INTRODUCTION
Cystic fibrosis (CF) is an autosomal recessive inherited disease caused by a mutation in the CF transmembrane conductance regulator (CFTR) protein.1 These mutations disrupt chloride and sodium transport across epithelial cell membranes, resulting in abnormally thick, dehydrated mucus that obstructs airways and organ system ducts. The ensuing effects include chronic pulmonary infections, pancreatic insufficiency, malabsorption, and progressive respiratory decline.2, 3 Advances in CF diagnostics and disease management have significantly improved life span and quality of life (QoL) for people with CF4; therefore, it is important to understand the disease process, comorbidities, and ways to manage the disease to optimize QoL in an aging population.
Body composition, particularly lean mass, has emerged as a critical factor influencing clinical outcomes in CF. Although body mass index (BMI) is commonly used as a clinical marker, previous work has demonstrated the importance of physical activity. Physical activity is important for the maintenance of lean mass and prevention of excess adiposity,5 and studies have shown that physical activity can extend life span and quality of body composition in CF populations.6, 7, 8 Lean mass, predominantly composed of skeletal muscle, has been shown to be a stronger predictor of lung function compared with BMI in CF populations.9 In contrast, greater fat mass is inversely correlated with lung function in people with CF.10, 11 Although fat‐free mass depletion is well documented in CF populations,12, 13 muscle strength and quality are less studied.14 Individuals with CF exhibit lower handgrip strength—a proxy for muscle strength—compared with healthy controls.15, 16, 17 A prior study found a positive relationship between handgrip strength and fat‐free mass in adolescents and adults with CF.18 Muscle quality, quantified by Barbat‐Artigas et al as the muscle power per unit of muscle mass,19 is an additional factor in determining muscle function and may serve as an additional nutrition assessment tool.20, 21 Despite its potential clinical utility, muscle quality has not been previously characterized in adults with CF.
Although handgrip strength is a validated proxy for muscle function in aging and other clinical populations, it has not been well characterized in adults with CF. In this study, we used handgrip strength as an operational measure of muscle function.
Health‐related QoL (HRQoL) is an important clinical outcome22 and the CF Questionnaire‐Revised (CFQ‐R) is a widely used and validated HRQoL tool for individuals with CF.23, 24 The CFQ‐R is a questionnaire that assesses the degree of the participant's physical, mental, and psychosocial symptoms for teens and adults (aged ≥14 years).25 Reported indices of the CFQ‐R, which follow disease progression and associations between the CFQ‐R and BMI, lung function, and respiratory muscle strength, have previously been described.24, 26, 27, 28 Both lung function and HRQoL measures decreased over time at similar rates,27 supporting the utility of this tool as an indicator of disease severity in people with CF. It is expected that HRQoL correlates positively with physical activity, lean mass, and strength; however, the data investigating these relationships in an adult CF population are scarce.29
The objective of this study was to assess muscle strength and physical activity in a cohort of adults with CF compared with healthy controls and to examine interrelationships among physical activity, body composition, handgrip strength and muscle quality, and QoL in adults with CF.
MATERIALS AND METHODS
Participants and study design
This observational, cross‐sectional study included 27 clinically stable adults with CF and 24 aged‐matched healthy controls recruited between October 2014 and November 2018. The Emory University institutional review board approved this study, and every participant provided written informed consent before participating. All testing procedures were conducted at the Emory University Hospital Clinical Research Network unit of the Georgia Clinical and Translational Science Alliance (Atlanta, GA, USA).
The inclusion criteria for participants with CF included confirmed CF diagnosis via a chloride sweat test and/or CFTR genetic test; confirmation of any Class I, II, or III CFTR mutation; and a stable medical regimen for ≥3 weeks (no recent pulmonary exacerbations or administration of oral or intravenous antibiotics or glucocorticoids). Exclusion criteria included pregnancy, inability or not willing to discontinue enteral tube feeds for a night before a study visit, most recently measured forced expiratory volume in 1 s as a percentage of predicted (FEV1%) of <40%, or self‐reported drug or alcohol abuse. FEV1% is a key measure of pulmonary function and disease severity in people with CF.30 Healthy control participants were recruited via flyers and word of mouth and were age‐matched within 18 months of an individual with CF.
The inclusion criteria for healthy control volunteers were being aged 18–50 years and the absence of any hospitalization in the previous year (with the exception of motor vehicle accidents). The exclusion criteria for controls were the presence of a chronic infection, respiratory disease, cardiometabolic disease, acute illness within the previous 2 weeks of measurement or recruitment, history of malignancy in the past 5 years, weight instability (±10% of body weight within the previous 6 months), drug or alcohol abuse, or a BMI >30 kg/m2.
The medical history information of participants with CF, including CFTR genotype and pancreatic sufficiency status, was obtained from the electronic medical record and/or the CF Foundation Patient Registry. Blood 25‐hydroxyvitamin D (ng/ml) was obtained from the most recent medical records. The most recent lung function data were obtained from the electronic medical record, with spirometry testing performed at the Emory University Hospital Adult CF Clinic, which follows the American Thoracic Society/European Respiratory Society guidelines for pulmonary function testing.31 The healthy controls did not undergo lung function testing.
Study assessments
All patients underwent total body composition assessment (lean mass, fat mass, percent body fat, arm lean mass, and bone mineral density [BMD]) via dual‐energy x‐ray absorptiometry (DXA) using a Lunar iDXA system. Height (in meters) and weight (in kilograms) were measured with no shoes, using a manual stadiometer and digital scale, respectively; and BMI was determined as kg/m2. Peripheral muscle strength was estimated by handgrip strength using a Jamar Plus Hand dynamometer.
Handgrip strength was used throughout the study as the operational measure of peripheral muscle function. For the procedure, participants were seated with the arm holding the dynamometer at a 90° angle. The participants contracted on the dynamometer at maximum strength three times, alternating hands between each measurement, with a 1‐min break in between each hand.
The mean of all six measurements (three per hand) was determined and used for analysis. Muscle quality was calculated as the average handgrip strength for both hands divided by the total arm lean mass from DXA assessment.19 All participants completed the International Physical Activity Questionnaire (IPAQ). The IPAQ is a validated, self‐reported physical activity questionnaire assessing physical activity over the span of 7 days.32 IPAQ provides a total score reporting overall physical activity as well as subscale scores for physical activity intensity domains including walking and moderate‐ and vigorous‐intensity activity.
Only participants with CF completed the validated CFQ‐R, a self‐reported and disease‐specific questionnaire covering 12 domains: physical functioning, role limitations, vitality, emotion, social health, body image, eating disturbances, treatment burden, health perception, weight, respiratory symptoms, and digestive symptoms. Higher total scores represent a better HRQoL.24
Statistical analysis
Data were stored in a REDCap database and imported into JMP Pro 14 (SAS Institute Inc, Cary, NC) for statistical analyses. Distributions of continuous variables were visually inspected for normality. The mean and SDs for normally distributed continuous variables, median and interquartile range for variables not normally distributed, and count and proportions for categorical variables were determined.
A two‐tailed t test or Wilcoxon rank sum test was used to assess differences in the mean or median values of the demographic and clinical measurements between the healthy control group and the CF group. Relationships between variables were assessed with Pearson correlations or Spearman correlation coefficients, as needed, depending on the normality of distributions. Statistical significance was determined at a P value < 0.05.
RESULTS
Demographic and clinical characteristics
Demographic and clinical characteristics of healthy controls and participants with CF are presented in Table 1. There were 51 participants included in this study (24 healthy controls and 27 participants with CF). The mean ± SD age was 26.6 ± 7.8 years in the healthy control group and 27.7 ± 8.9 years in the CF group.
Participants in both groups were predominantly White, and the mean BMI in both groups was in the normal weight range. All participants with CF were pancreatic insufficient.
Measures of handgrip strength, muscle quality, and IPAQ‐derived physical activity scores (total, walking, moderate, and vigorous) for all participants are presented in Table 2. There were no statistically significant differences in these measures between the groups.
Correlations among physical activity, body composition, muscle function, and muscle quality
The relationships among physical activity, body composition, muscle quality, and handgrip strength for adults with CF are presented in Table 3. Muscle quality was positively and significantly related to total IPAQ (ρ = 0.49, P = 0.009) and walking IPAQ scores (ρ = 0.60, P = 0.0001). Lung function was not associated with IPAQ scores (all P > 0.30).
The vigorous IPAQ score was inversely related to fat mass (ρ = −0.38, P = 0.05). Similarly, percent body fat was significantly inversely related to vigorous IPAQ among non‐CF controls (ρ = −0.43, P = 0.03; Table S1).
Correlations of body composition and handgrip strength
The relationship between handgrip strength and body composition measures among participants with CF is shown in Figure 1. Handgrip strength was positively correlated to body weight (r = 0.47, P = 0.02), lean mass (r = 0.77, P < 0.001), arm lean mass (r = 0.86, P < 0.001), and total BMD (r = 0.64, P < 0.001). Handgrip strength was inversely associated with percent body fat (r = −0.49, P = 0.01).
Handgrip strength was not associated with fat mass (r = −0.16, P = 0.43). Handgrip strength was not statistically significantly associated with lung function (r = 0.30, P = 0.15).
The relationship between handgrip strength and body composition measures among healthy participants is shown in Table S2. Handgrip strength was positively associated with weight (r = 0.79, P = 0.0001), arm lean mass (r = 0.87, P = 0.0001), lean mass (r = 0.89, P = 0.0001), and total BMD (r = 0.51, P = 0.01). Handgrip strength was inversely associated with percent body fat (r = −0.63, P = 0.001).
Handgrip strength was not associated with fat mass (r = −0.17, P = 0.43).
Correlations between CFQ‐R domains and body composition measures are presented in Table 4. Physical functioning was inversely associated with total body fat (ρ = −0.63, P = 0.004) and percent body fat (ρ = −0.66, P = 0.002). Emotion was positively and significantly associated with lean mass (ρ = 0.41, P = 0.03), fat‐free mass (ρ = 0.42, P = 0.03), and arm lean mass (ρ = 0.43, P = 0.03).
Treatment burdens were inversely associated with total body fat (ρ = −0.49, P = 0.009) and percent body fat (ρ = −0.47, P = 0.01). Social functioning was inversely associated with total body fat (ρ = −0.45, P = 0.02) and percent body fat (ρ = −0.47, P = 0.01). Body image was positively associated with body weight (ρ = 0.58, P = 0.001), lean mass (ρ = 0.41, P = 0.03), fat‐free mass (ρ = 0.42, P = 0.03), and arm lean mass (ρ = 0.40, P = 0.04).
The weight domain was positively associated with total body fat (ρ = 0.55, P = 0.003) and percent body fat (ρ = 0.59, P = 0.001). Digestive health was inversely associated with total body fat (ρ = −0.45, P = 0.02) and percent body fat (ρ = −0.53, P = 0.004).
DISCUSSION
With improvements in treatment extending life expectancy, there is a growing need to understand how muscle health and function impact long‐term outcomes and QoL among people with CF. In this study, we confirmed important interrelationships among body composition, handgrip strength, physical activity, and QoL in young adults with CF. Notably, our findings suggest that handgrip strength may serve as a clinically relevant surrogate for body composition.
Furthermore, we provide novel data integrating both muscle mass and function as a composite indicator of muscle quality in people with CF.
Although BMI has been the predominant indicator of nutrition status in CF, it does not distinguish among muscle, bone, and fat mass. Evidence suggests lean mass is a more important predictor of lung function in CF compared with BMI and other body composition components10, 33, 34; thus, there has been a recent push to assess body composition in individuals with CF. However, only relying on the quantity of lean mass is limiting because it does not provide information about muscle function, strength, or quality.
Studies in non‐CF aging populations have suggested that handgrip strength as a measure of muscle function is a better predictor of clinical outcomes compared with lean mass.20, 35
Contrary to our hypothesis, there was not a statistically significant difference in handgrip strength between adults with CF and the healthy control group. There was also no statistically significant association between handgrip strength and lung function as measured by FEV1%. As previously reported by Bellissimo et al, participants with CF in the present study had similar lean mass and BMI compared with healthy controls,33 thus null findings in handgrip strength difference likely reflect similarities in lean mass.
The null findings in our study may reflect the broader changes in the management and recommendations of patients with CF. Although previous studies have reported lower handgrip strength in individuals with CF compared with healthy controls, our findings suggest this difference may be diminishing in contemporary adult CF populations. Improved nutrition interventions, widespread emphasis on physical activity, and early adoption of CF care guidelines may contribute to more preserved muscle function.
Our cohort, although examined before the prevalence of CFTR modulators, still reflects this shift in management. Rather than conflicting with prior studies, our findings may reflect a changing clinical picture in which physical deficits are less pronounced.
Studies have shown that resistance training can improve fat‐free mass and muscle strength in both children and adults with CF without impairing their nutrition status.36 A recent Cochrane review supported resistance training as a key component of physical activity for patients with CF to help maintain and improve lean mass.37 The mean handgrip strength of our participants with CF was above European Sarcopenia Consensus guideline cut‐points to define risk for sarcopenia.21, 38 The present findings are consistent with widespread improvements in nutrition status in the CF population as a whole.39
To our knowledge, this is the first study to characterize muscle quality in adults with CF. Previous studies have identified significant muscle deficits in adults with CF using lower‐limb assessments such as quadriceps strength and cross‐sectional imaging.16 For example, Pinet et al reported reduced quadriceps strength and muscle size in adults with CF compared with controls, despite similar BMI and body weight, and found preserved or increased abdominal muscle thickness and diaphragm mass, suggesting that muscle wasting is more pronounced in the lower limbs.40 Similarly, Troosters et al found that >50% of participants with CF had quadriceps weakness, which was associated with impaired exercise capacity.15 In contrast, our findings suggest that handgrip strength may be relatively preserved in adults with CF. This may reflect regional differences in muscle involvement, as prior studies have reported greater impairments in lower‐limb muscles, particularly the quadriceps.
Muscle quality, operationalized as handgrip strength per unit measure of arm lean mass, did not differ between the individuals with CF and the healthy controls. It is important to note that other factors should be considered in the assessment of muscle quality, such as muscle tissue composition, which includes fat infiltration and cellular characterization of muscle fibers.41 We have previously shown in this cohort that, despite similar total body composition between adults with CF and healthy controls, visceral adipose tissue deposition was significantly higher in individuals with CF, and this was positively associated with fasting glucose levels.33 Future studies in CF should assess deposition of fat between muscles (intermuscular fat), as this may help explain muscle quality differences not captured by lean mass alone and has been shown in non‐CF populations to correlate with visceral adiposity and other predictors of metabolic health.42
In the present investigation, handgrip strength was significantly associated with several indices of body composition, including lean mass and BMD. Consistent with the current findings, another adult CF study found that lean mass was positively associated with handgrip strength.43 The positive correlations between handgrip strength and DXA‐derived body composition measures of lean mass and BMD suggest that handgrip strength may be clinically useful as a proxy for body composition assessments. Although DXA is considered the clinical gold standard for the assessment of body composition, its cost and radiation emission limits its feasibility as a tool to regularly monitor body composition.
Future studies should determine if changes in body composition over time correlate with changes in handgrip strength in a population with CF.
In this study, participants with CF who engaged in a higher level of physical activity had better muscle quality. Higher circulating and local proinflammatory cytokines, secondary to increasing respiratory distress and frequent infections, may place people with CF at risk for muscle loss and strength deficits.44 Previous studies have suggested anti‐inflammatory effects of physical activity in people with CF.37, 44 Although muscle strength was similar between the groups, the positive association between muscle quality and physical activity reflects the importance of staying active for people with CF.
Body composition measures were associated with several CF QoL questionnaire domains. Lean mass was positively associated with a higher body image and emotion scores. Olveira et al similarly reported a positive relationship between fat‐free mass and CFQ‐R domains.45 In the present investigation, levels of adiposity were inversely associated with several QoL domains including physical functioning, treatment burden, digestive health, social functioning, and weight.
This inverse relationship suggests that perceived QoL is lower with higher adiposity. Previous studies assessing body composition with CFQ‐R have not shown these inverse relationships with adiposity. In contrast, studies have shown a positive association between body fat and the weight domain, suggesting less perceived problems gaining weight with higher adiposity.45, 46 Together, these studies highlight key differences in the relationship of varying body composition components with perceived QoL domains in CF.
A major strength of the current investigation study was the use of an age‐matched healthy control group to make comparisons for clinical characteristics with the patient population with CF. Similarities in several body composition components minimized the level of confounding factors for the between‐group comparisons. In addition, DXA enabled accurate body composition assessment in comparison with measures that have been more traditionally used, such as BMI and skinfold thickness.
Experimental considerations include the small sample size, which limited our ability to assess complex regression models adjusting for potential confounding variables, and the cross‐sectional nature of the study, which limits the ability to make cause and effect inferences. Additionally, we used a handheld dynamometer to assess muscle strength, which, although more portable and clinically useful, does not take into account strength in quadriceps or biceps.16, 47 Further, the current study relied on self‐reported data for physical activity. Similar to food intake often being underreported, a social desirability bias may promote a tendency for participants to overestimate their physical activity.48 Future studies should employ objective measures of physical activity (accelerometers) and exercise capacity (such as 6‐min walking tests or cardiopulmonary exercise testing).49 Finally, this study was conducted before the widespread use of CFTR modulators designed to target the mutation in the CFTR gene defect, thus it is not known if observed relationships persist among people taking CFTR modulators.
However, given the increased median age of survival in people with CF, exercise and other lifestyle‐based studies and interventions designed to optimize QoL among people with CF in the post‐CFTR modulator era are highly warranted.
In summary, these findings reinforce the critical role of maintaining muscle mass and physical activity in promoting well‐being among individuals with CF. They further underscore the value of incorporating accessible measures of physical function and muscle quality into routine clinical care for people with CF. Particularly as the CF population continues to age, these results support the integration of simple functional assessments such as handgrip strength testing to guide personalized strategies aimed at enhancing QoL in this population.
AUTHOR CONTRIBUTIONS
Benjamin H. Crain, Vin Tangpricha, Thomas R. Ziegler, and Jessica A.
Alvarez contributed to the conception and design of research. Moriah P. Bellissimo, Lucia A.
Gonzalez Ramirez, Elizabeth A. Ivie, William R. Hunt, Thomas R.
Ziegler, and Jessica A. Alvarez contributed to the acquisition of the data. Benjamin H.
Crain, Carly Harris, Moriah P. Bellissimo, Lucia A. Gonzalez Ramirez, and Jessica A.
Alvarez contributed to analysis of the data. Benjamin H. Crain, Carly Harris, Moriah P.
Bellissimo, William R. Hunt, Vin Tangpricha, Thomas R. Ziegler, Ryan A.
Harris, and Jessica A. Alvarez contributed to the interpretation of the data. Benjamin H.
Crain, Carly Harris, and Jessica A. Alvarez drafted the manuscript.
CONFLICT OF INTEREST STATEMENT
None declared.
Supporting information