Step functions are commonly used in epidemiology and biostatistics for accounting for biological changes due to factor like age (age binning)

University of Michigan - Ann Arbor

Instead of using a linear model to fit the data gloabally, we can fit the data into a model of step functions. As is shown below,  Here we break the range of X into bins, and ﬁt a diﬀerent constant in each bin. This amounts to converting a continuous variable into an ordered categorical variable.
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Step Functions

Regression splines combine the benefits of polynomials and step functions to provide us with a more flexible estimated function. Assuming that we divide the range of independent variables $X$ into enough regions, we can theoretically fit any function. However, this flexibility comes with the expense of overfitting and less interpretability of the coefficients. So, the analyzer should consider a trade-off when deciding on the number of regions.

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