Abstract
Introduction. From birth, aging or biological age is affected by various environmental factors and lifestyles that determine the overall health of the subject, so it is necessary to have instruments to estimate biological age.
Objectives. To design and apply a multifactorial virtual instrument that estimates biological age based on lifestyles, perception of physical condition and general well-being in collaborators of a medical sports club. Materials and methods. In 2022, an analytical cross-sectional study was conducted in 1,370 subjects. The instrument included eight questions related to physical activity, general well-being, smoking, diet, weight, height, date of birth and biological sex. Biological age was estimated with the MiEdadBT tool, weighting the impact of each variable on life expectancy. A descriptive and normality data analysis was performed. Correlations between variables were established with the MiEdadBT application to generate a nonlinear polynomial regression model with the help of the R Studio program. Statistical significance was found (p<0.05).
Results. The mean chronological age was 31.6 ± 8.3 years, and 35 % of the participants were female. With the MyEdadBT application, the mean biological age was 30 ± 8.4 years. The mean difference between these values was -1.4 ± 1.8 years. Linear correlations were found with muscle mass index (R=0.16; p<0.01) and physical activity (R=-0.32; p<0.001). The polynomial model was four-degree with the variables: chronological age, muscle mass index, physical activity smoking, well-being and diet, which explains 43.1 % (R2 =0.4306; p<0.001) of the variability observed in MyAgeBT.
Conclusions. The MyEdadBT application mostly explains the influence of muscle mass index, well-being, physical activity, smoking and diet on the modification of the estimated chronological age of the subjects.
Objectives. To design and apply a multifactorial virtual instrument that estimates biological age based on lifestyles, perception of physical condition and general well-being in collaborators of a medical sports club. Materials and methods. In 2022, an analytical cross-sectional study was conducted in 1,370 subjects. The instrument included eight questions related to physical activity, general well-being, smoking, diet, weight, height, date of birth and biological sex. Biological age was estimated with the MiEdadBT tool, weighting the impact of each variable on life expectancy. A descriptive and normality data analysis was performed. Correlations between variables were established with the MiEdadBT application to generate a nonlinear polynomial regression model with the help of the R Studio program. Statistical significance was found (p<0.05).
Results. The mean chronological age was 31.6 ± 8.3 years, and 35 % of the participants were female. With the MyEdadBT application, the mean biological age was 30 ± 8.4 years. The mean difference between these values was -1.4 ± 1.8 years. Linear correlations were found with muscle mass index (R=0.16; p<0.01) and physical activity (R=-0.32; p<0.001). The polynomial model was four-degree with the variables: chronological age, muscle mass index, physical activity smoking, well-being and diet, which explains 43.1 % (R2 =0.4306; p<0.001) of the variability observed in MyAgeBT.
Conclusions. The MyEdadBT application mostly explains the influence of muscle mass index, well-being, physical activity, smoking and diet on the modification of the estimated chronological age of the subjects.
| Translated title of the contribution | Biological age estimation tool: My Age BodyTech |
|---|---|
| Original language | Spanish (Colombia) |
| Article number | 7G3 |
| Pages (from-to) | 209 |
| Number of pages | 1 |
| Journal | Biomédica : revista del Instituto Nacional de Salud |
| Volume | 43 |
| Issue number | 2 |
| State | Published - Nov 20 2023 |
All Science Journal Classification (ASJC) codes
- Physical Therapy, Sports Therapy and Rehabilitation