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In building a mortality model (or any other kind of risk model) it is usually best to build a single, over-arching model rather than split the data into sub-groups (an approach called stratification, the disadvantages of which are discussed in Macdonald et al (2018)). One obvious reason is to reduce the total number of parameters: why fit two parameters for age when one will do?
Enhancement
An oft-overlooked aspect of statistical models is that parameters are dependent on each other. Ignoring such dependencies can have important consequences, and in extreme cases can even undermine assumptions for a forecasting model. However, in the case of a regression model the correlations between regressor variables can sometimes have some unexpectedly positive results.