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	Biological Age Estimation	Characteristics Approach to Population Aging
Field	Social Gerontology	Social Gerontology
Family	Regression model	Survival analysis
Year of origin	2006	2013
Originator	Petr Klemera and Stanislav Doubal	Warren C. Sanderson and Sergei Scherbov
Type	Estimator of biological age from a panel of age-related biomarkers	Framework for measuring population aging by characteristics rather than chronological age
Seminal source	Klemera, P., & Doubal, S. (2006). A new approach to the concept and computation of biological age. Mechanisms of Ageing and Development, 127(3), 240-248.	Sanderson, W. C., & Scherbov, S. (2013). The characteristics approach to the measurement of population aging. Population and Development Review, 39(4), 673-685.
Aliases	KDM Biological Age, Klemera-Doubal Method, Biomarker-Based Biological Age, Physiological Age Estimation	Characteristics-Based Aging Measures, Sanderson-Scherbov Characteristics Approach, Alpha-Age Approach, Equivalent-Age Method
Related	4	3
Summary	Biological age estimation seeks to measure how old a person's body actually is, as distinct from the number of years since their birth. The most influential statistical approach is the Klemera-Doubal method (KDM), introduced in 2006, which derives a single biological-age value from a panel of age-related biomarkers. The central idea is that many physiological measures change predictably with age, so by regressing each biomarker on chronological age in a reference sample one can learn how each one tracks aging and then combine them to infer an individual's underlying biological age. Klemera and Doubal showed mathematically that treating biological age as a latent quantity estimated from all biomarkers jointly, weighted by how strongly and how cleanly each tracks age, yields a more accurate estimate than simply regressing chronological age on the biomarkers. The gap between estimated biological age and chronological age, often called biological age acceleration, indicates whether a person is aging faster or slower than average. This deviation predicts mortality and morbidity beyond chronological age, which is what makes the estimate useful.	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.