ | ↑ |
| Glucose, mg/dL | - | - | - | ↓ |
| eGFR, ml/min/1.73 m2 | ↑ | ↑ | ↑ | ↑ |
| Uric acid, mg/dL | - | ↑ | - | ↑ |
| Red blood cell count, 104/µL | - | - | ↑ | ↑ |
| Hemoglobin, g/dL | - | - | - | ↑ |
| Hematocrit, % | - | - | - | ↑ |
The general linear model was adjusted for age, smoking status, and body mass index
aAdjusted for weight instead of body mass index
bAdjusted for height instead of body mass index
WC: waist circumference; %BFM: percentage body fat mass; GS: grip strength; LS: leg extension strength; WC: waist circumference; %BFM: percentage body fat mass; VC: vital capacity; FVC: forced vital capacity; FEV1: forced expiratory volume in 1 s; SBP: systolic blood pressure; DBP: diastolic blood pressure; CIMT: carotid intima-media thickness; TC: total cholesterol; HDL-C: high-density lipoprotein cholesterol; HbA1c: hemoglobin A1c; and eGFR: estimated glomerular filtration rate; ↑: p < 0.05 for positive association; ↓: p < 0.05 for negative association; -: not significant associated
Table 6.
Summary of differences in the association of physiological data between grip and leg extension strength
| Consistent positive association in both the sexes |
| Bone area ratio, VC, FVC, FEV1, eGFR |
| Consistent negative association in both the sexes |
| WC, %BFM |
| Consistent positive association in men |
| DBP |
| Consistent positive association in women |
| HDL-C, Red blood cell count |
| Inconsistent association in both the sexes |
| Pulse rate, TC, HbA1c, Uric acid |
| Inconsistent association in men |
| CIMT |
| Inconsistent association in women |
| SBP, DBP, Glucose, Hemoglobin, Hematocrit |
WC: waist circumference; %BFM: percentage body fat mass; VC: vital capacity; FVC: forced vital capacity; FEV1: forced expiratory volume in 1 s; SBP: systolic blood pressure; DBP: diastolic blood pressure; CIMT: carotid intima-media thickness; TC: total cholesterol; HDL-C: high-density lipoprotein cholesterol; HbA1c: hemoglobin A1c; and eGFR: estimated glomerular filtration rate
Discussion
Through a large community-based cohort, we evaluated the association between physiological data and muscle strength (i.e., grip and leg extension strength). Grip and leg extension strength were positively associated with bone area ratio, VC, FVC, FEV1, and eGFR and negatively associated with the WC and percentage body fat mass in both the sexes. Diastolic blood pressure was positively associated with grip strength in both the sexes and leg extension strength in men, but not women. In women, higher grip and leg extension strength was associated with higher HDL cholesterol and red blood cell counts. Nonetheless, these associations were not confirmed in men. Total cholesterol and uric acid levels were positively associated with leg extension strength, but not grip strength. Furthermore, in women, we observed differences in the association between HbA1c and grip and leg extension strength. In summary, the association between grip strength and physiological data was mostly consistent with that between leg extension strength and physiological data. Several physiological parameters, such as pulse rate, total cholesterol, uric acid, and HbA1c, were inconsistent with the association between grip and leg extension strength.
Average muscle strength according to the age group
Grip and leg extension strength declined markedly from 50 years of age. Furthermore, the decline in muscle strength differed according to sex. Abe et al. reported that grip strength declined after the age of 50 years in 613 Japanese adults aged 20–89 years [43]. Makizako et al. studied 10,092 community-dwelling Japanese older adults and found that the patterns of age-dependent decrease in physical performance measures, including grip strength, also differed among the performance measures and between the sexes [44]. Our results are consistent with those of previous studies. Beside a decrease in muscle mass, which is a major factor in the age-related decline in muscle strength, physical inactivity is also an important factor [45]. In this study, the step counts were maintained from age 70 to 79 years, except after the age of 80 years. Therefore, the decline in muscle strength in the age group of the participants in the present study may be primarily due to age-related loss of muscle mass or a decrease in the intensity of exercise to maintain muscle strength, rather than physical inactivity.
Association between physiological data and muscle strength
Grip and leg extension strength demonstrated similar associations with WC, percentage body fat mass, bone area ratio, pulmonary function, and eGFR in both the sexes. These associations were consistent with those reported in previous cross-sectional studies on anthropometry [9, 46], pulmonary function [17, 47], and eGFR [41]. Thus, muscle strength assessed using grip or leg extension strength may be a useful marker of these functions.
HDL cholesterol and red blood cell count were associated with grip and leg extension strength only in women. In men, neither grip nor leg extension strength was significantly associated, but the regression coefficient for HDL cholesterol was greater in men than in women. We thought that the smaller sample size or larger standard deviation in men accounted for this lack of statistical significance. However, the standard deviation was not larger in men. Thus, we concluded that our sample size was not large enough to detect such a small difference in men.
CIMT was negatively associated with grip strength in men. Conversely, Yamanashi et al. investigated the association between grip strength and CIMT in 3,136 Japanese participants (1,234 men and 1,902 women) aged > 40 years and reported no significant association [14]. Our study included younger participants and a larger sample size, which may explain this discrepancy.
Diastolic blood pressure was positively associated with grip and leg extension strength in men. In women, systolic and diastolic blood pressures were positively associated with grip strength. Blanchard et al. reported that upper- and lower-body muscle strengths were greater among adults with pre-established hypertension than adults with normal blood pressure [48]. In contrast, Gubelmann et al. investigated the association between grip strength and cardiovascular risk markers in 3,468 Swiss participants (1,577 men and 1,891 women) aged 50–75 years and reported no significant association between grip strength and blood pressure levels [9]. Notably, the large sample size in our study may have facilitated detecting the relatively small associations to be detected in sample sizes used previously [9]. The positive association between blood pressure and grip strength can be explained as follows: Takase et al. reported that the fat-free mass index was positively associated with the prevalence of hypertension [20]. Markus et al. reported that lower grip strength was associated with lower structural and functional parameters of the heart [49]. Thus, high muscle mass and grip strength may serve as markers of cardiac strength and high blood pressure, respectively.
Pulse rate was negatively associated with leg extension strength in both the sexes. Our grip strength results are consistent with those of previous cross-sectional studies that demonstrated no significant association between grip strength and heart rate [17, 49]. We could not identify reports indicating an association between leg strength and pulse rate; nonetheless, exercises that maintain and improve the lower extremity muscle strength decreases the resting heart rate [50], thus supporting our results.
Total cholesterol level was positively associated with leg extension strength in both the sexes. Kohl reported that lower-body leg press strength was not significantly associated with total cholesterol in a group of 6,653 American participants aged 20–69 years (5,460 men and 1,193 women) [51]. Our results, which did not demonstrate significant associations between grip strength and total cholesterol in either sex, are partly consistent with those of a previous cross-sectional study that indicated a positive association between the grip strength and total cholesterol in men, but no significant association in women [9]. As our study included Japanese participants aged ≥ 20 years, the differences in participant characteristics may have affected our results.
Uric acid level was positively associated with leg extension strength in both the sexes. Similarly, peak isokinetic knee extensor strength was positively associated with uric acid level in both the sexes [52]. Researchers have mentioned the lack of a unified view on the association between uric level and grip strength, with reports suggesting a positive association in women [53] or no significant association [9].
Hemoglobin and hematocrit levels were positively associated with leg extension strength in women. While there are no studies on leg extension strength in relation to hemoglobin, the following studies have reported the association between these physiological data and other lower extremity muscle strengths. Regarding lower extremity muscle strength, the hemoglobin level was not significantly associated with ankle extension [54] or knee joint strength [55]. Our results, which indicated no significant association between grip strength and these physiological parameters, are inconsistent with those of a previous cross-sectional study that demonstrated an association between grip strength and anemia [12].
HbA1c levels were negatively associated with grip strength in women. Mainous et al. studied 1,463 adults aged ≥ 20 years and mentioned that the grip strength was lower in individuals with an HbA1c level ≥ 6.5% compared with that of individuals with an HbA1c level < 6.5% [56]. Our grip strength results are consistent with those of a previous study. By contrast, leg extension strength was positively associated with HbA1c levels in women. Furthermore, a meta-analysis reported that resistance training interventions, such as increasing leg extension strength, reduced HbA1c levels in adults with type 2 diabetes mellitus [57]. The subgroup analysis according to age (Supplementary Table 2) showed that leg extension strength was positively associated with HbA1c for < 65-year-old women. In contrast, leg extension strength was negatively associated with HbA1c for 65–74-year-old men. Therefore, an inconsistent association between leg extension strength and HbA1c may be explained by differences in age structure. Additionally, in the cross-sectional analysis (Table 3), despite different ages, HbA1c levels in the higher leg extension strength group were similar to those in the lower leg extension strength group. Thus, a mechanism may increase HbA1c levels in people with lower leg extension strength. However, further studies are required delineate this mechanism.
Strengths and limitations of the study
The strength of this study is that it is one of the largest cross-sectional studies to report the association between muscle strength and various physiological parameters in the lower and upper limbs. Furthermore, we observed the characteristics of participants with low muscle strength in relation to grip and leg extension strength. However, this study had a limitation. The cross-sectional design made it impossible to assess the causal effect of muscle strength on physiological data. Therefore, studies should include a continued follow-up of the participants to evaluate the effects of muscle strength on physiological data.
Conclusion
This population-based cross-sectional study indicated an association between muscle strength and anthropometric and physiological data. The grip and leg extension strength of both the sexes demonstrated similar associations with anthropometry, pulmonary function, and eGFR. Furthermore, diastolic blood pressure demonstrated a similar association with grip and leg extension strength in men. HDL cholesterol and red blood cell counts indicated similar associations with grip and leg extension strength in women. Grip and leg extension strength displayed variable associations with HbA1c levels in women. The impact of muscle strength on physiological data may partially follow different paths for grip and leg extension strength. Further longitudinal studies are required to determine the causal effect of muscle strength on physiological data.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Supplementary Material 1: Supplementary Table 1. Grip strength and physiological data by age groups. Supplementary Table 2. Leg extension strength and physiological data by age groups.
Acknowledgements
The authors thank the members of the Tohoku Medical Megabank Organization, including the Genome Medical Research Coordinators and the office and administrative personnel, for their assistance. The complete list of members is available at https://www.megabank.tohoku.ac.jp/english/a220901/.
Abbreviations
- ANOVA
Analysis of Variance
- BMI
Body Mass Index
- CIMT
Carotid Intima-Media Thickness
- eGFR
Estimated Glomerular Filtration Rate
- FEV1
Forced Expiratory Volume in One Second
- FVC
Forced Vital Capacity
- HDL
High-Density Lipoprotein
- HbA1c
Hemoglobin A1c
- IMT
Intima-Media Thickness
- VC
Vital Capacity
- WC
Waist Circumference
Author contributions
YN and AH were involved in study concept and design. YN contributed to statistical analysis. YN, RH and AH were involved statistical analysis and data interpretation, and the manuscript preparation. RH, NN, MK, KN, IC, IK, TN, NT, HM, YH, MO, TK, AU, EK, RN, NF, SK and AH were involved the enrollment of participants and data collection. AH was project administrator. All authors read and approved the final manuscript.
Funding
This research was supported by the Japan Agency for Medical Research and Development, AMED, under the Grant Number JP21tm0124005. This research used the supercomputer system provided by the Tohoku Medical Megabank Project (founded by AMED under Grant Number JP21tm0424601).
Data availability
All data used to support the findings of this study shall be released upon application to the Tohoku Medical Megabank Organization (Sendai, Japan), which can be contacted through Prof. Atsushi Hozawa (email: hozawa@megabank.tohoku.ac.jp).
Declarations
Ethics approval and consent to participate
Informed consent was obtained from all the participants. The study was approved by the Institutional Review Board of the Tohoku Medical Megabank Organization (approval number: 2022-4-092).
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.Zhao X, Chen S, Liu N, Hu F, Yu J. Handgrip strength is positively associated with successful aging in older adults: a national cross-sectional study in China. J Affect Disord. 2023;333:30–7. doi: 10.1016/j.jad.2023.04.041. [DOI] [PubMed] [Google Scholar]
- 2.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 (Online) 2018;361:1–19. doi: 10.1136/bmj.k1651. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Leong DP, Teo KK, Rangarajan S, Lopez-Jaramillo P, Avezum A, Orlandini A, et al. Prognostic value of grip strength: findings from the prospective Urban Rural Epidemiology (PURE) study. Lancet. 2015;386:266–73. doi: 10.1016/S0140-6736(14)62000-6. [DOI] [PubMed] [Google Scholar]
- 4.Li R, Xia J, Zhang X, Gathirua-Mwangi WG, Guo J, Li Y, et al. Associations of muscle Mass and Strength with all-cause mortality among US older adults. Med Sci Sports Exerc. 2018;50:458–67. doi: 10.1249/MSS.0000000000001448. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Sanderson WC, Scherbov S, Weber D, Bordone V. Combined measures of Upper and Lower Body Strength and Subgroup differences in subsequent survival among the Older Population of England. J Aging Health. 2016;28:1178–93. doi: 10.1177/0898264316656515. [DOI] [PubMed] [Google Scholar]
- 6.Kishimoto H, Hata J, Ninomiya T, Nemeth H, Hirakawa Y, Yoshida D, et al. Midlife and late-life handgrip strength and risk of cause-specific death in a general Japanese population: the Hisayama Study. J Epidemiol Community Health (1978) 2014;68:663–8. doi: 10.1136/jech-2013-203611. [DOI] [PubMed] [Google Scholar]
- 7.Ortega FB, Silventoinen K, Tynelius P, Rasmussen F. Muscular strength in male adolescents and premature death: Cohort study of one million participants. BMJ (Online) 2012;345:1–12. doi: 10.1136/bmj.e7279. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.García-Hermoso A, Cavero-Redondo I, Ramírez-Vélez R, Ruiz JR, Ortega FB, Lee DC, et al. 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;99:2100–2113e5. doi: 10.1016/j.apmr.2018.01.008. [DOI] [PubMed] [Google Scholar]
- 9.Gubelmann C, Vollenweider P, Marques-Vidal P. Association of grip strength with cardiovascular risk markers. Eur J Prev Cardiol. 2017;24:514–21. doi: 10.1177/2047487316680695. [DOI] [PubMed] [Google Scholar]
- 10.Peterson MD, Duchowny K, Meng Q, Wang Y, Chen X, Zhao Y. Low normalized grip strength is a biomarker for Cardiometabolic Disease and Physical Disabilities among U.S. and Chinese adults. Journals of Gerontology - Series A Biological sciences and Medical sciences. 2017;72:1525–31. [DOI] [PMC free article] [PubMed]
- 11.Lee MR, Jung SM, Bang H, Kim HS, Kim YB. Association between muscle strength and type 2 diabetes mellitus in adults in Korea: Data from the Korea national health and nutrition examination survey (KNHANES) VI. Medicine (United States). 2018;97. [DOI] [PMC free article] [PubMed]
- 12.Gi YM, Jung B, Kim KW, Cho JH, Ha IH. Low handgrip strength is closely associated with anemia among adults: a cross-sectional study using Korea National Health and Nutrition Examination Survey (KNHANES) PLoS ONE. 2020;15:1–15. doi: 10.1371/journal.pone.0218058. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Lawman HG, Troiano RP, Perna FM, Wang C-Y, Fryar CD, Ogden CL. Associations of relative Handgrip Strength and Cardiovascular Disease biomarkers in U.S. adults, 2011–2012. Am J Prev Med. 2016;50:677–83. doi: 10.1016/j.amepre.2015.10.022. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Yamanashi H, Kulkarni B, Edwards T, Kinra S, Koyamatsu J, Nagayoshi M, et al. Association between atherosclerosis and handgrip strength in non-hypertensive populations in India and Japan. Geriatr Gerontol Int. 2018;18:1071–8. doi: 10.1111/ggi.13312. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Kim W, Kim SH, Choi CU, Lee SK, Kang DO, Choi JY, et al. Role of arterial stiffness in the association between hand grip strength and cardiovascular events: the Korean Genome and Epidemiology Study. J Hypertens. 2021;39:1203–9. doi: 10.1097/HJH.0000000000002753. [DOI] [PubMed] [Google Scholar]
- 16.Ntuk UE, Celis-Morales CA, Mackay DF, Sattar N, Pell JP, Gill JMR. Association between grip strength and diabetes prevalence in black, South-Asian, and white European ethnic groups: a cross-sectional analysis of 418 656 participants in the UK Biobank study. Diabet Med. 2017;34:1120–8. doi: 10.1111/dme.13323. [DOI] [PubMed] [Google Scholar]
- 17.Zhu R, Li W, Xia L, Yang X, Zhang B, Liu F, et al. Hand grip strength is associated with cardiopulmonary function in Chinese adults: results from a cross-sectional study. J Exerc Sci Fit. 2020;18:57–61. doi: 10.1016/j.jesf.2019.12.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Hozawa A, Tanno K, Nakaya N, Nakamura T, Tsuchiya N, Hirata T, et al. Study profile of the tohoku medical megabank community-based cohort study. J Epidemiol. 2021;31:65–76. doi: 10.2188/jea.JE20190271. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Takase M, Nakamura T, Hirata T, Tsuchiya N, Kogure M, Itabashi F, et al. Association between fat mass index, fat-free mass index and hemoglobin A1c in a Japanese population: the Tohoku Medical Megabank Community-based Cohort Study. J Diabetes Investig. 2022;13:858–67. doi: 10.1111/jdi.13729. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Takase M, Nakamura T, Tsuchiya N, Kogure M, Itabashi F, Narita A, et al. Association between the combined fat mass and fat-free mass index and hypertension: the Tohoku Medical Megabank Community-based Cohort Study. Clin Exp Hypertens. 2021;43:610–21. doi: 10.1080/10641963.2021.1925681. [DOI] [PubMed] [Google Scholar]
- 21.Takase M, Nakamura T, Nakaya N, Kogure M, Hatanaka R, Nakaya K et al. Associations between the combined Fat Mass Index and Fat-Free Mass Index with Carotid Intima-Media thickness in a Japanese Population: the Tohoku Medical Megabank Community-based Cohort Study. J Atheroscler Thromb. 2022;:1–19. [DOI] [PMC free article] [PubMed]
- 22.Kotozaki Y, Tanno K, Sakata K, Takusari E, Otsuka K, Tomita H, et al. Association between the social isolation and depressive symptoms after the great East Japan earthquake: findings from the baseline survey of the TMM CommCohort study. BMC Public Health. 2021;21:1–11. doi: 10.1186/s12889-021-10896-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Tashiro A, Kogure M, Nagata S, Itabashi F, Tsuchiya N, Hozawa A, et al. Coastal exposure and residents’ mental health in the affected areas by the 2011 Great East Japan Earthquake and Tsunami. Sci Rep. 2021;11:1–11. doi: 10.1038/s41598-021-96168-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Kogure M, Nakamura T, Tsuchiya N, Hirata T, Nochioka K, Narita A, et al. Consideration of the reference value and number of measurements of the urinary sodium-to-potassium ratio based on the prevalence of untreated home hypertension: TMM Cohort Study. Hypertens Res. 2022;45:866–75. doi: 10.1038/s41440-021-00843-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Itabashi F, Hirata T, Kogure M, Narita A, Tsuchiya N, Nakamura T, et al. Combined associations of Liver enzymes and obesity with diabetes Mellitus Prevalence: the Tohoku Medical Megabank Community-based Cohort Study. J Epidemiol. 2022;32:221–7. doi: 10.2188/jea.JE20200384. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Kanno I, Hasegawa K, Nakamura T, Kogure M, Itabashi F, Narita A, et al. Relationship between the housing coldness/warmth evaluation by CASBEE Housing Health Checklist and psychological distress based on TMM Community-based Cohort Study: a cross-sectional analysis. Public Health. 2022;208:98–104. doi: 10.1016/j.puhe.2022.05.003. [DOI] [PubMed] [Google Scholar]
- 27.Nishimoto Y, Tsubono Y, Kogure M, Nakamura T, Itabashi F, Tsuchiya N, et al. The prevalence of current smokers and alcohol drinkers among cancer survivors and subjects with no history of cancer among participants in a community-based cardiometabolic screening program in Miyagi prefecture, Japan: a comparison with nationally repres. Cancer Med. 2021;10:9000–11. doi: 10.1002/cam4.4364. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Nakaya N, Nakaya K, Tsuchiya N, Sone T, Kogure M, Hatanaka R, et al. Similarities in cardiometabolic risk factors among random male-female pairs: a large observational study in Japan. BMC Public Health. 2022;22:1978. doi: 10.1186/s12889-022-14348-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Hirata T, Kogure M, Tsuchiya N, Miyagawa K, Narita A, Nochioka K, et al. Impacts of the urinary sodium-to-potassium ratio, sleep efficiency, and conventional risk factors on home hypertension in a general Japanese population. Hypertens Res. 2021;44:858–65. doi: 10.1038/s41440-021-00628-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Hirata T, Nakamura T, Kogure M, Tsuchiya N, Narita A, Miyagawa K, et al. Reduced sleep efficiency, measured using an objective device, was related to an increased prevalence of home hypertension in Japanese adults. Hypertens Res. 2020;43:23–9. doi: 10.1038/s41440-019-0329-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Wagata M, Kogure M, Nakaya N, Tsuchiya N, Nakamura T, Hirata T, et al. Hypertensive disorders of pregnancy, obesity, and hypertension in later life by age group: a cross-sectional analysis. Hypertens Res. 2020;43:1277–83. doi: 10.1038/s41440-020-0463-8. [DOI] [PubMed] [Google Scholar]
- 32.Miura E, Tsuchiya N, Igarashi Y, Arakawa R, Nikkuni E, Tamai T, et al. Respiratory resistance among adults in a population-based cohort study in Northern Japan. Respir Investig. 2019;57:274–81. doi: 10.1016/j.resinv.2018.12.008. [DOI] [PubMed] [Google Scholar]
- 33.Nakaya N, Xie T, Scheerder B, Tsuchiya N, Narita A, Nakamura T, et al. Spousal similarities in cardiometabolic risk factors: a cross-sectional comparison between Dutch and Japanese data from two large biobank studies. Atherosclerosis. 2021;334:85–92. doi: 10.1016/j.atherosclerosis.2021.08.037. [DOI] [PubMed] [Google Scholar]
- 34.Kuriyama S, Yaegashi N, Nagami F, Arai T, Kawaguchi Y, Osumi N, et al. The Tohoku Medical Megabank Project: design and mission. J Epidemiol. 2016;26:493–511. doi: 10.2188/jea.JE20150268. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Saito S, Aoki Y, Tamahara T, Goto M, Matsui H, Kawashima J, et al. Oral Microbiome analysis in prospective genome Cohort studies of the Tohoku Medical Megabank Project. Front Cell Infect Microbiol. 2021;10:1–17. doi: 10.3389/fcimb.2020.604596. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Fuse N, Sakurai M, Motoike IN, Kojima K, Takai-Igarashi T, Nakaya N, et al. Genome-Wide Association Study of Axial Length in Population-based cohorts in Japan. Ophthalmol Sci. 2022;2:100113. doi: 10.1016/j.xops.2022.100113. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Kohri T, Kaba N, Murakami T, Narukawa T, Yamamoto S, Sakai T, et al. Search for promotion factors of ultrasound bone measurement in Japanese males and pre/post-menarcheal females aged 8–14 years. J Nutr Sci Vitaminol (Tokyo) 2012;58:263–71. doi: 10.3177/jnsv.58.263. [DOI] [PubMed] [Google Scholar]
- 38.Kohri T, Kaba N, Itoh T, Sasaki S. Effects of the National School Lunch Program on bone growth in Japanese Elementary School Children. J Nutr Sci Vitaminol (Tokyo) 2016;62:303–9. doi: 10.3177/jnsv.62.303. [DOI] [PubMed] [Google Scholar]
- 39.Kawabata A, Suzuki T, Urabe M, Fukumoto T, Nishimura Y. Automated IMT measurement for atherosclerosis screening. Panasonic Tech J. 2011;57:10–5. [Google Scholar]
- 40.Horio M, Imai E, Yasuda Y, Watanabe T, Matsuo S. GFR estimation using standardized serum cystatin C in Japan. Am J Kidney Dis. 2013;61:197–203. doi: 10.1053/j.ajkd.2012.07.007. [DOI] [PubMed] [Google Scholar]
- 41.Kabasawa K, Nakamura K, Ito Y, Tanaka J, Narita I. Association between estimated glomerular filtration rate based on cystatin C and grip strength in community-dwelling Japanese older adults. Journals of Gerontology - Series A Biological sciences and Medical sciences. 2021;76:1653–60. [DOI] [PubMed]
- 42.Kubota M, Kobayashi H, Quanjer PH, Omori H, Tatsumi K, Kanazawa M, et al. Reference values for spirometry, including vital capacity, in Japanese adults calculated with the LMS method and compared with previous values. Respir Investig. 2014;52:242–50. doi: 10.1016/j.resinv.2014.03.003. [DOI] [PubMed] [Google Scholar]
- 43.Abe T, Thiebaud RS, Loenneke JP. Age-related change in handgrip strength in men and women: is muscle quality a contributing factor? Age (Omaha) 2016;38:1–7. doi: 10.1007/s11357-016-9891-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Makizako H, Shimada H, Doi T, Tsutsumimoto K, Lee S, Lee SC, et al. Age-dependent changes in physical performance and body composition in community-dwelling Japanese older adults. J Cachexia Sarcopenia Muscle. 2017;8:607–14. doi: 10.1002/jcsm.12197. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Doherty TJ. Invited review: aging and sarcopenia. J Appl Physiol (1985) 2003;95:1717–27. doi: 10.1152/japplphysiol.00347.2003. [DOI] [PubMed] [Google Scholar]
- 46.Jackson AW, Lee DC, Sui X, Morrow JR, Church TS, Maslow AL, et al. Muscular strength is inversely related to prevalence and incidence of obesity in adult men. Obesity. 2010;18:1988–95. doi: 10.1038/oby.2009.422. [DOI] [PubMed] [Google Scholar]
- 47.Son DH, Yoo JW, Cho MR, Lee YJ. Relationship between handgrip strength and pulmonary function in apparently healthy older women. J Am Geriatr Soc. 2018;66:1367–71. doi: 10.1111/jgs.15410. [DOI] [PubMed] [Google Scholar]
- 48.Blanchard AR, Taylor BA, Thompson PD, Lepley LK, White CM, Corso LM, et al. The influence of resting blood pressure on muscle strength in healthy adults. Blood Press Monit. 2018;23:185–90. doi: 10.1097/MBP.0000000000000325. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.Markus MRP, Ittermann T, Kim S, Schipf S, Siewert-Markus U, Santana CC, et al. Lower muscular strength is associated with smaller left and right chambers and lower cardiac mass in the general population - the Sedentary’s heart. Prog Cardiovasc Dis. 2021;68:36–51. doi: 10.1016/j.pcad.2021.09.004. [DOI] [PubMed] [Google Scholar]
- 50.Huang G, Shi X, Davis-Brezette JA, Osness WH. Resting heart rate changes after endurance training in older adults: a meta-analysis. Med Sci Sports Exerc. 2005;37:1381–6. doi: 10.1249/01.mss.0000174899.35392.0c. [DOI] [PubMed] [Google Scholar]
- 51.Kohl HW, 3rd, Gordon NF, Scott CB, Vaandrager HBSN. Musculoskeletal strength and serum lipid levels in men and women. Med Sci Sports Exerc. 1992;24:1080–7. doi: 10.1249/00005768-199210000-00003. [DOI] [PubMed] [Google Scholar]
- 52.Nahas PC, Rossato LT, de Branco FMS, Azeredo CM, Rinaldi AEM, de Oliveira EP. Serum uric acid is positively associated with muscle strength in older men and women: findings from NHANES 1999–2002. Clin Nutr. 2021;40:4386–93. doi: 10.1016/j.clnu.2020.12.043. [DOI] [PubMed] [Google Scholar]
- 53.Kawamoto R, Ninomiya D, Kasai Y, Kusunoki T, Ohtsuka N, Kumagi T, et al. Serum uric acid is positively Associated with Handgrip Strength among Japanese Community-Dwelling Elderly women. PLoS ONE. 2016;11:e0151044. doi: 10.1371/journal.pone.0151044. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 54.Cesari M, Penninx BWJH, Lauretani F, Russo CR, Carter C, Bandinelli S, et al. Hemoglobin levels and skeletal muscle: results from the InCHIANTI study. J Gerontol Biol Sci Med Sci. 2004;59:249–54. doi: 10.1093/gerona/59.3.M249. [DOI] [PubMed] [Google Scholar]
- 55.Aung KCY, Feng L, Yap KB, Sitoh YY, Leong IYO, Ng TP. Serum albumin and hemoglobin are associated with physical function in community-living older persons in Singapore. J Nutr Health Aging. 2011;15:877–82. doi: 10.1007/s12603-011-0120-7. [DOI] [PubMed] [Google Scholar]
- 56.Mainous AG, Tanner RJ, Anton SD, Jo A. Grip Strength as a marker of hypertension and diabetes in healthy weight adults. Am J Prev Med. 2015;49:850–8. doi: 10.1016/j.amepre.2015.05.025. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 57.Jansson AK, Chan LX, Lubans DR, Duncan MJ, Plotnikoff RC. Effect of resistance training on HbA1c in adults with type 2 diabetes mellitus and the moderating effect of changes in muscular strength: a systematic review and meta-analysis. BMJ Open Diabetes Res Care. 2022;10:1–8. doi: 10.1136/bmjdrc-2021-002595. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supplementary Material 1: Supplementary Table 1. Grip strength and physiological data by age groups. Supplementary Table 2. Leg extension strength and physiological data by age groups.
Data Availability Statement
All data used to support the findings of this study shall be released upon application to the Tohoku Medical Megabank Organization (Sendai, Japan), which can be contacted through Prof. Atsushi Hozawa (email: hozawa@megabank.tohoku.ac.jp).