In sedentary individuals, muscle mass and strength decrease progressively after the age of 20 yr (5,10), with a peak loss observed around 65 yr of age (5,10,26). Although sarcopenia is a well-established consequence of aging (5), the loss of muscle strength appears to be a more robust determinant of age-related morbidity (7,11). For example, impaired physical function is increased 2-fold in individuals with low muscle strength but only 1.4-fold among individuals with low muscle mass (24). In addition to loss of function, low muscle strength is a predictor of type 2 diabetes (29), cardiovascular morbidity and mortality, and quality of life (25,27,29,36). The mechanisms underlying the association between muscle strength with health outcomes in older individuals remain unclear; however, they may be attributed to a propensity for cardiometabolic risk factor clustering.
Metabolic syndrome is a clustering of risk factors associated with type 2 diabetes and cardiovascular disease (17) characterized by a state of insulin resistance (18). Metabolic syndrome is more prevalent in men (9) and older individuals (9) and is associated with several modifiable lifestyle factors, including physical activity levels (20), cardiorespiratory fitness (8,16), and muscle strength (38). Our group previously reported that the prevalence and incidence of the metabolic syndrome increase in a dose–response manner, with decreasing muscle strength in middle-age men (15,16). However, the threshold of muscle strength needed to prevent metabolic syndrome with aging remains unclear.
In light of these limitations in the literature, we performed a cross-sectional analysis of the Aerobics Center Longitudinal Study data in men between 20 and 100 yr in age, aiming at identifying the minimal threshold of muscle strength associated with the presence of metabolic syndrome. A secondary aim of the study was to determine whether this association was more robust in men older than 50 yr, as previous studies by our group suggest that the association between strength and metabolic syndrome may be modified by age. Analyses were restricted to men because the metabolic syndrome is more common among men, thereby increasing the statistical power to detect and association.
Between 1981 and 1989, 7393 men between 20 and 100 yr in age participated in the Aerobics Center Longitudinal Study and provided a valid assessment of upper and lower body muscle strength. Among these men, 113 had established cardiovascular disease or stroke before testing and were excluded for the analysis and 54 were excluded because of an established diagnosis of cancer. Therefore, 7226 participants were included in the final analysis. No differences in age (mean ± SD; 42.0 ± 9.5 vs 45.8 ± 9.8 yr), body mass index (BMI; 26.0 ± 3.4 vs 26.8 ± 3.8 kg·m−2), or cardiorespiratory fitness (12.4 ± 2.5 vs 12.0 ± 2.4 METs) were noted between individuals excluded from the analysis and those who remained in the analysis. The Cooper Institute institutional review board approved the study protocol, and all participants read the consent form and provided written informed consent before data collection.
The primary outcome measure was metabolic syndrome, defined according to the National Cholesterol Education Program Adult Treatment Panel III criteria (1) as meeting three or more of the following criteria: abdominal obesity (waist girth >102 cm), high serum triglycerides (≥150 mg·dL−1), low high-density lipoprotein (HDL) cholesterol (< 40 mg·dL−1), high blood pressure (BP) (≥130 mm Hg systolic or ≥85 mm Hg diastolic or self-reported hypertension), and high fasting glucose (≥100 mg·dL−1) or self-reported diabetes. All participants completed a medical history questionnaire, which included personal and family health history, smoking habits, and alcohol intake.
Resting blood pressure was measured manually with a mercury sphygmomanometer in a sitting position. Two measures separated by 2 min were taken after the participants were sitting for at least 5 min. A third measure was taken and averaged if the two measures differed by more than 5 mm Hg. After a 12-h fast, serum triglycerides, HDL cholesterol, and plasma glucose were sampled and assayed with automated techniques. The laboratory meets the quality control standards of the U.S. Centers for Disease Control and Prevention Lipid Standardization Program.
Primary Exposure Variable
Muscle strength was assessed from a standardized strength assessment protocol using variable-resistance universal weight machines (Universal Equipment, Cedar Rapids, IA) (2). Upper and lower body strength was assessed with a one-repetition maximum (1-RM) supine bench press and seated leg press. Initial loads were set at 70% and 100% of body weight for the bench and leg press, respectively. Thereafter, load was increased by 2.27–4.54 kg (5–10 lb) until maximal effort was achieved for both bench and leg press. The 1-RM bench press and leg press were expressed by kilograms of weight lifted per kilogram of body weight as suggested by the American College of Sports Medicine (2). Other validated and precise methods of reporting muscle strength could have been used (i.e., allometric scaling); however, the 1-RM was expressed relative to body weight to facilitate translation of study findings into a practical setting. Finally, a composite of muscle strength was calculated by combining the relative 1-RM for the bench and leg press. We have previously documented a strong intraclass correlation for the 1-RM bench press and leg press (15), suggesting an acceptable reliability, and supported the use of the composite measure.
Height and body weight were measured with a standard stadiometer and physician’s scale at the nearest 0.1 cm and 0.1 kg, respectively. BMI was computed from measured height and weight with the following formula: weight (kg) / height (m2). Waist circumference was measured at the umbilicus between the iliac crest and the last lower ribs, with an anthropometric tape at the nearest 0.1 cm.
Cardiorespiratory fitness was determined with a graded maximal treadmill test to exhaustion using a modified Balke protocol as previously described (6). Participants began walking at 3.3 mph without an incline for 1 min. The treadmill grade was increased by 2% after the first minute and 1% every minute thereafter. When the participants reached 25 min, the elevation was maintained at 25% and the speed was increased by 0.2 mph every minute until exhaustion of the participants or if the physician stopped the test for medical reasons. The maximal METs of task were calculated from the total treadmill time using an age-specific formula (1.44 × (time, min) + 14.99) / 3.5 to estimate maximal oxygen uptake (31).
Leisure-time physical activity was self-reported with a validated health habits questionnaire (28) and estimated from a recollection of activities in the previous 3 months. Participant physical activity levels were stratified into one of three categories. Those reporting no exercise in the previous 3 months were given a score of 0 and were considered sedentary. Those who participated in sports, leisure-time physical activity, or walked, jogged, or ran ≤10 miles per week were given a value of 1 and were categorized as moderately active. Participants who walked, jog, or ran >10 miles per week were given a number of three and considered as vigorously active.
Smoking status and alcohol intake.
Participants were questioned about their smoking status and were categorized into categories (never smoked, former smoker, and current smoker), whereas alcohol consumption was reported in number of drinks per week.
Continuous and categorical variables are presented as mean ± SD and n (%), respectively. Muscle strength measured by bench press or leg press was reported relative to body weight in kilograms. Muscle strength was also treated as a binary outcome and low muscle strength was defined according to age-specific criteria established by the American College of Sports Medicine (ACSM) (2). Specifically, 1-RM values below the 20th percentile for an individual’s age was classified as low muscle strength. Considering there is no age-specific cut point from the ACSM for the composite strength, men below the 20th percentile for both tests were classified as low muscle strength as harmonizing the stratification with the ACSM criteria would facilitate the integration of study results into a practical setting. We tested for an interaction between muscle strength and age because participants in our sample are aged between 20 and 100 yr. The interaction was significant (P = 0.008), and therefore, analyses were run separately for men older and younger than 50 yr. We selected 50 yr as a cut point because only 4.1% of the sample were 60 yr and older, and previous studies by our group reveal that stratifying the cohort at age 50 yr provides adequate power to test for differences in metabolic syndrome between men categorized by modifiable lifestyle behaviors (35).
The following formula (z 2 = P(1 − P) / m2) was used to determine the power available to detect differences in the prevalence of metabolic syndrome between the two groups in this sample. Assuming a sample size of 1175 in men aged <50 yr in the low muscle strength group and a sample of 4510 in the high muscle strength group, we had 99% power to detect a difference of 13% in the metabolic syndrome using a chi-square test.
Independent t-tests, chi-square tests, or Fisher exact tests were performed when appropriate to identify differences between high and low muscle strength in men. Logistic regression analyses were performed to investigate the association between low muscle strength and metabolic syndrome in men after adjustment for confounding variables. Finally, receiver operating characteristic curves were created to quantify sensitivity, specificity, area under the curve, and threshold of muscle strength associated with the metabolic syndrome. Analyses were adjusted for age, drinking, smoking status, cardiorespiratory fitness, and BMI. For all statistical tests, P value ≤ 0.05 (two-tailed) was considered significant. Statistical analysis was performed with SAS version 9.2 (SAS Institute Inc., Cary, NC).
Among the 7226 men included in the final analysis, 27% were older than 50 yr (age = 55.6 ± 5.4 yr), and 23% displayed the metabolic syndrome.
Comparison of baseline characteristics between young and older men.
Baseline characteristics of participants stratified by age group are presented in Table 1. Compared with older men, young men displayed lower waist circumference (92.2 ± 10.3 vs 94.9 ± 9.5 cm, P < 0.01) and BMI (25.8 ± 3.5 vs 26.2 3.1 kg·m−2, P < 0.01). As for the metabolic profile, young men displayed lower fasting triglycerides (125.6 ± 88.9 vs 143.3 ± 97.9 mg·dL−1, P < 0.01), glucose (99.0 ± 12.2 vs 104.0 ± 19.3 mg·dL−1, P < 0.01), and systolic blood pressure (117.67± 11.6 vs 123.3 ± 14.8 mm Hg, P < 0.01). The proportion of men with the metabolic syndrome was lower in young men compared with older men (20.7% vs 31.6%, P < 0.01).
Comparisons of exposure variables between low and moderate–high muscle strength stratified by age group.
Participant characteristics stratified according to muscle strength are presented in Table 2. Among men <50 yr, individuals with low muscle strength displayed a higher BMI (27.4 ± 4.3 vs 25.4 ± 3.1 kg·m−2, P < 0.01), fasting triglycerides (143.7 ± 95.1 vs 121.1 86.7 mg·dL−1, P < 0.01), fasting glucose (101.5 ± 16.2 vs 98.4 ± 10.9 mg·dL−1, P < 0.01), and systolic and diastolic blood pressure (systolic = 119.3 ± 12.0 vs 117.4 ± 11.5 mm Hg, diastolic = 80.4 ± 9.3 vs 78.1 ± 8.8 mm Hg, P < 0.01) compared with those with moderate–high muscle strength. The proportion of participants having the metabolic syndrome was ~ 2-fold higher in men with low muscle strength (33.4% vs 17.4%, P < 0.01). Individuals with low muscle strength also had lower cardiorespiratory fitness compared with men with moderate–high muscle strength (11.3 ± 2.1 vs 13.0 ± 2.4 METs, P < 0.01). Similar results were observed in men aged ≥50 yr.
Association between low muscle strength and metabolic syndrome in men.
Table 3 presents the results of logistic regression analyses testing for differences in metabolic syndrome between the age groups after adjusting for confounding variables. In men age <50 yr, independent of age, smoking, and alcohol intake, the odds of metabolic syndrome were 2.20-fold (95% confidence interval [CI] = 1.90–2.54) greater in men with low muscle strength. This association remained significant after adjusting for BMI (1.29 95% CI = 1.10–1.53) and cardiorespiratory fitness alone (1.23 95% CI = 1.05–1.45). However, this association disappears when both variables were added simultaneously in the model (P > 0.05).
In participants age ≥50 yr, independent of age, smoking, and alcohol intake, the odds of metabolic syndrome were 2.11-fold (95% CI = 1.62–2.74) higher in men with low composite muscle strength. This association was no longer significant after adjusting for BMI.
Threshold of muscle strength associated with metabolic syndrome stratified by age group in men.
In men age <50 yr, independent of age, smoking, alcohol intake, and BMI, the adjusted lower limit of muscle strength associated with a reduced odds of the metabolic syndrome was 2.56 kg·kg−1 of body weight. The corresponding sensitivity and specificity for predicting the metabolic syndrome was 75.7 and 71.0.
In men ≥50 yr, independent of age, smoking, alcohol intake, and BMI, the adjusted lower limit of muscle strength associated with a lower odds of the metabolic syndrome was 2.50 kg·kg−1 of body weight. The corresponding sensitivity and specificity for predicting metabolic syndrome according was 73.0 and 64.3, respectively (Table 4).
The current analysis supports the concept that muscle strength is an important determinant of health outcomes in men and provides several novel findings that are relevant to the prevention of cardiometabolic diseases among men. First, similar to previous studies, we found that men with low muscle strength are more likely to display the metabolic syndrome, independent of age, BMI, or cardiorespiratory fitness. Second, we found that the cardiometabolic consequences of low muscle strength are more significant among men <50 yr of age than those in older men. Finally, we have defined thresholds of muscle strength that are associated with a significantly increased risk of metabolic syndrome. Collectively, these data reinforce the importance of muscle strength as a modifiable determinant of cardiometabolic risk in men and provide targets for practitioners.
Loss of muscle strength is emerging as an independent determinant of health outcomes, especially among older individuals (34). The results presented here support previous work demonstrating that low muscle strength is associated with metabolic syndrome (34). Interestingly, we found that this association is particularly evident in men less than 50 yr of age. This result is surprising considering that metabolic syndrome is more common among older individuals (9) and muscle strength decreases significantly with aging (5,10,26). Previous studies have shown that handgrip strength is associated with cardiometabolic risk (34,40) and mortality (22). The results presented here extend these findings by demonstrating that overall muscle strength is associated with metabolic syndrome, which is not trivial, as a composite measure of lower and upper body strength is a better predictor of health than handgrip strength (22). Furthermore, studies performed in older population failed to control for important confounding variables. The current study overcomes these limitations as we adjusted for adiposity and fitness to investigate the relationship between muscle strength measured by common exercises in a large population of men. The results presented here suggest that men with muscle strength below the 20th percentile for age are at a greater risk for the metabolic syndrome especially in young men.
Muscle strength thresholds have been identified for measures of low cardiorespiratory fitness (3), insulinemic profile (4), independence (30,33), and activities of daily living in older individuals (12). Very few studies have identified a threshold of muscle strength associated with health outcomes in adults (3,4,39), in particular, the metabolic syndrome (39). Wilkerson et al. (2010) (39) found that leg muscle strength <2.93 N·m·kg−1 was associated with an increase likelihood of metabolic syndrome; however, they failed to adjust for cardiorespiratory fitness. In our study, we found that a composite strength <2.86 kg·kg−1 of body weight was associated with the presence of metabolic syndrome in men age <50 yr independent of cardiorespiratory fitness. The sensitivity and the specificity observed for this threshold were 74.3 and 66.9, respectively, whereas in the study performed by Wilkerson et al. (2010) (39), the sensitivity and the specificity of this muscle strength threshold were 92.0 and 64.0, respectively. The lower sensitivity and specificity reported in our study might be related to the differences in age (38 vs 19 yr), the cardiorespiratory fitness levels of the populations studied (43 vs 30 mL·kg−1·min−1), the methods used to assess muscle strength (Biodex vs leg and bench press), and the use of a composite measure of muscle strength in the model (23). The data presented in the current study extend these observations by delineating thresholds of muscle strength for commonly used exercises that are associated with chronic disease risk in independent men. The data reinforce the concept that muscle strength may be an important modifiable lifestyle factor for cardiometabolic disease risk assessment, similar to physical activity, cardiorespiratory fitness, and healthy dietary patterns (19,32).
Recent experimental trials of resistance training support observational studies by demonstrating that increasing muscle strength improves cardiometabolic risk profiles (37). In fact, several resistance training trials have demonstrated clinically relevant improvements in glycemic control and blood pressure in adults with the metabolic syndrome (38) and type 2 diabetes (21). These effects appear to be related in part to gains in muscle strength rather than changes in muscle mass (13,14) and are comparable with the improvements seen with aerobic exercise alone. The data presented here support these findings and highlight the importance of muscle strength for achieving health benefits in men <50 yr of age.
The strength of this study includes a large sample size, two commonly used exercises of muscle strength, and a broad age range. Despite these strengths, there are some limitations that need to be highlighted. First, the test of muscle strength used was performed in relatively healthy individuals, without cardiovascular disease. Therefore, the generalization of our results is limited to healthy younger and older men. Second, the thresholds proposed by the current study were developed from measurements made on Universal fitness equipment. Therefore, the thresholds identified may not be generalizable to other devices such as free weights that are commonly used for training and measurement. Third, the stratification of the cohort at age 50 yr was based on power and therefore may not reflect the age at which the association between muscle strength and metabolic syndrome become more robust. Fourth, although we were able to adjust for several confounding variables, we were unable to adjust for medication use and the level of hydration, which may affect muscle strength and, therefore, could have influenced study results. Finally, because of the cross-sectional nature of the study design, we are unable to draw conclusions regarding the causality of the associations observed.
In summary, we found that low muscle strength is associated with an increased likelihood of metabolic syndrome, particularly among men <50 yr of age. A threshold of muscle strength also exists, which may help practitioners (i.e., exercise physiologists) identify high-risk patients or serve as targets for exercise training programs designed to reduce the risk of metabolic syndrome in men. Future studies should examine the temporal nature of the association between thresholds of muscle strength and metabolic syndrome and/or determine whether increasing muscle strength in older men reduces the likelihood of metabolic syndrome.
This research was supported by the National Institutes of Health (grant nos. AG06945 and HL62508). The Canadian Institutes of Health Research and the Manitoba Health Research Council support Dr. Martin Sénéchal and Dr. Jonathan M. McGavock. Dr. D.C. Lee was supported by a postdoctoral fellowship from an unrestricted research grant from The Coca-Cola Company.
The authors thank Kenneth H. Cooper, M.D., for establishing the Aerobics Center Longitudinal Study, the physicians and technicians of the Cooper Clinic for collecting the baseline data, and Margo Simmons and her staff for data entry.
The funding organizations played no role in the design and conduct of the study; the collection, management, analysis, and interpretation of data; or the preparation, review, or approval of the manuscript. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
The author reports no conflicts of interests.
The results of the present study do not constitute endorsement by the American College of Sports Medicine.
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