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1 Institute for Research in Extramural Medicine, VU University Medical Center, Amsterdam, The Netherlands.
2 National Institute on Aging, Laboratory of Epidemiology, Demography, and Biometry, Bethesda, Maryland.
3 Department of Medicine, University of Pittsburgh, Pennsylvania.
4 Sticht Center on Aging, Wake Forest University School of Medicine, Winston-Salem, North Carolina.
5 Division of Geriatric Medicine, University of Pittsburgh.
6 Prevention Sciences Group, University of California, San Francisco.
7 National Institute on Aging, Gerontology Research Center, Baltimore, Maryland.
Address correspondence to Dr. M. Visser, Institute for Research in Extramural Medicine, VU University Medical Center, Van der Boechorststraat 7, 1081 BT Amsterdam, The Netherlands. E-mail: m.visser{at}vumc.nl
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Abstract |
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Methods. Our study cohort included 3075 well-functioning black and white men and women aged 70–79 years participating in the Health, Aging, and Body Composition study. Participants were followed for 2.5 years. Muscle cross-sectional area and muscle tissue attenuation (a measure of fat infiltration) were measured by computed tomography at the mid-thigh, and knee extensor strength by using a KinCom dynamometer. Incident mobility limitation was defined as two consecutive self-reports of any difficulty walking one-quarter mile or climbing 10 steps.
Results. Mobility limitations were developed by 22.3% of the men and by 31.8% of the women. Cox's proportional hazards models, adjusting for demographic, lifestyle, and health factors, showed a hazard ratio of 1.90 [95% confidence interval (CI), 1.27–2.84] in men and 1.68 (95% CI, 1.23–2.31) in women for the lowest compared to the highest quartile of muscle area (p <.01 for trend). Results for muscle strength were 2.02 (95% CI, 1.39–2.94) and 1.91 (95% CI, 1.41–2.58), p <.001 trend, and for muscle attenuation were 1.91 (95% CI, 1.31–2.83) and 1.68 (95% CI, 1.20–2.35), p <.01 for trend. When included in one model, only muscle attenuation and muscle strength independently predicted mobility limitation (p <.05). Among men and women, associations were similar for blacks and whites.
Conclusion. Lower muscle mass (smaller cross-sectional thigh muscle area), greater fat infiltration into the muscle, and lower knee extensor muscle strength are associated with increased risk of mobility loss in older men and women. The association between low muscle mass and functional decline seems to be a function of underlying muscle strength.
Recent cross-sectional studies have shown that low muscle mass is associated with poor functional performance (3,4) and self-reported disability (4–6). Because muscle mass is highly correlated with muscle strength (7), the observed relationship between muscle mass and physical function could be simply a function of muscle strength. Whether low muscle mass itself contributes to decline in physical function, or whether this association is mediated by muscle strength remains unclear. Moreover, this research question has never been addressed using a prospective study design.
With aging, declines in both muscle mass and muscle strength are well documented (8–10). In addition, the composition of muscle changes (11–13) with increasing infiltration of fat. Recent studies by our group (3,14) have shown a cross-sectional association between the amount of fat infiltration into the muscle, determined by the attenuation of mid-thigh muscle tissue using computed tomography, and muscle strength and mobility performance. The increasing fat infiltration into the muscle with aging may be an important, if not central, aspect of sarcopenia (the loss of muscle mass and muscle strength with aging; 15). Whether greater fat infiltration into the muscle is prognostic for future mobility limitations, independent of muscle strength, has never been studied.
Muscle mass, muscle strength, and fat infiltration into the muscle can be modified by behavioral and pharmacological interventions in older persons. Hormone supplementation, nutritional interventions, and strength and exercise training are most often used to increase muscle mass and strength (16–19), and may decrease the amount of fat infiltration into the muscle (17,20). To prevent or slow the decline in physical function with aging, it is important to know which muscle components independently contribute to functional loss in old age. This information will help to optimize intervention strategies focused on the muscles, as different aspects of muscle integrity may respond to different treatments.
This prospective study aims to investigate the independent and joint contributions of low muscle mass, low muscle strength, and greater fat infiltration into the muscle on incident mobility limitations in older men and women.
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METHODS |
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Of the 3075 participants, we excluded those with missing data on incident mobility limitations (n = 7), muscle area or muscle attenuation (n = 53), total body fat mass (n = 14), or muscle strength (n = 370, see muscle strength section). A total of 2631 participants (85.6% of original cohort, 1286 men and 1345 women) were available for analysis, of whom 117 died during the follow-up period used for this analysis.
Incident Mobility Limitations
Mobility limitations were assessed by self-reported level of difficulty walking one-quarter mile and climbing 10 steps without resting. Response categories were: no difficulty, a little difficulty, some difficulty, a lot of difficulty, and unable to do. Because of the eligibility criteria of the study, all participants had no self-reported mobility limitations at baseline. The 2.5-year incidence of mobility limitations was assessed using information collected during the Year 2 and Year 3 clinic examinations and the 6-, 18-, and 30-month telephone contacts. Persistent mobility limitation was based on two consecutive reports of either having any difficulty walking one-quarter mile or having any difficulty climbing 10 steps without resting.
Muscle Mass
The cross-sectional area of muscle in both thighs was used as a measure of muscle mass. Muscle area was measured by computed tomography (Memphis clinic site: Somatom Plus 4, Siemens, Erlangen, Germany, or PQ 2000S, Marconi Medical Systems, Cleveland, OH; at Pittsburgh clinic site: 9800 Advantage, General Electric, Milwaukee, WI) as described previously (3). In short, a single 10-mm-thick axial image (120 kVp, 200–250 mA) of both thighs was obtained at the midpoint of the distance between the medial edge of the greater trochanter and the intercondyloid fossa of the right leg. For each participant, the determination of soft tissue type was made using the bimodal image distribution histogram resulting from the distribution numbers in adipose tissue and muscle tissue. Intermuscular and visible intramuscular adipose tissue was separated from subcutaneous adipose tissue by drawing a line along the deep fascial plane surrounding the thigh muscles. The total area of nonadipose, nonbone tissue within the deep fascial plane was used as a measure of muscle area (cm2). Reproducibility of muscle mass by computed tomography was assessed by reanalyzing a 5% convenience sample of the study cohort, showing a coefficient of variation of less than 5%.
Muscle Strength
The maximal isokinetic strength of the knee extensors (Nm) was assessed by a KinCom 125 AP Dynamometer (Chattanooga, TN) at 60°/s and was calculated from the average of three reproducible and acceptable trials of a maximum of six trials. Participants with a systolic blood pressure 
200 mmHg, diastolic blood pressure 110 mmHg, or who reported a history of cerebral aneurysm, cerebral bleeding, bilateral total knee replacement, or severe bilateral knee pain were excluded from testing (12.7% of original cohort).
Muscle Fat Infiltration
The mean attenuation (Hounsfield Units, HU) of thigh muscle tissue obtained by computed tomography, excluding intermuscular and intramuscular adipose tissue lying interior to the deep fascial plane surrounding the muscle, was used as an indicator of fat infiltration into the muscle. Lower muscle attenuation indicates greater fat infiltration. The validity of this noninvasive measure has been previously established (21). In 45 men and women between 25 and 49 years old with a BMI ranging from 18.5 to 35.9 kg/m2, the correlation between muscle attenuation and muscle fiber lipid content determined with histological Oil Red O staining was –0.43 (p <.01). In a subset of 19 volunteers, the correlation between muscle attenuation and triglyceride content in percutaneous biopsy specimens from vastus lateralis was –0.58 (p =.02) (21). Reproducibility of muscle attenuation was assessed by reanalyzing a 5% convenience sample of the study cohort, showing a coefficient of variation of less than 5%.
Covariates
Covariates included demographic variables (clinic site, age, race, sex, and education), lifestyle indicators (physical activity, smoking status, alcohol consumption, total body fat mass, and body height) and health status variables (prevalent disease, self-rated health, depression, and cognitive status). Education was categorized into three groups: less than high school, high school graduate, and postsecondary school. Physical activity of the past 7 days was assessed by an interviewer-administered questionnaire. The time spent climbing stairs, walking for exercise, walking for other purposes, aerobics, weight or circuit training, high intensity exercise activities, and moderate intensity exercise activities was obtained as well as information on the intensity level at which each activity was carried out. A metabolic equivalent value was assigned to each activity–intensity combination and was used to calculate the number of kilocalories per week per kilogram of body weight spent on that activity (22). For each participant, the scores of all performed activities were summed and multiplied by body weight to create an overall physical activity score in kilocalories per week. Smoking status was categorized as current, former, or never smoker. Alcohol consumption in a typical week during the past 12 months was categorized as none, 1–7 per week, or >7 per week. Total body fat mass was included as a covariate, because higher fat mass is associated with greater muscle mass (23), greater muscle strength (24), but poorer physical function (23). Total body fat mass was assessed using fan-beam dual-energy x-ray absorptiometry (software version 8.21, QDR4500A; Hologic, Waltham, MA). Body height was measured to the nearest millimeter using a wall-mounted stadiometer, and body weight was assessed using a standard balance beam scale. Body mass index (BMI) was calculated as body weight (kg) divided by height (m) squared. Current presence of disease was determined using self-reported physician-diagnosed disease information, clinic data, and medication use. The diseases included individually in the analysis were cerebrovascular disease (self-reported history of stroke, transient ischemic attack, or carotid endarterectomy), coronary heart disease (self-reported history of coronary artery bypass graft/percutaneous transarterial coronary angioplasty or coronary heart disease), peripheral arterial disease (self-reported history of claudication or history of lower extremity bypass/angioplasty), congestive heart failure (self-reported history of congestive heart failure), hypertension (systolic blood pressure 140 or diastolic blood pressure 90 mmHg), current symptomatic hip or knee osteoarthritis (self-reported history of knee/hip osteoarthritis and a history of knee/hip symptoms in the past year), osteoporosis (self-reported history of osteoporosis or use of osteoporosis medication), pulmonary disease (self-reported history of current asthma, chronic bronchitis, emphysema, or chronic obstructive pulmonary disease, and medication use), diabetes mellitus (self-reported diagnosis of diabetes and medication use, or a fasting glucose concentration 126 mmol/L), and depression (use of antidepressants). Self-rated health was categorized as: excellent/very good, good, or fair/poor. Cognitive status was assessed using the Teng-modified Mini-Mental Status Examination (25).
Statistical Analyses
Analyses were performed for men and women separately using SAS software (SAS Institute, Cary, NC). Each muscle parameter was categorized by race- and sex-specific quartiles; the highest quartile served as the reference group. When a threshold in the relationship was suspected, additional analyses were performed using race-and sex-specific deciles. The main outcome of the study was incident mobility limitations. Person-time for each participant was calculated from the date of the baseline examination to the date of the first of the two consecutive self-reports of mobility limitations, date of death, or date of the last study contact, whichever came first. Cox's proportional hazards models were used to test the association of each muscle parameter with incident mobility limitations, adjusting for the selected covariates. The results are presented as hazard ratios with 95% confidence intervals (CIs). To test for trend, we ordered the muscle parameter quartiles from lowest to highest, and included this variable in the models as a linear variable. To investigate which muscle parameters were independently associated with incident mobility limitations, we used a Cox's proportional hazards model that included all muscle parameters and the selected covariates. The results from log(–log) plots and time interactions terms indicated that the proportional hazards model assumption was valid in all models. Potential interaction between the muscle parameters and race was investigated in stratified analyses by sex, and was tested using the muscle parameter * race product term in models stratified by sex.
A comparison of the 444 participants excluded from the present analysis with the 2631 who were included showed that those excluded were slightly older (74.0 vs 73.6 years), were more likely to be black (50.5% vs 40.2%), were less physically active (27.7% vs 20.6% in the low-activity group), had a higher BMI (28.0 vs 27.3 kg/m2), had poorer cognitive scores (87.8 vs 89.9 on the Mini-Mental State Examination), had greater fat infiltration into the muscle (33.9 vs 35.6 HU), had more prevalent disease (p <.05), and were less likely to rate their health as excellent/very good (32.0% vs 45.9%). No significant differences were observed for sex, muscle mass, muscle strength (when available), and total body fat mass.
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RESULTS |
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DISCUSSION |
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We used computed tomography attenuation values of muscle tissue as indicators of fat infiltration into the muscle. A greater fat infiltration into the mid-thigh muscle was a strong predictor of incident mobility limitations, confirming previous cross-sectional associations by our group. Increasing fat infiltration into the muscle with aging may be a crucial aspect of sarcopenia influencing functional status in old age. Fat infiltration into the muscle is known to be positively correlated with overall body fatness (30–32). Moreover, our group previously showed a cross-sectional association between greater fat infiltration into the muscle and lower muscle strength (14). However, after adjustment for total body fat mass and knee extensor muscle strength, greater fat infiltration into the mid-thigh muscle remained an independent risk factor for incident mobility limitations. It remains unclear what mechanism(s) might explain the observed, independent association. Muscle attenuation may be a marker of functional aspects of the muscle other than muscle strength, such as muscle metabolism or neural factors, or may be the result of early-life lifestyle (e.g., physical activity history). Alternatively, knee extensor muscle strength may not be representative of strength in the collateral leg muscle groups and/or may not fully capture the true strength of the muscle because it is a volitional measure, explaining why muscle strength did not mediate the association between muscle attenuation and mobility limitation.
As stated in the Methods section, we included total body fat mass in all regression models because it is positively associated with muscle mass and muscle strength, and negatively associated with physical function (3,23,24). Of interest was our observation that total body fat mass was a strong predictor of incident mobility limitations in women but not in men. In women, the hazard ratios for mobility limitations were 1.0 (reference), 1.57 (95% CI, 1.13–2.19), 1.75 (95% CI, 1.24–2.47), and 2.73 (95% CI, 1.91–3.91) with increasing quartile of total body fat mass. In men, the corresponding hazard ratios were 1.0 (reference), 0.96 (95% CI, 0.66–1.39), 1.14 (95% CI, 0.76–1.70), and 1.18 (95% CI, 0.77–1.80). This association was independent of the three muscle parameters. The results of the present study suggest that interventions designed to prevent or delay disability should focus not only on increasing muscle strength, but also on optimizing body composition, especially in older women.
The prevalence and incidence of functional limitation is generally higher in women and blacks compared to men and whites (33,34). Although socioeconomic and health-related factors may (partly) explain these differences, sex and race differences in muscle integrity and total body fat mass may also contribute to the difference in functional status in old age. In our study, women had less muscle mass, greater fat infiltration into the muscle, lower muscle strength, and more total body fat compared to men. Similarly, blacks had a greater fat infiltration into the muscle and more body fat than whites.
Some limitations of the study need to be addressed. Due to the strict exclusion criteria for the strength-testing procedure, a relatively healthier sample may have been included in the statistical analyses. However, when we repeated the analyses for muscle area and muscle attenuation including persons with missing muscle strength data, the associations were similar. Including self-reported weight loss greater than 2.3 kg (5 lbs) in the 12 months prior to the start of the study also did not markedly affect the observed hazard ratios. Incident mobility limitation was based on self-report; this subjective measure may have been influenced by cognitive status, perceived mastery, and depressive symptoms (35,36) leading to potential misclassification (26). Because the study participants had to report mobility limitations on two consecutive contacts, our study outcome is unlikely to be influenced by short-term fluctuations in mobility. Future studies should include prospective measurements of objective function tests and a longer follow-up time to complement our results. Because the study cohort was selected to have no self-reported mobility limitation at baseline, the observed associations may be an underestimation of the true associations in the general population. Muscle attenuation was used as an indicator of fat infiltration into the muscle. No muscle biopsies were available in the study to directly assess the fat content of muscle tissue. However, the fat and triglyceride content of the vastus lateralis has been shown to be negatively associated with mid-thigh muscle attenuation (21). In addition, good correlations between tissue attenuation measured by computed tomography and histological or chemical assessment of tissue fat content has been observed for other organs (37).
Conclusion
Lower muscle mass (smaller cross-sectional muscle area), lower muscle strength, and greater fat infiltration into the muscle are associated with incident mobility limitations in older men and women. The association between low muscle mass and incident mobility limitations seems to be a function of lower muscle strength.
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Acknowledgments |
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Footnotes |
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Received July 31, 2003
Accepted January 2, 2004
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