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	Epigenetic Clock (DNA Methylation Age)	Characteristics Approach to Population Aging
Field	Social Gerontology	Social Gerontology
Family	Regression model	Survival analysis
Year of origin	2013	2013
Originator	Steve Horvath	Warren C. Sanderson and Sergei Scherbov
Type	Penalized-regression predictor of age from DNA methylation	Framework for measuring population aging by characteristics rather than chronological age
Seminal source	Horvath, S. (2013). DNA methylation age of human tissues and cell types. Genome Biology, 14(10), R115.	Sanderson, W. C., & Scherbov, S. (2013). The characteristics approach to the measurement of population aging. Population and Development Review, 39(4), 673-685.
Aliases	DNAm Age, Horvath Clock, DNA Methylation Clock, Methylation Age Predictor	Characteristics-Based Aging Measures, Sanderson-Scherbov Characteristics Approach, Alpha-Age Approach, Equivalent-Age Method
Related	4	3
Summary	An epigenetic clock is a statistical predictor that estimates age from patterns of DNA methylation, the chemical marks on the genome that change in a regular way over the life course. The most influential is Steve Horvath's 2013 multi-tissue clock, which predicts chronological age from methylation levels at 353 specific CpG sites using a penalized regression model. Methylation is measured as a beta-value between zero and one at each site, representing the fraction of cells in which that site is methylated, and the clock combines a weighted set of these values into a predicted DNA methylation age, or DNAm age. Remarkably, Horvath's clock works across many tissues and cell types from the same individual, suggesting it captures a fundamental aging process rather than a tissue-specific quirk. The difference between predicted DNAm age and actual chronological age, known as epigenetic age acceleration, serves as a biomarker of biological aging. Age acceleration predicts mortality and a range of age-related conditions, which has made epigenetic clocks central to modern aging research.	The characteristics approach reconceptualizes what it means to be 'old' by measuring age through people's characteristics rather than the number of years since birth. Developed by Warren Sanderson and Sergei Scherbov and set out comprehensively in their 2013 Population and Development Review article, it responds to the fact that conventional aging measures treat a fixed chronological age, such as 65, as a permanent marker of old age even though people at 65 today are healthier and longer-lived than their counterparts decades ago. The core idea is that many relevant attributes, such as remaining life expectancy, health, cognitive function, and disability, vary with both age and time, so old age should be defined by reaching a given level of such a characteristic rather than a fixed birthday. The approach computes equivalent or 'alpha' ages, the ages at which a characteristic takes a chosen reference value, and uses them to build characteristic-based aging indicators. Comparing these with conventional measures often shows that populations are aging more slowly, or even getting younger on some dimensions, than chronological measures suggest. The framework has reshaped how demographers assess the consequences of population aging.