A more accurate method to estimate muscle mass: A new estimation equation
Abstract Background Measurement of muscle mass is important in the diagnosis of sarcopenia. Current measurement equipment are neither cost‐effective nor standardized and cannot be used in a variety of medical settings. Some simple measurement tools have been proposed that are subjective and unvalida...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2023-08-01
|
| Series: | Journal of Cachexia, Sarcopenia and Muscle |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/jcsm.13254 |
| _version_ | 1797754711875518464 |
|---|---|
| author | Shanshan Shi Weihua Chen Yizhou Jiang Kaihong Chen Ying Liao Kun Huang |
| author_facet | Shanshan Shi Weihua Chen Yizhou Jiang Kaihong Chen Ying Liao Kun Huang |
| author_sort | Shanshan Shi |
| collection | DOAJ |
| description | Abstract Background Measurement of muscle mass is important in the diagnosis of sarcopenia. Current measurement equipment are neither cost‐effective nor standardized and cannot be used in a variety of medical settings. Some simple measurement tools have been proposed that are subjective and unvalidated. We aimed to develop and validate a new estimation equation in a more objective and standardized way, based on current proven variables that accurately reflect muscle mass. Methods Cross‐sectional analysis with The National Health and Nutrition Examination Survey database for equation development and validation. Overall, 9875 participants were included for development (6913 participants) and validation (2962 participants), for whom the database included demographic data, physical measurements, and main biochemical indicators. Appendicular skeletal muscle mass (ASM) was estimated by dual‐energy x‐ray absorptiometry (DXA) and low muscle mass was defined by reference to five international diagnostic criteria. Linear regression was used to estimate the logarithm of the actual ASM from demographic data, physical measurements, and biochemical indicators. Results This study of 9875 participants comprised 4492 females (49.0%), with a weighted mean (SE) age of 41.83 (0.36) years and range of 12 to 85 years. The estimated ASM equations performed well in the validation data set. The variability in estimated ASM was low compared with the actual ASM (R2: Equation 1 = 0.91, Equation 4 = 0.89), with low bias (median difference: Equation 1 = −0.64, Equation 4 = 0.07; root mean square error: Equation 1 = 1.70 [1.69–1.70], Equation 4 = 1.85 [1.84–1.86]), high precision (interquartile range of the differences: Equation 1 = 1.87, Equation 4 = 2.17), and high efficacy in diagnosing low muscle mass (area under the curve: Equation 1 = 0.91 to 0.95, Equation 4 = 0.90 to 0.94). Conclusions The estimated ASM equations are accurate and simple and can be routinely applied clinically to estimate ASM and thus assess sarcopenia. |
| first_indexed | 2024-03-12T17:36:31Z |
| format | Article |
| id | doaj.art-431e4c18a9294452af658fceb456df80 |
| institution | Directory Open Access Journal |
| issn | 2190-5991 2190-6009 |
| language | English |
| last_indexed | 2024-03-12T17:36:31Z |
| publishDate | 2023-08-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Cachexia, Sarcopenia and Muscle |
| spelling | doaj.art-431e4c18a9294452af658fceb456df802023-08-04T10:07:00ZengWileyJournal of Cachexia, Sarcopenia and Muscle2190-59912190-60092023-08-011441753176110.1002/jcsm.13254A more accurate method to estimate muscle mass: A new estimation equationShanshan Shi0Weihua Chen1Yizhou Jiang2Kaihong Chen3Ying Liao4Kun Huang5Longyan First Affiliated Hospital of Fujian Medical University Longyan ChinaLongyan First Affiliated Hospital of Fujian Medical University Longyan ChinaState Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases Chinese Academy of Medical Sciences and Peking Union Medical College Beijing ChinaLongyan First Affiliated Hospital of Fujian Medical University Longyan ChinaLongyan First Affiliated Hospital of Fujian Medical University Longyan ChinaCenter of Statistical Science, Department of Industrial Engineering Tsinghua University Beijing ChinaAbstract Background Measurement of muscle mass is important in the diagnosis of sarcopenia. Current measurement equipment are neither cost‐effective nor standardized and cannot be used in a variety of medical settings. Some simple measurement tools have been proposed that are subjective and unvalidated. We aimed to develop and validate a new estimation equation in a more objective and standardized way, based on current proven variables that accurately reflect muscle mass. Methods Cross‐sectional analysis with The National Health and Nutrition Examination Survey database for equation development and validation. Overall, 9875 participants were included for development (6913 participants) and validation (2962 participants), for whom the database included demographic data, physical measurements, and main biochemical indicators. Appendicular skeletal muscle mass (ASM) was estimated by dual‐energy x‐ray absorptiometry (DXA) and low muscle mass was defined by reference to five international diagnostic criteria. Linear regression was used to estimate the logarithm of the actual ASM from demographic data, physical measurements, and biochemical indicators. Results This study of 9875 participants comprised 4492 females (49.0%), with a weighted mean (SE) age of 41.83 (0.36) years and range of 12 to 85 years. The estimated ASM equations performed well in the validation data set. The variability in estimated ASM was low compared with the actual ASM (R2: Equation 1 = 0.91, Equation 4 = 0.89), with low bias (median difference: Equation 1 = −0.64, Equation 4 = 0.07; root mean square error: Equation 1 = 1.70 [1.69–1.70], Equation 4 = 1.85 [1.84–1.86]), high precision (interquartile range of the differences: Equation 1 = 1.87, Equation 4 = 2.17), and high efficacy in diagnosing low muscle mass (area under the curve: Equation 1 = 0.91 to 0.95, Equation 4 = 0.90 to 0.94). Conclusions The estimated ASM equations are accurate and simple and can be routinely applied clinically to estimate ASM and thus assess sarcopenia.https://doi.org/10.1002/jcsm.13254Appendicular skeletal muscle massDual‐energy X‐ray absorptiometryEstimated equationsMuscle massSarcopenia |
| spellingShingle | Shanshan Shi Weihua Chen Yizhou Jiang Kaihong Chen Ying Liao Kun Huang A more accurate method to estimate muscle mass: A new estimation equation Journal of Cachexia, Sarcopenia and Muscle Appendicular skeletal muscle mass Dual‐energy X‐ray absorptiometry Estimated equations Muscle mass Sarcopenia |
| title | A more accurate method to estimate muscle mass: A new estimation equation |
| title_full | A more accurate method to estimate muscle mass: A new estimation equation |
| title_fullStr | A more accurate method to estimate muscle mass: A new estimation equation |
| title_full_unstemmed | A more accurate method to estimate muscle mass: A new estimation equation |
| title_short | A more accurate method to estimate muscle mass: A new estimation equation |
| title_sort | more accurate method to estimate muscle mass a new estimation equation |
| topic | Appendicular skeletal muscle mass Dual‐energy X‐ray absorptiometry Estimated equations Muscle mass Sarcopenia |
| url | https://doi.org/10.1002/jcsm.13254 |
| work_keys_str_mv | AT shanshanshi amoreaccuratemethodtoestimatemusclemassanewestimationequation AT weihuachen amoreaccuratemethodtoestimatemusclemassanewestimationequation AT yizhoujiang amoreaccuratemethodtoestimatemusclemassanewestimationequation AT kaihongchen amoreaccuratemethodtoestimatemusclemassanewestimationequation AT yingliao amoreaccuratemethodtoestimatemusclemassanewestimationequation AT kunhuang amoreaccuratemethodtoestimatemusclemassanewestimationequation AT shanshanshi moreaccuratemethodtoestimatemusclemassanewestimationequation AT weihuachen moreaccuratemethodtoestimatemusclemassanewestimationequation AT yizhoujiang moreaccuratemethodtoestimatemusclemassanewestimationequation AT kaihongchen moreaccuratemethodtoestimatemusclemassanewestimationequation AT yingliao moreaccuratemethodtoestimatemusclemassanewestimationequation AT kunhuang moreaccuratemethodtoestimatemusclemassanewestimationequation |