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The primarily alternative to epigenetic clocks and other omics clocks to assess biological age is the use of aging clocks constructed from clinical chemistry, physical, and other simple measures, such as result from the Klemera-Doubal Method or Phenotypic Age. Examples of suitable measures include specific metabolite levels in serum, blood count data, morphometry based on waist circumference, blood pressure, grip strength, and so forth. The construction of a clock proceeds in much the same way regardless; data is assembled from a large study population of different ages, and machine learning approaches are employed to discover algorithmic combinations of data that predict chronological age. Where the predicted clock age is higher than chronological age, it is said that this person exhibits accelerated aging. The advantage of simple measure clocks versus omics clocks is that the data used is easier to theorize on; if one sees that an individual has a higher predicted age because their blood pressure increased, for example, one can form a hypothesis quite quickly and easily. When the cause is a different prevalence of DNA methylation on seven CpG sites on the genome, well, that is largely inscrutable.
