The shape of things to come: using models with physiological structure to predict mortality trajectories

Area of Science:

• Physiology
• Demography
• Mathematical Biology

Background:

• Mortality rate is traditionally viewed as a demographic outcome.
• Understanding mortality requires integrating biological and behavioral processes.
• Predictive models for mortality trajectories are needed.

Purpose of the Study:

• To develop methods for predicting mortality rate based on underlying physiological processes.
• To explore how different physiological models influence mortality trajectories.
• To investigate the relationship between growth, metabolism, and mortality.

Main Methods:

• Utilized the method of linear chains to model mortality from multiple, potentially delayed, physiological processes.
• Developed a second model assuming mortality arises from growth and metabolism-associated damage.
• Analyzed the resulting mortality trajectories from both modeling approaches.

Main Results:

• Both modeling approaches generated a wide range of predicted mortality trajectories.
• Many predicted trajectories exhibited Gompertzian patterns at younger ages.
• Mortality patterns at older ages were dependent on the specific physiological details within each model.

Conclusions:

• Predicting mortality rate from physiological processes is feasible.
• The choice of physiological model significantly impacts predicted mortality dynamics, especially at older ages.
• This framework allows for a more mechanistic understanding of mortality patterns.