Navia-Casanova C1,2, Monrroy-Uarac M3,4, Cancino-Caamaño B3, Medina-Fritz MJ5, Casanova-Laudien MP5
1Universidad Austral de Chile, Programa de Doctorado en Ciencias Médicas, Escuela de Graduados, Facultad de Medicina, Valdivia, Chile, 2Centro de Estudios Científicos, CECS, Laboratorio de Biología, Valdivia, Chile, 3Universidad Austral de Chile, Instituto de Aparato Locomotor y Rehabiltación, Valdivia, Chile, 4Universidad Austral de Chile, Laboratorio de Fisiología del Ejercicio, Valdivia, Chile, 5Universidad de Concepcion, Departamento de Estadística, Valdivia, Chile
Background: Ageing is associated to a decline and progressive detriment of the physical function. In older women (OW) many factors can affect the physical function, leading to disability and loss of independence. Even if healthcare professionals can prevent and treat many of the age-associated disease, the motor dysfunction (MD) is almost always an unavoidable condition.
Purpose: The aim of this study is to create a model predictive risk of Motor Dysfunction (MD) based of anthropometric and functional characteristics of Old Women (OW).
Methods: A cross-sectional descriptive study aimed at predicting MD in terms of statistically significant variables was conducted. 96 OW aged 60 and older belonging to two “Senior Centres”. Each participant underwent a survey, an anthropometric assessment, a muscle function evaluation and performed a 6MWT. Biodemographic data were obtained and OW were classified into active or sedentary. Anthropometric measures were performed. Muscle function was evaluated using the Grip Strength (GS) and the Maximum Voluntary Isometric Contraction (MVIC) of the right quadriceps. OW were considered Dynapenic if MVIC was less than two standard deviations from a reference group average. OW who walk less than 400 meters during the 6MTW was considered with MD. To select the most adequate predictive variables for MD from a set of 93 variables, four methods of variable selection were used and to determine which method was better, the sensitivity, specificity and the percentage of correct selection were considered. Finally, to assess the predictive power of this model, a guided selection of variables was done, to identify those who were easier to obtain during an anamnesis and a physician appointment.
Results: Average age of OW was 67.5 ± 3.91 years, WC average was 95.45 ± 11.60 cm and 91% was Obese (PCI > 80cm). The variable of interest for MD was the distance walked in 6 minutes. LASSO was the method for selecting the best predictor variables and the percentage of correct selection was 84%. Variables included were: WC, GS, T2DM and Dynapenic-Obesity (DO). The determining variable of MD was T2DM; OW with T2DM has more than 8000 times more chance of having MD. Also, OW with DO has 2.3 times more chance of DM.
Conclusion(s): The proposed model simplifies the MD evaluation and prophylactic clinical decisions. Based on this model, a MD Risk Table was created, which help health professionals who work with older adults.
Implications: The MD risk tables developed in this study can be used to predict MD in OW and to determine its severity. Therefore, it can be useful in the implementation of prevention measures for MD in Dynapenic-Obese women who suffer from T2DM.
Keywords: Motor Dysfunction, Older Women, Dynapenic-Obesity
Funding acknowledgements: The work was unfunded.
Purpose: The aim of this study is to create a model predictive risk of Motor Dysfunction (MD) based of anthropometric and functional characteristics of Old Women (OW).
Methods: A cross-sectional descriptive study aimed at predicting MD in terms of statistically significant variables was conducted. 96 OW aged 60 and older belonging to two “Senior Centres”. Each participant underwent a survey, an anthropometric assessment, a muscle function evaluation and performed a 6MWT. Biodemographic data were obtained and OW were classified into active or sedentary. Anthropometric measures were performed. Muscle function was evaluated using the Grip Strength (GS) and the Maximum Voluntary Isometric Contraction (MVIC) of the right quadriceps. OW were considered Dynapenic if MVIC was less than two standard deviations from a reference group average. OW who walk less than 400 meters during the 6MTW was considered with MD. To select the most adequate predictive variables for MD from a set of 93 variables, four methods of variable selection were used and to determine which method was better, the sensitivity, specificity and the percentage of correct selection were considered. Finally, to assess the predictive power of this model, a guided selection of variables was done, to identify those who were easier to obtain during an anamnesis and a physician appointment.
Results: Average age of OW was 67.5 ± 3.91 years, WC average was 95.45 ± 11.60 cm and 91% was Obese (PCI > 80cm). The variable of interest for MD was the distance walked in 6 minutes. LASSO was the method for selecting the best predictor variables and the percentage of correct selection was 84%. Variables included were: WC, GS, T2DM and Dynapenic-Obesity (DO). The determining variable of MD was T2DM; OW with T2DM has more than 8000 times more chance of having MD. Also, OW with DO has 2.3 times more chance of DM.
Conclusion(s): The proposed model simplifies the MD evaluation and prophylactic clinical decisions. Based on this model, a MD Risk Table was created, which help health professionals who work with older adults.
Implications: The MD risk tables developed in this study can be used to predict MD in OW and to determine its severity. Therefore, it can be useful in the implementation of prevention measures for MD in Dynapenic-Obese women who suffer from T2DM.
Keywords: Motor Dysfunction, Older Women, Dynapenic-Obesity
Funding acknowledgements: The work was unfunded.
Topic: Older people; Primary health care; Disability & rehabilitation
Ethics approval required: Yes
Institution: Valdivia Health Service
Ethics committee: Scientific Ethics Committee
Ethics number: Approved
All authors, affiliations and abstracts have been published as submitted.
