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This prospective observational study aims to determine the prevalence of malnutrition in patients with relapsing-remitting multiple sclerosis and to evaluate its association with disability. Nutritional status will be assessed using the Mini Nutritional Assessment-Short Form, and body composition will be evaluated with bioelectrical impedance analysis and anthropometric measurements. The study will also assess urinary incontinence, depression, and anger-related features, and compare the findings with those of healthy controls.
Multiple sclerosis is a chronic inflammatory and demyelinating disease of the central nervous system that may lead to disability, reduced mobility, bladder dysfunction, depression, and impaired quality of life. In the early stages of the disease, overweight and obesity may be common, whereas with disease progression, malnutrition and cachexia may become more prominent. Malnutrition may contribute to muscle loss, reduced mobility, worsening functional status, and increased clinical burden.
This single-center, hospital-based, prospective cross-sectional observational study will be conducted in the multiple sclerosis and neurology outpatient clinics of Antalya Training and Research Hospital. Adult patients diagnosed with relapsing-remitting multiple sclerosis and healthy controls will be included. Nutritional status will be assessed using the Mini Nutritional Assessment-Short Form. Body composition and anthropometric parameters, including waist-to-height ratio, waist-to-hip ratio, body fat percentage, fat mass, fat-free mass, total body water, and predicted muscle mass, will be evaluated using bioelectrical impedance analysis and standard anthropometric measurements. Disability in the patient group will be assessed with the Expanded Disability Status Scale. Depression, anger-related characteristics, and urinary incontinence profiles will also be evaluated using structured questionnaires and validated scales.
The study is designed to investigate the prevalence of malnutrition in relapsing-remitting multiple sclerosis, compare nutritional and related clinical parameters with healthy controls, and examine the relationship between malnutrition, body composition, and disability.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Patients | Patients with Relapsing-Remitting Multiple Sclerosis | ||
| Controls | Healthy Controls |
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| Measure | Description | Time Frame |
|---|---|---|
| Prevalence of malnutrition assessed by Mini Nutritional Assessment-Short Form | Malnutrition status and risk of malnutrition will be assessed using the Mini Nutritional Assessment-Short Form (MNA-SF) in patients with relapsing-remitting multiple sclerosis and healthy controls. MNA-SF is a screening tool with a total score ranging from 0 to 14. Lower scores indicate worse nutritional status. Scores from 12 to 14 indicate normal nutritional status, scores from 8 to 11 indicate risk of malnutrition, and scores from 0 to 7 indicate malnutrition. The relationships between MNA-SF and anthropometric, body composition, depressive and anger-related variables will also be evaluated. | At baseline |
| Measure | Description | Time Frame |
|---|---|---|
| Expanded Disability Status Scale score | Disability severity will be assessed in patients with Multiple Sclerosis (MS) using the Expanded Disability Status Scale (EDSS), which ranges from 0 to 10 in 0.5-point increments. Higher scores indicate worse disability. A score of 0 indicates normal neurological status, and a score of 10 indicates death due to MS. The relationships between disability severity and anthropometric, body composition, depressive, anger-related, and urinary incontinence-related variables will also be evaluated. |
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Inclusion Criteria:
Exclusion Criteria:
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This study population will consist of adults aged 18 years or older. The patient group will include individuals with relapsing-remitting multiple sclerosis who are followed in the neurology outpatient clinic of Antalya Training and Research Hospital and meet the predefined inclusion and exclusion criteria. A healthy control group of adult volunteers without multiple sclerosis will be recruited for comparison.
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| Name | Affiliation | Role |
|---|---|---|
| Serkan Özben, PhD | Antalya Training and Research Hospital | Study Chair |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Antalya Training and Research Hospital | Antalya | Antalya | 07100 | Turkey (Türkiye) |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 26440775 | Background | Pilutti LA, Motl RW. Body Mass Index Underestimates Adiposity in Persons With Multiple Sclerosis. Arch Phys Med Rehabil. 2016 Mar;97(3):405-12. doi: 10.1016/j.apmr.2015.09.014. Epub 2015 Oct 9. | |
| 31817216 | Background | Matusik E, Augustak A, Durmala J. Functional Mobility and Basic Motor Skills in Patients with Multiple Sclerosis and Its Relation to the Anthropometrical Status and Body Composition Parameters. Medicina (Kaunas). 2019 Dec 4;55(12):773. doi: 10.3390/medicina55120773. |
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| At baseline |
| Height as an anthropometric measurement | Height will be measured in meters in both patients with relapsing-remitting multiple sclerosis and healthy controls. | At baseline |
| Body weight as an anthropometric measurement | Body weight will be measured in kilograms in both patients with relapsing-remitting multiple sclerosis and healthy controls. | At baseline |
| Body mass index as an anthropometric measurement | Body mass index (BMI) will be calculated in kilograms per square meter (kg/m²) using measured body weight and height in both patients with relapsing-remitting multiple sclerosis and healthy controls. | At baseline |
| Waist circumference as an anthropometric measurement | Waist circumference will be measured in centimeters in both patients with relapsing-remitting multiple sclerosis and healthy controls. | At baseline |
| Hip circumference as an anthropometric measurement | Hip circumference will be measured in centimeters in both patients with relapsing-remitting multiple sclerosis and healthy controls. | At baseline |
| Waist-to-height ratio as an anthropometric measurement | Waist-to-height ratio (WHtR) will be calculated using waist circumference and height measurements in both patients with relapsing-remitting multiple sclerosis and healthy controls. Higher values indicate greater central adiposity. | At baseline |
| Waist-to-hip ratio as an anthropometric measurement | Waist-to-hip ratio (WHR) will be calculated using waist circumference and hip circumference measurements in both patients with relapsing-remitting multiple sclerosis and healthy controls. | At baseline |
| Fat mass (kg) | Fat mass (FM) will be measured in kilograms using the TANITA® MC-180MA Bioelectric Impedance Analyser device in both patients with RRMS and healthy controls. Bioelectrical impedance analysis will be performed 2 hours after a meal, following 5 minutes of rest, with participants standing still on the device with bare hands and feet. | At baseline |
| Fat mass (%) | Fat mass percentage will be derived from fat mass relative to body weight and expressed as a percentage in both patients with RRMS and healthy controls. Measurements will be obtained using the TANITA® MC-180MA Bioelectric Impedance Analyser. Bioelectrical impedance analysis will be performed 2 hours after a meal, following 5 minutes of rest, with participants standing still on the device with bare hands and feet. | At baseline |
| Fat-free mass (kg) | Fat-free mass (FFM) will be measured in kilograms using the TANITA® MC-180MA Bioelectric Impedance Analyser in both patients with RRMS and healthy controls. Bioelectrical impedance analysis will be performed 2 hours after a meal, following 5 minutes of rest, with participants standing still on the device with bare hands and feet. | At baseline |
| Total body water (kg) | Total body water (TBW) will be measured in kilograms using the TANITA® MC-180MA Bioelectric Impedance Analyser in both patients with RRMS and healthy controls. Bioelectrical impedance analysis will be performed 2 hours after a meal, following 5 minutes of rest, with participants standing still on the device with bare hands and feet. | At baseline |
| Predicted muscle mass (kg) | Predicted muscle mass (PMM) will be measured in kilograms using the TANITA® MC-180MA Bioelectric Impedance Analyser in both patients with RRMS and healthy controls. Bioelectrical impedance analysis will be performed 2 hours after a meal, following 5 minutes of rest, with participants standing still on the device with bare hands and feet. | At baseline |
| Beck Depression Inventory score | Depressive symptoms will be assessed using the Beck Depression Inventory (BDI), which ranges from 0 to 63. Higher scores indicate more severe depressive symptoms. Commonly used score ranges are 0-9 for minimal depression, 10-16 for mild depression, 17-29 for moderate depression, and 30-63 for severe depression. | At baseline |
| Trait anger score | Anger disposition will be assessed using the Trait Anger subscale of the State-Trait Anger Scale (STAS). Scores range from 10 to 40, with higher scores indicating greater trait anger. | At baseline |
| Anger-in score | Suppressed anger will be assessed using the Anger In subscale of the State-Trait Anger Scale (STAS). Scores range from 8 to 32, with higher scores indicating a greater tendency to suppress anger. | At baseline |
| Anger-out score | Outward expression of anger will be assessed using the Anger Out subscale of the State-Trait Anger Scale (STAS). Scores range from 8 to 32, with higher scores indicating a greater tendency to express anger outwardly. | At baseline |
| Anger control score | Anger control will be assessed using the Anger Control subscale of the State-Trait Anger Scale (STAS). Scores range from 8 to 32, with higher scores indicating better anger control. | At baseline |
| Urinary incontinence symptom-based subtype classification | Urinary incontinence symptoms will be assessed using semi-structured symptom-based urinary incontinence screening questionnaires designed to identify stress, urge, and overflow incontinence patterns. The questionnaires include symptom-oriented items with response options such as yes, no, and "more than half of the time," and additional questions on urinary frequency, nocturia, leakage frequency, and leakage amount where applicable. Participants will be classified according to the predominant symptom pattern identified from the questionnaire responses as stress, urge, or overflow urinary incontinence. | At baseline |
| Correlation between EDSS score and MNA-SF | The correlation between disability severity, as measured by EDSS, and nutritional status as measured by MNA-SF will be evaluated in patients with RRMS. | At baseline |
| 15732263 | Background | Schwarz S, Leweling H. Multiple sclerosis and nutrition. Mult Scler. 2005 Feb;11(1):24-32. doi: 10.1191/1352458505ms1119oa. |
| 29274834 | Background | Burgos R, Breton I, Cereda E, Desport JC, Dziewas R, Genton L, Gomes F, Jesus P, Leischker A, Muscaritoli M, Poulia KA, Preiser JC, Van der Marck M, Wirth R, Singer P, Bischoff SC. ESPEN guideline clinical nutrition in neurology. Clin Nutr. 2018 Feb;37(1):354-396. doi: 10.1016/j.clnu.2017.09.003. Epub 2017 Sep 22. |
| 19169174 | Background | Khurana SR, Bamer AM, Turner AP, Wadhwani RV, Bowen JD, Leipertz SL, Haselkorn JK. The prevalence of overweight and obesity in veterans with multiple sclerosis. Am J Phys Med Rehabil. 2009 Feb;88(2):83-91. doi: 10.1097/PHM.0b013e318194f8b5. |
| 17388952 | Background | Lassmann H, Bruck W, Lucchinetti CF. The immunopathology of multiple sclerosis: an overview. Brain Pathol. 2007 Apr;17(2):210-8. doi: 10.1111/j.1750-3639.2007.00064.x. |
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| Release Date | Unrelease Date | Unrelease Date Unknown | Reset Date | MCP Release Number |
|---|---|---|---|---|
| Jun 28, 2026 |
| ID | Term |
|---|---|
| D020529 | Multiple Sclerosis, Relapsing-Remitting |
| D044342 | Malnutrition |
| D009103 | Multiple Sclerosis |
| D014549 | Urinary Incontinence |
| D003863 | Depression |
| ID | Term |
|---|---|
| D020278 | Demyelinating Autoimmune Diseases, CNS |
| D020274 | Autoimmune Diseases of the Nervous System |
| D009422 | Nervous System Diseases |
| D003711 | Demyelinating Diseases |
| D001327 | Autoimmune Diseases |
| D007154 | Immune System Diseases |
| D009748 | Nutrition Disorders |
| D009750 | Nutritional and Metabolic Diseases |
| D014555 | Urination Disorders |
| D014570 | Urologic Diseases |
| D052776 | Female Urogenital Diseases |
| D005261 | Female Urogenital Diseases and Pregnancy Complications |
| D000091642 | Urogenital Diseases |
| D052801 | Male Urogenital Diseases |
| D059411 | Lower Urinary Tract Symptoms |
| D020924 | Urological Manifestations |
| D012816 | Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |
| D001526 | Behavioral Symptoms |
| D001519 | Behavior |
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