Conclusion

Conclusion

With our analysis we hoped to tackle three main issues when discussing biological aging: how can I estimate my biological age without having to conduct a test; if I do a test, how do I know if my results are concerning or not; and, if I want to work towards reversing my biological age, what are the metrics I can use to track my progress? 

Predicting one’s own biological aging process with an explainable model using behavioural and anthropometric factors can be a wake-up call for individuals to develop a healthier lifestyle. While we are unable to draw conclusions for the general audience to assist in their own biological aging journeys, we hope that this project is able to lay as an example to inspire future studies with long-term, diverse data points to eventually develop a comprehensive biological aging predictor for everyone to use. 

The anomaly detection methodology has great potential to be implemented as an assistance tool for healthcare providers, utilising machine learning models trained on broader datasets to identify the anomalies in biological aging process when factoring in behavioural and anthropometric measurements as well. Since senescence biomarkers are closely related to the body’s response to inflammation, this technology could be developed further into detecting early signs of chronic illnesses. 

This study also highlights the role of physical activity in our personal health, whether by senescence biomarkers or anthropometric measures. It provides policy makers with a clear target (increasing moderate-to-vigorous physical activity) to decrease obesity and improve longevity in communities across the world. Overall, this encouragement–if widespread–can relieve significant pressure on a society’s healthcare system and allow everyone to live longer and happier lives.