Abstract
Objectives
Data regarding the occurrence of risk factors that promote the loss of muscle mass, strength and function in sarcopenia patients in elderly Chinese patients are sparse. Here, we investigated the alterations in muscle mass, function and strength in those with sarcopenia over a 4-year period. We further evaluated the risk factors leading to a loss of grip strength, gait speed and skeletal muscle mass index in sarcopenia patients.
Design
A face-to-face cross-sectional survey.
Setting and Participants
The study population consisted of 560 Chinese aged over 59 years.
Measurements
Study recordings took places over a four-year period from 2014. Muscle mass was assessed through bioelectrical impedance analysis (BIA) performed on an Inbody720, Biospace. Hand-grip strength and 6 m walking speed were used as measurements of muscle strength and function. Sarcopenia was diagnosed using the Asian Working Group for Sarcopenia criteria (AWGS).
Results
In total, 474 of the elderly residents completed the follow-up. The rates of decreased ASMI, grip strength, and gait speed in the sarcopenia patients increased over the 4-year period. Following multivariate analysis, age was identified as the main risk factor for all the observed decrease, gender was specifically related to the loss of ASMI, stroke was a risk factor for gait speed and sarcopenia. A high BMI was a risk factor for a low gait speed but was protective for a loss of skeletal muscle mass and sarcopenia.
Conclusions
Age leads to a decline in muscle strength and function. In elderly Chinese patients with sarcopenia, the rates of reduced grip strength, gait-speed and sarcopenia increased. A high BMI was protective against the decline in muscle mass and sarcopenia, but represented a risk factor for low gait speed. Stoke was identified to cause a loss of gait speed in sarcopenia patients.
Key words: Sarcopenia, muscle mass, muscle function, elderly
Introduction
The loss of skeletal muscle mass in the elderly is an area of intense research interest. Rosenberg and colleagues first identified the role of sarcopenia in the loss of muscle mass of elderly individuals (1). Sarcopenia encompasses the progressive loss of skeletal muscle mass and function that correlates with disability and death. Its risk factors are known to include gender, age and levels of exercise. Sarcopenia leads to a high incidence of falls, fractures, hospitalizations, a loss of mobility and subsequently reduced quality of life (QOL) of sufferers (2, 3, 4, 5). In the last 30 years, methods to assay muscle strength and function have emerged to fully define sarcopenia. The loss of muscle activity varies according to population and physical performance assessments. The occurrence of sarcopenia is also highly variable due to the diagnostics, measurement methods, appropriate cut-off values, and variations in age, sex, race and living status. Sarcopenia is depend on both region and age, with a prevalence of 1% to 29% in community-dwelling residents, a prevalence of 14% to 33% in those receiving long-term care, and 10% in those transiently admitted to hospital (6). In China, the occurrence of sarcopenia in elderly residents can range from 0% to 10% according to IGWS, EWGSOP (the European Working Group on Sarcopenia in Older People) and AGWS (the Asian Working Group for Sarcopenia) criteria (7). Epidemiology assessments of the prevalence of sarcopenia in elderly Chinese residents are limited to cross-sectional evaluations. Here, we assessed 474 patients aged ≥ 59 years over a period of 4-years in China to monitor variations in muscle strength and mass. Our ultimate aims are to assess the prevalence of sarcopenia and its associated risk factors on the occurrence of muscle mass decline in the elderly Chinese population.
Materials and Methods
Study population
We assessed 560 Chinese residents aged ≥ 59 years old (274 males and 286 females) in the Chengdu, Sichuan province from July to August in 2014 to 2018. Individuals were enrolled through the placement of recruitment notes in community centers and housing estates. We excluded those with disabilities, those with difficulty walking, those who had undergone hip replacements, those unable to perform hand grip assessments, those with implanted electronic devices such as defibrillators, metal implants or pacemakers, those with neuronal deficits such as dementia, and those with drug or alcohol addictions. We used a general questionnaire which to identify the age, gender, level of educational, occupation, and medical history of the study participants. A physical examination including bodyweight, height, and blood pressure were also assessed. BMI was defined as kg/m2.
All included subjects provided consent and the study protocol was approved by our local ethics board.
Muscle mass and strength measurements
Muscle mass was assessed through bioelectrical impedance analysis (Inbody720, Biospace China Inc.). ASM was defined as the levels of skeletal muscle in the arms and legs. ASMI represented the ASM/height2.
Grip strength assessments were used to assays muscle strength on a dynamometer (CAMRY EH 101). We performed measurements from each hand (n=3) and only the highest values were recorded. The assessment of Gait speed was used to assess physical performance on a 6 meters course (m/s). Participants were allowed to warm up for ∼ 5 min and performed a total of 2 walks. The fastest walking speed was recorded.
Sarcopenia measurements
We defined sarcopenia using AWGS criteria to identify those with low levels of muscle mass and strength. A low muscle mass was defined as the ASM index <7.0 kg/m2 for males and <5.7 kg/m2 for females. A grip strength < 26 kg and <18 kg was recorded for males and females. Low levels of physical performance were defined as gait speeds ≤ 0.8 m/s.
Statistics
Continuous data are shown as the mean ± SD. Significance difference between the groups were identified through independent samples t-tests for continuous variables, and ≤2-test or Fisher’s exact tests for categorical variables. We employed binary logistic regression analysis to identify the risk factors for sarcopenia. Data were analyzed using IBM SPSS 21.0 (IBM, Armonk, NY, USA). P Values < 0.05 were deemed significant.
Results
Baseline characteristics and muscle strength over the 4-year period
From July-August 2014, we assessed 560 Chinese residents aged ≥ 59 years old. A total of 76 were missed and 484 completed follow-ups (238 males with a mean age of 69.01 ± 6.35 years and 236 females with a mean age of 67.21 ± 6.02 in baseline). From baseline to 4-year follow up, the ASM decreased by 0.54 ± 0.86kg (−2.72%) from 19.85 ± 2.77 kg to 19.31 ± 2.82kg (p=0.00) in males and 0.31 ± 1.06 kg (−2.19%) from 14.16 ± 2.34 kg tol3.85 ± 2.22 kg (p=0.00 in females over the 4-year period. The ASMI decreases to 0.11 ± 0.27 kg/m2 (1.50%) from 7.31 ± 0.69 kg/m2 to 7.20 ± 0.72 kg/m2, p=0.00) in males and 0.04 ± 0.31 kg/m2 (0.67%) from 6.00 ± 0.68 kg/m2 to 5.96 ± 0.69 kg/m2, p=0.04) in females. Grip strength declined to 5.00 ± 6.17 kg (13.54%) from 36.93 ± 7.48 kg to 31.93 ± 7.28 kg (p=0.00) in males to 1.43 ± 3.86 kg (65.97%) reduction from 23.97 ± 4.42 kg to 22.54 ± 4.47 kg (p=0.00) in females. In males. The gait speed decreased by 0.13 ± 0.27m/s (from 1.07 ± 0.18 m/s to 0.94 ± 0.25m/s, p=0.00) in females to 0.09 ± 0.29 m/s from 1.02 ± 0.17 m/s to 0.93 ± 0.28m/s (p=0.00) after 4 years. Both weight and BMI showed no significant changes over the 4-year follow-up period. (Table 1)
Table 1.
Baseline characteristics and alterations in muscle indices over the 4-year follow-up period
| Variable | Gender | N | Baseline | 4-year later | Change in 4-years | P value |
|---|---|---|---|---|---|---|
| Age (y) | M | 238 | 69.01 ±6.35 | 73.01±6.35 | 4.00±0.00 | |
| Female | 236 | 67.21 ±6.02 | 71.21±6.02 | 4.00±0.00 | ||
| Height, (m) | Male | 238 | 1.64±0.06 | 1.63±0.06 | −0.01±0.01 | 0.00 |
| Female | 236 | 1.53±0.06 | 1.52±0.06 | −0.01±0.01 | 0.00 | |
| Weight, (kg) | Male | 238 | 64.77±8.41 | 64.59±8.75 | −0,17±2.93 | 0.36 |
| Female | 236 | 56.91 ±8.42 | 56.59±8.36 | −0,31±3.39 | 0.16 | |
| BMI(kg/m2) | Male | 238 | 23.93±2.67 | 24.30±3.12 | 0.38±3.95 | 0.15 |
| Female | 236 | 24.20±3.20 | 24.32±2.85 | 0.12±4.40 | 0.68 | |
| Total ASM(kg) | Male | 238 | 19.85±2.77 | 19.31±2.82 | −0.54±0.86 | 0.00 |
| Female | 236 | 14.16±2.34 | 13.85±2.22 | −0.31±1.06 | 0.00 | |
| ASMI(kg/m2) | Male | 238 | 7.31 ±0.69 | 7.20±0.72 | −0.11 ±0.27 | 0.00 |
| Female | 236 | 6.00±0.68 | 5.96±0.69 | −0.04±0.31 | 0.04 | |
| grip strength(kg) | Male | 238 | 36.93±7.48 | 31.93±7.28 | −5.00±6.17 | 0.00 |
| Female | 236 | 23.97±4.42 | 22.54±4.47 | −1.43±3.86 | 0.00 | |
| Gait speed (m/s) | Male | 238 | 1.07±0.18 | 0.94±0.25 | 0.13±0.27 | 0.00 |
| Female | 236 | 1.02±0.17 | 0.93±0.28 | 0.09±0.29 | 0.00 | |
Changes in muscle indices over the 4-year period according to age
The total AMS, ASMI, grip strength and gait speed declined over the 4-year period in all age groups. No significant differences in the magnitude of the decline occurred according to age (p>0.05), (Table 2).
Table 2.
Changes in muscle indices across the age groups
| Males | Females | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| <65y (n=74) | 65–69y (n=57) | 70–74y (n=47) | 75–79y (n=S0) | >80y (n=10) | <65y (n=100) | 65–69y (n=60) | 70–74y (n=44) | 75–79y (n=25) | >80y (n=7) | |
| Total ASM (kg) changes | −0.54± 0.73 | −0.30± 1.05 | −0.55± 0.79 | −0.79± 0.85 | −0.46± 0.58 | −0.35± 1.36 | −0.24± 0.79 | −0.33± 0.73 | −0.22± 0.89 | −0.63± 0.46 |
| P | 0.070 | 0.878 | ||||||||
| SMI(kg/m2) changes | −0.09± 0.23 | −0.04± 0.32 | −0.11± 0.25 | −0.19± 0.30 | −0.18± 0.27 | −0.05± 0.32 | −0.02± 0.30 | −0.03± 0.27 | −0.01± 0.35 | −0.19± 0.19 |
| P | 0.076 | 0.636 | ||||||||
| Grip strength(kg) changes | −5.43± 6.72 | −4.74± 6.54 | −5.01± 6.22 | −4.40± 5.29 | −6.15±3.62 | −1.15± 3.89 | −2.10± 3.91 | −0.73± 3.90 | −1.73± 3.24 | −2.27± 4.59 |
| P | 0.867 | 0.373 | ||||||||
| Gait speed (m/s) Changes | −0.10± 0.26 | −0.18± 0.27 | −0.13± 0.24 | −0.13± 0.30 | −0.18± 0.18 | −0.09± 0.24 | −0.06± 0.34 | −0.13± 0.25 | −0.06± 0.38 | −0.23± 0.23 |
| P | 0.456 | 0.419 | ||||||||
Sarcopenia, muscle strength and function and gait speed changes
In total, 32.06%, 36.71% of the study participants had a low muscle mass index at baseline and at 4-years, respectively. In total, 39 (8.2%) of those with a normal ASMI developed a low ASMI, whilst 17 (3.58%) recovered to a normal ASMI at follow-up. The proportion of subjects with a low grip strength and low gait speed were 3-fold higher than at baseline (6.12% to 18.57% and from 8.02% to 25.32%, respectively). A total of 71 (14.97%) and 95 (20.04%) participants with normal grip strengths and gait speeds showed lower values at follow-up. A total of 12 (2.53%) and 13 (2.73%) participants in the low grip strength and gait speed groups recovered to normal levels. In total, 52 (10.97%) of those who lacking sarcopenia developed the disorder, whilst 6 subjects with the disorder at baseline (1.26%) recovered. The rates of sarcopenia increased from 5.70% to 15.40%. The average annual incidence of sarcopenia over the 4 years study period was 2.47% (Table 3).
Table 3.
Occurrence of ASMI, muscle strength, functional muscle decline, reduced gait speed and sarcopenia patients
| N | Low skeletal muscle mass index, n (%) | Reduced grip strength, n (%) | Reduced gait speed, n (%) | Sarcopenia, n (%) | |
|---|---|---|---|---|---|
| Baseline | 474 | 152 (32.06) | 29 (6.12) | 38 (8.02) | 27 (5.70) |
| After 4-years | 474 | 174 (36.71) | 88 (18.57) | 120 (25.32) | 73 (15.40) |
Risk factor assessments
Following the adjustment for age, BMI and medical history (stoke, heart disease, hypertension, diabetes, liver disease, kidney disease, cancer, COPD, bone and joint disease), age (adjusted OR 1.070, 95% CI (1.013–1.130)), sex (adjusted OR 0.398, 95% CI (0.183–0.864) and high BMI (adjusted 0.315, 95% CI (0.155–0.638) were associated with a low muscle mass. Only age (adjusted OR 1.107, 95% CI (1.061–1.153) was related to low grip strength. Medical history showed no association with a loss of muscle mass or grip strength. Age (adjusted OR 1.107,95% CI (1.034–1.115)), a high BMI (adjusted OR 1.899, 95% CI (1.170–3.081), and stroke (OR 5.213, 95%CI (1.397–19.457) were associated with a low gait speed. Age (adjusted OR1.108, 95% CI (1.054–1.164), a high BMI (adjusted OR 0.218, 95% CI (0.108–0.442), and stroke (adjusted OR 5.382, 95% CI (1.294–22.393) were associated with sarcopenia (Table 4).
Table 4.
Binary logistic regression on the identified risk factors for the incidence of reduced muscle mass, grip strength, gait speed and sarcopenia
| Factors | low muscle mass(SMI) | Low grip strength | low gait speed | Sarcopenia | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Total | Incident cases | OR(95% CI) | Total | Incident cases | OR(95% CI) | Total | Incident cases | OR(95% CI) | Total | Incident cases | OR(95% CI) | |||||
| Univariate | Multivariate | Univariate | Multivariate | Univariate | Multivariate | Univariate | Multivariate | |||||||||
| Age | 322 | 39 | 1.070 (1.013–1.130) | 1.069 (1.009–1.132) | 445 | 71 | 1.107 (1.061–1.153) | 1.101 (1.056–1.148) | 436 | 95 | 1.071 (1.032–1.111) | 1.107 (1.034–1.115) | 474 | 52 | 1.104 (1.053–1.158) | 1.108 (1.054–1.164) |
| P value | 0.016 | 0.023 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | ||||||||
| Sex | ||||||||||||||||
| Male | 167 | 29 | 0.328 (0.154–0.699) | 0.398 (0.183–0.864) | 227 | 46 | 0.510 (0.301–0.864) | 0.592 (0.344–1.019) | 223 | 45 | 1.213 (0.770–1.913) | 226 | 23 | 0.789(0.441–1.412) | ||
| Female | 155 | 10 | 218 | 25 | 213 | 50 | 221 | 29 | ||||||||
| P value | 0.003 | 0.020 | 0.011 | 0.059 | 0.405 | 0.463 | ||||||||||
| BMI | ||||||||||||||||
| Low | 0 | 0 | - | - | 4 | 0 | 0.860 (0.815–0.908) | 6 | 2 | 2.472 (0.436–14.011) | 3.407 (0.585–19.857) | 4 | 1 | 1.479 (0.150–14.597) | 2.155 (0.208–22.347) | |
| P value | 1.00 | 214 | 36 | 0.277 | 0.173 | 0.562 | 0.520 | |||||||||
| Normal | 108 | 23 | Reference | Reference | 214 | 30 | Reference | 216 | 57 | Reference | Reference | 212 | 39 | Reference | Reference | |
| High | 214 | 16 | 0.299 (0.150–0.594) | 0.315 (0.155–0.638) | 227 | 41 | 1.381 (0.827–2.307) | 1.773 (1.109–2.833) | 1.899 (1.170–3.081) | 231 | 12 | 0.243 (0.124–0.478) | 0.218 (0.108–0.442) | |||
| P value | 0.000 | 0.001 | 0.216 | 0.016 | 0.09 | 0.000 | 0.000 | |||||||||
| Medical history Stroke | ||||||||||||||||
| No | 314 | 38 | 1.038 (0.124–8.666) | 434 | 69 | 1.176 (0.249–5.559) | 426 | 89 | 5.680 (1.569–20.562) | 5.213 (1.397–19.457) | 436 | 48 | 4.619 (1.304–16.358) | 5.382 (1.294–22.393) | ||
| Yes | 8 | 1 | 11 | 2 | 10 | 6 | 11 | 4 | ||||||||
| P value | 1.000 | 0.690 | 0.009 | 0.014 | 0.029 | 0.021 | ||||||||||
| Heart disease | ||||||||||||||||
| No | 266 | 31 | 1.263 (0.547–2.918) | 365 | 58 | 1.027 (0.532–1.981) | 361 | 79 | 0.968 (0.528–1.775) | 369 | 43 | 0.989 (0.461–2.123) | ||||
| Yes | 56 | 8 | 80 | 13 | 75 | 16 | 78 | 9 | ||||||||
| P value | 0.583 | 0.937 | 0.916 | 0.977 | ||||||||||||
| Hypertension | ||||||||||||||||
| No | 160 | 23 | 0.653 (0.331–1.288) | 237 | 37 | 1.056 (0.636–1.755) | 239 | 46 | 1.389 (0.881–2.191) | 241 | 31 | 0.769 (0.427–1.385) | ||||
| Yes | 162 | 16 | 208 | 34 | 206 | 21 | ||||||||||
| P value | 0.216 | 0.833 | 197 | 49 | 0.157 | 0.380 | ||||||||||
| Diabetes | ||||||||||||||||
| No | 248 | 29 | 1.180 (0.546–2.551) | 348 | 52 | 1.387 (0.775–2.481) | 336 | 67 | 1.561 (0.936–2.605) | 347 | 37 | 1.479 (0.775–2.821) | ||||
| Yes | 74 | 10 | 97 | 19 | 100 | 28 | 100 | 15 | ||||||||
| P value | 0.674 | 0.269 | 0.087 | 0.233 | ||||||||||||
| Liver disease | ||||||||||||||||
| No | 299 | 39 | 0.870 (0.832–0.909) | 418 | 69 | 0.405 (0.094–1.748) | 409 | 91 | 0.608 (0.205–1.802) | 421 | 52 | 0.876 (0.849–0.908) | ||||
| Yes | 23 | 0 | 27 | 2 | 27 | 4 | 26 | 0 | ||||||||
| 0.091 | 0.283 | 0.365 | 0.058 | |||||||||||||
| Kidney disease | ||||||||||||||||
| No | 300 | 36 | 1.158 (0.326–4.109) | 411 | 65 | 1.141 (0.454–2.864) | 407 | 87 | 1.401 (0.600–3.272) | 415 | 49 | 0.773 (0.227–2.632) | ||||
| Yes | 22 | 3 | 34 | 6 | 29 | 8 | 32 | 3 | ||||||||
| P value | 0.738 | 0.779 | 0.434 | 1.000 | ||||||||||||
| Cancer | ||||||||||||||||
| No | 317 | 38 | 1.836 (0.200–16.856) | 440 | 70 | 1.321 (0.146–11.999) | 430 | 94 | 0.715 (0.083–6.194) | 441 | 52 | 0.882 (0.852–0.913) | ||||
| Yes | 5 | 1 | 5 | 1 | 6 | 1 | 6 | 0 | ||||||||
| P value | 0.478 | 0.582 | 1.00 | 1.000 | ||||||||||||
| COPD | ||||||||||||||||
| No | 313 | 36 | 3.847 (0.922–12.056) | 431 | 67 | 2.173 (0.662–7.132) | 422 | 94 | 0.268 (0.035–2.078) | 433 | 50 | 1.277 (0.278–5.870) | ||||
| Yes | 9 | 3 | 14 | 4 | 14 | 1 | 14 | 2 | ||||||||
| P value | 0.082 | 0.254 | 0.320 | 0.672 | ||||||||||||
| Bone and joint disease | ||||||||||||||||
| No | 223 | 28 | 0.871 (0.415–1.827) | 313 | 47 | 1.258 (0.733–2.159) | 304 | 63 | 1.224 (0.754–1.989) | 310 | 35 | 1.113(0.600–2.065) | ||||
| Yes | 99 | 11 | 132 | 24 | 132 | 32 | 137 | 17 | ||||||||
| P value | 0.714 | 0.405 | 0.414 | 0.734 | ||||||||||||
Discussion
Muscle mass, muscle strength and muscle function decline with age (8, 9, 10). Studies assessing changes in muscle mass, strength and function in the elderly Chinese population from a long-range perspective are lacking. Here, we examined alterations in muscle parameters over a 4- year study period. A similar 12-year longitudinal study investigating muscle strength in the elbows, knees and flexors, exhibited losses that ranged from 20–30%. The cross-sectional thigh area as assessed by computerized tomography decreased by 12.5%, the thigh decreased by 14.7%, the quadriceps femoris decreased by 16.1%, and the flexor muscles decreased by 14.9% (11). In Sarcopenia assessments performed in Copenhagen, the appendicular lean mass (ALM), ALM/height2, gait speed, leg extension muscle power, 30 s sit-to-stand tests, and gait speed decreased in both males and females (12). In this study, we observed a significant loss in ASM, gait-speed and grip strength across both genders with age. The Copenhagen Sarcopenia study revealed a reduction in power-based parameters with aging but TLM, ALM, and ALM/h2 were unaltered until the age of 70+ years (12). We found that the ASM, grip strength and gait speed decreased across all age groups ≥ 59 years, but the magnitude of the decline observed were comparable.
Sarcopenia describes the progressive loss of skeletal muscle mass and function that correlates with disability and death. The disorder is considered a type of progressive muscle failure. Sarcopenia is diagnosed by the EWGSOP2 as a low muscle quantity and poor physical performance (13). Muscle mass determines power and strength, and is known to decline with age (14). The relationship between muscle mass and strength is low to moderate. Cross-sectional studies suggested no association of muscle mass content to variations in isometric muscle strength in well-functioning elderly participants (15). Independently of the ASMI, those with a high muscle quality possess a reduced risk of functional impairment, whilst those with a high ASMI but low muscle quality are susceptible to impairments (16). In this study, muscle mass decreased over time. The incidence of low grip strength and gait speed were 3-fold more prevalent after 4 years compared to baseline values. We observed only a 14% increase in the incidence of low muscle mass over the 4-year period. Impairments in muscle strength and function in the elderly were more striking than those of muscle mass.
A significant positive association between BMI and ASMI exists, and BMI is inversely associated with the occurrence of sarcopenia in Asians (17, 18) and Caucasians (19). In this study, higher BMI values were protective factors against the development of low ASMI (adjusted 0.315, 95% CI (0.155–0.638) and sarcopenia (OR 0.218, 95% CI (0.108–0.442) in agreement with previous studies performed in the elderly population of Hong Kong (20). However, those with a high BMI had lower gait speeds (adjusted OR 1.899, 95% CI 1.170–3.081) in agreement with previous studies (21, 22, 23). Longitudinal studies in the elderly with a normal BMI from mid-life had 5-cm/s faster gaits than the elderly with high BMI values and were 11 cm/s faster than elderly obese patients (24). Higher BMIs showed the opposite correlation with muscle mass and gait-speed. Further studies are required to assess the optimal BMI values that dictate the most favorable prognosis for elderly sarcopenia patients. This was not possible in this study due to our limited sample size.
Stroke leads to disability due to phenotypic shifts and muscle atrophy. Sarcopenia and impaired gait speed are more prevalent in the stroke vs. non-stoke population (25, 26). We further identified stroke as a risk factor for a low gait speed (OR 5.213, 95% CI (1.397–19.457) and sarcopenia (OR 5.382, 95% CI 1.294–22.393). Others reported sarcopenia as a predictor of daily living capability in stroke patients undergoing rehabilitation (27). Skeletal muscle dysfunction is prevalent in patients suffering from chronic diseases including COPD (28), cancer (29), liver disease (30), and chronic heart failure (31). We found that chronic diseases other than stroke did not increase the incidence of sarcopenia. This may be because the major of our cohort were from the community as opposed to hospitalized patients, in which chronic diseases are more stable or general less severe.
There were some limitations in this study. Firstly, we only followed community-dwelling older adults, most of whom were healthy and had no disabilities. As such, our findings were biased towards those with a higher ASM, grip strength, gait speed and lower incidence of sarcopenia. Secondly, we failed to analyze missing cases which for any of the risk factors of sarcopenia. Thirdly, longer follow-ups are required to achieve more reliable conclusions.
Conclusions and Implications
Both muscle mass, strength and physical function decreases with age. The magnitude of this decline showed no differences across the age groups assessed. Impaired muscle strength and function occurred more frequently in the elderly than the loss of muscle mass. A high BMI was protective against a low muscle mass and sarcopenia, but represented a risk factor for low gait speed. A history of stroke was a risk factor for a low gait speed and sarcopenia. Further studies over an extended study period are now required to validate these findings.
Acknowledgments
This work was supported by Platform Construction of National Clinical Research Center for Geriatric Medicine (Supported by 1.3.5 project for disciplines of excellence, West China Hospital, Sichuan University). Item Number: ZY2017201. The financial sponsors had no role in the design, implementation, analyses, or reporting of the results. We thank the Yulin Community Health Center, Chengdu who supported the recruitment of all study participants.
Conflict of interests
The authors declare no conflict of interests.
Ethical Standards
This study was approved by the Ethics Committee of West China Hospital, Sichuan University
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