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METHODOLOGICAL ISSUES AND THE IMPACT OF AGE STRATIFICATION ON THE PROPORTION OF PARTICIPANTS WITH LOW APPENDICULAR LEAN MASS WHEN ADJUSTING FOR HEIGHT AND FAT MASS USING LINEAR REGRESSION: RESULTS FROM THE CANADIAN LONGITUDINAL STUDY ON AGING

 

A.J. Mayhew1,2,3, S.M. Phillips4, N. Sohel1,2,3, L. Thabane1,5, P.D. McNicholas6, R.J. de Souza1,7, G. Parise4, P. Raina1,2,3

 

1. Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada; 2. Labarge Centre for Mobility in Aging, Hamilton, Ontario, Canada; 3. McMaster Institute for Research on Aging, Hamilton, Ontario, Canada; 4. Department of Kinesiology, McMaster University, Hamilton, Ontario, Canada; 5. Biostatistics Unit, Research Institute at St Joes, St. Joseph’s Healthcare Hamilton, Hamilton, Ontario, Canada; 6. Department of Mathematics & Statistics, McMaster University, Hamilton, Ontario, Canada; 7. Population Genomics Program, Chanchlani Research Centre, McMaster University, Hamilton, Ontario, Canada.
Corresponding author: Parminder Raina, PhD, Department of Health Research Methods, Evidence, and Impact, McMaster University, MIP 309A, 175 Longwood Road South, Hamilton, Ontario, L8P 0A1, Canada, Tel: 905 525 9140 x 22197, e-mail: praina@mcmaster.ca

J Frailty Aging 2020;in press
Published online September 29, 2020, http://dx.doi.org/10.14283/jfa.2020.48

 


Abstract

Background: Using residual values calculated from models regressing appendicular lean mass on fat mass and height is one of several suggested strategies for adjusting appendicular lean mass for body size when measuring sarcopenia. However, special consideration is required when using this technique in different subgroups in order to capture the correct individuals as sarcopenic. Objectives: To provide guidance about how to conduct stratified analyses for the regression adjustment technique using age groups as an example. Design: Cross-sectional study. Setting: Data collected at baseline (2012-2015) for the Canadian Longitudinal Study on Aging. Participants: Community dwelling participants of European descent aged 45 to 85 years (n=25,399). Measurements: Appendicular lean mass, height, and weight were measured. Sex-specific residuals were calculated in participants before and after stratifying participants by age group (45-54, 55-64, 65-74, 75-85 years). Cut offs corresponding to the sex-specific 20th percentile residual values in participants ≥65 years were determined first in the residuals calculated in all participants and residuals calculated in only those aged ≥65 years. For each set of cut offs, the percentage of age and sex-stratified participants with low appendicular lean mass were compared for the residuals calculated in all participants and the residuals calculated after stratifying by age. Results: In 12,622 males and 12,737 females, regardless of the cut off used, the percentage of participants with low appendicular lean mass decreased with age when residuals were calculated after age stratification. When the residuals were calculated in all participants, the percentage of participants with sarcopenia increased from the youngest to the oldest age groups. Conclusions: Sex-specific residuals in all participants should be calculated prior to stratifying the sample by age group, or other stratification variables, for the purposes of developing appendicular lean mass cut offs or subgroup analyses.

Key words: Appendicular lean mass, CLSA, muscle, residuals, sarcopenia, skeletal muscles.


 

Introduction

Sarcopenia refers to the decline in muscle mass, muscle strength, and muscle function that occurs with age (1). It is associated with an increased risk of falls and fractures, activities of daily living limitations, and mortality (2–5). Given the profound individual and societal costs of sarcopenia, there has been substantial interest in finding ways to prevent and treat sarcopenia. However, the field of sarcopenia research has been hindered by the lack of a clear definition and standardized diagnostic criteria (6).
Four expert-group definitions for sarcopenia define sarcopenia as the combination of low muscle mass, typically measured as appendicular lean mass (ALM), with either low muscle strength or impaired physical performance (6–10). There is a consensus among the definitions that ALM should be adjusted for body size due to the strong correlation between ALM with height and weight, however there is little agreement about which measure of body size should be utilized (6, 11). Four techniques are recommended; dividing by height squared, body mass, body mass index (BMI), and regressing ALM on height and fat mass (6–10). Of these methods, regressing ALM on height and fat mass may most accurately identify individuals with low ALM as it adjusts for two measures of body size whereas the other techniques only adjust for one measure of body size (12). This technique involves creating a regression model (ALM = intercept + height (m2) + fat mass (kg)) in a sample of individuals. For each individual, a predicted value of ALM is calculated based on the regression equation. Subtracting the estimated value of ALM from the actual value of ALM for each person provides a residual value. Positive residual values indicate that the individual has more ALM than would be expected given their height and weight and negative residual values indicate the individual has less ALM than would be expected given their height and weight.
Unlike adjusting ALM by height, weight, or BMI which are done at the individual level and are not influenced by other participants, calculating residuals is dependent on the sample. For height, weight, and BMI adjustment, the adjusted values refer to the same amount of ALM relative to the anthropometric measure adjusted for regardless of the person or sample. In contrast, the residual value for each person is dependent on the regression equation which in turn is dependent on the distribution of the variables in the sample. Consequently, even if low ALM offs are developed in a random, population-based sample, they cannot be appropriately applied to another population unless the two samples have identical joint distributions of ALM, fat mass, and height. Due to the unavailability of cut offs, studies that have investigated sarcopenia using the residual adjustment technique have considered the lowest quintile of sex-specific residual values as sarcopenic (13–19). However, a consequence of using the lowest quintile is that sarcopenia prevalence is the same for all studies, regardless of age, which is problematic for a condition for which the prevalence increases with age. This poses additional challenges for studies with a wide range of ages which want to conduct age stratified analyses.
To our knowledge, there has not been any discussion in the literature about the implications of stratifying a sample by age when applying the residual technique. We aimed to provide the necessary guidance for how to handle age stratification when calculating residual values for ALM adjusted for height and fat mass.

 

Methods

Setting and study population

We used data from the Canadian Longitudinal Study on Aging (CLSA), a national longitudinal research platform. There were 51,338 participants aged 45 to 85 years recruited from the ten Canadian provinces at baseline. Participants had to be physically and cognitively able to participate on their own as well as not living in institutions such as long term care to be eligible for the study. The participants were recruited in to one of two cohorts, the Tracking cohort and the Comprehensive cohort. Participants from all ten provinces were randomly selected for the Tracking cohort (n=21,241) and were interviewed by telephone. The Comprehensive cohort participants (n=30,097) lived within 25-50kg of one of 11 Data Collection Sites located in seven provinces. The Comprehensive cohort participants were interviewed in-person and also completed in-depth physical assessments and provided blood and urine samples. Details on the study design have been described elsewhere (20). Only participants from the Comprehensive cohort (n=30,097) were included in these analyses as the physical assessment data was required. The sample was further limited to those identifying as European as ALM, muscle strength, and physical function have shown to vary by ethnicity (21–23). This project uses data collected at baseline (September 2011 to May 2015). Ethics approval was received by the Hamilton Research Ethics Board (#2686).

Clinical measurements

Trained research assistants collected data on height, weight, and muscle mass. Height was measured twice using a stadiometer and the mean value of the two measurements was used in the analyses. The Hologic Discovery ATM DXA machine was calibrated daily using a spine phantom, weekly using a whole body step phantom, and yearly using a gold standard phantom. DXA provides a valid measures of ALM and fat mass when compared to the gold standards of computerized tomography (CT) and magnetic resonance imaging (MRI) scans (24, 25).
All analyses were stratified by sex. We used multiple linear regression models with ALM as the dependent variable and height (m2) and fat mass (kg) as the independent variables to estimate the predicted value of ALM for each participant. The residual values were calculated as the predicted value of ALM subtracted from the actual value of ALM. To test the impact of age stratification on the residual values, we first calculated residuals based on the regression model including participants aged 45 to 85 years. We then calculated residuals based on regression models run separately for each age strata (45 to 54, 55 to 64, 65 to 74, and 75 to 85 years). We followed the EWGSOP recommendation of using the lowest sex-specific 20th percentile of residual values as the cut off for low ALM (7). We chose to limit the sample for calculating cut offs to participants ≥65 years based on guidance from the literature (7). To explore the impact of age stratification on the values of the residual cut offs, we determined the cut offs for the residuals in the model that included all participants aged 45 to 85 years, as well as for residual values based on a model that only included participants 65 years and older.
The cut-offs detertmined using the non-age stratified residuals and the residuals calculated in just participants aged ≥65 years were applied to the residuals calculated in the whole sample and the age-stratified residuals. Therefore, there were four different strategies used to identify participants: Strategy 1: all residuals calculated in all participant; Strategy 2: individual residuals calculated in all participants, cut offs developed in participants ≥65 years; Strategy 3: individual residuals calculated in specific age groups, cut offs developed in all participants; Strategy 4: individual residuals calculated in specific age groups, cut offs developed in participants ≥65 years.

Statistical anaylses

Of the 30,097 participants at baseline, 1324 were excluded as they were non-European, 3356 were excluded for missing ALM, grip strength, gait speed, or BMI data resulting in a final sample size of 25,399 participants. All statistical analyses were completed using SAS (version 12.3).
The percentage of age and sex-stratified participants categorized as having low ALM by each of the four strategies for handling age-stratification for the development of cut offs and individual residual values were determined. Bootstrap percentile confidence intervals were calculated for each estimate. This technique involves resampling with replacement and calculating the proportion of participants with sarcopenia for each resample (26). We resampled 10,000 times and identified the values corresponding to the 2.5th and 97.5th percentiles of the 10,000 resamples in order to estimate the 95% confidence interval. This technique has the advantage of only including valid values of parameter estimates in the confidence interval (26).

 

Results

Participant characteristics

The mean (SD) age of the participants was 62.8 (10.2) years and 49.9% of the sample were males (Table 1). Younger males and females had greater mean (SD) ALM: 27.2kg (4.2) and 17.9kg (3.4), grip strength: 47.3kg (9.1) and 28.6kg (5.6), and gait speed: 1.03m/s (0.18) and 1.02m/s (0.19) compared to older males and females (ALM: 24.4kg (3.7) and 16.3kg (2.9), grip strength: 39.4kg (8.5) and 23.6kg (5.2), and gait speed: 0.94m/s (0.19) and 0.90m/s (0.19).

Table 1
Participant characteristics

1. Heart disease includes angina, myocardial infarction, and heart disease; 2. Cardiovascular disease includes stroke and transient ischemic attack; 3. Neurological conditions include multiple sclerosis, epilepsy, migraine headaches, and Parkinson’s Disease
 

Distribution of residuals

The overall distribution of the residual values was calculated in all participants versus calculating the residuals in age-stratified groups. In males, the mean (SD) for all participants was 0 (2.90), while the mean of the residuals for all age-stratified residuals pooled together was 0 (3.13). The corresponding values were 0 (2.08) and 0 (2.16) in females. However, the distribution of the data within each age group was markedly different. In both males and females, when the residuals were calculated after stratifying the sample by age, the residuals of each age group had a mean of 0. In contrast, when the residuals were calculated in the whole sample, there was a gradient of mean values when stratified by age group. The mean residual value for males 45 to 54 years was 1.36 and for females was 0.84 which decreased to -1.95 in males and -0.67 in females aged 75 to 85 years (Supplementary Appendix 1).

Muscle mass cut off estimates

The lowest 20th percentile cut offs corresponded to -3.51 for males and -2.15 for females when the residual values were calculated all participants, then restricted to participants aged ≥65 years. When the residuals were calculated in only participants ≥65 years, the 20th percentile cut offs were -2.23 for males and -1.58 for females.

Low muscle mass prevalence

The lower cut offs determined using the non-age stratified residual values of -3.51 for males and -2.23 for females identified fewer participants as having low muscle mass compared to the age-stratified residual values of -2.15 for males and -1.58 for females (Figure 1). For these cut offs, the prevalence of low muscle mass was 12.3% for males and 14.6% for females when the individual residuals were not age stratified (Strategy 1) and 10.3% for males and 13.8% for females when the individual residuals were age stratified (Strategy 3). The cut offs developed using residual values calculated in only participants ≥65 years, identified 23.8% of males and 22.8% of females as having low ALM when the non-age stratified residual values (Strategy 2) and 21.7% of males and 21.9% of females as having low ALM when the age-stratified values were used (Strategy 4).
When looking at the percentage of people with low muscle mass within each age group, the percentage of males and females with low muscle mass increased with age when the individual residuals were not age-stratified, regardless of the cut offs used (Strategy 1 and Strategy 2). In contrast, the percentage of males and females with low muscle mass decreased with age when the age-stratified residuals were used (Strategy 3 and Strategy 4).

Figure 1
Percentage of participants with low ALM adjusted for height and fat mass stratified by age group and sex

 

Discussion

To our knowledge, this is the first study to investigate the implications of age stratification when using the residual values for ALM after regressing on height and fat mass. We determined that residual values should be calculated in all participants before stratifying by age for the purposes of subgroup analyses or developing muscle mass cut offs (Strategy 1).
Stratifying the sample by age prior to calculating residuals for the purpose of subgroup analyses based on age or for developing cut offs proved problematic. When the sample was stratified by age before calculating the residuals (Strategy 3 and Strategy 4), the percentage of participants with low ALM decreased from the youngest to the oldest age groups (Figure 1) because of how the residuals are calculated. The maximum likelihood estimation technique used in linear regression to calculate the residuals requires that the sum of the residuals for the sample to equal zero. When the sample was stratified by age before calculating the residuals, the mean value of the residuals for each age group was zero. However, the standard deviation decreased with age (Supplementary Appendix 1). The greater the standard deviation for the age group, the more participants were below the low ALM cut off and therefore the higher the percentage of people with low ALM.
The problems we encountered stratifying our sample by age before calculating the residuals extend to any situation in which residuals calculated in one sample are combined or applied to another sample. Residual values are sample dependent and therefore unless two groups of participants have identical joint distributions of ALM, height, and fat mass, the residuals from one study will not identify people with the same amount of ALM relative to height and fat mass. This means that cut offs for the residual technique, even if developed in a population-based random sample with cut offs validated against relevant health outcomes, cannot be meaningfully applied to another sample. For this reason, in our analyses Strategy 1 which calculates the residuals in all participants before limiting to those ≥65 years to determine the lowest quintile is the appropriate strategy.
To resolve the issue of residual values and corresponding cut offs not being comparable between studies, prediction equations, similar to those that have been used for lung function can be developed (27). A sample of representative older adults could be used to create sex-specific prediction equations for ALM based on height and fat mass. Variables such as age, ethnicity, and other body composition variables could be explored for inclusion in the equation, as well as possible interactions between variables. These equations would allow for results to be meaningfully compared between studies and would also allow clinicians to use this technique to diagnose low ALM in individuals. Low ALM cut offs, ideally determined by assessing which cut offs best predict health outcomes relevant to sarcopenia, could be established and used differents studies.
To our knowledge, only one study has assessed the relationship between low ALM operationalized using the residual adjustment technique with health (12, 28). Cawthon et al. observed that low ALM adjusted for height and fat mass was significantly associated with risk of functional limitations and mortality, but not recurrent falls or hip fractures (12). Studies operationalizing sarcopenia as low ALM only often do not find significant associations with health, therefore the associations found with functional limitations and mortality are particularly notable (12, 29, 30). Given this evidence as well as the strong face validity for adjusting ALM simultaneously for height and fat mass, future studies are required to determine if adjusting ALM for height and fat mass, alone and in combination with muscle strength or function, better identifies people at poor risk for health compared to the other adjustment techniques.
In conclusion, adjusting ALM for height and fat mass using the regression technique is a promising method of operationalizing low ALM that warrants greater inclusion in future sarcopenia studies. In this study, we show that to appropriately apply the residual technique to a stratified sample, the regression equation must be calculated in all participants before stratifying the sample in order to identify the correct individuals as sarcopenic.

 
Acknowledgements: This research was made possible using the data/biospecimens collected by the Canadian Longitudinal Study on Aging (CLSA). Funding for the Canadian Longitudinal Study on Aging (CLSA) is provided by the Government of Canada through the Canadian Institutes of Health Research (CIHR) under grant reference: LSA 94473 and the Canada Foundation for Innovation. This research has been conducted using the CLSA dataset, Baseline Comprehensive Dataset version 4.0, under Application Number 160608. The CLSA is led by Drs. Parminder Raina, Christina Wolfson and Susan Kirkland. The opinions expressed in this manuscript are the author’s own and do not reflect the views of the Canadian Longitudinal Study on Aging.
Funding: No funding to report.
Conflict of interest: None declared
Author contributions: AJM, SMP, and PR conceptualized this project with feedback from NS, LT, PDM, RJd and GP. AJM and NS completed the analysis of the data. AJM, NS, and PR interpreted the results. AJM completed the draft of the manuscript with revisions from the remaining authors. All authors provided approval for the final version to be published and agree to be accountable for all aspects of the work.
Ethical standards: Ethics approval for this project was received by the Hamilton Research Ethics Board (#2686).
 
SUPPLEMENTARY MATERIAL
 

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INCREASED INTRAMUSCULAR ADIPOSE TISSUE IS RELATED TO INCREASED CAPILLARIZATION IN OLDER ADULTS

 

O. Addison1,2, A.S. Ryan1,3, J. Blumenthal1, S.J. Prior1,4

 

1. Department of Veterans Affairs and Veterans Affairs Medical Center Baltimore, Geriatric Research, Education and Clinical Center (GRECC), Baltimore, MD, USA; 2. Department of Physical Therapy and Rehabilitation Science, University of Maryland School of Medicine, Baltimore, MD, USA; 3. Department of Medicine, Division of Gerontology and Geriatric Medicine, University of Maryland School of Medicine, Baltimore, MD, USA; 4. Department of Kinesiology, University of Maryland School of Public Health, College Park, MD, USA.Corresponding author: Odessa Addison, 10 N. Greene Street, Baltimore, MD, 21201, Phone- (410)605-7000 ext 55393, Fax: (410)605-7913, Email – oaddison@som.umaryland.edu

J Frailty Aging 2020;9(3)134-138
Published online April 24, 2020, http://dx.doi.org/10.14283/jfa.2020.20

 


Abstract

Background: High levels of intramuscular adipose tissue and low levels of capillarization are both predicative of low muscle and mobility function in older adults, however little is known about their relationship. Objectives: The purpose of this study was to examine the relationship of intramuscular adipose tissue and capillarization in older adults. Setting: An outpatient medical center. Participants: Forty-seven sedentary adults (age 59.9 ± 1.0 years, BMI 32.0 ± 0.7 kg/m2, VO2max 22.4 ± 0.7 ml/kg/min); Measurements: All participants underwent CT scans to determine intramuscular adipose tissue and muscle biopsies to determine capillarization in the mid-thigh. A step-wise hierarchical linear regression analysis was used to examine the contributions of age, sex, race, body mass index, 2-hour postprandial glucose, VO2max, and muscle capillarization, to the variability in intramuscular adipose tissue. Results: The predictors as a group accounted for 38.1% of the variance in intramuscular adipose tissue, with body mass index and capillarization each significantly contributing to the final model (P<0.001). The part correlation of body mass index with intramuscular adipose tissue was r = 0.47, and the part correlation of capillarization with intramuscular adipose tissue was r = 0.39, indicating that body mass index and capillarization explained 22.1%, and 15.2% of the variance in intramuscular adipose tissue. Conclusions: While increased muscle capillarization is typically thought of as a positive development, in some clinical conditions, such as tendinopathies, an increase in capillarization is part of the pathological process related to expansion of the extracellular matrix and fibrosis. This may also be an explanation for the surprising finding that high capillarization is related to high levels of intramuscular adipose tissue. Future studies are necessary to determine the relationship of changes in both capillarization and intramuscular adipose tissue after interventions, such as exercise.

Key words: Myosteatosis, muscle, vascular.


 

Introduction

Aging is associated with numerous muscular changes including a loss of muscle strength and lean mass, and an increase in muscle intramuscular fat (IMAT), also known as myosteatosis (1). Changes in muscles composition are an important factor related to metabolism, strength, and physical function in older adults (1). Older adults with high levels of IMAT often have insulin resistance, decreased muscle quality and physical function, and an increased risk for future mobility limitations (1, 2) . While the cause of increased IMAT is currently unknown, comorbid conditions such as diabetes and obesity, as well as inactivity and disuse all appear to contribute (3). Likewise, lifestyle interventions such as weight loss, exercise, and physical activity interventions appear to ameliorate the accumulation, or even result in reductions in IMAT (4) .
Capillarization in skeletal muscle is also an important factor associated with metabolism and muscle function in older adults (5). Low skeletal muscle capillarization is associated with sarcopenia (6), increased insulin resistance (7), and low physical function (8). Decreases in skeletal muscle capillarization also occur with aging (9), sedentary behavior (10), and in co-morbid conditions such as diabetes (11). Similarly, higher aerobic capacity is associated with increased capillarization in skeletal muscle, and exercise may likewise increase capillarization in previously sedentary older adults (12). Due to the close proximity of IMAT with the skeletal muscle, and the secretion of pro- and anti-angiogentic factors from adipose tissue (13), IMAT may exert an influence on the capillarization of a muscle.
It is reasonable to suspect that high levels of IMAT may be related to decreased capillarization in skeletal muscle; however, the relationship between the two variables has not yet been examined. Understanding this relationship is important for the effective development of treatment to both decrease IMAT and increase capillarization in the muscle of older adults. Therefore, the purpose of this paper is to examine the relationship of IMAT and capillarization in the thigh muscle of older adults. We hypothesize that low levels of capillarization would be associated with high levels of IMAT.

 

Methods

This study was conducted as a secondary data analysis from a previously published study (6). In brief, participants age 45-80 who participated in studies examining the metabolic responses to exercise or exercise and weight loss, and had complete baseline data for muscle composition, exercise capacity, and capillarization were included, resulting in 47 participants with an age range of 50-77 years for this study. Only baseline data were used in this cross-sectional analysis. Individuals were included in this study if they were non-smokers who were weight stable (self-reported weight change of <2.0 kg in the last year), sedentary (<20 minutes of aerobic exercise two times per week), and free from diabetes (confirmed with an oral glucose tolerance test), stroke, coronary artery disease, heart failure, peripheral arterial disease, and liver, kidney or lung disease. Health status was confirmed in a physical examination performed by a physician or nurse practitioner that included a medical history, fasting blood chemistry, a graded maximal exercise test, and a two-hour fasting oral glucose tolerance test. All participants signed written informed consent approved by the University of Maryland Baltimore Institutional Review Board.

Body Mass Index and Muscle Composition

Body mass index (BMI) was calculated as body weight (kg) divided by the square of height (m2). Cross-sectional area (cm2) of both high and low-density lean tissue was determined utilizing computed tomography (CT). The methods have previously been reported in detail (2). Briefly, participants underwent a mid-thigh CT scan (Siemens Somatom Sensation 64 Scanner). High (HDLT) and low-density lean tissue (LDLT) cross-sectional area of the thigh were determined using Medical Image Processing, Analysis and Visualization (MIPAV, v 7.0, NIH) software. (14) CT data for each muscle were expressed as a cross-sectional area of tissue (cm2) using Hounsfield units 30-100 for HDLT and 0-29 for LDLT. LDLT was normalized to thigh size by calculating a percentage of LDLT (% LDLT) relative to the sum of LDLT and HDLT (LDLT/(LDLT+HDLT). As done previously, %LDLT was used as a measure of IMAT (14).

Exercise Capacity

During a maximal graded treadmill exercise test, VO2max was measured by indirect calorimetry (Quark, Cosmed USA, Chicago, IL) as previously described (12). In brief, participants walked at a constant speed during the test with a starting grade of 0%, the grade was increased every two minutes until a maximal effort was achieved. VO2max was verified using standard physiological criteria (i.e., respiratory exchange ratio >1.10 or a plateau in VO2 with increased workload).

Capillarization

Skeletal muscle capillarization was determined using percutaneous muscle biopsies from the vastus lateralis. Using a Bergstrom needle (Stille, Solna, Sweden), muscle samples were obtained from 12-13 cm above the patella on the right thigh (12). Muscle samples were embedded and rapidly frozen in optimal cutting temperature-tragacanth gum mixture, then stored at -80° C for histochemical analyses. Samples were sectioned to a thickness of 14 µm on a cryostat, and capillaries were identified using a modified double stain technique in our laboratory as described previously (12). Three measures of capillarization were obtained: 1) capillary density (CD: the number of capillaries per mm2 of muscle cross-sectional area), 2) the capillary to fiber ratio (C:F: the number of whole capillaries equivalents in contact with each muscle fiber) and 3) the capillary-to-fiber perimeter exchange index (CFPE: the number of capillaries per millimeter of muscle fiber perimeter). CFPE was chosen as the primary measurement for analyses as it is thought to best represent the potential for blood-tissue exchange (15).

Statistical Analysis

All statistical analyses were performed using SPSS Statistics v. 22 (IBM, Armonk, NY). Data were ensured to meet the assumptions of a normal distribution prior to all analysis. Descriptive statistics were performed for demographic variables and dependent measures and are presented as mean +/- SEM. Pearson product-moment correlation analyses were used to test for bivariate correlations between %LDLT, muscle capillarization, age, BMI, 2-hr postprandial glucose (G120), and exercise capacity. To assess the relationship of capillarization and IMAT, individuals were divided into tertiles of capillarization and the 1st and 3rd tertial were compared using independent samples t-tests. The alpha level for analyses was set at <0.05.
To further assess the relative contributions of demographic variables (age, sex, race, BMI, G120), muscle capillarization, and VO2max to the variability in %LDLT were examined using a step-wise hierarchical linear regression model. In the model, %LDLT was the dependent variable and age, sex, race, BMI, G120, VO2max, and muscle capillarization, as represented by CFPE, were considered for entry in a stepwise manner. A second step-wise hierarchical linear regression was used to examine the contributions of demographics, VO2max, and %LDLT to variability in muscle capillarization. In this second model, muscle capillarization (CFPE) was the dependent variable and demographics, VO2max, and %LDLT were considered for entry in a stepwise manner. The criterion for entry to both models was a significance level of P<0.10. For each variable entered in the final model, the part-correlation was examined to determine the unique amount of variance in the outcome (%LDLT or muscle capillarization) that was accounted for by the variable.

 

Results

Participants were all middle-aged to older women and men with BMI ranging from 24.2-46.1 kg/m2 and low physical fitness (VO2max range 8.9-33.5 ml/kg/min; Table 1). The bivariate correlations of %LDLT with all other variables revealed moderately strong (r = 0.40-0.48) and significant (p<0.004) correlations with capillarization (Figure 1) and BMI (Table 2). After dividing the groups into tertiles by capillarization there was no significant difference between those in the high and low capillarization groups for age, race, or BMI (table 1). There was however a tendency (p=0.06) for a difference in the %LDLT and a significant difference (P<0.05) in VO2max, and G120 with the higher capillarization group demonstrating higher levels of %LDLT and VO2max and lower G120 levels.

Table 1
Participant Characteristics

Notes: Data are means ± SEM with the exceptions of sex and race. High CFPE refers to those in the top tertial of CFPE while low CFPE are those in the bottom tertial. BMI: Body mass index; 120-minute postprandial glucose; CFPE: capillary fiber perimeter exchange index; CD: capillary density; C:F: Capillary to fiber ratio. * Significant difference between the high and low CFPE groups (P<0.05)

 

Table 2
Bivariate Correlations

Note: Bivariate Person correlation coefficients are presented to show the relationships among percentage low density lean and CFPE and other variables. BMI: Body mass index; CFPE: Capillary fiber perimeter exchange index; G120: 120 minute postprandial glucose; %LDLT: percentage of low density lean tissue a representation of intramuscular adipose tissue. *P<0.05

 

Figure 1
Scatterplot depicting the relationship of the percentage of low density lean tissue with capillary-to-fiber perimeter exchange index (CFPE) in sedentary older adults. In both bivariate correlation and regression analyses %LDLT was directly associated with CFPE

 

The multiple regression analysis revealed that the predictors as a group accounted for 38.1% of the variance in %LDLT, with BMI (P<0.001) and capillarization (P=0.002), each significantly contributing to the final model (P<0.001). The part correlation of BMI with %LDLT was r = 0.47, and the part correlation of CFPE with %LDLT r = 0.39, indicating that BMI and capillarization explained 22.1%, 15.2% of the variance in %LDLT respectively, with all other variables in the model held constant (Table 3).
For the second regression analysis, the predictors as a group accounted for 38.0% of the variance in CFPE, with %LDLT (P<0.002), VO2max (P=0.01), and G120 (P=0.05) each significantly contributing to the final model (P<0.001). In this model, the part correlation of %LDLT with CFPE was r = 0.40, of VO2max with CFPE was r = 0.32, and of G120 with CFPE was r = -0.24 indicating that %LDLT, VO2max, and G120 explained 16.0%, 10.1%, and 5.7% of the variance in capillarization, with all other variables in the model held constant (Table 3).

Table 3
Regression Models

Note: Regression analysis presented to show the relationships of low density lean tissue, a representation of intramuscular adipose tissue, capillarization (defined as CFPE) and other variables. Partial correlation coefficients are presented to show the relationships among low density lean tissue, capillarization and the other variables in the regression analysis. %LDL: percentage of low density lean as a representation of intramuscular adipose tissue; BMI: body mass index; 120-minute postprandial glucose; CFPE: capillary fiber perimeter exchange index

 

Discussion

Contrary to our original hypothesis, we found that increased amounts of LDLT were related to increased levels of capillarization in the thigh. To our knowledge, this is the first time this relationship has been reported. Our findings that the most significant predictors of %LDLT in the thigh were BMI and capillarization, and that the most significant predictor of capillarization in the thigh was %LDLT are surprising. Previous work has found high levels of IMAT in individuals with compromised microvasculature such as in diabetes, aging, and sedentary behavior (1, 3). Conversely, interventions such as aerobic exercise and weight loss may increase capillarization and decrease IMAT (4, 12). Our paradoxical finding of increased IMAT being related to increased capillarization is surprising in light of this previous literature.
Adipose tissue is known to release a host of proteins that act in endocrine, paracrine, and autocrine signaling including increased inflammatory and angiogenic factors (13). The intimate relationship between IMAT and muscle cells indicates that IMAT may have a unique interactions with muscle (16). Previous work has demonstrated that increased levels of IMAT may promote an increase in the local proinflammatory environment (17), modify the extracellular matrix (16), and ultimately result in muscle fibrosis (18). It is possible that this combination of changes also results in an increase in capillarization within the muscle. Increased intramyocellular lipid levels (one component of IMAT) are found both in athletes (who have high levels of capillarization) and in sedentary obese adults when compared to lean sedentary individuals (19). However, given the low VO2max levels of individuals in this study, they would not be considered athletes and this is an unlikely explanation for our findings.

While increasing capillarization in muscle is typically thought of as a positive development, in some musculoskeletal conditions, such as tendinopathies, an increase in angiogenesis is part of the pathological process. For example, in patellar and Achilles tendinopathies an increase in the microvascular density occurs (20). This increase is related to the expansion of the extracellular matrix and ultimately the fibrosis of the tendon. It is possible that with increased levels of IMAT, the increased capillarization of the muscle is also related to the increased local inflammatory environment and changes in the extracellular matrix. However, as this is a cross-sectional study, this is only speculative and we do not know the nature of the relationship of timing between increased IMAT and capillarization.
As we eliminated any individuals with diabetes from our sample, in an effort to control for the numerous effects of diabetes on both IMAT and capillarization, more studies are necessary to examine the relationships of capillarization and IMAT in those with diabetes. The older adults in this study were also all sedentary individuals and it is possible that if we included active individuals in the study we would find something similar to the athletes paradox.
In conclusion, contrary to our initial hypothesis that high levels of IMAT would be related to low levels of capillarization, we found that high levels of IMAT were related to high levels of capillarization. Given the cross-sectional nature of this study, future studies are necessary to determine the relationship of changes in both capillarization and IMAT with interventions, such as exercise.

 

Funding: This research was supported by the University of Maryland Claude D. Pepper Center (P30-AG-12583), the Baltimore Veterans Affairs Medical Center Geriatric Research, Education and Clinical Center (GRECC), the National Institutes of Health (grant numbers R01-AG019319 and R01-AG020116) plus the Department of Veterans Affairs. OA was supported by a Veterans Affairs Career Development Award (IK2RX001788), A.S.R. was supported by a Veterans Affairs Senior Research Career Scientist Award, and S.J.P was supported by a Paul B. Beeson Patient-Oriented Research Career Development Award in Aging (National Institutes of Health K23-AG040775 and AFAR). The sponsors had no role in the design and conduct of the study; in the collection, analysis, and interpretation of the data; in the preparation of the manuscript, or in the review or approval of the manuscript.
Conflicts of Interest: All the authors (OA, ASR, JB, SJP) declare no conflicts of interest.

 

References

1. Addison O, Marcus RL, Lastayo PC, Ryan AS. Intermuscular fat: a review of the consequences and causes. Int J Endocrinol. 2014;2014:309570. doi:10.1155/2014/309570.
2. Ryan AS, Nicklas BJ. Age-related changes in fat deposition in mid-thigh muscle in women: relationships with metabolic cardiovascular disease risk factors. Int J Obes Relat Metab Disord. 1999 Feb;23(2):126-32.
3. Goodpaster BH, Thaete FL, Kelley DE. Thigh adipose tissue distribution is associated with insulin resistance in obesity and in type 2 diabetes mellitus. Am J Clin Nutr. 2000 Apr;71(4):885-92. eng. Epub 2000/03/25.
4. Prior SJ, Joseph LJ, Brandauer J, Katzel LI, Hagberg JM, Ryan AS. Reduction in midthigh low-density muscle with aerobic exercise training and weight loss impacts glucose tolerance in older men. J Clin Endocrinol Metab. 2007 Mar;92(3):880-6. doi:10.1210/jc.2006-2113.
5. Landers-Ramos RQ, Prior SJ. The Microvasculature and Skeletal Muscle Health in Aging. Exerc Sport Sci Rev. 2018 Jul;46(3):172-179. doi:10.1249/JES.0000000000000151.
6. Prior SJ, Ryan AS, Blumenthal JB, Watson JM, Katzel LI, Goldberg AP. Sarcopenia Is Associated With Lower Skeletal Muscle Capillarization and Exercise Capacity in Older Adults. J Gerontol A Biol Sci Med Sci. 2016 Aug;71(8):1096-101. doi:10.1093/gerona/glw017.
7. Prior SJ, McKenzie MJ, Joseph LJ, Ivey FM, Macko RF, Hafer-Macko CE, Ryan AS. Reduced skeletal muscle capillarization and glucose intolerance. Microcirculation. 2009 Apr;16(3):203-12. eng. Epub 2009/02/20. doi:10.1080/10739680802502423.
8. Nicklas BJ, Leng I, Delbono O, Kitzman DW, Marsh AP, Hundley WG, Lyles MF, O’Rourke KS, Annex BH, Kraus WE. Relationship of physical function to vastus lateralis capillary density and metabolic enzyme activity in elderly men and women. Aging Clin Exp Res. 2008 Aug;20(4):302-9.
9. Frontera WR, Hughes VA, Fielding RA, Fiatarone MA, Evans WJ, Roubenoff R. Aging of skeletal muscle: a 12-yr longitudinal study. J Appl Physiol (1985). 2000 Apr;88(4):1321-6. doi:10.1152/jappl.2000.88.4.1321.
10. Vigelso A, Gram M, Wiuff C, Andersen JL, Helge JW, Dela F. Six weeks’ aerobic retraining after two weeks’ immobilization restores leg lean mass and aerobic capacity but does not fully rehabilitate leg strength in young and older men. J Rehabil Med. 2015 Jun;47(6):552-60. doi:10.2340/16501977-1961.
11. Solomon TP, Haus JM, Li Y, Kirwan JP. Progressive hyperglycemia across the glucose tolerance continuum in older obese adults is related to skeletal muscle capillarization and nitric oxide bioavailability. J Clin Endocrinol Metab. 2011 May;96(5):1377-84. doi:10.1210/jc.2010-2069.
12. Prior SJ, Blumenthal JB, Katzel LI, Goldberg AP, Ryan AS. Increased Skeletal Muscle Capillarization After Aerobic Exercise Training and Weight Loss Improves Insulin Sensitivity in Adults With IGT. Diabetes Care. 2014 May;37(5):1469-75. doi:10.2337/dc13-2358.
13. Tahergorabi Z, Khazaei M. The relationship between inflammatory markers, angiogenesis, and obesity. ARYA Atheroscler. 2013 Jun;9(4):247-53. Epub 2013/08/24.
14. Addison O, Inacio M, Bair WN, Beamer BA, Ryan AS, Rogers MW. Role of Hip Abductor Muscle Composition and Torque in Protective Stepping for Lateral Balance Recovery in Older Adults. Arch Phys Med Rehabil. 2017 Jun;98(6):1223-1228. Epub 2016/11/15. doi:10.1016/j.apmr.2016.10.009.
15. Hepple RT. A new measurement of tissue capillarity: the capillary-to-fibre perimeter exchange index. Can J Appl Physiol. 1997 Feb;22(1):11-22. Epub 1997/02/01.
16. Sachs S, Zarini S, Kahn DE, Harrison KA, Perreault L, Phang T, Newsom SA, Strauss A, Kerege A, Schoen JA, Bessesen DH, Schwarzmayr T, Graf E, Lutter D, Krumsiek J, Hofmann SM, Bergman BC. Intermuscular adipose tissue directly modulates skeletal muscle insulin sensitivity in humans. Am J Physiol Endocrinol Metab. 2019 May 1;316(5):E866-E879. Epub 2019/01/09. doi:10.1152/ajpendo.00243.2018.
17. Addison O, Drummond MJ, LaStayo PC, Dibble LE, Wende AR, McClain DA, Marcus RL. Intramuscular fat and inflammation differ in older adults: the impact of frailty and inactivity. J Nutr Health Aging. 2014 May;18(5):532-8. Epub 2014/06/03. doi:10.1007/s12603-014-0019-1.
18. McGregor RA, Cameron-Smith D, Poppitt SD. It is not just muscle mass: a review of muscle quality, composition and metabolism during ageing as determinants of muscle function and mobility in later life. Longev Healthspan. 2014;3(1):9. Epub 2014/12/19. doi:10.1186/2046-2395-3-9.
19. Goodpaster BH, He J, Watkins S, Kelley DE. Skeletal muscle lipid content and insulin resistance: evidence for a paradox in endurance-trained athletes. J Clin Endocrinol Metab. 2001 Dec;86(12):5755-61. Epub 2001/12/12. doi:10.1210/jcem.86.12.8075.
20. Xu Y, Murrell GA. The basic science of tendinopathy. Clin Orthop Relat Res. 2008 Jul;466(7):1528-38. Epub 2008/05/15. doi:10.1007/s11999-008-0286-4.

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PRACTICAL IMPLICATIONS FOR STRENGTH AND CONDITIONING OF OLDER PRE-FRAIL FEMALES

 

N.W. Bray1, G.J. Jones1, K.L. Rush2, C.A. Jones3, J.M. Jakobi1

1. School of Health and Exercise Sciences, Faculty of Health and Social Development, University of British Columbia Okanagan, Kelowna, British Columbia, Canada; 2. School of Nursing, Faculty of Health and Social Development, University of British Columbia Okanagan, Kelowna, British Columbia, Canada; 3. Southern Medical Program, Faculty of Medicine, University of British Columbia Okanagan, Kelowna, British Columbia, Canada.
Corresponding author: Jennifer M. Jakobi, School of Health and Exercise Sciences, Faculty of Health and Social Development, University of British Columbia Okanagan, Kelowna, British Columbia, Canada, V1V 1V7, jennifer.jakobi@ubc.ca

J Frailty Aging 2020;9(2)118-121
Published online March 30, 2020, http://dx.doi.org/10.14283/jfa.2020.15

 


Abstract

Approaches to and benefits from resistance training for non-compromised older adults are well known. Less is understood about resistance training with pre-frail older adults, and even less information is available on the practical approaches to delivery. Herein, we describe an approach in pre-frail females who undertook a multi-component exercise intervention, inclusive of high-intensity, free-weight, functional resistance training. Capitalizing on the principle of overload is possible and safe for pre-frail females through constant reassurance of ability and adjustments in technique. Making exercise functionally relevant, for example, a squat is the ability to get on and off a toilet, resonates meaning. Older pre-frail females are affected by outside (clinical) influences. The exercise participant, and extraneous persons need to be educated on exercise approaches, to increase awareness, debunk myths, and enhance support for participation. Identification of individuality in a group session offers ability to navigate barriers for successful implementation.

Key words: Multi-component exercise, females, aging, strength, muscle.


 

Introduction

This Research Note supplements the original research article, “Multi-component exercise with high-intensity, free-weight, functional resistance training in pre-frail females: A quasi-experimental, pilot study” (1). The primary aim of this study was to examine the feasibility and safety of multi-component exercise (MCE), inclusive of resistance training that is high in intensity, uses free-weights, and is based upon functional movement. Previous exercise interventions in pre-frail females have primarily used low-intensity, single-joint resistance training exercises (2), likely because of the commonly held, yet unsupported belief that the alternative is unsafe (3). Researchers and clinicians working with frail older adults can apply principles of our training program to exercise interventions.
Older adults are challenged with chronic health conditions and functional deficits that can render them frail (4). The incidence of frailty increases with age and is more prevalent in females (5); however, this syndrome can be positively influenced by interventions (6), especially exercise (7,8). Current recommendations to reverse frailty provide evidence to support an exercise strategy based upon the individual’s level of frailty (9). However, few studies report on the practical applications of effective delivery. Hence, we openly describe our experience administering a MCE intervention, inclusive of resistance training utilizing free-weight functional movements at high intensities, in a group of pre-frail older females.

 

Main text

Progression – Resistance exercise programs benefit muscle strength, power, and endurance when there is a progressive increase in work, balanced with appropriate recovery (10). During the early stages of resistance training, progression for pre-frail females may involve increasing the range of motion (ROM), as opposed to a traditional model of increasing the weight lifted. It is likely advantageous to first increase ROM as it has greater application to everyday tasks. We used a combination of custom built, stackable, “plyo-boxes” and free-weight plates to adjust the ROM when performing the squat and deadlift (Figure 1-2). The squat and deadlift are rarely implemented to train older adults yet, when boxes 12-24ˮ are used to adjust the ROM, these exercises can be safely undertaken.

Figure 1
A. Box heights (12-24ˮ) used to progressively and safely increase range of motion (ROM) for the squat and deadlift exercises.
1B and 1C highlight individuality, as it shows each participant squatting to a ~20ˮ and 12ˮ box, respectively. The participant squatting to the 20” box was working to achieve full ROM, while the participant squatting to the 12ˮ box is holding a dumbbell because they had progressed to the maximal ROM required of the training program, and this was the next level of progression

 

The squat exercise was initiated by squatting to a 24ˮ box. Progressive overload was applied by having the participant complete squats through a greater ROM (deeper squat) until the full-squat (~90 degree flexed knee bend/12ˮ box) was completed. Progression then involved the traditional approach of adding weight (dumbbell held in goblet position). The squat exercise should not be overlooked in designing programs for older females as it simulates functional activities, such as rising from a toilet.
Deadlifts, using a 35lb barbell, followed an identical progression. However, once participants reached the 12ˮ box, a 10lb bumper plate was added to each side of the barbell (total = 55lbs) instead of progressing to the ground, as the latter would likely represent a greater challenge. Once participants performed the prescribed sets and repetitions from the 12ˮ box, with the additional weight (total = 55lbs), they were then progressed to the ground. Exercise progression then included increasing the barbell load (Figure 2). The deadlift exercise should also not be overlooked as it simulates functional activities, such as picking up grandchildren.

 

For both the squat and deadlift, when a 6ˮ difference in box height represented too great of an increase in ROM, weight-plates (Virgin Rubber Grip Olympic Plates, Element Fitness; Latvia) ~2ˮ in width were used to safely progress (Figure 1B).
Overload – Refers to the gradual increase in stress that is placed upon the body during training, and is likely of particular importance to combatting the natural deterioration that occurs with aging. Exercise leaders, inclusive of Clinical Exercise Physiologists, were responsible for prescribing overload by increasing the weight/ROM and/or repetitions for each exercise over the course of the intervention. For example, if a participant performed three sets of eight repetitions during block one (weeks 1-4), they were then encouraged to complete nine repetitions on the next visit. The number of repetitions were increased until the participant reached 12, at which point resistance was increased and repetitions reduced back to eight. Not all participants willingly accepted the recommended progressive overload, and the exercise leaders needed to regularly build confidence for the participants to undertake this training principle.
Individuality – All exercises were modified based upon individual need (limited ROM, joint problems), as well as self-perceived ability. For example, during the early stages of the program, participants were instructed to lower the incline leg press sled (60lbs) to a point that they felt strong enough to still return it to the starting position (leg press guard ensured safety). Eventually, ROM was increased and then weight added to the sled. Continual monitoring assists in ensuring that resistance is added when participants can complete the full ROM safely.
Self-perceived Intensity – After the final set of every exercise, the OMNI Resistance Exercise Scale (OMNI-RES) was used to quantify Rating of Perceived Exertion (RPE; 11). RPE is a subjective indicator of how hard an individual is working. The OMNI-RES permits exercisers to report a measure from 0(extremely easy)-10(extremely hard). Participants often found it difficult to distinguish levels 3-8; frequently reporting a rating of 1-2 or 9-10, indicating that they could only perceive their level of exertion as very easy or very hard. The incongruity between completing more of the exercise and self-perceived scoring resulted in the decision to switch to the RPE method proposed by Zourdos (12), which has the exerciser rate their exertion based upon the number of repetitions they believe they could have executed before muscle failure. This type of RPE scale was more easily understood, potentially because of the objectivity, and thus, appeared to be more accurate in self-assessment.
Group Dynamics – Groups often adopt a ‘team’ approach, encouraging each other to improve and recognizing milestones. Positive group exercise dynamics can also foster social activities, further enhancing quality of life for older adults. The opposite situation may occur in random group assignment. Participants who question the exercise intervention and the necessity of progressive overload can minimize the development of positive group dynamics. Group settings bring together different personalities and it is not realistic to believe that they will consistently exist in harmony. The role of group dynamics should be considered in future frailty exercise interventions/programs (13).
Outside Clinician Influence – Pre-frail older females have co-morbidities that require clinical monitoring. Some participants made clear, to the certified exercise leaders, that their clinicians held negative, preconceived notions towards older females performing high-intensity, free-weight, functional resistance training. This negative influence phenomenon is quite common, despite evidence that exercise is beneficial in mitigating frailty. We observed that participants who relied on clinical suggestions were more apprehensive in the exercise program and tenuous in overloading. Importantly, our exercise intervention did not have any adverse events. Progressively overloading exercises for pre-frail older females is challenging, but it is feasible, safe, and beneficial.
Prior to the start of the intervention, researchers should hold a mandatory information session. During this session, participants should be educated about the intervention and granted the opportunity to pose concerns, as well as understand the qualifications of those administering the program. The participants primary clinician should be offered educational material (i.e. brochure) outlining the program as it could help address concerns and prevent contradictory recommendations.

Limitations

This research note offers guidance to those undertaking exercise with frail older adults. However, the applicability might be limited to females. Researchers were aware that the OMNI-RES can be poorly understood given that new trainees often report less accurate perception of their exertion than more advanced exercisers (14). Therefore, careful explanation was undertaken prior to beginning and during the exercise session. Switching to an adapted RPE might have slowed exercise progression and influenced confidence in the exercise leaders. Across frailty scales, there is considerable confusion in classification, therefore, observations may vary with the level and scale used to identify frailty (15). This progressive exercise program was successful in inducing positive adaptations, yet, the approach needs to be applied in a large randomized controlled trial.

 

Discussion

Trainers should create options for participants to work in a functional ROM, and to teach the squat and deadlift. Boxes of varying heights supported the prescription of the squat and deadlift exercise. When there was an improvement in strength, the boxes were lowered/ROM was increased. However, the height of boxes used for progression should be limited to ≤ 3″. Overall, this approach offers flexibility in exercise prescription for those with joint limitations. The following fitness equipment is also beneficial in creating progressive resistance: 1) a barbell weighing < 35lbs; 2) dumbbells increasing in 2.5lbs increments; and 3) an inclined leg press with a starting weight < 60lbs. Across all elements, pre-frail older females benefit from understanding the functional application of exercises.
Frailty is often an unfortunate reality for an aging population, its characteristics are all synonymous with lack of fitness. Strength and conditioning specialists are well suited to address frailty. To be most effective, exercise specialists need to tailor the exercise intervention, and constantly use monitoring approaches to create small progressions that promote meaningful strength gains and in-turn, enhance functional ability.

 

Funding: Partial funding for this study through the Canadian Institutes for Health Research (CIHR) Grant # 385692. The sponsors had no role in the design and conduct of the study; in the collection, analysis, and interpretation of data; in the preparation of the manuscript; or in the review or approval of the manuscript.
Acknowledgments: We wish to acknowledge the support from Flaman Fitness™ and the Okanagan Men’s Shed Club for generously donating the exercise equipment, graduate students (Rowan Smart and Sam Kuzyk) and senior undergraduate students (Anup Dhaliwal, Brett Yungen, Savannah Frederick, Paul Cotton and Cydney Richardson), and all the participants involved in this study.
Ethics approval and consent: All participants read and signed a letter of informed consent. Ethical approval was granted by the institutional Research Ethics Board (H16-00712).
Availability of the data and materials: The original data and materials are available through the institutions open access graduate thesis repository https://open.library.ubc.ca/cIRcle/collections/ubctheses/24/items/1.0353165
Competing interests: None
Trial Registration: This study was prospectively registered with ClincalTrials.gov (NCT02952443) on October 31, 2016.

 

References

1. Bray NW, Jones GR, Rush KL, Jones CA, Jakobi JM. Multi-component exercise with high-intensity, free-weight, functional resistance-training in pre-frail females: A quasi-experimental, pilot study. J Frailty Aging 2019;In Press.
2. Puts MTE, Toubasi S, Andrew MK, et al. Interventions to prevent or reduce the level of frailty in community-dwelling older adults: A scoping review of the literature and international policies. Age Ageing 2017;46(3):383-392.
3. Watson SL, Weeks BK, Weis LJ, Horan SA, Beck BR. Heavy resistance training is safe and improves bone, function, and stature in postmenopausal women with low to very low bone mass: novel early findings from the LIFTMOR trial. Osteoporos Int 2015;26(12):2889–94.
4. Hicks GE, Shardell M, Alley DE, et al. Absolute strength and loss of strength as predictors of mobility decline in older adults: The InCHIANTI study. J Gerontol A Biol Sci Med Sci 2012;67(1):66–73.
5. Bandeen-Roche K, Seplaki CL, Huang J, et al. Frailty in Older Adults: A Nationally Representative Profile in the United States. J Gerontol A Biol Sci Med Sci 2015;70(11):1427–34.
6. Bray NW, Doherty TJ, Montero-Odasso M. The Effect of High Dose Vitamin D3 on Physical Performance in Frail Older Adults. A Feasibility Study. J Frailty Aging 2018;7(3):155–61.
7. Theou O, Stathokostas L, Roland KP, et al. The effectiveness of exercise interventions for the management of frailty: a systematic review. J Aging Res 2011;2011:569194.
8. Jones GR, Jakobi JM. Launching a new initiative. Appl Physiol Nutr Metab 2017;42(9):iii–iv.
9. Bray NW, Smart RR, Jakobi JM, Jones GR. Exercise prescription to reverse frailty. Appl Physiol Nutr Metab 2016;41(10):1112–16.
10. Riebe D, Ehrman JK, Liguori G, et al. ACSM’s Guidelines for Exercise Testing and Prescription. 10th ed. Baltimore (MD): Lippincott Williams & Wilkins; 2018. 249-257 p.
11. Gearhart RF, Lagally KM, Riechman SE, et al. Strength Tracking Using the OMNI Resistance Exercise Scale in Older Men and Women. J Strength Cond Res 2009;23(3):1011–5.
12. Zourdos MC, Klemp A, Dolan C, et al. Novel Resistance Training-Specific Rating of Perceived Exertion Scale Measuring Repetitions in Reserve. J Strength Cond Res 2016;30(1):267-75.
13. Beauchamp MR, Eys M. Group dynamics in exercise and sport psychology. New York, NY: Routledge, 2014.
14. Testa M, Noakes TD, Desgorces F-D. Training state improves the relationship between rating of perceived exertion and relative exercise volume during resistance exercises. J Strength Cond Res 2012;26(11):2990–6.
15. Theou O, Brothers TD, Peña FG, et al. Identifying common characteristics of frailty across seven scales. J Am Geriatr Soc 2014;62(5):901–6.

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PSOAS AND PARASPINOUS MUSCLE MEASUREMENTS ON COMPUTED TOMOGRAPHY PREDICT MORTALITY IN EUROPEAN AMERICANS WITH TYPE 2 DIABETES MELLITUS

 

B.M. TUCKER1, F.C. HSU2, T.C. REGISTER3, J. XU4, S.C. SMITH4, M. MUREA1, D.W. BOWDEN4, B.I. FREEDMAN1, L. LENCHIK5

1. Department of Internal Medicine, Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA; 2. Department of Biostatistical and Data Sciences, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA; 3. Department of Pathology, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA; 4. Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA; 5. Department of Radiology, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA.
Corresponding author: Barry I. Freedman, MD, Internal Medicine – Nephrology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC 27157-1053, Phone: 336-716-6461, Fax: 336-716-4318, bfreedma@wakehealth.edu

J Frailty Aging 2019;in press
Published online March 22, 2019, http://dx.doi.org/10.14283/jfa.2019.5

 


Abstract

Background: Appendicular skeletal muscle mass index and muscle attenuation (density) are negatively associated with mortality in European-derived populations. Objectives: The present analyses assessed association between axial skeletal muscle density and muscle index with mortality in European Americans with type 2 diabetes mellitus (T2D). Design: Single-center observational study. Setting: Diabetes Heart Study. Participants:  839 European Americans with T2D. Methods: Computed tomography-measured psoas and paraspinous muscle mass index (cross sectional area/height2) and radiographic density (Hounsfield Units) were assessed in all participants. A Cox proportional hazards model was computed. The fully-adjusted model included covariates age, sex, body mass index, smoking, alcohol use, diabetes duration, insulin use, hormone replacement therapy (women), prevalent cardiovascular disease (CVD), hypertension, and coronary artery calcified atherosclerotic plaque mass score. Deaths were recorded in the National Death Index data through December 31, 2015. Results: Participants included 428 women and 411 men with median (25th, 75th quartile) age 62.8 (56.1, 69.1) years and diabetes duration 8.0 (5.0, 14.0) years. After 11.9 (9.4, 13.3) years of follow-up, 314 (37.4%) of participants were deceased. In the fully-adjusted model, psoas muscle density (hazard ratio [HR] 0.81, p<0.001), psoas muscle index (HR 0.82, p=0.008), and paraspinous muscle density (HR 0.85, p=0.003) were inversely associated with mortality. Paraspinous muscle index was not significantly associated with mortality (HR 0.90, p=0.08). Results did not differ significantly between men and women. Conclusions: In addition to established risk factors for mortality and CVD, higher psoas muscle index, psoas muscle density, and paraspinous muscle density were significantly associated with lower all-cause mortality in European Americans with T2D.

Keywords: European American, mortality, muscle, computed tomography, type 2 diabetes.


 

Introduction

The relationship between sarcopenia and type 2 diabetes mellitus (T2D) appears to be reciprocal, where individuals with sarcopenia are at a higher risk for developing T2D and individuals with T2D are at a higher risk for developing sarcopenia (1). In 2016, the International Conference on Frailty and Sarcopenia Research (ICFSR) Task Force concluded that individuals with T2D provide a useful target population for sarcopenia trials (2). To date, very few studies of T2D cohorts have examined the relationship between sarcopenia and health outcomes (3-6).
Studies of sarcopenia increasingly use computed tomography (CT) to evaluate skeletal muscle size and muscle density (7).  These CT-derived muscle metrics have been shown to be independent risk factors for morbidity and mortality (8, 9). The loss of skeletal muscle mass and infiltration of muscle with fat (i.e., myosteatosis) increase with aging, as well as in patients with endocrine disorders (diabetes mellitus, hypogonadism, growth hormone deficiency, hyperthyroidism, hypercortisolism, and vitamin D deficiency), chronic obstructive pulmonary disease, congestive heart failure, advanced kidney disease, cirrhosis, cancer, rheumatoid arthritis and HIV infection (10). Given increasing prevalence of T2D and increasing use of CT for the evaluation of sarcopenia, the relationships between CT-derived muscle metrics and mortality in individuals with T2D require further study.
Recently, inverse associations were reported between CT-derived psoas and paraspinous muscle indices with mortality in middle-aged African American men with T2D in the African American-Diabetes Heart Study (AA-DHS) (6). These associations were independent from the presence and severity of cardiovascular disease (CVD) risk factors; however, they were not observed in women (6). It is unclear whether CT-derived measures of muscle health associate with mortality in individuals with T2D from other ancestral populations. As such, the present analyses assessed relationships between psoas and paraspinous muscle mass index and muscle density with long-term mortality in a cohort of European Americans with T2D from the Diabetes Heart Study (DHS).

 

Methods

Study sample

The DHS is a single-center Wake Forest School of Medicine (WFSM) study. Detailed recruitment criteria have been reported (11). In brief, sibling pairs with T2D lacking advanced kidney disease were recruited from the community and endocrinology clinics in Winston-Salem, North Carolina from 1998 through 2005. T2D was defined as clinically-diagnosed diabetes developing after the age of 35 years and initially treated with diet, exercise or oral agents in the absence of diabetic ketoacidosis or insulin therapy alone. Participants underwent interviews for medical history and health behaviors, fasting blood and urine collection, and CT imaging for calcified atherosclerotic plaque in the coronary arteries, carotid arteries and aorta using multi-detector scanners with cardiac gating on chest scans. The study was approved by the WFSM Institutional Review Board and all participants provided written informed consent. This report is limited to self-reported European American participants. Vital status was assessed through Dec 31, 2015 using the National Death Index. Causes of death were listed on death certificates; however, all-cause mortality was selected as the primary outcome since specific causes could not be adjudicated for accuracy.

Psoas and paraspinous muscle imaging

Skeletal muscle index and radiographic density (attenuation) were assessed on CT. The proximal and distal borders of the psoas and paraspinous muscles were determined on a single 2.5 mm slice thickness image at the level of the L4 pedicle. Using picture archiving and communication system (PACS) software, the free-hand region of interest tool was used to define the periphery of the muscles without Hounsfield Units (HU) thresholding for measurement of mean muscle attenuation in HU and muscle cross-sectional area (CSA). Lower CT-measured skeletal muscle densities by this approach reflect greater intermuscular and intramuscular fat content. CT scans with left-right asymmetry between muscles due to scoliosis, degenerative diseases, or prior surgery, as well as scans with internal or external artifacts were excluded (N=27). The skeletal muscle index (SMI) was calculated by dividing muscle CSA by height squared. This index is commonly used instead of CSA in CT studies of sarcopenia to adjust for different body sizes. The muscle segmentation process was standardized by following the Standard Operating Procedures manual. CT measurements of muscle were performed by a musculoskeletal radiology fellow, following specialized training. CT images with measurements were archived and validated for measurement accuracy by a musculoskeletal radiology faculty member, with extensive expertise in quality assurance of body composition phenotypes (LL).

Statistical analyses

Demographic and laboratory characteristics of participants were contrasted by survival status using the unadjusted Cox proportional hazards models with sandwich-based variance estimation for familial relationships. The primary outcome was time to death, determined by the interval between the date of study enrollment and death. Study participants who were known to be alive as of December 31, 2015 were censored.
Kaplan-Meier curves were constructed to estimate the survival probabilities by muscle phenotype group (skeletal muscle density and skeletal muscle mass index in the psoas and paraspinous distributions). The four muscle phenotypes were standardized and categorized into three groups: Z ≤-1, Z >-1 and Z ≤1, and Z >1. The comparison of survival curves was calculated using the Cox proportional hazards model due to the correlated data structure.
Cox proportional hazards models with sandwich-based variance estimation were subsequently fitted to evaluate the associations between muscle phenotypes and mortality. Covariates were selected to limit confounding effects and ensure that reported effects were not due to other measured variables not accounted for in the model.
Association results were presented for an unadjusted model, a minimally-adjusted model accounting for age, sex, smoking status, alcohol use, diabetes duration, insulin use, and hormone replacement therapy (women), as well as a fully-adjusted model with all covariates in the minimally-adjusted model plus body mass index (BMI), self-reported prevalent CVD (angina, myocardial infarction, coronary artery bypass surgery, coronary angioplasty, stroke or carotid endarterectomy), coronary artery calcified atherosclerotic plaque, and hypertension. To determine whether the associations between muscle phenotypes and mortality were the same in men and women, interactions between sex and muscle phenotypes were added to the model.  If the interactions were significant, the sex specific analyses would be performed. Because there are 4 muscle phenotypes, the significance level was set at 0.0125 (p=0.05/4) based on a strict Bonferroni correction. All analyses were performed using SAS version 9.4 (SAS Inc., Cary, NC).

 

Results

The full sample of 839 European American DHS participants with T2D from 428 families were included in these analyses, 49% were men (N=412) and 51% (N=427) women. The median (25th, 75th quartile) age of the cohort at recruitment was 62.8 (56.1, 69.1) years with diabetes duration 8.0 (5.0, 14.0) years. After 11.9 (9.4, 13.3) year median follow-up, 314 (37.4%) of participants had died.
Table 1 displays baseline demographic and clinical data in this cohort, based upon vital status as of December 31, 2015. Participants who had died during follow-up were older at recruitment with longer durations of T2D and they had higher rates of baseline CVD, smoking, hypertension and insulin use. Significant differences in body mass index or use of statins, aspirin, angiotensin converting enzyme inhibitors (ACEi)/angiotensin receptor blockers (ARB), or oral hypoglycemic agents were not observed between those living and deceased at the end of follow-up.

Table 1 Baseline demographic and clinical characteristics of the Diabetes Heart Study cohort*

Table 1
Baseline demographic and clinical characteristics of the Diabetes Heart Study cohort*

*Data presented as median (25th, 75th percentile) for continuous variables or % for categorical variables; ^p-value calculated using the unadjusted Cox proportional hazards models with sandwich-based variance estimation; ACEi angiotensin converting enzyme inhibitor; ARB angiotensin receptor blocker

Table 2 displays baseline biochemical and CT imaging results in participants. Similar levels of glycemic (fasting blood sugar and HbA1c) and lipid (LDL-cholesterol, HDL-cholesterol and triglycerides) control were present in those alive and those who had died. In contrast, markedly higher levels of subclinical atherosclerosis (CT-detected calcified atherosclerotic plaque in the coronary arteries, carotid arteries and aorta) were present in participants who died during follow-up. In addition, baseline psoas and paraspinous muscle densities and psoas muscle index were significantly lower in participants who died, with a trend toward a lower paraspinous muscle index (p=0.08).

Table 2 Baseline biochemical and radiological characteristics of the Diabetes Heart Study cohort*

Table 2
Baseline biochemical and radiological characteristics of the Diabetes Heart Study cohort*

*Data presented as median (25th percentile, 75th percentile) for continuous variables or % for categorical variables; CP calcified plaque; HU Hounsfield Units.

Figure 1 shows survival curves based on the three groups (Z score ≤ -1, -1 < Z score ≤ 1, and Z score >1) for each muscle phenotype. The survival curves were different between the three groups for psoas density, psoas index, and paraspinous density (all p≤ 0.008). Participants with  Z scores >1 tended to have the highest survival probability over time, those with Z scores between -1 and 1 had the medium survival probability, and those with Z scores ≤ -1 had the lowest survival probability. Survival curves were not different between the three groups for paraspinous index.

Figure 1 Kaplan-Meier survival curves for muscle phenotype groups (Z score ≤-1, -11) for: (a) psoas muscle density, (b) psoas muscle index, (c) paraspinous muscle density, and (d) paraspinous muscle index

Figure 1
Kaplan-Meier survival curves for muscle phenotype groups (Z score ≤-1, -1< Z score ≤1, and Z score >1) for: (a) psoas muscle density, (b) psoas muscle index, (c) paraspinous muscle density, and (d) paraspinous muscle index

FIG 2 FREEDMAN

Older participants, women, and participants with lower diastolic blood pressure (DBP), higher blood urea nitrogen, and lower CKD-EPI estimated glomerular filtration rate (eGFR) were more likely to have lower psoas muscle density (Supplementary Tables 1-2).  Older participants, women, non-smokers, and participants with lower BMI, longer diabetes duration, lower DBP, lower serum creatinine, and higher HDL cholesterol were more likely to have lower psoas muscle indices (Supplementary Tables 3-4).
Table 3 contains results of the Cox proportional hazards models for association between the four skeletal muscle phenotypes and mortality. In the full model (Model 3) considering age, sex, smoking, alcohol use, diabetes duration, insulin use, hormone replacement therapy (women), BMI, prior CVD, coronary artery calcified atherosclerotic plaque and hypertension as covariates, psoas muscle density (HR per SD = 0.81, 95% confidence interval [CI] 0.73-0.90, p  < 0.001), psoas muscle index (HR per SD = 0.82, 95% CI 0.72-0.95, p = 0.008), and paraspinous muscle density (HR per SD = 0.85, 95% CI 0.76-0.94, p = 0.003) remained inversely associated with mortality. Paraspinous muscle index (HR per SD = 0.90, 95% CI 0.80-1.01, p = 0.08) was not significantly associated with mortality.
Table 4 presents the association between categorized muscle metrics and mortality. Subgroup analyses based on sex did not reveal significantly different relationships between psoas and paraspinous muscle phenotypes and mortality between men and women (data not shown).

Table 3 Relationships between muscle phenotypes and mortality in the Diabetes Heart Study cohort

Table 3
Relationships between muscle phenotypes and mortality in the Diabetes Heart Study cohort

Hazard ratios (HR), 95% confidence intervals (CI) and P values were obtained with Cox proportional hazard models with sandwich-based variance estimation. Model 1, unadjusted; Model 2 adjusted for age, sex, smoking, alcohol use, diabetes duration, insulin use, and estrogen supplementation (women). Model 3 adjusted for all variables in Model 2, plus body mass index, prior cardiovascular disease, coronary artery calcified atherosclerotic plaque, and hypertension.

Table 4 Relationships between muscle phenotypes and mortality in the Diabetes Heart Study cohort

Table 4
Relationships between muscle phenotypes and mortality in the Diabetes Heart Study cohort

Hazard ratios (HR), 95% confidence intervals (CI) and P values were obtained with Cox proportional hazard models with sandwich-based variance estimation. Model 1, unadjusted; Model 2 adjusted for age, sex, smoking, alcohol use, diabetes duration, insulin use, and estrogen supplementation (women). Model 3 adjusted for all variables in Model 2, plus body mass index, prior cardiovascular disease, coronary artery calcified atherosclerotic plaque, and hypertension. 

 

Discussion

The present study assessed associations between CT-derived psoas and paraspinous skeletal muscle indices and muscle densities with all-cause mortality in a large cohort of European Americans with T2D. The DHS cohort has been intensively phenotyped for CVD risk factors and had median 11.9 year follow-up with linkage to the National Death Index (12). Significant inverse associations were detected between psoas muscle index, psoas muscle density, and paraspinous muscle density with all-cause mortality. Relationships were robust to adjustment for BMI as well as clinical and subclinical CVD (CT-derived coronary artery calcified atherosclerotic plaque).
An increased risk of T2D in older adults with sarcopenia has been observed in various studies, most notably in an 11-year follow-up of the Health, Aging and Body Composition (Health ABC) study and a 6-year follow-up of the English Longitudinal Study of Ageing (13, 14). Conversely, the increased risk of sarcopenia in older adults with increased insulin resistance has been shown in a 5-year follow-up of the Osteoporotic Fractures in Men (MrOs) study (15). While the mechanisms underlying the reciprocal relationship between sarcopenia and T2D are complex, age-related inflammation of adipose tissue and skeletal muscle likely play major roles (16).
The clinical relevance of sarcopenia in individuals with T2D is especially important to determine owing to the high background of cardiovascular morbidity and mortality in this population. In a landmark study using the AGES-Reykjavik cohort, Murphy et al. (3) concluded that increased mortality in T2D was mediated by the smaller muscle CSA on CT images of the thigh. The present study showed increased mortality associated with lower psoas muscle index in T2D (CSA, adjusted for height) on CT of the abdomen, a more commonly imaged region on clinical CT examinations. Using a somewhat different methodology, CT-derived skeletal muscle index at L3 predicted 5-year mortality in a small cohort with T2D and limb amputations (5).
The present study employed the same methodology for measuring muscle phenotypes on CT as the AA-DHS (6). Compared to European Americans in the current study, African Americans in AA-DHS had higher psoas density (54.0 vs 49.3 HU), higher paraspinous density (40.7 vs 31.6 HU), higher psoas index (4.0 vs 3.6), and higher paraspinous index (8.1 vs 7.7).  In contrast to African Americans with T2D, where only muscle indices were inversely associated with mortality (6), muscle densities were more strongly predictive of mortality in European Americans with T2D.
CT-derived muscle density is a measure of myosteatosis, a phenotype that captures aspects of muscle quality, rather than muscle quantity. Because insulin sensitivity has ancestral/ethnic determinants, differences in ectopic fat deposition including myosteatosis in African Americans compared to European Americans with T2D were not unexpected.  Prior studies have shown higher muscle mass in African American compared to European American men and women (17). This is why serum creatinine-based equations to estimate the GFR need to account for African American ancestry. In addition, myosteatosis has been reported to be higher in African Americans than European Americans and this finding is hypothesized to contribute to the increased risk for type 2 diabetes (and hypertension) in African Americans (18-22).  Since African Americans had higher baseline muscle density than European Americans, a longer follow-up interval in AA-DHS would likely be necessary to show association between lower muscle density and mortality.
Although studies of sarcopenia in cohorts with T2D are few, prior studies of CT-derived muscle metrics and mortality in non-T2D cohorts likely included some individuals with T2D, although the true percentage may not have been known or reported. In general, CT-derived muscle mass has been used to predict mortality more often than CT-derived muscle density. In a cohort of 274 hip-fracture patients followed for 8 years, CT-derived muscle index and muscle attenuation had comparable ability to predict survival (23). But in several cancer cohorts that used both muscle phenotypes, CT-derived muscle density was a better predictor of survival than muscle mass (8).
Similar to results in AA-DHS, the present findings confirmed that the psoas muscle index was inversely associated with mortality in T2D. However, in European Americans the paraspinous muscle index only showed a trend towards a similar protective relationship (p=0.11). Similar differences in the ability of the psoas versus the paraspinous muscle metrics to predict mortality have been observed in cohorts with T2D (23). While the psoas muscles are composed of more type II (fast-twitch) fibers, the paraspinous muscles are composed of more type I (slow-twitch) fibers. Muscle fiber types are differentially affected by aging and disease, with the proportion of slow-twitch fibers correlating with insulin responsiveness (24, 24). The muscle fiber type may even dependent on the location of analysis, with more slow-twitch fibers cranially and more fast-twitch fibers caudally (25). The differences in the relative proportion of muscle fiber type may help explain the difference in the observed muscle-mortality relationship in African Americans compared to European Americans with T2D.
In contrast to results in African Americans with T2D from the AA-DHS where the muscle indices were inversely associated with mortality only in men and no relationships were seen in women (6), the results in European Americans with T2D were consistent in men and women. This may relate to a longer follow-up period in the current study (11.9 years) compared to AA-DHS (7.1 years), older ages at baseline and greater numbers of deaths.
This study has strengths and limitations. Limitations include that routine PACS software was used, without thresholding of muscle as performed in other reports. While this approach may change disease prevalence, prior studies have shown it to be valid in predicting important health outcomes, including mortality in over 23,000 trauma patients (26). In addition, markers of physical function commonly used in sarcopenia studies were not obtained (such as gait speed or grip strength). Integrating measures of physical function with CT-derived muscle metrics may improve prognostication. Finally, the findings in this retrospective study do not prove causality; underlying disease processes that caused the changes in muscle metrics may have led to the increased mortality. Despite these limitations, our results showed that CT-derived muscle metrics were significant prognostic markers for long-term mortality in men and women with T2D. Strengths include use of routine PACS software to measure psoas and paraspinous muscle metrics, more generalizable to clinical workflows than methods using specialized segmentation software and tissue thresholding. The DHS cohort was extensively phenotyped for risk factors that determine mortality, including vascular calcification, medication use, and markers of glycemic control. In the Framingham Heart Study, which used the same methodology to measure muscle as the present study, paraspinous muscle density was associated with metabolic risk factors but the association was lost after adjustment for BMI (27). In the present study, the fully-adjusted models included BMI and CVD risk factors and association between muscle density and mortality persisted.
If future studies support our findings, the implications for research and patient care would be substantial. CT-derived muscle metrics could be incorporated into intervention studies evaluating diet, exercise, and pharmacologic agents to improve muscle metrics in patients with T2D. CT scans obtained during routine clinical care of patients could be used to opportunistically screen for sarcopenia. Interventions may then be prescribed to improve CT-measured muscle metrics, thereby improving survival.
In conclusion, although the interaction of adipose tissue and skeletal muscle is well established and the relationship of sarcopenia and T2D is increasingly recognized, studies of CT-derived muscle metrics in T2D cohorts are lacking. In this large cohort of European American men and women with T2D, atrophy and fatty infiltration of skeletal muscle determined from CT images was significantly associated with mortality, independent from major CVD risk factors.

Acknowledgements: The authors thank the study investigators, study staff, and participants for their continued participation.
Funding: This work was supported by grants from the National Institutes of Health R01 DK071891 (BIF), HL67348 (DWB), and the Wake Forest Claude D. Pepper Older Americans for Independence Center P30 AG21332 (TCR and LL).
Conflict of interest: No conflicts exist.
Ethical standards: All study participants provided written informed consent. DHS is approved by the Wake Forest School of Medicine IRB.

 

SUPPLEMENTARY TABLE

 

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NEUROMUSCULAR CHANGES WITH AGING AND SARCOPENIA

 

B.C. Clark

 

Ohio Musculoskeletal and Neurological Institute (OMNI), Department of Biomedical Sciences, and the Division of Geriatric Medicine at Ohio University, Athens, Ohio, USA
Corresponding author: Brian C. Clark, Ph.D. Ohio University, Ohio Musculoskeletal & Neurological Institute (OMNI), 250 Irvine Hall, Athens, OH 45701, USA, Phone: 740.593.2354, Email: clarkb2@ohio.edu

J Frailty Aging 2018;in press
Published online October 22, 2018, http://dx.doi.org/10.14283/jfa.2018.35

 


Abstract

Abstract: Sarcopenia was originally conceptualized as the age-related loss of skeletal muscle mass. Over the ensuing decades, the conceptual definition of sarcopenia has changed to represent a condition in older adults that is characterized by declining muscle mass and function, with “function” most commonly conceived as muscle weakness and/or impaired physical performance (e.g., slow gait speed). Findings over the past 15-years, however, have demonstrated that changes in grip and leg extensor strength are not primarily due to muscle atrophy per se, and that to a large extent, are reflective of declines in the integrity of the nervous system. This article briefly summarizes findings relating to the complex neuromuscular mechanisms that contribute to reductions in muscle function associated with advancing age, and the implications of these findings on the development of effective therapies.

Key words: Sarcopenia, dynapenia, aging, muscle, strength, weakness.


 

 

Sarcopenia was originally conceptualized, thirty years ago, as the age-related loss of skeletal muscle mass (1). Over the ensuing decades, sarcopenia has come to be conceptually defined as a condition in older adults that is characterized by declining muscle mass and function, with “function” most commonly conceived as muscle weakness and/or impaired physical performance (e.g., slow gait speed) (2, 3).
The central tenet for the evolution of the definition of sarcopenia is based on the premise that the loss of muscle mass leads to the loss of muscle function (e.g., weakness) and that this contributes to limitations in physical function and mobility. Two critical arguments, however, strongly question the scientific premise of this tenet:
1. Longitudinal data indicate that the age-related changes in strength are not due to muscle wasting (4, 5), and that strength, but not mass, is associated with negative health outcomes (6, 7). For instance, using data from the Health ABC study, Delmonico and colleagues (2009) assessed changes in thigh muscle size using computed tomography and isokinetic leg extensor strength serially over a 5-year period in a cohort of older adults that were between 70-79 years at baseline (4). They reported that annualized decreases in muscle strength were 2-5 times greater than the loss of muscle size in those who lost or maintained weight over the five-year period. Moreover, individuals that gained weight actually exhibited a small increase in muscle size, but this increase in muscle size did not prevent a loss of strength. Findings of this nature clearly indicate that the loss of muscle strength (and presumably power) in older adults is modestly associated with the loss of muscle mass or size, and suggest that neurological and non-muscle mass related factors are critical in the development of age-related muscle weakness. It should be noted that muscle atrophy should not be regarded as a negligible corollary of aging. Low muscle mass is associated with negative outcomes in a variety of disease conditions, and its importance to overall health should not be diminished (8).
2. Impairments in neural activation of skeletal muscle is (9) a key contributor to muscle weakness in older adults. Grip strength, due to widespread availability of grip dynamometers and ease of assessment, is by far the most common index of muscle strength in the field of aging systems and geriatrics. Loss of grip strength with advancing age has been shown to have predictive power in relation to a range of health-related conditions (6, 7, 10, 11). Grip strength is generally interpreted as a simple measure of skeletal muscle function, which is why it has largely been used in the recent conceptual definitions of sarcopenia. The interpretation of grip strength as a measure of skeletal muscle function is, however, arguably incorrect (9). Rather, a strong case can be made that grip strength, and age-related changes in grip strength in particular, is neither simple nor a measure skeletal muscle function per se (see reference (9) for a more detailed discussion) . Instead, evidence suggests that the force generated during a maximum voluntary grip force task is around half of what would be expected if the skeletal musculature itself were fully activated by the nervous system (Figure 1) (12-14), due to reduced neural drive to the muscles (15). Specifically, the maximum force that can be produced by each finger decreases in proportion to the number of other fingers that are engaged simultaneously, such that when four fingers contribute to the grip task, the maximum force that can be generated by each digit is typically less than half that produced when it is engaged in isolation (i.e., there is a force deficit) (14, 16). Moreover, this grip strength ‘force deficit’ is larger in older adults in comparison to young adults (14, 17). In agreement with the above-mentioned notion of impairments in neural activation being a key contributor to age-related changes in muscle strength, we have reported that weaker older adults exhibit a 20% deficit in voluntary (neural) activation of the wrist flexor muscles (18). In this study, the motor nerve was electrically stimulated during a maximal voluntary wrist flexion contraction and any increment in force evoked by a stimulus indicates that voluntary activation is less than 100%. Thus, voluntary activation represents the proportion of maximal possible force that is produced voluntarily, and impairment indicates some motor units are not recruited or are not firing fast enough to produce fused contractions (19). Accordingly, these findings indicate that impairments in neural activation, broadly speaking, is a key contributor to muscle weakness in older adults.

Figure 1 The force that can be generated during a maximum voluntary grip force task is around half of what would be expected if the skeletal musculature itself were fully activated. This data, which was recreated from data presented in Shinohara et al. (14), was obtained from 12 young (filled bars) and 12 older adults (unfilled bars). Subjects performed single-finger maximal voluntary contractions (MVC) as well as a four finger MVC by pressing on individual force transducers. Note the dramatic drop in the force of individual fingers during four-finger MVC tasks compared with single-finger MVC tasks (i.e., a force deficit). Further note that this force deficit was larger in older adults than young adults. Findings of this nature suggest that grip strength is heavily reflective of nervous system function, and not skeletal muscle function per se

Figure 1
The force that can be generated during a maximum voluntary grip force task is around half of what would be expected if the skeletal musculature itself were fully activated. This data, which was recreated from data presented in Shinohara et al. (14), was obtained from 12 young (filled bars) and 12 older adults (unfilled bars). Subjects performed single-finger maximal voluntary contractions (MVC) as well as a four finger MVC by pressing on individual force transducers. Note the dramatic drop in the force of individual fingers during four-finger MVC tasks compared with single-finger MVC tasks (i.e., a force deficit). Further note that this force deficit was larger in older adults than young adults. Findings of this nature suggest that grip strength is heavily reflective of nervous system function, and not skeletal muscle function per se

Significant differences for men vs. women, *P<0.05 and for elderly vs. young, +P<0.05.

 

Collectively, findings of this nature question the notion that 1) the loss of muscle mass is a critical mechanism leading to loss of muscle strength, and 2) that age-related muscle weakness is solely due to declining skeletal muscle function per se. Rather, these findings suggest that the nervous system, and specifically the neural control of skeletal muscle, is a key contributor to declining muscle and physical function commonly observed with advancing age. There is strong proof-of-concept evidence that aging results in a plethora of changes in the neuromuscular system that could theoretically effect neuromuscular function. These include changes in the nervous system, such as reductions in corticospinal excitability, degeneration as well as altered biophysical and behavioral characteristics of motor neurons, among others (for review see (19-22)). It should also be noted there are a number of non-mass dependent age-related changes in skeletal muscle properties that may also contribute to impaired neuromuscular function (e.g., excitation-contraction uncoupling and alterations in musculotendinous properties that lead to reductions in intrinsic muscle quality) (for review see (23, 24)). There has been much discussion in the literature about the relationship between fat infiltration in muscle and dynapenia. While it’s contribution to weakness is not fully understood, there is strong evidence that questions the contributing role of intermuscular fat. Specifically, a study that tracked 1,678 older adults over a 5-year period and examined the relationship between changes in muscle size, muscle fat infiltration and muscle strength, it was observed that the change in intermuscular fat explained less than 1% of the between subject variance in the change in muscle strength (4). Nevertheless, the salient point is that strong consideration needs to be given to the multiple mechanisms contributing to age-related reductions in neuromuscular function in the development of an operational definition of sarcopenia (or dynapenia, which we have previously recommended for consideration as an alternative to the term “sarcopenia”, in order to distinguish between the age-related loss of muscle strength (dynapenia) and the age-related loss of muscle mass (sarcopenia) for the reasons stated above (20, 21)).
Are We Barking Up the Wrong Tree? Sarcopenia is commonly conceptualized as a condition of the muscular system based on the rationale that the muscular system is responsible for the function of mobility (2, 3). However, this conceptualization does not give sufficient consideration to “muscle function” being a subset of “motor function”. Accordingly, one must raise the question of whether the sarcopenia field is at a critical junction in need of a major paradigm shift away from the traditional “skeletal muscle centric” focus that the field has largely pursued. For instance, the “graying of the nation” has resulted in a large number of pharmaceutical companies pursuing compounds to enhance muscle and physical function in older adults (25). To date, they have focused on compounds designed to target skeletal muscle, such as those designed to promote muscle growth, or— at a minimum— attenuate atrophy (e.g., myostatin-inhibitors) or those designed to increase skeletal muscle calcium sensitivity. These trials have, generally speaking, reported modest, if not disappointing effects, for enhancing muscle strength and physical function. Is it possible that these disappointing results are due to these compounds targeting the entirely wrong system— skeletal muscle— as opposed to the nervous system? There has certainly been an increased interest in the role of the nervous system in muscle weakness and mobility limitations in older adults in recent years, and in the coming years this answer to this question should become clearer.

 

Grant Support: This work was supported, in part, by a grant from the National Institute on Aging (R01AG044424).
Conflict of Interest Statement: Brian Clark has received research funding from the National Institutes of Health, Regeneron Pharmaceuticals, Astellas Pharma Global Development, Inc., RTI Health Solutions, Ohio Department of Higher Education, and the Osteopathic Heritage Foundations. In the past 5-years Brian Clark has received consulting fees from Regeneron Pharmaceuticals, Abbott Laboratories, and the Gerson Lehrman Group. Additionally, Brian Clark is co-founder with equity and scientific director of AEIOU Scientific, LLC.
Acknowledgements: The author wishes to thank Leatha A. Clark, DPT, MS and David W. Russ, PT, PhD for providing critical comments on an initial draft of the manuscript.
Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

 

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2.    Fielding, R.A., B. Vellas, W.J. Evans, S. Bhasin, J.E. Morley, A.B. Newman, et al. Sarcopenia: an undiagnosed condition in older adults. Current consensus definition: prevalence, etiology, and consequences. International working group on sarcopenia. J Am Med Dir Assoc 2011; 12: p. 249-56.
3.    Cruz-Jentoft, A.J., J.P. Baeyens, J.M. Bauer, Y. Boirie, T. Cederholm, F. Landi, et al. Sarcopenia: European consensus on definition and diagnosis: Report of the European Working Group on Sarcopenia in Older People. Age Ageing 2010; 39: p. 412-23.
4.    Delmonico, M.J., T.B. Harris, M. Visser, S.W. Park, M.B. Conroy, P. Velasquez-Mieyer, et al. Longitudinal study of muscle strength, quality, and adipose tissue infiltration. Am J Clin Nutr 2009; 90: p. 1579-85.
5.    Legrand, D., B. Vaes, C. Mathei, W. Adriaensen, G. Van Pottelbergh and J.M. Degryse. Muscle strength and physical performance as predictors of mortality, hospitalization, and disability in the oldest old. J Am Geriatr Soc 2014; 62: p. 1030-8.
6.    Newman, A.B., V. Kupelian, M. Visser, E.M. Simonsick, B.H. Goodpaster, S.B. Kritchevsky, et al. Strength, but not muscle mass, is associated with mortality in the health, aging and body composition study cohort. J Gerontol A Biol Sci Med Sci 2006; 61: p. 72-7.
7.    Metter, E.J., L.A. Talbot, M. Schrager and R. Conwit. Skeletal muscle strength as a predictor of all-cause mortality in healthy men. J Gerontol A Biol Sci Med Sci 2002; 57: p. B359-65.
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MUSCLE MEASURES AND NUTRITIONAL STATUS AT HOSPITAL ADMISSION PREDICT SURVIVAL AND INDEPENDENT LIVING OF OLDER PATIENTS – THE EMPOWER STUDY

 

S. VERLAAN1,2, J.M. VAN ANCUM3,5, V.D. PIERIK1, J.P. VAN WIJNGAARDEN2, K. SCHEERMAN1,5, C.G.M. MESKERS4,5, A.B. MAIER3,5,6

 

1. Department of Internal Medicine, Section of Gerontology and Geriatrics, VU University Medical Center, Amsterdam, The Netherlands; 2. Nutricia Research, Nutricia Advanced Medical Nutrition, Utrecht, The Netherlands; 3.  Department of Human Movement Sciences, VU University, Amsterdam, The Netherlands; 4. Department of Rehabilitation Medicine, VU University Medical Center, Amsterdam, The Netherlands; 5. MOVE Research Institute Amsterdam, VU University, Amsterdam, The Netherlands; 6. Department of Medicine and Aged Care, Royal Melbourne Hospital, University of Melbourne, Melbourne, Australia
Corresponding author: Sjors Verlaan, VU University Medical Center, Department of Internal Medicine, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands, E-mail: G.Verlaan@vumc.nl

J Frailty Aging 2017;6(3):161-166
Published online July 4, 2017, http://dx.doi.org/10.14283/jfa.2017.23

 


Abstract

Objectives: Older adults with sarcopenia and malnutrition are at risk for co-morbidities, hospitalization, institutionalization, and mortality. In case of hospitalization, risks may be further increased, especially in case of suboptimal dietary intake. The aim of our study was to assess whether muscle mass, muscle strength, functional performance, and nutritional status at hospital admission were associated with survival and independent living among older patients three months after discharge. Design, Setting, Participants: The EMPOWER study was an observational, prospective and longitudinal inception cohort of patients older than 70 years admitted to the VU University Medical Centre in Amsterdam, the Netherlands. Measurements: Patients were assessed for demographic and clinical characteristics, measurements of muscle mass (by bioelectrical impedance analysis), handgrip strength (by dynamometry), functional performance (self-reported ability to walk), and screened for risk of malnutrition (by SNAQ). Three months after hospital discharge, survival and living situation were assessed by a follow-up telephone interview. Results: The majority of the 378 patients enrolled were living independently at the time of hospitalization (90%) and three months post-discharge (83%). Fifty-two patients died in the period from hospital admission to three months after discharge (survival rate 86%). Higher absolute muscle mass measures and not being malnourished at admission were significantly associated with the likelihood of survival. Handgrip strength and self-reported ability to walk were positively associated with a higher chance of living independently three months after discharge, but not with survival. Conclusions: Older patients with greater muscle mass and without malnutrition at hospital admission had a higher survival rate, while measures of muscle strength and functional performance were predictive for living independently three months after hospital discharge. Different components of muscle health relate to different relevant outcomes and therefore require investigation of specifically targeted interventions in the hospitalized older population.

Key words: Muscle, sarcopenia, malnutrition, hospital.


 

 

Introduction

The age-related loss of muscle mass, strength and function constitutes the concept of sarcopenia (1), and is one of the main drivers of physical frailty in older adults (2). Sarcopenia threatens independent living, increases risk of falls and disability, hospitalization, morbidity and even mortality (3, 4). An active lifestyle and a healthy diet providing adequate protein and other essential nutrients are necessary to maintain muscle mass, strength and function (5-7), particularly in older adults who often show sedentary behaviour and are at risk for comorbidities (8, 9).  Reduced physical activity, inadequate nutritional intake, chronic inflammation and diseases, have all been described as risk factors for developing sarcopenia (2).
When older adults with sarcopenia enter the hospital, they have a higher risk of poorer clinical outcomes (10), limited recovery (11, 12), and even mortality (13, 14). Furthermore, malnutrition, especially inadequate intakes of protein, has detrimental effects on muscle mass and strength, and clinical outcomes in hospitalized patients (9). As limited physical activity, due to bed rest, and poor dietary quality and intake during hospitalization are often inevitable, hospitalization itself can thus be considered a “crisis event” that hastens the development of sarcopenia (15).  As muscle acts as reserve pool for the supply of amino acids to other organs (9), sufficient muscle mass and an adequate nutritional status at hospital admission will support patients to cope with this ‘crisis’ and may prevent vulnerable older patients from crossing the threshold of disability, dependence, and mortality (15).
The aim of our study was to assess whether components of sarcopenia, muscle mass, muscle strength, functional performance, and the nutritional status at hospital admission were associated with survival and independent living among older adults three months after discharge.

 

Methods

Study design

The Evaluation of Muscle parameters in a Prospective cohort of Older patients at clinical Wards Exploring Relations with bed rest and malnutrition (EMPOWER) study was an observational, prospective and longitudinal inception cohort study conducted from April until December 2015 at the VU university medical center in Amsterdam, the Netherlands. The study was approved by the Medical Ethics Committee of the VU university medical center.
A flowchart of patient screening, inclusion, and follow-up included in this study is shown in Figure 1. Details of the methods of enrolment are described elsewhere  (Van Ancum JM, Scheerman K, Pierik VD, et al. Muscle strength and muscle mass in older patients during hospitalization: the EMPOWER study. Under review). Briefly, all patients aged 70 years and older who were admitted to the internal medicine, acute admission, trauma and orthopedic wards and who were able and willing to sign informed consent were considered eligible for participation in the study. Patients were excluded if they were admitted to air-pressure isolation rooms, suffering from terminal illness, expected to be discharged within 24 hours, or could not be assessed within 48 hours after admission. The included patients were assessed for their demographic and clinical characteristics, measurements of muscle mass and strength, and nutritional status at hospital admission. Three months after hospital discharge, a follow-up telephone interview was performed to assess their post-discharge living situation and functional status. Living independently was defined as living at home as opposed to assisted living, living in care homes, nursing homes, and rehabilitation centres. Mortality was extracted from the hospital data system and checked by study staff.

Muscle mass

Direct segmental multi-frequency bioelectrical impedance analysis (DSM-BIA; In-Body S10; Biospace Co., Ltd, Seoul, Korea) was used to assess muscle mass, expressed as: 1) skeletal muscle mass (SMM) in kg; 2) skeletal muscle index (SMI: SMM/height2) in kg/m2; 3) relative skeletal muscle mass (SMM/body weight in kg*100) in percentage (%); and 4) fat free mass (FFM) in kg. Exclusion criteria for DSM-BIA measurement were a pacemaker or an implantable cardioverter-defibrillator, plasters or bandages that could not be removed from the positioning place of the electrodes, or amputated arm and/or leg. In 57 patients, DSM-BIA was omitted due to presence of these contraindications.

Muscle strength

Handgrip strength (HGS) was assessed using a Jamar Hydraulic Handheld Dynamometer (Sammons Preston, Inc. Bolingbrook, IL, USA). Patients were asked to squeeze maximally twice for each hand, encouraged by the trained assessor. The maximum score (in kg) of the four trials was used for the analyses (16).

Functional performance

Functional performance was assessed by the self-reported ability to walk before hospitalization as an earlier pilot study showed that the measurement of walking speed at admission was not feasible predominantly due to acute disease. Patients were asked to rate their pre-admission walking ability: either as unable to walk or to be able to walk less than 250 m, between 250m and 1 km, or able to walk more than 1 km. The reported data were dichotomized for the statistical analyses as able to walk either less or more than 1 km, following the principle of mobility disability as defined previously by Pahor, et al. (17).

Nutritional status

Nutritional status was determined using the Short Nutritional Assessment Questionnaire (SNAQ) score (range 0-7). The SNAQ is a practical, valid and reproducible questionnaire for early detection of hospital malnutrition including questions about unintentional weight loss, decrease in appetite over the last month and the use of supplemental drinks or tube feeding over the last month. Patients with a SNAQ score of zero or one point were considered as not malnourished; two or more points as moderately or severely malnourished (18).

Statistical analysis

The characteristics of included hospitalized patients with normal distribution were expressed as mean and standard deviation (SD). Non-normally distributed continuous variables were presented as median and interquartile ranges (IQR). Categorical and binomial variables were presented as numbers (n) and percentage (%). Descriptive statistics of muscle mass and strength were presented separately for male and female patients.
The associations of muscle mass, handgrip strength, self-reported ability to walk, and nutritional status versus survival and living independently three months after hospital discharge were analyzed by logistic regression adjusted for age and sex (model 1) and for age, sex, and presence of more than two comorbidities (model 2). The associations between determinant and outcome variables were presented as odds ratios (95% confidence interval (CI)). Statistical significance was set at p=0.05. All analyses were performed using the Statistical Package for the Social Sciences (IBM SPSS Statistics for Windows, Version 22.0. Armonk, NY, IBM Corp).

 

Results

During 9 months of recruitment, 838 patients were admitted to the wards, of which 378 patients were included in the present analysis (Figure 1). Patient characteristics at the time of hospital admission are presented in Table 1. The mean age was 80 ± 6 years and 49% was female.  Ninety percent of the patients were living independently at the time of hospitalization, while 83% was living independently three months after discharge. Of the 378 enrolled, 52 patients died in the period from hospital admission to three months after discharge, which resulted in a cumulative survival rate of 86%. At admission, over one third (35%) of the patients was classified as malnourished according to the SNAQ screening tool. The descriptive results for mean absolute and relative muscle mass measurements and mean handgrip strength, stratified by male and female are presented in Table 2.

 

Table 1 Demographic and clinical characteristics at hospital admission

Table 1
Demographic and clinical characteristics at hospital admission

KATZ-ADL Katz Index of Independence in Activities of Daily Living (range 0-6); 6-item CIT 6-item Cognitive Impairment Test (range 0-28); NRS Numerical Rating Scale (range 0-10); FAC Functional Ambulation Classification (range 0-5).

 

Table 2 Muscle mass and strength characteristics at hospital admission for total study population and stratified for sex

Table 2
Muscle mass and strength characteristics at hospital admission for total study population and stratified for sex

All variables are presented as mean (SD)

Figure 1 Flowchart of patient screening, inclusion, and follow-up

Figure 1
Flowchart of patient screening, inclusion, and follow-up

 

Table 3 shows that higher measures of absolute skeletal muscle mass, muscle mass adjusted for height (SMM/h2) and fat-free mass at hospital admission were significantly associated with survival. Relative skeletal muscle mass, determined as skeletal muscle mass adjusted for body weight, did not show any association. The absence of malnutrition at admission was positively associated with survival.  Neither muscle mass measures nor nutritional status were significantly associated with independent living three months post-discharge. Handgrip strength and self-reported ability to walk were significantly associated with independent living three months after discharge, while neither measure was associated with survival (Table 3).

Table 3 Associations between muscle measures and nutritional status at hospital admission with survival and living independently 3 months after hospital discharge

Table 3
Associations between muscle measures and nutritional status at hospital admission with survival and living independently 3 months after hospital discharge

Model 1 adjusted for age and sex, Model 2 adjusted for age, sex, and presence of more than two co-morbidities

 

Discussion

In this observational, prospective and longitudinal inception cohort study, we investigated the impact of the components of sarcopenia, measures of absolute and relative muscle mass, muscle strength, functional performance, and the nutritional status on survival and independent living. Older hospitalized patients with greater absolute muscle mass and without malnutrition at admission had a higher likelihood for three months survival. On the other hand, greater handgrip strength and better self-reported ability to walk were associated with a higher chance of living independently three months post-discharge.
Nutritional status and muscle measures in our group of older hospitalized patients are comparable with vulnerable older populations described in other studies. Over one third of the patients was malnourished at admission, which is in line with a prevalence rate between 20 to 50% in hospitalized patients reported in other studies (18-21). Since patients with advanced dementia were excluded and a median CIT score of 4 (IQR: 0-8) of the study population implies a normal cognitive function (22), the impact of dementia on malnutrition has not been examined in this study. Mean handgrip strength was comparable with handgrip strength in sarcopenic community dwelling older adults and acutely hospitalized older patients (23, 24). Mean skeletal muscle mass index in both male and female patients were similar to what was found in a sample of Dutch geriatric outpatients (25).
The observation that absolute muscle mass and malnutrition were associated with three months survival is in line with other studies that described an association between sarcopenia and malnutrition and increased risk of mortality in older hospitalized patients (10, 13, 14, 26, 27). These studies, however, all used different sarcopenia definitions and did not analyze the effect of the individual components of sarcopenia.
Greater absolute muscle mass appeared more important than an adequate body composition, since the relative muscle mass did not show any association with survival. In addition to the function of muscle to contract and enable movement, skeletal muscle is a reservoir of amino acids and glucose that can support protein synthesis or energy production elsewhere (28). Muscle helps to meet the metabolic needs of other organs, which is of particular importance when dealing with traumas, infections and acute (wasting) diseases (9).  This specific role of muscle is even more crucial during periods of inadequate dietary intake. Therefore, relatively small differences of muscle mass can increase the risk of morbidity and mortality in patients undergoing such a ‘catabolic crisis’ as an acute illness and hospitalisation, especially when the patients are malnourished and other sources are depleted. Thus assessing muscle mass in addition to nutritional status as part of routine care, followed by targeted exercise and nutritional interventions, can help older adults to cope with a ‘crisis’ such as hospitalization (8, 15, 23, 29).
Measurements of muscle strength and functional performance at hospital admission did not show an association with mortality, in contrast to results published in a large meta-analysis (30), where community dwelling adults with impaired physical performance measures had a higher risk of long term (2 to >20 years follow up) mortality. As such, functional measures may be less critical for short-term survival in recently hospitalized patients than the actual physical state of the patient’s body. The association of handgrip strength and the self-reported ability to walk with independent living three months after hospital discharge suggest, however, that impairments in functional measures are strong predictors for loss of independence. Preventing decline in functional performance is one of the key goals for vulnerable community dwelling older people to maintain independence in daily living and activities.  Mobility disability, determined in the LIFE study (17) and the ongoing Sprint-T study (31) by the inability to walk 400 meters, has been shown to be a reliable and important clinical and public health outcome in older people. In hospital settings, it is often impossible to measure this for all incoming patients, but the self-reported ability to walk more than 1 km could be a useful proxy, and thus requires further validation.

Strengths and limitations

The strength of this study is that we enrolled a robust sample of older adults admitted to various departments in the hospital. This variation in the type of admission helped to minimize selection bias in this sample. The longitudinal nature of the study enabled us to observe the impact of the study exposures not only during hospitalization, but also three months post-discharge.
A limitation to report is that we could not measure gait speed in patients admitted to hospital, which hampers the comparison with other studies in community dwelling older people that use gait speed in the definition of sarcopenia. Although muscle mass measurements by BIA have been used and validated in clinical trials in both community and hospital settings (13, 27, 32), BIA measurements can be influenced by the hydration status during hospital admission. One of the drawbacks of the longitudinal design was that the muscle measures were not assessed post-discharge, since the follow up data were collected by telephone interviews.

 

Conclusions

Older patients with greater muscle mass and without malnutrition at hospital admission had a higher survival rate, whereas measures of muscle strength and functional performance were predictive for living independently. Therefore, assessing muscle health and nutritional status is recommended as part of routine care in the hospitalized older population. The protective value of targeted interventions – which should be aimed at specifically improving muscle mass and function – should be addressed further next to counteracting the malnourished state.

 

Funding sources: This study was part of European Union’s Horizon 2020 research and innovation programme (No 689238 and No 675003) and financially supported by Nutricia Research, Nutricia Advanced Medical Nutrition, The Netherlands.
Conflict of interest: None declared by the authors.

 

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GRIP STRENGTH AND GAIT SPEED OF OLDER WOMEN RECEIVING PHYSICAL THERAPY IN A HOME-CARE SETTING

R.W. BOHANNON1

Program in Physical Therapy, Department of Kinesiology; Neag School of Education; University of Connecticut.

Corresponding author: Richard W Bohannon, Program in Physical Therapy, Department of Kinesiology, Neag School of Education, University of Connecticut, 358 Mansfield Road, Storrs, Connecticut, USA 06269-1101; e-mail: richard.bohannon@uconn.edu

J Frailty Aging 2014;3(1):15-17
Published online December 4, 2014, http://dx.doi.org/10.14283/jfa.2014.3


Abstract

Grip strength and gait speed have both been recommended as “vital signs” for older adults. I, therefore, sought to determine the extent to which grip strength and comfortable gait speed were limited and related in a sample of older women home-care patients. A retrospective bonus analysis was conducted using archived initial therapy records of 33 older women (mean age = 80.7 years) residing in their homes in New England (USA). Demographics, bilateral grip strength and usual gait speed data were extracted from the records. Best grip strength was 80.1% of its reference norm. Usual gait speed was 38.4% of its reference norm. Significantly more patients were below reference norm for gait speed. Both measures were significantly less than functional standards as well. The measures were not correlated significantly. Grip strength and gait speed are sensitive to limitations in older women home-care patients, but not equally so.

 

Key words: Muscle, gait, measurement, aging.


 

Both grip strength (1) and walking speed (2) have implications for everyday functioning and have been recommended for use as “vital signs” or indicators of physical status with older adults (3, 4). The 2 measures are also aspects of the frailty index proposed by Fried and associates (5). Although the measurements are simple and applicable to older women referred for rehabilitation in a home-care setting (6, 7), the literature does not contrast and compare the ability of the measures to identify limitations among such patients. The purpose of this brief report, therefore, was to describe the extent to which grip strength and walking speed were limited and related among a sample of older women patients in a home-care setting.

 

Methods

 

This study involved the retrospective review of archived initial physical therapy examination records of patients personally managed by the author in a home-care setting in New England (USA). Use of the records without informed consent was approved by the Institutional Review Board of the University of Connecticut (H10-316). To be included in the study, consecutively examined patients had to be female, at least 65 years of age, ambulatory, and have both grip strength and gait speed recorded in their initial examination note. The limitation to females was based on the small sample of males (n=3) among the patients.

Age and height were documented on the basis of self report. Weight was determined using digital scales unless impracticable; in such cases self-report was used. Body mass index was calculated using the height and weight data.

In accordance with the recommendations of the American Society of Hand Therapists, grip strength was measured with a Jamar dynamometer while patients were sitting with their arms against their sides, their elbows flexed 90 degrees, and the dynamometer handle in the second position (8). A single measurement was obtained from each side while patients were verbally encouraged to squeeze the dynamometer as hard as they could. Gait speed was measured after patients were asked to walk at a “comfortable safe speed” (usual pace). Timing with a digital stopwatch began as patients’ mid-sagittal line crossed the start of the course and ended as it passed the end of the course. Courses varied in length from 2.1 to 6.1 meters depending on the maximum testing distance available in each home. Walking began about .6 meters before the start of the course and continued for a similar distance after the end of the course.

The ability of the measurements to identify limitations involved comparing measurements obtained with published reference norms and functional criteria. For grip strength, limitations were identified by selecting the best grip strength from the 2 sides tested and comparing that value to the side- and age- relevant norms (9, 10) and to the criterion for older women performing “heavy tasks” (18.5 kg) reported by Wang and Chen (1). For gait speed, comparisons were made with the age-relevant norms published by Bohannon and Andrews (11) and the street-crossing criterion of .49 m/s described by Andrews and associates (2).

In addition to standard descriptive statistics, the patients’ best grip and gait performance were compared to norms and functional criteria using the sign test. The proportion of patients with grip and gait limitations (values less than norms) was compared using McNemar. Best grip impairments and gait limitations relative to norms (measured value/norms) were also compared using a Pearson product moment correlation.

Results

The archived records of 36 women at least 65 years of age were available. Two were non-ambulatory and 1 had no gait speed recorded. The remaining 33 women patients included in this study were diverse in regard to primary diagnosis. The primary diagnosis relevant to 2 or more patients was: cancer (n= 4), back pain (n= 3), fracture (n= 3), stroke (n= 3), trauma (n= 3), infection (n= 3), spinal stenosis (n= 2), and congestive heart failure (n= 2). No other primary diagnosis was relevant to more than a single patient. The patients’ age, height, weight, body mass index (BMI) are summarized in Table 1.

Table 1: Descriptive Statistics for Demographics, Grip Strength and Gait Speed

 

Descriptive statistics for the patients’ best grip strength and gait speed data are summarized in Table 1. Their grip strength ranged from 5.0 to 27.2 kg. Corresponding norms ranged from 14.8 to 25.6 kg. The sign test demonstrated that the patients’ grip strength was significantly less than relevant norms (z=- 3.482, p<0.001) and the criterion reported by Wang and Chen (1) (z= -3.133, p=0.002). The patients’ gait speed ranged from 12.2 to 88.4 cm/sec. Corresponding norms ranged from 94.3 to 124.1 cm/sec. The sign test demonstrated that the patients’ speed was significantly less than relevant norms (z= -5.570, p<0.001) and the standard reported by Andrews and associates (2) (z=-2.785, p=0.005). The proportion of patients whose grip strength and gait speed were below relevant norms was 27/33 (81.8%) and 33/33 (100%) respectively. The McNemar test showed these proportions to be significantly different (p=0.031). The proportion of patients whose grip strength and gait speed were below relevant criterion values was 26/33 (78.8%) and 25/33 (75.8%) respectively. The McNemar test showed that these proportions did not differ significantly (p= 1.00). Best grip strength and gait speed expressed as a percentage of norms were not correlated significantly (r=0.191, p=0.287).

 

Discussion

This study demonstrated that 2 measures recommended as vital signs for older adults, grip strength and gait speed, are readily obtainable in a home care setting. The data gathered indicate that older women managed in such a setting tended to have hand-grip strengths that were impaired and walks that were limited in speed. These findings reinforce those of previous studies of the same population (6, 7). The data also suggest that the patients’ grip strength and walking speed were low relative to functional criteria. Together these findings provide support for the use of the measures as vital signs.

Grip strength and gait speed were not equally likely to be limited in this study. Relative to norms, gait speed was more likely to be limited. This may be because gait is more complex and multifaceted than grasping. It might also be because lower limb strength, to which gait speed is related, declines more than upper limb strength with age (12). Relative to the criteria selected for comparison, the proportion of patients with limited grip strength and walking speed did not differ. These findings along with the discovery of a low and insignificant correlation between grip impairments and gait limitations indicate that either measure is not a surrogate for the other for identifying physical limitations in older women.

While informative, this study has several limitations. First, the study was retrospective and was generated from the case- load of a single clinician in a specific setting (patients’ homes). Whether the case load is representative of that of other clinicians practicing in a home-care setting or other settings is not established. Second, the sample size was small. This factor, however, did not preclude identifying significant results. Third, the gait speed measured may have been influenced by differences in test distances. It may have also been suppressed by the short distance measured and the acceleration provided prior to timing. That said, evidence exists that measurement distances are not particularly critical and that stable walking speed can be realized after a single stride (13, 14). Finally, a single criterion was selected for determining the functional adequacy of measured grip strength and gait speed. Alternative criteria may reveal different results.

In conclusion, grip strength and gait speed may both be appropriate indicators of physical status (vital signs) for older women managed in a home-care setting. However, they are not equally sensitive to limitations and are not correlated significantly. Therefore, one can not be used in lieu of the other to identify limitations.

 

Conflict of Interest Statement: The author declares that there is no conflict of interest.

Financial Disclosure: I certify that no party with a direct interest in the findings of this research has or will confer any benefit to the author or any organization with which he is associated.