Assessing Muscle Quality in Women with Fibromyalgia and Associations with Biopsychological Factors: A Cross-Sectional Study

Assessing Muscle Quality in Women with Fibromyalgia and Associations with Biopsychological Factors: A Cross-Sectional Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Assessing Muscle Quality in Women with Fibromyalgia and Associations with Biopsychological Factors: A Cross-Sectional Study Vike Maria Tamar Leão Leão de Almeida, Ana Cristina Rodrigues Lacerda, and 11 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8080873/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Introduction: Fibromyalgia (FM) is a chronic condition affecting predominantly women, characterized by widespread pain, fatigue, and impaired functionality. Poorer clinical outcomes are linked to changes in muscle strength and body composition. The Muscle Quality Index (MQI) has been proposed as a relevant measure to detect the risk of functional disability. However, the assessment of MQI in women with FM and its association with biopsychosocial factors remains unclear. Methods: Forty-seven women with FM (53.45 ± 7.32 years) were assessed for quality of life (SF-36), FM impact, depressive symptoms, sleep quality, oxidative stress markers, and functional capacity. MQI was calculated using laboratory-based (five times sit-to-stand test [5xSTS]/lower limb lean mass by DEXA) and field-based (5xSTS/body mass index) methods. Results: The pain domain of the SF-36 showed significant associations with both laboratory-based MQI (r=0.534; p<0.001) and field-based MQI (r=0.461; p=0.001), explaining 27.8% and 20.4% of their variance, respectively. MQI also correlated with SF-36 physical functioning, role-physical, and functional capacity. Field- and laboratory-based MQI were strongly correlated (r=0.93; p<0.0001). Conclusion: Pain emerged as the primary factor negatively affecting MQI. The field MQI proved to be a practical, valid, and clinically applicable alternative for functional assessment in women with FM Health sciences/Diseases Health sciences/Health care Health sciences/Medical research Health sciences/Rheumatology Health sciences/Signs and symptoms Fibromyalgia Women Muscle quality Pain Figures Figure 1 Figure 2 Introduction Fibromyalgia (FM) is a rheumatic condition characterized by chronic, widespread musculoskeletal pain. It is often accompanied by manifestations such as fatigue, sleep disturbances, morning stiffness, depressive symptoms, gastrointestinal changes, and irritable bowel syndrome 1,2 . It is estimated that 80 to 90% of individuals diagnosed with FM are women 3 . This female predominance is attributed to multiple factors, including changes in central nervous system responsiveness, a higher prevalence of anxiety and depression, altered behavior in response to pain, and hormonal influences related to the menstrual cycle 4 . In addition to the clinical presentation of persistent widespread pain 1 , psychological manifestations such as anxiety and depression are also common in FM. They are often associated with pain catastrophizing, which in turn leads to high levels of stress and increase sensitivity to painful stimuli 5 . Furthermore, evidence points to a significant increase in oxidative stress in individuals with FM, which is associated with disease severity and may lead to muscle damage, affecting strength and endurance, and predisposing to early fatigue 6,7,8 . In this regard, oxidative stress biomarkers and quality of life were identified as significant contributors to muscle pain and reduced lean body mass in patients with FM, reinforcing the systemic impact of the disease 9 . Additionally, subsequent findings from the same research group 9 demonstrated that exercise-based interventions, such as whole-body vibration training, can modulate oxidative stress markers and improve body composition, indicating promising strategies to mitigate the deleterious effects associated with FM. Consequently, individuals with FM commonly present with reduced functional capacity, impaired ability to perform activities of daily living, a negative impact on social and professional life, and poorer quality of life 10, 11, 3 . Additionally, high annual economic costs are incurred, which include medical consultations, productivity loss, hospitalizations, and the use of multiple classes of medications 12 . Previous studies have shown that individuals with FM may exhibit unfavorable body composition, which is associated with physical inactivity and worse clinical presentation 13.14,15 . Women with FM tend to have a higher body fat percentage, higher body mass index, and greater waist circumference 16 . Furthermore, a lower lean mass index has been linked to decreased muscle performance and poorer quality of life in women with FM 9. Compared to healthy controls, these women demonstrated lower muscle strength and functional capacity 17 . Possible physiological explanations for the reduced muscle strength in women with FM include impaired blood circulation, disturbances in growth regulation and energy metabolism, alterations in muscle fibers, and altered neuromuscular control mechanisms caused by pain and reduced levels of physical activity 18,19,20,21,22 . In this context, women with FM may have an increased risk of impaired muscle quality index (MQI). This measure has been proposed as clinically relevant for identifying individuals at risk of functional disability and is considered an important prognostic factor for mortality 23 . According to the literature, the MQI can be calculated using laboratory-based estimates (laboratory MQI) and field-based estimates (field MQI). Laboratory MQI is typically determined by the ratio of muscle strength to lean muscle mass measured by dual-energy X-ray absorptiometry (DEXA). Conversely, field MQI is calculated as the muscle strength ratio to body mass index (BMI) 24,25,26 . These methods for assessing skeletal muscle mass vary in cost and availability and are used for research and clinical purposes. The choice between laboratory- and field-based MQI estimations involves a trade-off between assessment sensitivity and cost 24 . Individuals with a high MQI have a lower risk of functional impairment compared to those with a low MQI, while individuals with greater muscle mass but low MQI are at increased risk of functional impairment 27 . In this sense, high muscle quality is more beneficial than having greater muscle mass 27 . Evidence indicates a direct relationship between muscle strength and MQI, indicating that lower strength levels are associated with poorer muscle quality 28,29 . Furthermore, MQI is also negatively influenced by subcutaneous adipose tissue accumulation and high body fat percentages, demonstrating an inverse relationship between MQI and adiposity 30,31 . Despite the importance of this measure, no studies to date have investigated MQI in women diagnosed with FM and its relationship with biopsychosocial factors. Therefore, this study aimed to evaluate MQI in women with FM and its association with biopsychosocial aspects, including pain, quality of life, sleep quality, depressive symptoms, functional capacity, and oxidative stress. Additionally, this study examined the association between field-based and laboratory-based MQI in women with FM. METHODS Study Design and Ethical Considerations This quantitative, cross-sectional, and exploratory study was conducted in accordance with the guidelines of the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) 32,33 . The research was approved by the Research Ethics Committee of the Federal University of Vales do Jequitinhonha and Mucuri (approval number 4.510.517) and was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki for research involving human subjects. This is a secondary analysis of a study examining the association between FM and oxidative stress parameters, with results published elsewhere 9 . Sample The sample size was estimated at 41 participants using an a priori analysis based on F-tests for a multiple linear regression model, with an effect size (f²) of 0.44, an alpha error of 5%, and a power of 80%. The model included seven predictors: FM impact, functional capacity, depressive symptoms, sleep quality, pain, quality of life, and oxidative stress, with MQI as the dependent variable. The effect size (f²) was calculated using the Psychometrica calculator 34 , based on the results of a previous study 25 . The sample size was determined using the G*Power® software (Franz Faul, University of Kiel, Germany), version 3.1.9.2. Women aged ≥ 18 years with a medical diagnosis of FM, confirmed according to the criteria set by the American College of Rheumatology 35 , were included in this study. Women with any condition that prevented them from completing the questionnaires and/or performing the physical tests were excluded. Assessment of the impact of fibromyalgia The Fibromyalgia Impact Questionnaire (FIQ) is a tool developed to assess the impact of FM on individuals’ daily lives. It encompasses dimensions such as physical functioning, work ability, physical symptoms, and emotional aspects, organized into 10 main items. The score ranges from 0 to 100, with higher values indicating greater impairment in quality of life. The FIQ has been translated and validated for the Brazilian population 36 . Assessment of quality of life Short Form Health Survey 36 (SF-36): The SF-36 questionnaire assesses multidimensional quality of life over one year. It consists of 36 items grouped into eight scales: physical functioning (10 items), role limitations due to physical problems (4 items), pain (2 items), general health perceptions (5 items), vitality (4 items), social functioning (2 items), role limitations due to emotional problems (3 items), and mental health (5 items). Each item yields a score that is subsequently transformed into a scale ranging from 0 (worst health state) to 100 (best health state), and each domain is analyzed separately 37 . Assessment of depressive symptoms Beck Depression Inventory (BDI): The BDI is a clinical and research instrument used to assess the severity of depressive symptoms. It consists of 21 items with four response options scored from 0 to 3, indicating increasing symptom intensity. The items evaluate emotional, cognitive, motivational, and somatic aspects, such as sadness, pessimism, fatigue, sleep disturbances, appetite changes, and self-critical thoughts. The total score ranges from 0 to 63, with higher scores indicating more severe depressive symptoms. According to the Brazilian validation, depression severity is classified as minimal or absent for scores from 0 to 13, mild from 14 to 19, moderate from 20 to 28, and severe from 29 to 63 38 . Assessment of sleep quality Pittsburgh Sleep Quality Index (PSQI): The PSQI consists of 19 items grouped into seven components: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, the use of sleep medication, and daytime dysfunction. Each component is scored from 0 to 3, and the sum of these scores yields a global score ranging from 0 to 21. Higher scores indicate worse perceived sleep quality. The Brazilian version of the PSQI has been validated and demonstrates adequate reliability for use in clinical and research settings 39 . Oxidative Stress Biomarkers The median cubital vein was punctured aseptically to obtain blood samples. To remove cells and debris, tubes containing EDTA were centrifuged at 3000× g for 10 min at 20 °C and stored as plasma and erythrocyte aliquots at –80 °C. According to previously published methods, oxidative stress biomarkers were assessed by measuring plasma levels of lipid peroxidation products (thiobarbituric acid reactive substances TBARS), enzymatic antioxidants (erythrocyte activity levels of the enzymes catalase CAT and superoxide dismutase SOD) and non-enzymatic antioxidants (total antioxidant capacity of plasma FRAP). The TBARS level was reported in nanomoles MDA per milligram of protein, SOD activity was reported in units (U) per milligram of protein, and the CAT activity was reported in DE/min per milligram protein, where DE represents the variation in enzyme activity for 1 min 40, 41, 42, 43 . Functional capacity and muscle strength Functional capacity was assessed using the Timed Up and Go (TUG) test. Performance on this test is related to the time taken to walk, perform postural transitions, and change direction while walking. The test involves standing up from a chair with a backrest (without using the arms for support), walking a distance of three meters, turning around, returning, and sitting down again 44, 45 . The Five Times Sit-to-Stand Test (5xSTS) was used to assess lower limb muscle strength. The test began with the participant seated in the middle of a chair, with an upright back, feet flat on the floor, and arms crossed over the chest. Upon an auditory signal, the participant was instructed to stand up fully and return to a seated position, repeating this movement as quickly as possible. The time required to complete five repetitions was recorded 46 . Anthropometric and body composition assessment Dual-energy X-ray absorptiometry (DEXA) (Lunar Radiation Corporation, Madison, Wisconsin, USA, DPX model with Encore 2005 software) was used to assess body composition, allowing for the quantification of lower limb lean mass (kg). For this study, participants were positioned in the scanner area so that the sagittal line marked on the equipment aligned with the center of specific anatomical landmarks, such as the skull, spine, pelvis, and lower limbs 47 . Body Mass Index (BMI): Participants had their weight and height measured using an analog scale (Welmy, model 110, precision of 0.1 kg) with an attached stadiometer (precision of 0.5 cm). BMI was calculated by dividing body weight by height squared (kg/m²), according to the classification of the World Health Organization 48. Muscle Quality Index (MQI) The MQI was obtained using the following calculations: a) Laboratory-based MQI: the ratio between lower limb strength, assessed by the 5xSTS test, and lower limb lean mass, measured by DEXA 49 ; b) Field-based MQI: the ratio between lower limb strength, assessed by the 5xSTS test, and BMI 25, 50 . Statistical Analysis GPower software version 3.1.9.2 was used to calculate the sample size. A pilot study with ten FM patients was conducted to assess the sample size. We calculated that 47 FM patients were needed using all dependent variables, an effect size of 0.21 (for muscle pain), seven feasible predictors, a likelihood of error of 5% and 80% power. The Statistical Package for the Social Sciences version 22.0 (SPSS Statistics; IBM, Armonk, NY, USA) and MedCalc Statistical Software version 13.1 (MedCalc Software, Ostend, Belgium) were used to conduct statistical analyses. The Kolmogorov–Smirnov test was used to verify the data distribution. Continuous variables were displayed as the mean and standard deviation (normal distribution) or the median and interquartile range (non-normal distribution), depending on the distribution. Univariate and stepwise multivariate linear regression were used to confirm the determinants of muscle soreness and lean body mass. In each multivariate model adjusted for age, variables related to muscle pain and lean body mass were included in the univariate analysis (p < 0.1). Four assumptions were used in the linear regression analysis: linearity, residual distribution, homoscedasticity, and the absence of multicollinearity. Scatter plots were used to assess the linearity of the independent variables and residuals, and a histogram was used to examine the distribution of residuals. The scatter plot confirmed the homoscedasticity, which was defined by the evenly distributed residuals in the regression line. The variance inflation factor (VIF) values below 10.0 were used to define the absence of multicollinearity. Additionally, the Durbin–Watson test verified the variables' autocorrelation, and the values between 1.5 and 2.5 showed no autocorrelation in the data. Statistical significance was set at 5%. RESULTS A total of 71 participants were initially screened. Of these, 21 did not meet the inclusion criteria, and three declined to participate. Thus, 47 women with FM were included in the study. The flow of participants through the study is shown in Figure 1. Participant characteristics, muscle quality indicators, and biopsychosocial variables are presented in Table 1. Among the variables analyzed in the study, five demonstrated a correlation with laboratory-based MQI and presented a p-value < 0.20: SF-36 pain domain (Pearson’s r = 0.534; p = 0.001); SF-36 physical functioning domain (Spearman's r = 0.374; p = 0.037); SF-36 role-physical domain (Spearman's r = 0.428; p = 0.012); TUG (Spearman's r = -0.371; p = 0.038); and CAT (Spearman's r = 0.295; p = 0.134). For field-based MQI, five variables demonstrated significant correlations: SF-36 pain domain (Pearson's r = 0.461; p = 0.005); SF-36 physical functioning domain (Spearman's r = 0.440; p = 0.009); PSQI (Spearman's r = -0.282; p = 0.161); TUG (Spearman's r = -0.401; p = 0.021) and CAT (Spearman's r = 0.319; p = 0.095). These variables were selected for simple linear regression analysis (Table 2). Only the SF-36 physical functioning, the SF-36 role-physical domain, and the SF-36 pain domain showed a significant association with laboratory-based MQI (p < 0.05). Subsequently, multiple linear regression analysis was performed (Table 2), revealing a significant association of laboratory-based MQI with pain. These independent variables explained 27.8% of the variation in MQI (p = 0.000). Table 2. Univariate and multivariate linear regression analysis (stepwise) for predicting laboratory-based MQI in women with FM (n=47). Independent Variable mean ±SD Univariate Multivariate β R 2 p -value β R 2 p -value SF-36 Pain 30.93 + 16.18 0.534 0.285 0.001 0.528 0.278 0.000 SF-36 Role-Physical 16.17 + 27.88 0.428 0.183 0.012 TUG 8.44 + 1.74 -0.371 0.138 0.038 SF-36 Physical Functioning 38.72 + 20.81 0.374 0.140 0.037 CAT 2.99 + 1.44 0.295 0.087 0.134 Legend: β, standardized regression coefficient; R 2 , adjusted determination coefficient; p -value, statistical significance; FM, fibromyalgia; Muscle Quality Index, MQI; timed up and go, TUG; Short Form Health Survey 36, SF-36; catalase, CAT. Simple linear regression analysis revealed a significant association between field-based MQI and the SF-36 pain, physical functioning, and role-physical domains, as well as with the PSQI and the TUG (p < 0.05). Subsequently, multiple linear regression analysis was performed (Table 3), showing a significant association between field-based MQI and Pain. This independent variable explained 20.4% of the variance in field-based MQI (p < 0.001). Table 3. Univariate and multivariate linear regression analysis (stepwise) for predicting Field-based MQI in women with FM (n=47). Independent Variable mean ±SD Univariate Multivariate β R 2 p -Value β R 2 p -Value SF-36 Pain 30.93 + 16.18 0.461 0.213 0.005 0.452 0.204 0.001 SF-36 Physical Functioning 38.72 + 20.81 0.440 0.194 0.009 TUG 8.44 + 1.74 -0.401 0.161 0.021 PSQI 12.12 + 3.8 -0.282 0.080 0.161 CAT 2.99 + 1.44 0.319 0.102 0.095 Legend: β, standardized regression coefficient; R 2 , adjusted determination coefficient; p -value, statistical significance; FM, fibromyalgia; Muscle Quality Index, MQI; timed up and go, TUG; Short Form Health Survey 36, SF-36; Pittsburgh sleep quality index, PSQI; catalase, CAT. There was a strong correlation between field-based MQI and laboratory-based MQI measurements (r = 0.93, p < 0.0001; Figure 2). A strong positive correlation was observed between the two methods (r = 0.93, p < 0.0001), supporting the validity of field-based MQI as a feasible alternative to laboratory-based assessments. DISCUSSION The primary objective of this study was to investigate the association between MQI measures and several biopsychosocial factors in women with FM, including disease impact, quality of life, pain, sleep quality, depressive symptoms, functional capacity, and oxidative stress. Additionally, we aimed to examine the relationship between laboratory-based and field-based MQI measures. Our main findings indicate that: (1) MQI values (both field and laboratory) were significantly associated with lower pain levels in women with FM; (2) a strong and positive association was observed between laboratory-based MQI and field-based MQI. Furthermore, we found that higher values of both laboratory and field MQI were correlated with improved quality of life, specifically in the physical functioning and role domains of the SF-36 questionnaire, and better performance on the TUG test. Chronic pain is one of the most debilitating symptoms of FM, significantly affecting functional capacity, quality of life, and mental health in affected individuals 51 . In the present study, pain showed a significant association with laboratory-based MQI (r = 0.528; p = 0.000) and field-based MQI (r = 0.452; p = 0.001). Moreover, pain was the only variable that remained in the regression model, accounting for 27.8% of the variance in based-laboratory MQI (p = 0.000) and 20.4% of the variance in based-field MQI (p < 0.001). These results underscore the pivotal role of pain in explaining the variability in muscle quality among women with FM. These findings suggest that individuals with higher muscle quality experience lower pain perception, indicating that efficient muscle support may exert a protective effect against the central sensitization characteristic of the disease. Several studies support our findings, indicating that muscle quality is relevant in mediating pain across chronic conditions. In osteoarthritis, higher muscle quality and strength have been associated with a reduced risk of pain progression and improved functional performance 52, 53 . Similar evidence has been reported in low back pain, where alterations in paraspinal muscles assessed by magnetic resonance imaging correlated with higher pain intensity 54 . In chronic musculoskeletal pain, reduced grip strength was also linked to neuropathic symptoms, particularly among women 55 . Moreover, a recent meta-analysis demonstrated that pain negatively affects strength stability, thereby impairing muscle quality and function and ultimately hindering rehabilitation 56 . These findings reinforce that preserving muscle mass alone is insufficient; muscle quality, i.e., the ability to efficiently generate force, is essential for modulating pain and functional capacity. Population-based evidence further supports this hypothesis. In a study using the National Health and Nutrition Examination Survey (2011–2014), a higher MQI was associated with a reduced risk of arthritis (adjusted OR = 0.73; CI: 95%; 0.61–0.88; p = 0.001) 12 . So, individuals with greater contractile efficiency are less prone to experiencing painful symptoms in degenerative joint conditions, which aligns with our findings in women with FM. Additionally, studies indicate that even among individuals with preserved muscle mass, poor muscle quality is associated with greater functional disability and higher pain intensity in chronic musculoskeletal conditions 52, 53 . From a functional perspective, muscles with reduced efficiency may generate joint and tissue overload, thereby increasing peripheral nociceptive stimuli and reflecting alterations in motor unit recruitment and neuromuscular transmission 57 . These mechanisms highlight the importance of improving muscle quality rather than focusing solely on muscle mass. In the present study, higher MQI values were associated with better performance on the TUG test for both laboratory-based MQI (r = -0.371; p = 0.038) and field-based MQI (r = -0.401; p = 0.021). We also observed a positive correlation between MQI and self-reported functional capacity assessed by the SF-36 questionnaire (laboratory-based MQI: r = 0.374; p = 0.037; field-based MQI: r = 0.440; p = 0.009). These findings reinforce the relevance of muscle quality as a determinant of functional autonomy, particularly when assessed through field-based methods. Each 1-unit increase in field-based MQI has been associated with a 2.59-second reduction in TUG performance (β = −0.540; p = 0.004), highlighting the strong discriminative capacity of this measure to detect impaired mobility in obese older women 58 . Across different populations, such evidence supports field-based MQI as a consistent and clinically applicable predictor of mobility. In contrast, the explanatory value of laboratory-based MQI may vary depending on sample characteristics or methodological approaches. These findings are particularly relevant given that functional capacity is essential for maintaining autonomy in daily activities 59 . The loss of this capacity leads to greater dependence, negatively affecting self-esteem, psychological well-being, and overall quality of life 14. Therefore, interventions aimed at improving muscle quality may not only alleviate pain but also restore movement confidence, thereby helping to break the cycle of inactivity, pain, and disability 60 . From a mechanical and physiological perspective, maintaining muscle strength can help mitigate abnormal biomechanical loads on joints and soft tissues, thereby reducing nociceptive input 61 . Therefore, optimizing MQI may serve as a functional indicator and a strategic therapeutic target for managing chronic pain in FM. The different methods for calculating the Muscle Quality Index (MQI) remain a subject of debate in the scientific literature. While laboratory-based measures are obtained through specialized and less accessible equipment 28, field-based measures are easily applicable in clinical practice 62, 27, 63 . Recent studies have explored and compared these two approaches 24, 26, 58 . Investigating the association between these methods is particularly relevant, as field-based MQI offers an accessible and feasible methodology for clinical and community settings, serving as a quick and practical tool for health professionals to assess physical function. In this study, a strong positive correlation was observed between laboratory-based MQI and field-based MQI (r = 0.93; p < 0.0001) in women with FM. This finding corroborates previous research conducted with older adults 24 and adolescents with Down syndrome 26, demonstrating the feasibility of using both approaches to predict physical performance rather than focusing solely on global "strength" which often only reflects the quantity of muscle mass 62, 24, 26 . Our results further suggest that field-based MQI assessment in women with FM may effectively indicate functional performance, comparable to more complex laboratory-based measures. In addition to the variables significantly associated with MQI, other biopsychosocial and physiological dimensions evaluated in this study warrant contextualization, even though they did not demonstrate significant or robust associations in the regression models. In FM, sleep disturbances are highly prevalent and often linked to increased pain perception, persistent fatigue, and poorer physical performance 64 . Similarly, depression is a highly prevalent comorbidity among patients with FM. It can negatively impact pain perception, functional capacity, and engagement in therapeutic activities, highlighting the need for multidimensional management strategies that consider both the emotional state and physical intervention of patients 54 . The lack of associations with muscle quality observed in this study may reflect the indirect effect of these symptoms, mediated by variables such as pain, functional capacity, and vitality. Oxidative stress plays a crucial role in the pathogenesis of FM, being associated with mitochondrial dysfunction, redox imbalance, and central sensitization, mechanisms that exacerbate pain 12. Alterations in these markers have been linked to greater clinical severity, including increased pain, fatigue, impaired muscle performance, and reduced quality of life 65, 66 . Although oxidative stress was not a significant predictor of muscle quality in our model, it remains a relevant biomarker for muscle deterioration and pain chronification in women with FM. Supporting this perspective, reduced antioxidant levels and poorer quality of life were associated with greater muscle pain, whereas higher oxidative stress levels, lower muscle performance, and poorer quality of life explained the reduction of lean mass in women with FM, reinforcing the central role of these mechanisms in the clinical severity of the syndrome 9 . In summary, the strong correlation between laboratory-based and field-based MQI underscores the robustness of this measure, supporting the validity of both approaches for assessing muscle quality in women with fibromyalgia (FM). While laboratory-based MQI provides precise information by integrating body composition measures obtained through DEXA, field-based MQI offers a practical and cost-effective alternative that can be easily applied in clinical and community settings. This finding highlights the potential of field-based MQI as a valuable tool for functional monitoring, particularly in contexts where access to advanced imaging technologies is limited. Consequently, field-based MQI may facilitate the broader implementation of muscle quality assessment, guiding individualized rehabilitation strategies and enhancing the applicability of research findings in real-world clinical practice. Strengths and limitations This study showcases several strengths. To our knowledge, it is the first to investigate the association between laboratory- and field-based MQI and biopsychosocial factors in women with FM. Another strength is the use of complementary methods to assess MQI, which combines both laboratory-based and clinically feasible field-based approaches, enhancing the findings' external validity and clinical applicability. Furthermore, the inclusion of multidimensional outcomes encompassing physical, psychological, and physiological aspects such as muscle strength, body composition, quality of life, depressive symptoms, sleep quality, and oxidative stress enabled a comprehensive analysis within a biopsychosocial framework. Finally, the study highlights the potential of the field-based MQI as an accessible and cost-effective tool for clinical practice and functional monitoring in women with FM, supporting its integration into healthcare and rehabilitation settings. However, several limitations should be acknowledged. First, the cross-sectional design of the study precludes causal inferences between the investigated variables. Second, the study focused solely on women, which limits which limits the generalizability of the findings to men with fibromyalgia (FM). While the sample size was sufficient for the statistical analyses, it was relatively small, which may have restricted the detection of more subtle associations. Additionally, the absence of a control group hindered the ability to directly compare muscle quality levels with those of individuals without FM. Conclusion In women with FM, pain emerged as the primary factor significantly associated with both field- and laboratory-based MQI. Moreover, higher laboratory and field-based MQI values were correlated with improved quality of life and better functional capacity. The strong agreement between laboratory- and field-based MQI suggests that field-based assessment may be a practical and cost-effective alternative for clinical and community settings. These findings underscore the importance of muscle quality as a relevant therapeutic target in women with FM. Abbreviations 5xSTS : Five Times Sit-to-Stand test BDI : Beck Depression Inventory BMI : Body Mass Index CAT : Catalase DEXA : Dual-energy X-ray absorptiometry FIQ : Fibromyalgia Impact Questionnaire FM : Fibromyalgia FRAP : Ferric Reducing Antioxidant Power MQI : Muscle Quality Index PSQI : Pittsburgh Sleep Quality Index SF-36 : Short Form Health Survey 36 SOD : Superoxide Dismutase TBARS : Thiobarbituric Acid Reactive Substances TUG : Timed Up and Go test Declarations Acknowledgments: The authors are grateful for the technical support and provision of equipment by the Centro Integrado de Pós-Graduação e Pesquisa em Saúde , Universidade Federal dos Vales do Jequitinhonha e Mucuri, Diamantina, MG, Brazil. Author contributions: Conceptualization: VMTLA; JMS; SFF. Formal analysis: VMTLA; LACT; SFF; Investigation: VMTLA; JMF; LACT; SFF; Methodology: VMTLA; JMF; VGCR; SFF; Resources: SFF; Supervision: SFF; Visualization: JMF; JNVS; SFF; Writing – original draft: VMTLA, VMF, JNVS, SFF; Writing – review & editing: VMTLA; JNVS; VGCR; SEM; CMR; VAM; RT; ACRL; MCMO; DFMV; SFF; Funding We thank the Universidade Federal dos Vales do Jequitinhonha e Mucuri for institutional support, CNPq 407629/2023-8, CAPES PROEXT-PG 88881.926996/2023-01, and FAPEMIG for support and scholarships. Data availability The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Ethics approval and consent to participate: The Research Ethics Committee on Human Beings of the Federal University of Jequitinhonha and Mucuri Valleys (UFVJM) approved the study, and all participants signed the Informed Consent Form. 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Oxidative stress in fibromyalgia: a systematic review. Oxid Med Cell Longev. 2022;2022:1–12. Table Table 1 is available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Table1.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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09:05:28","extension":"html","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":122076,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8080873/v1/95bf81c297780baef8f37f86.html"},{"id":97133037,"identity":"638256ed-afe0-42f7-8efe-9083aa1324ac","added_by":"auto","created_at":"2025-12-01 09:05:28","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":272522,"visible":true,"origin":"","legend":"\u003cp\u003eFlow diagram of participants through the study.\u003c/p\u003e\n\u003cp\u003eFlow diagram illustrating the selection process of participants with fibromyalgia, including the number assessed for eligibility, excluded cases (with reasons), and final sample included in the analysis (n = 47).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8080873/v1/74626587a0d75517f7763a73.png"},{"id":97133034,"identity":"7bfd1639-ff2f-4197-a54a-7ab9d7a9ab6c","added_by":"auto","created_at":"2025-12-01 09:05:28","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":139169,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation between laboratory-based Muscle Quality Index (MQI) and field-based MQI in women with fibromyalgia.\u003c/p\u003e\n\u003cp\u003eScatter plot showing the strong positive correlation between laboratory-based MQI (five times sit-to-stand test/lower limb lean mass by DEXA) and field-based MQI (five times sit-to-stand test/body mass index) in women with fibromyalgia (r = 0.93; p \u0026lt; 0.001).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8080873/v1/62a7f5f48dc1c0d4b23fb4b1.png"},{"id":98626078,"identity":"c8257111-edd1-4f6f-8c19-91e9ead01eb6","added_by":"auto","created_at":"2025-12-19 17:09:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1504720,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8080873/v1/1f254a66-6f93-494e-8d48-37a77ddbc9d1.pdf"},{"id":97141776,"identity":"c96510ca-3f89-4457-a21b-49eacd3a1f99","added_by":"auto","created_at":"2025-12-01 10:07:00","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":15963,"visible":true,"origin":"","legend":"","description":"","filename":"Table1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8080873/v1/e3f5394518eff2306d763574.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Assessing Muscle Quality in Women with Fibromyalgia and Associations with Biopsychological Factors: A Cross-Sectional Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eFibromyalgia (FM) is a rheumatic condition characterized by chronic, widespread musculoskeletal pain. It is often accompanied by manifestations such as fatigue, sleep disturbances, morning stiffness, depressive symptoms, gastrointestinal changes, and irritable bowel syndrome \u003csup\u003e1,2\u003c/sup\u003e. It is estimated that 80 to 90% of individuals diagnosed with FM are women \u003csup\u003e3\u003c/sup\u003e. This female predominance is attributed to multiple factors, including changes in central nervous system responsiveness, a higher prevalence of anxiety and depression, altered behavior in response to pain, and hormonal influences related to the menstrual cycle \u003csup\u003e4\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn addition to the clinical presentation of persistent widespread pain\u003csup\u003e1\u003c/sup\u003e, psychological manifestations such as anxiety and depression are also common in FM. They are often associated with pain catastrophizing, which in turn leads to high levels of stress and increase sensitivity to painful stimuli \u003csup\u003e5\u003c/sup\u003e. Furthermore, evidence points to a significant increase in oxidative stress in individuals with FM, which is associated with disease severity and may lead to muscle damage, affecting strength and endurance, and predisposing to early fatigue \u003csup\u003e6,7,8\u003c/sup\u003e. In this regard, oxidative stress biomarkers and quality of life were identified as significant contributors to muscle pain and reduced lean body mass in patients with FM, reinforcing the systemic impact of the disease \u003csup\u003e9\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eAdditionally, subsequent findings from the same research group \u003csup\u003e9\u003c/sup\u003e demonstrated that exercise-based interventions, such as whole-body vibration training, can modulate oxidative stress markers and improve body composition, indicating promising strategies to mitigate the deleterious effects associated with FM.\u003c/p\u003e\u003cp\u003eConsequently, individuals with FM commonly present with reduced functional capacity, impaired ability to perform activities of daily living, a negative impact on social and professional life, and poorer quality of life \u003csup\u003e10, 11, 3\u003c/sup\u003e. Additionally, high annual economic costs are incurred, which include medical consultations, productivity loss, hospitalizations, and the use of multiple classes of medications \u003csup\u003e12\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003ePrevious studies have shown that individuals with FM may exhibit unfavorable body composition, which is associated with physical inactivity and worse clinical presentation \u003csup\u003e13.14,15\u003c/sup\u003e. Women with FM tend to have a higher body fat percentage, higher body mass index, and greater waist circumference \u003csup\u003e16\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eFurthermore, a lower lean mass index has been linked to decreased muscle performance and poorer quality of life in women with FM 9. Compared to healthy controls, these women demonstrated lower muscle strength and functional capacity \u003csup\u003e17\u003c/sup\u003e. Possible physiological explanations for the reduced muscle strength in women with FM include impaired blood circulation, disturbances in growth regulation and energy metabolism, alterations in muscle fibers, and altered neuromuscular control mechanisms caused by pain and reduced levels of physical activity \u003csup\u003e18,19,20,21,22\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn this context, women with FM may have an increased risk of impaired muscle quality index (MQI). This measure has been proposed as clinically relevant for identifying individuals at risk of functional disability and is considered an important prognostic factor for mortality \u003csup\u003e23\u003c/sup\u003e. According to the literature, the MQI can be calculated using laboratory-based estimates (laboratory MQI) and field-based estimates (field MQI). Laboratory MQI is typically determined by the ratio of muscle strength to lean muscle mass measured by dual-energy X-ray absorptiometry (DEXA). Conversely, field MQI is calculated as the muscle strength ratio to body mass index (BMI) \u003csup\u003e24,25,26\u003c/sup\u003e. These methods for assessing skeletal muscle mass vary in cost and availability and are used for research and clinical purposes. The choice between laboratory- and field-based MQI estimations involves a trade-off between assessment sensitivity and cost \u003csup\u003e24\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIndividuals with a high MQI have a lower risk of functional impairment compared to those with a low MQI, while individuals with greater muscle mass but low MQI are at increased risk of functional impairment \u003csup\u003e27\u003c/sup\u003e. In this sense, high muscle quality is more beneficial than having greater muscle mass \u003csup\u003e27\u003c/sup\u003e. Evidence indicates a direct relationship between muscle strength and MQI, indicating that lower strength levels are associated with poorer muscle quality \u003csup\u003e28,29\u003c/sup\u003e. Furthermore, MQI is also negatively influenced by subcutaneous adipose tissue accumulation and high body fat percentages, demonstrating an inverse relationship between MQI and adiposity \u003csup\u003e30,31\u003c/sup\u003e. Despite the importance of this measure, no studies to date have investigated MQI in women diagnosed with FM and its relationship with biopsychosocial factors. Therefore, this study aimed to evaluate MQI in women with FM and its association with biopsychosocial aspects, including pain, quality of life, sleep quality, depressive symptoms, functional capacity, and oxidative stress. Additionally, this study examined the association between field-based and laboratory-based MQI in women with FM.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003e\u003cstrong\u003eStudy Design and Ethical Considerations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis quantitative, cross-sectional, and exploratory study was conducted in accordance with the guidelines of the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) \u003csup\u003e32,33\u003c/sup\u003e. The research was approved by the Research Ethics Committee of the Federal University of Vales do Jequitinhonha and Mucuri (approval number 4.510.517) and was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki for research involving human subjects.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis is a secondary analysis of a study examining the association between FM and oxidative stress parameters, with results published elsewhere \u003csup\u003e9\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe sample size was estimated at 41 participants using an a priori analysis based on F-tests for a multiple linear regression model, with an effect size (f\u0026sup2;) of 0.44, an alpha error of 5%, and a power of 80%. The model included seven predictors: FM impact, functional capacity, depressive symptoms, sleep quality, pain, quality of life, and oxidative stress, with MQI as the dependent variable. The effect size (f\u0026sup2;) was calculated using the Psychometrica calculator \u003csup\u003e34\u003c/sup\u003e, based on the results of a previous study \u003csup\u003e25\u003c/sup\u003e. The sample size was determined using the G*Power\u0026reg; software (Franz Faul, University of Kiel, Germany), version 3.1.9.2.\u003c/p\u003e\n\u003cp\u003eWomen aged \u0026ge; 18 years with a medical diagnosis of FM, confirmed according to the criteria set by the American College of Rheumatology \u003csup\u003e35\u003c/sup\u003e, were included in this study. Women with any condition that prevented them from completing the questionnaires and/or performing the physical tests were excluded.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssessment of the impact of fibromyalgia\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Fibromyalgia Impact Questionnaire (FIQ) is a tool developed to assess the impact of FM on individuals\u0026rsquo; daily lives. It encompasses dimensions such as physical functioning, work ability, physical symptoms, and emotional aspects, organized into 10 main items. The score ranges from 0 to 100, with higher values indicating greater impairment in quality of life. The FIQ has been translated and validated for the Brazilian population \u003csup\u003e36\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssessment of quality of life\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eShort Form Health Survey 36 (SF-36): The SF-36 questionnaire assesses multidimensional quality of life over one year. It consists of 36 items grouped into eight scales: physical functioning (10 items), role limitations due to physical problems (4 items), pain (2 items), general health perceptions (5 items), vitality (4 items), social functioning (2 items), role limitations due to emotional problems (3 items), and mental health (5 items). Each item yields a score that is subsequently transformed into a scale ranging from 0 (worst health state) to 100 (best health state), and each domain is analyzed separately \u003csup\u003e37\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssessment of depressive symptoms\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBeck Depression Inventory (BDI): The BDI is a clinical and research instrument used to assess the severity of depressive symptoms. It consists of 21 items with four response options scored from 0 to 3, indicating increasing symptom intensity. The items evaluate emotional, cognitive, motivational, and somatic aspects, such as sadness, pessimism, fatigue, sleep disturbances, appetite changes, and self-critical thoughts. The total score ranges from 0 to 63, with higher scores indicating more severe depressive symptoms. According to the Brazilian validation, depression severity is classified as minimal or absent for scores from 0 to 13, mild from 14 to 19, moderate from 20 to 28, and severe from 29 to 63 \u003csup\u003e38\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssessment of sleep quality\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePittsburgh Sleep Quality Index (PSQI): The PSQI consists of 19 items grouped into seven components: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, the use of sleep medication, and daytime dysfunction. Each component is scored from 0 to 3, and the sum of these scores yields a global score ranging from 0 to 21. Higher scores indicate worse perceived sleep quality. The Brazilian version of the PSQI has been validated and demonstrates adequate reliability for use in clinical and research settings \u003csup\u003e39\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOxidative Stress Biomarkers\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe median cubital vein was punctured aseptically to obtain blood samples. To remove cells and debris, tubes containing EDTA were centrifuged at 3000\u0026times; g for 10 min at 20 \u0026deg;C and stored as plasma and erythrocyte aliquots at \u0026ndash;80 \u0026deg;C. According to previously published methods, oxidative stress biomarkers were assessed by measuring plasma levels of lipid peroxidation products (thiobarbituric acid reactive substances TBARS), enzymatic antioxidants (erythrocyte activity levels of the enzymes catalase CAT and superoxide dismutase SOD) and non-enzymatic antioxidants (total antioxidant capacity of plasma FRAP). The TBARS level was reported in nanomoles MDA per milligram of protein, SOD activity was reported in units (U) per milligram of protein, and the CAT activity was reported in DE/min per milligram protein, where DE represents the variation in enzyme activity for 1 min \u003csup\u003e40, 41, 42, 43\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunctional capacity and muscle strength\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFunctional capacity was assessed using the Timed Up and Go (TUG) test. Performance on this test is related to the time taken to walk, perform postural transitions, and change direction while walking. The test involves standing up from a chair with a backrest (without using the arms for support), walking a distance of three meters, turning around, returning, and sitting down again \u003csup\u003e44, 45\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe Five Times Sit-to-Stand Test (5xSTS) was used to assess lower limb muscle strength. The test began with the participant seated in the middle of a chair, with an upright back, feet flat on the floor, and arms crossed over the chest. Upon an auditory signal, the participant was instructed to stand up fully and return to a seated position, repeating this movement as quickly as possible. The time required to complete five repetitions was recorded \u003csup\u003e46\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnthropometric and body composition assessment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDual-energy X-ray absorptiometry (DEXA) (Lunar Radiation Corporation, Madison, Wisconsin, USA, DPX model with Encore 2005 software) was used to assess body composition, allowing for the quantification of lower limb lean mass (kg). For this study, participants were positioned in the scanner area so that the sagittal line marked on the equipment aligned with the center of specific anatomical landmarks, such as the skull, spine, pelvis, and lower limbs \u003csup\u003e47\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eBody Mass Index (BMI): Participants had their weight and height measured using an analog scale (Welmy, model 110, precision of 0.1 kg) with an attached stadiometer (precision of 0.5 cm). BMI was calculated by dividing body weight by height squared (kg/m\u0026sup2;), according to the classification of the World Health Organization 48.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMuscle Quality Index (MQI)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe MQI was obtained using the following calculations: a) Laboratory-based MQI: the ratio between lower limb strength, assessed by the 5xSTS test, and lower limb lean mass, measured by DEXA \u003csup\u003e49\u003c/sup\u003e; b) Field-based MQI: the ratio between lower limb strength, assessed by the 5xSTS test, and BMI \u003csup\u003e25, 50\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGPower software version 3.1.9.2 was used to calculate the sample size. A pilot study with ten FM patients was conducted to assess the sample size. We calculated that 47 FM patients were needed using all dependent variables, an effect size of 0.21 (for muscle pain), seven feasible predictors, a likelihood of error of 5% and 80% power. The Statistical Package for the Social Sciences version 22.0 (SPSS Statistics; IBM, Armonk, NY, USA) and MedCalc Statistical Software version 13.1 (MedCalc Software, Ostend, Belgium) were used to conduct statistical analyses. The Kolmogorov\u0026ndash;Smirnov test was used to verify the data distribution. Continuous variables were displayed as the mean and standard deviation (normal distribution) or the median and interquartile range (non-normal distribution), depending on the distribution. Univariate and stepwise multivariate linear regression were used to confirm the determinants of muscle soreness and lean body mass. In each multivariate model adjusted for age, variables related to muscle pain and lean body mass were included in the univariate analysis (p \u0026lt; 0.1). Four assumptions were used in the linear regression analysis: linearity, residual distribution, homoscedasticity, and the absence of multicollinearity. Scatter plots were used to assess the linearity of the independent variables and residuals, and a histogram was used to examine the distribution of residuals. The scatter plot confirmed the homoscedasticity, which was defined by the evenly distributed residuals in the regression line. The variance inflation factor (VIF) values below 10.0 were used to define the absence of multicollinearity. Additionally, the Durbin\u0026ndash;Watson test verified the variables\u0026apos; autocorrelation, and the values between 1.5 and 2.5 showed no autocorrelation in the data. Statistical significance was set at 5%.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eA total of 71 participants were initially screened. Of these, 21 did not meet the inclusion criteria, and three declined to participate. Thus, 47 women with FM were included in the study. The flow of participants through the study is shown in Figure 1. Participant characteristics, muscle quality indicators, and biopsychosocial variables are presented in Table 1.\u003c/p\u003e\n\u003cp\u003eAmong the variables analyzed in the study, five demonstrated a correlation with laboratory-based MQI and presented a p-value \u0026lt; 0.20: SF-36 pain domain (Pearson\u0026rsquo;s r = 0.534; p = 0.001); SF-36 physical functioning domain (Spearman\u0026apos;s r = 0.374; p = 0.037); SF-36 role-physical domain (Spearman\u0026apos;s r = 0.428; p = 0.012); TUG (Spearman\u0026apos;s r = -0.371; p = 0.038); and CAT (Spearman\u0026apos;s r = 0.295; p = 0.134).\u003c/p\u003e\n\u003cp\u003eFor field-based MQI, five variables demonstrated significant correlations: SF-36 pain domain (Pearson\u0026apos;s r = 0.461; p = 0.005); SF-36 physical functioning domain (Spearman\u0026apos;s r = 0.440; p = 0.009); PSQI (Spearman\u0026apos;s r = -0.282; p = 0.161); TUG (Spearman\u0026apos;s r = -0.401; p = 0.021) and CAT (Spearman\u0026apos;s r = 0.319; p = 0.095).\u003c/p\u003e\n\u003cp\u003eThese variables were selected for simple linear regression analysis (Table 2). Only the SF-36 physical functioning, the SF-36 role-physical domain, and the SF-36 pain domain showed a significant association with laboratory-based MQI (p \u0026lt; 0.05). Subsequently, multiple linear regression analysis was performed (Table 2), revealing a significant association of laboratory-based MQI with pain. These independent variables explained 27.8% of the variation in MQI (p = 0.000).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Univariate and multivariate linear regression analysis (stepwise) for predicting laboratory-based MQI in women with FM (n=47).\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"625\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIndependent\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003emean \u0026plusmn;SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnivariate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 184px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Multivariate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026beta;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026beta;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eSF-36\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ePain\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e30.93 \u003cu\u003e+\u003c/u\u003e 16.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.534\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.285\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.528\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.278\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eSF-36 Role-Physical\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e16.17 \u003cu\u003e+\u003c/u\u003e 27.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.428\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.183\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTUG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e8.44 \u003cu\u003e+\u003c/u\u003e 1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-0.371\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.038\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eSF-36\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ePhysical Functioning\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e38.72 \u003cu\u003e+\u003c/u\u003e 20.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.374\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.140\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eCAT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.99 \u003cu\u003e+\u003c/u\u003e 1.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.295\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.087\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eLegend: \u0026nbsp;\u0026beta;, standardized regression coefficient; R\u003csup\u003e2\u003c/sup\u003e, adjusted determination coefficient; \u003cem\u003ep\u003c/em\u003e-value, statistical significance; FM, fibromyalgia; Muscle Quality Index, MQI; timed up and go, TUG; Short Form Health Survey 36, SF-36; catalase, CAT.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSimple linear regression analysis revealed a significant association between field-based MQI and the SF-36 pain, physical functioning, and role-physical domains, as well as with the PSQI and the TUG (p \u0026lt; 0.05). Subsequently, multiple linear regression analysis was performed (Table 3), showing a significant association between field-based MQI and Pain. This independent variable explained 20.4% of the variance in field-based MQI (p \u0026lt; 0.001).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. Univariate and multivariate linear regression analysis (stepwise) for predicting Field-based MQI in women with FM (n=47).\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"616\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIndependent\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003emean \u0026plusmn;SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnivariate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 191px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Multivariate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026beta;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep\u003c/em\u003e-Value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026beta;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep\u003c/em\u003e-Value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eSF-36\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ePain\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e30.93 \u003cu\u003e+\u003c/u\u003e 16.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.461\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.213\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0.452\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0.204\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eSF-36 Physical Functioning\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e38.72 \u003cu\u003e+\u003c/u\u003e 20.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.440\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.194\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTUG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e8.44 \u003cu\u003e+\u003c/u\u003e 1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-0.401\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.161\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ePSQI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e12.12 \u003cu\u003e+\u003c/u\u003e 3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-0.282\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.080\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.161\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eCAT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.99 \u003cu\u003e+\u003c/u\u003e 1.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.319\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.095\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eLegend: \u0026nbsp;\u0026beta;, standardized regression coefficient; R\u003csup\u003e2\u003c/sup\u003e, adjusted determination coefficient; \u003cem\u003ep\u003c/em\u003e-value, statistical significance; FM, fibromyalgia; Muscle Quality Index, MQI; timed up and go, TUG; Short Form Health Survey 36, SF-36; Pittsburgh sleep quality index, PSQI; catalase, CAT.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThere was a strong correlation between field-based MQI and laboratory-based MQI measurements (r = 0.93, p \u0026lt; 0.0001; Figure 2).\u003c/p\u003e\n\u003cp\u003eA strong positive correlation was observed between the two methods (r = 0.93, p \u0026lt; 0.0001), supporting the validity of field-based MQI as a feasible alternative to laboratory-based assessments.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe primary objective of this study was to investigate the association between MQI measures and several biopsychosocial factors in women with FM, including disease impact, quality of life, pain, sleep quality, depressive symptoms, functional capacity, and oxidative stress. Additionally, we aimed to examine the relationship between laboratory-based and field-based MQI measures. Our main findings indicate that: (1) MQI values (both field and laboratory) were significantly associated with lower pain levels in women with FM; (2) a strong and positive association was observed between laboratory-based MQI and field-based MQI. Furthermore, we found that higher values of both laboratory and field MQI were correlated with improved quality of life, specifically in the physical functioning and role domains of the SF-36 questionnaire, and better performance on the TUG test.\u003c/p\u003e\u003cp\u003eChronic pain is one of the most debilitating symptoms of FM, significantly affecting functional capacity, quality of life, and mental health in affected individuals \u003csup\u003e51\u003c/sup\u003e. In the present study, pain showed a significant association with laboratory-based MQI (r\u0026thinsp;=\u0026thinsp;0.528; p\u0026thinsp;=\u0026thinsp;0.000) and field-based MQI (r\u0026thinsp;=\u0026thinsp;0.452; p\u0026thinsp;=\u0026thinsp;0.001). Moreover, pain was the only variable that remained in the regression model, accounting for 27.8% of the variance in based-laboratory MQI (p\u0026thinsp;=\u0026thinsp;0.000) and 20.4% of the variance in based-field MQI (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). These results underscore the pivotal role of pain in explaining the variability in muscle quality among women with FM. These findings suggest that individuals with higher muscle quality experience lower pain perception, indicating that efficient muscle support may exert a protective effect against the central sensitization characteristic of the disease.\u003c/p\u003e\u003cp\u003eSeveral studies support our findings, indicating that muscle quality is relevant in mediating pain across chronic conditions. In osteoarthritis, higher muscle quality and strength have been associated with a reduced risk of pain progression and improved functional performance \u003csup\u003e52, 53\u003c/sup\u003e. Similar evidence has been reported in low back pain, where alterations in paraspinal muscles assessed by magnetic resonance imaging correlated with higher pain intensity \u003csup\u003e54\u003c/sup\u003e. In chronic musculoskeletal pain, reduced grip strength was also linked to neuropathic symptoms, particularly among women \u003csup\u003e55\u003c/sup\u003e. Moreover, a recent meta-analysis demonstrated that pain negatively affects strength stability, thereby impairing muscle quality and function and ultimately hindering rehabilitation \u003csup\u003e56\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThese findings reinforce that preserving muscle mass alone is insufficient; muscle quality, i.e., the ability to efficiently generate force, is essential for modulating pain and functional capacity. Population-based evidence further supports this hypothesis. In a study using the National Health and Nutrition Examination Survey (2011\u0026ndash;2014), a higher MQI was associated with a reduced risk of arthritis (adjusted OR\u0026thinsp;=\u0026thinsp;0.73; CI: 95%; 0.61\u0026ndash;0.88; p\u0026thinsp;=\u0026thinsp;0.001) \u003csup\u003e12\u003c/sup\u003e. So, individuals with greater contractile efficiency are less prone to experiencing painful symptoms in degenerative joint conditions, which aligns with our findings in women with FM.\u003c/p\u003e\u003cp\u003eAdditionally, studies indicate that even among individuals with preserved muscle mass, poor muscle quality is associated with greater functional disability and higher pain intensity in chronic musculoskeletal conditions \u003csup\u003e52, 53\u003c/sup\u003e. From a functional perspective, muscles with reduced efficiency may generate joint and tissue overload, thereby increasing peripheral nociceptive stimuli and reflecting alterations in motor unit recruitment and neuromuscular transmission \u003csup\u003e57\u003c/sup\u003e. These mechanisms highlight the importance of improving muscle quality rather than focusing solely on muscle mass.\u003c/p\u003e\u003cp\u003eIn the present study, higher MQI values were associated with better performance on the TUG test for both laboratory-based MQI (r = -0.371; p\u0026thinsp;=\u0026thinsp;0.038) and field-based MQI (r = -0.401; p\u0026thinsp;=\u0026thinsp;0.021). We also observed a positive correlation between MQI and self-reported functional capacity assessed by the SF-36 questionnaire (laboratory-based MQI: r\u0026thinsp;=\u0026thinsp;0.374; p\u0026thinsp;=\u0026thinsp;0.037; field-based MQI: r\u0026thinsp;=\u0026thinsp;0.440; p\u0026thinsp;=\u0026thinsp;0.009). These findings reinforce the relevance of muscle quality as a determinant of functional autonomy, particularly when assessed through field-based methods. Each 1-unit increase in field-based MQI has been associated with a 2.59-second reduction in TUG performance (β = \u0026minus;0.540; p\u0026thinsp;=\u0026thinsp;0.004), highlighting the strong discriminative capacity of this measure to detect impaired mobility in obese older women \u003csup\u003e58\u003c/sup\u003e. Across different populations, such evidence supports field-based MQI as a consistent and clinically applicable predictor of mobility. In contrast, the explanatory value of laboratory-based MQI may vary depending on sample characteristics or methodological approaches.\u003c/p\u003e\u003cp\u003eThese findings are particularly relevant given that functional capacity is essential for maintaining autonomy in daily activities \u003csup\u003e59\u003c/sup\u003e. The loss of this capacity leads to greater dependence, negatively affecting self-esteem, psychological well-being, and overall quality of life 14. Therefore, interventions aimed at improving muscle quality may not only alleviate pain but also restore movement confidence, thereby helping to break the cycle of inactivity, pain, and disability \u003csup\u003e60\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eFrom a mechanical and physiological perspective, maintaining muscle strength can help mitigate abnormal biomechanical loads on joints and soft tissues, thereby reducing nociceptive input \u003csup\u003e61\u003c/sup\u003e. Therefore, optimizing MQI may serve as a functional indicator and a strategic therapeutic target for managing chronic pain in FM.\u003c/p\u003e\u003cp\u003eThe different methods for calculating the Muscle Quality Index (MQI) remain a subject of debate in the scientific literature. While laboratory-based measures are obtained through specialized and less accessible equipment 28, field-based measures are easily applicable in clinical practice \u003csup\u003e62, 27, 63\u003c/sup\u003e. Recent studies have explored and compared these two approaches \u003csup\u003e24, 26, 58\u003c/sup\u003e. Investigating the association between these methods is particularly relevant, as field-based MQI offers an accessible and feasible methodology for clinical and community settings, serving as a quick and practical tool for health professionals to assess physical function.\u003c/p\u003e\u003cp\u003eIn this study, a strong positive correlation was observed between laboratory-based MQI and field-based MQI (r\u0026thinsp;=\u0026thinsp;0.93; p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) in women with FM. This finding corroborates previous research conducted with older adults 24 and adolescents with Down syndrome 26, demonstrating the feasibility of using both approaches to predict physical performance rather than focusing solely on global \"strength\" which often only reflects the quantity of muscle mass \u003csup\u003e62, 24, 26\u003c/sup\u003e. Our results further suggest that field-based MQI assessment in women with FM may effectively indicate functional performance, comparable to more complex laboratory-based measures.\u003c/p\u003e\u003cp\u003eIn addition to the variables significantly associated with MQI, other biopsychosocial and physiological dimensions evaluated in this study warrant contextualization, even though they did not demonstrate significant or robust associations in the regression models. In FM, sleep disturbances are highly prevalent and often linked to increased pain perception, persistent fatigue, and poorer physical performance \u003csup\u003e64\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eSimilarly, depression is a highly prevalent comorbidity among patients with FM. It can negatively impact pain perception, functional capacity, and engagement in therapeutic activities, highlighting the need for multidimensional management strategies that consider both the emotional state and physical intervention of patients \u003csup\u003e54\u003c/sup\u003e. The lack of associations with muscle quality observed in this study may reflect the indirect effect of these symptoms, mediated by variables such as pain, functional capacity, and vitality.\u003c/p\u003e\u003cp\u003eOxidative stress plays a crucial role in the pathogenesis of FM, being associated with mitochondrial dysfunction, redox imbalance, and central sensitization, mechanisms that exacerbate pain 12. Alterations in these markers have been linked to greater clinical severity, including increased pain, fatigue, impaired muscle performance, and reduced quality of life \u003csup\u003e65, 66\u003c/sup\u003e. Although oxidative stress was not a significant predictor of muscle quality in our model, it remains a relevant biomarker for muscle deterioration and pain chronification in women with FM. Supporting this perspective, reduced antioxidant levels and poorer quality of life were associated with greater muscle pain, whereas higher oxidative stress levels, lower muscle performance, and poorer quality of life explained the reduction of lean mass in women with FM, reinforcing the central role of these mechanisms in the clinical severity of the syndrome \u003csup\u003e9\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn summary, the strong correlation between laboratory-based and field-based MQI underscores the robustness of this measure, supporting the validity of both approaches for assessing muscle quality in women with fibromyalgia (FM). While laboratory-based MQI provides precise information by integrating body composition measures obtained through DEXA, field-based MQI offers a practical and cost-effective alternative that can be easily applied in clinical and community settings. This finding highlights the potential of field-based MQI as a valuable tool for functional monitoring, particularly in contexts where access to advanced imaging technologies is limited. Consequently, field-based MQI may facilitate the broader implementation of muscle quality assessment, guiding individualized rehabilitation strategies and enhancing the applicability of research findings in real-world clinical practice.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eStrengths and limitations\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThis study showcases several strengths. To our knowledge, it is the first to investigate the association between laboratory- and field-based MQI and biopsychosocial factors in women with FM. Another strength is the use of complementary methods to assess MQI, which combines both laboratory-based and clinically feasible field-based approaches, enhancing the findings' external validity and clinical applicability. Furthermore, the inclusion of multidimensional outcomes encompassing physical, psychological, and physiological aspects such as muscle strength, body composition, quality of life, depressive symptoms, sleep quality, and oxidative stress enabled a comprehensive analysis within a biopsychosocial framework. Finally, the study highlights the potential of the field-based MQI as an accessible and cost-effective tool for clinical practice and functional monitoring in women with FM, supporting its integration into healthcare and rehabilitation settings.\u003c/p\u003e\u003cp\u003eHowever, several limitations should be acknowledged. First, the cross-sectional design of the study precludes causal inferences between the investigated variables. Second, the study focused solely on women, which limits which limits the generalizability of the findings to men with fibromyalgia (FM). While the sample size was sufficient for the statistical analyses, it was relatively small, which may have restricted the detection of more subtle associations. Additionally, the absence of a control group hindered the ability to directly compare muscle quality levels with those of individuals without FM.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eIn women with FM, pain emerged as the primary factor significantly associated with both field- and laboratory-based MQI. Moreover, higher laboratory and field-based MQI values were correlated with improved quality of life and better functional capacity. The strong agreement between laboratory- and field-based MQI suggests that field-based assessment may be a practical and cost-effective alternative for clinical and community settings. These findings underscore the importance of muscle quality as a relevant therapeutic target in women with FM.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cstrong\u003e5xSTS\u003c/strong\u003e: Five Times Sit-to-Stand test\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBDI\u003c/strong\u003e: Beck Depression Inventory\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBMI\u003c/strong\u003e: Body Mass Index\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCAT\u003c/strong\u003e: Catalase\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDEXA\u003c/strong\u003e: Dual-energy X-ray absorptiometry\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFIQ\u003c/strong\u003e: Fibromyalgia Impact Questionnaire\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFM\u003c/strong\u003e: Fibromyalgia\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFRAP\u003c/strong\u003e: Ferric Reducing Antioxidant Power\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMQI\u003c/strong\u003e: Muscle Quality Index\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePSQI\u003c/strong\u003e: Pittsburgh Sleep Quality Index\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSF-36\u003c/strong\u003e: Short Form Health Survey 36\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSOD\u003c/strong\u003e: Superoxide Dismutase\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTBARS\u003c/strong\u003e: Thiobarbituric Acid Reactive Substances\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTUG\u003c/strong\u003e: Timed Up and Go test\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e The authors are grateful for the technical support and provision of equipment by the \u003cem\u003eCentro Integrado de P\u0026oacute;s-Gradua\u0026ccedil;\u0026atilde;o e Pesquisa em Sa\u0026uacute;de\u003c/em\u003e, Universidade Federal dos Vales do Jequitinhonha e Mucuri, Diamantina, MG, Brazil.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: VMTLA; JMS; SFF. Formal analysis: VMTLA; LACT; SFF; Investigation: VMTLA; JMF; LACT; SFF; Methodology: VMTLA; JMF; VGCR; SFF; Resources: SFF; Supervision: SFF; Visualization: JMF; JNVS; SFF; Writing \u0026ndash; original draft: VMTLA, VMF, JNVS, SFF; Writing \u0026ndash; review \u0026amp; editing: VMTLA; JNVS; VGCR; SEM; CMR; VAM; RT; ACRL; MCMO; DFMV; SFF;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the Universidade Federal dos Vales do Jequitinhonha e Mucuri for institutional support, CNPq 407629/2023-8, CAPES PROEXT-PG 88881.926996/2023-01, and FAPEMIG for support and scholarships.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u0026nbsp;\u003c/strong\u003eThe Research Ethics Committee on Human Beings of the Federal University of Jequitinhonha and Mucuri Valleys (UFVJM) approved the study, and all participants signed the Informed Consent Form. Written informed consent was obtained per the ethical principles established in the Declaration of Helsinki.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e The authors declare no conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eGarofalo C, \u003cem\u003eet al.\u003c/em\u003e Fibromyalgia and irritable bowel syndrome interaction: a possible role for gut microbiota and gut\u0026ndash;brain axis. \u003cem\u003eDiagnosis (Berl).\u003c/em\u003e 2023;11(6):e2023116.\u003c/li\u003e\n\u003cli\u003eWolfe F, Clauw DJ, Fitzcharles M-A, Goldenberg DL, H\u0026auml;user W, Katz RS, \u003cem\u003eet al.\u003c/em\u003e The American College of Rheumatology preliminary diagnostic criteria for fibromyalgia and measurement of symptom severity. \u003cem\u003eArthritis Care Res (Hoboken).\u003c/em\u003e 2010;62(5):600\u0026ndash;610.\u003c/li\u003e\n\u003cli\u003eWolfe F, Walitt B, Rasker JJ, Katz RS, H\u0026auml;user W. 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Pain intensity reduces strength steadiness in chronic musculoskeletal pain: a systematic review and meta-analysis. \u003cem\u003eArch Phys Med Rehabil.\u003c/em\u003e 2022;103(7):1341\u0026ndash;1355.\u003c/li\u003e\n\u003cli\u003eMurphy MC, Byrne JM, Brown JT, \u003cem\u003eet al.\u003c/em\u003e Maximising neuromuscular performance in people with musculoskeletal pain: a narrative review. \u003cem\u003eBMJ Open Sport Exerc Med.\u003c/em\u003e 2024;10(2):e001935.\u003c/li\u003e\n\u003cli\u003eNeto IVS, Costa RS, Vasconcelos KS, \u003cem\u003eet al.\u003c/em\u003e Field-based estimates of muscle quality index determine Timed-Up-and-Go test performance in obese older women. \u003cem\u003eClin Interv Aging.\u003c/em\u003e 2023;18:293\u0026ndash;303.\u003c/li\u003e\n\u003cli\u003eRusu C, Bancej C, Jayabalasingham B, \u003cem\u003eet al.\u003c/em\u003e Prevalence of chronic fatigue syndrome and fibromyalgia in Canada: a population-based study. \u003cem\u003eHealth Promot Chronic Dis Prev Can.\u003c/em\u003e 2015;35(1):3\u0026ndash;11.\u003c/li\u003e\n\u003cli\u003eLe\u0026oacute;n-Llamas JL, Cruz-Mu\u0026ntilde;oz ND, Rodr\u0026iacute;guez-M\u0026eacute;ndez AJ, \u003cem\u003eet al.\u003c/em\u003e Relationship between kinesiophobia and mobility, impact of the disease, and fear of falling in women with and without fibromyalgia: a cross-sectional study. \u003cem\u003eInt J Environ Res Public Health.\u003c/em\u003e 2022;19(14):8257. doi:10.3390/ijerph19148257.\u003c/li\u003e\n\u003cli\u003eBement MK, Sluka KA. Exercise-induced hypoalgesia: an evidence-based review. \u003cem\u003eHand Clin.\u003c/em\u003e 2015;31(2):301\u0026ndash;310.\u003c/li\u003e\n\u003cli\u003eStraight CR, Pipinos II, Lentz MR, \u003cem\u003eet al.\u003c/em\u003e Comparison of laboratory- and field-based estimates of muscle quality for predicting physical function in older women. \u003cem\u003eJ Aging Res Clin Pract.\u003c/em\u003e 2013;2(3):276\u0026ndash;279.\u003c/li\u003e\n\u003cli\u003eTakai Y, Ohta M, Akagi R, \u003cem\u003eet al.\u003c/em\u003e Sit-to-stand test to evaluate knee extensor muscle size and strength in the elderly: a novel approach. \u003cem\u003eScand J Med Sci Sports.\u003c/em\u003e 2009;19(5):728\u0026ndash;733.\u003c/li\u003e\n\u003cli\u003eKaratay S, Yildirim K, Sogut E, \u003cem\u003eet al.\u003c/em\u003e Serum magnesium levels and their association with sleep quality and disease severity in fibromyalgia syndrome. \u003cem\u003eMedicine (Baltimore).\u003c/em\u003e 2025;104(8):e39812.\u003c/li\u003e\n\u003cli\u003eChung CP, Titiz A, Ong KH, \u003cem\u003eet al.\u003c/em\u003e Estresse oxidativo na fibromialgia e sua rela\u0026ccedil;\u0026atilde;o com os sintomas. \u003cem\u003eClin Rheumatol.\u003c/em\u003e 2008;28(4):435\u0026ndash;438.\u003c/li\u003e\n\u003cli\u003eAssavarittirong C, Woraphat N, Sattayaprasert P, \u003cem\u003eet al.\u003c/em\u003e Oxidative stress in fibromyalgia: a systematic review. \u003cem\u003eOxid Med Cell Longev.\u003c/em\u003e 2022;2022:1\u0026ndash;12.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table","content":"\u003cp\u003eTable 1 is available in the Supplementary Files section.\u003c/p\u003e\n"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Fibromyalgia, Women, Muscle quality, Pain","lastPublishedDoi":"10.21203/rs.3.rs-8080873/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8080873/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eIntroduction:\u003c/strong\u003e Fibromyalgia (FM) is a chronic condition affecting predominantly women, characterized by widespread pain, fatigue, and impaired functionality. Poorer clinical outcomes are linked to changes in muscle strength and body composition. The Muscle Quality Index (MQI) has been proposed as a relevant measure to detect the risk of functional disability. However, the assessment of MQI in women with FM and its association with biopsychosocial factors remains unclear.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003eForty-seven women with FM (53.45 ± 7.32 years) were assessed for quality of life (SF-36), FM impact, depressive symptoms, sleep quality, oxidative stress markers, and functional capacity. MQI was calculated using laboratory-based (five times sit-to-stand test [5xSTS]/lower limb lean mass by DEXA) and field-based (5xSTS/body mass index) methods.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e The pain domain of the SF-36 showed significant associations with both laboratory-based MQI (r=0.534; p\u0026lt;0.001) and field-based MQI (r=0.461; p=0.001), explaining 27.8% and 20.4% of their variance, respectively. MQI also correlated with SF-36 physical functioning, role-physical, and functional capacity. Field- and laboratory-based MQI were strongly correlated (r=0.93; p\u0026lt;0.0001).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003ePain emerged as the primary factor negatively affecting MQI. The field MQI proved to be a practical, valid, and clinically applicable alternative for functional assessment in women with FM\u003c/p\u003e","manuscriptTitle":"Assessing Muscle Quality in Women with Fibromyalgia and Associations with Biopsychological Factors: A Cross-Sectional Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-01 09:05:23","doi":"10.21203/rs.3.rs-8080873/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a534bd6e-40cb-4a67-af91-8d016e069a18","owner":[],"postedDate":"December 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":58725190,"name":"Health sciences/Diseases"},{"id":58725191,"name":"Health sciences/Health care"},{"id":58725192,"name":"Health sciences/Medical research"},{"id":58725193,"name":"Health sciences/Rheumatology"},{"id":58725194,"name":"Health sciences/Signs and symptoms"}],"tags":[],"updatedAt":"2025-12-18T18:08:45+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-01 09:05:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8080873","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8080873","identity":"rs-8080873","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}