Public Health Data repositories in the United States are moving toward an AGE in years format of five year increments due to the impact of the HIPAA regulations regarding the intentional blinding and masking of data for personal privacy reasons.
Given this challenge to what was had been in the past (prior to HIPAA) a fairly scale level of measure data element based upon the difference between date of birth and date of death, we may need to reconsider AGE as a scale variable that can be parametrically described at all in public health data sets, in favor of models that describe AGE in a non-parametric fashion, as an ordinal level of measure. I know this may seem "over the top" to many factions within the biomedical informatics community, but this idea may have some merit in terms of "interpretation" as described in the comments above.
What about all of the analytical power that is available to the non-parametric approaches? Yes, it is true that every one of us almost universally will attempt to apply GLM (general linear model) techniques to a variable that presents itself to us in distributions that behave the way AGE does.
At the same time the shape of that distribution and how that shape is being determined by multiple dimension interaction effects upon multi-dimensional centroids and sub-group centroids present in the distribution, must be taken into consideration. What to do with these very complex data sets?
When a data element fails to meet the "assumptions of the model", we progressively scan across (I said across, not down; we should be equal opportunity employers of method, each tool comes from the factory with form follows function rules) the list of other possible models to find the ones that "do not fail" the assumptions tests.
In the present format in public health data sets, we really do need (as a data visualization community) to come up with a more standard model for handling AGE in five year increments (5YI). My vote for data visualization of AGE (given the new 5YI format) is to use histograms and box and whisker plots. Yes, this means the median. (No pun intended!)
Sometimes a picture really is worth a thousand words, and an abstract is a summary of a thousand words. The box and whisker plot shows the "shape" of the distribution as a meaningful symbolic representation of the histogram at nearly an iconic level of resolution. Comparing the distributions of five year age increments by showing "side by side" box and whisker plots where one can instantly visually compare patterns of 75th to 50th (median) to lower 25th ntiles, would make an elegant "universal standard" for comparing AGE across the world. For those of us that continue to enjoy the thrill of data representation through the textual mechanics of tabular display, the "stem and leaf" diagram may also be of service when employed as an animated visual graphics element in a "sparkline" approach that portrays variation of the shapes of distributions over time.
AGE has come of age. It needs to be explored further with the more powerful computational algorithms that are now available.