Literature DB >> 27093315

Appendicular Skeletal Muscle Mass: Development and Validation of Anthropometric Prediction Equations.

R Visvanathan1, S Yu, J Field, I Chapman, R Adams, G Wittert, T Visvanathan.   

Abstract

OBJECTIVES: Sarcopenia is the loss of muscle mass and function seen with increasing age. Central to making the diagnosis of sarcopenia is the assessment of appendicular skeletal muscle mass (ASM). The objective of this study was to develop and validate novel anthropometric prediction equations (PEs) for ASM that would be useful in primary or aged care.
DESIGN: PEs were developed using best subset regression analysis. Three best performing PEs (PE1, PE2, PE3) were selected and validated using the Bland-Altman and Sheiner and Beal methods.
SETTING: Community dwelling adults in South Australia. PARTICIPANTS: 188 healthy subjects were involved in the development study. 2275 older(age ≥ 50years) subjects were involved in the validation study. MEASUREMENTS: ASM was assessed using dual x-ray abosrptiometry (DEXA). Weight and height was measured and body mass index (BMI) estimated.
RESULTS: A strong correlation between PE derived ASM and the DEXA derived ASM was seen for the three selected PEs. PE3: ASM= 10.047427 + 0.353307(weight) - 0.621112(BMI) - 0.022741(age) + 5.096201(if male) performed the best. PE3 over-estimated (P<0.001) ASM by 0.36 kg (95% CI 0.28-0.44 Kg) and the adjusted R2 was 0.869. The 95% limit of agreement was between -3.5 and 4.35 kg and the standard error of the estimate was 1.95. The root mean square error was 1.91(95% CI 1.80-2.01). PE3 also performed the best across the various age (50-65, 65-<80, 80+ years) and weight (BMI <18.5, 18.5-24.9, 25-29.9, ≥30 kg/m2) groups.
CONCLUSIONS: A new anthropometric PE for ASM has been developed for use in primary or aged care but is specific to Caucasian population groups.

Entities:  

Year:  2012        PMID: 27093315     DOI: 10.14283/jfa.2012.23

Source DB:  PubMed          Journal:  J Frailty Aging        ISSN: 2260-1341


  10 in total

1.  The Unhealthy Lifestyle Factors Associated with an Increased Risk of Poor Nutrition among the Elderly Population in China.

Authors:  W-Q Lin; H H X Wang; L-X Yuan; B Li; M-J Jing; J-L Luo; J Tang; B-K Ye; P-X Wang
Journal:  J Nutr Health Aging       Date:  2017       Impact factor: 4.075

Review 2.  Clinical Screening Tools for Sarcopenia and Its Management.

Authors:  Solomon C Y Yu; Kareeann S F Khow; Agathe D Jadczak; Renuka Visvanathan
Journal:  Curr Gerontol Geriatr Res       Date:  2016-02-04

Review 3.  Sarcopenia in daily practice: assessment and management.

Authors:  Charlotte Beaudart; Eugène McCloskey; Olivier Bruyère; Matteo Cesari; Yves Rolland; René Rizzoli; Islène Araujo de Carvalho; Jotheeswaran Amuthavalli Thiyagarajan; Ivan Bautmans; Marie-Claude Bertière; Maria Luisa Brandi; Nasser M Al-Daghri; Nansa Burlet; Etienne Cavalier; Francesca Cerreta; Antonio Cherubini; Roger Fielding; Evelien Gielen; Francesco Landi; Jean Petermans; Jean-Yves Reginster; Marjolein Visser; John Kanis; Cyrus Cooper
Journal:  BMC Geriatr       Date:  2016-10-05       Impact factor: 3.921

4.  Z-score of the log-transformed A Body Shape Index predicts low muscle mass in population with abdominal obesity: The U.S. and Korea National Health and Nutrition Examination Survey.

Authors:  Shinje Moon; Yoon Jung Kim; Jae Myung Yu; Jun Goo Kang; Hye Soo Chung
Journal:  PLoS One       Date:  2020-11-24       Impact factor: 3.240

5.  Cut-off points to screening for sarcopenia in community-dwelling older people residents in Brazil.

Authors:  Sabrina Gabrielle Gomes Fernandes; Luiz Eduardo Lima de Andrade; Rafaella Silva Dos Santos Aguiar Gonçalves; Saionara Maria Aires da Câmara; Ricardo Oliveira Guerra; Alvaro Campos Cavalcanti Maciel
Journal:  PeerJ       Date:  2021-08-25       Impact factor: 2.984

6.  The Flexibility of Physio-Cognitive Decline Syndrome: A Longitudinal Cohort Study.

Authors:  Yi-Cheng Lin; Chih-Ping Chung; Pei-Lin Lee; Kun-Hsien Chou; Li-Hung Chang; Szu-Ying Lin; Yi-Jung Lee; Ching-Po Lin; Pei-Ning Wang
Journal:  Front Public Health       Date:  2022-06-06

7.  Development of prediction equations for estimating appendicular skeletal muscle mass in Japanese men and women.

Authors:  Taishi Furushima; Motohiko Miyachi; Motoyuki Iemitsu; Haruka Murakami; Hiroshi Kawano; Yuko Gando; Ryoko Kawakami; Kiyoshi Sanada
Journal:  J Physiol Anthropol       Date:  2017-08-29       Impact factor: 2.867

8.  Construct validation of a Frailty Index, an HIV Index and a Protective Index from a clinical HIV database.

Authors:  Iacopo Franconi; Olga Theou; Lindsay Wallace; Andrea Malagoli; Cristina Mussini; Kenneth Rockwood; Giovanni Guaraldi
Journal:  PLoS One       Date:  2018-10-17       Impact factor: 3.240

9.  Development & cross-validation of anthropometric predictive models to estimate the appendicular skeletal muscle mass in middle-aged women in Sri Lanka.

Authors:  Nirmala Rathnayake; Gayani Alwis; Janaka Lenora; Sarath Lekamwasam
Journal:  Indian J Med Res       Date:  2019-09       Impact factor: 2.375

Review 10.  A Call to Action: Now Is the Time to Screen Elderly and Treat Osteosarcopenia, a Position Paper of the Italian College of Academic Nutritionists MED/49 (ICAN-49).

Authors:  Tiziana Montalcini; Arturo Pujia; Lorenzo M Donini; Lucia Frittitta; Fabio Galvano; Andrea Natali; Loris Pironi; Marisa Porrini; Patrizia Riso; Angela Albarosa Rivellese; Diego Russo; Giovanni Scapagnini; Mauro Serafini; Anna Tagliabue; Antonino De Lorenzo
Journal:  Nutrients       Date:  2020-08-31       Impact factor: 5.717

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.