Process / pipelineSocial GerontologyGeriatric assessment / biological aging measurementPipeline

Healthy Aging Index Construction

Also known as: HAI, Healthy Ageing Index, Multisystem Healthy Aging Index, Physiologic Aging Index

OriginatorJason L. Sanders, Anne B. Newman, and colleagues (Cardiovascular Health Study; Long Life Family Study)Year2014Sources1Related methods9

The Healthy Aging Index (HAI) is a simple composite that summarizes the burden of subclinical physiologic decline across several organ systems into a single score. Introduced by Jason Sanders, Anne Newman, and colleagues in 2014 using the Cardiovascular Health Study, it captures the idea that biological aging is a multisystem process rather than the failure of any one organ. The index combines five readily measured markers, one from each of five physiologic systems: systolic blood pressure (vascular), fasting glucose (metabolic), Mini-Mental State Examination score (cognitive), serum creatinine (renal), and forced vital capacity (pulmonary). Each marker is scored 0, 1, or 2 according to which tertile of risk an individual falls into, and the five scores are summed to give a total from 0 to 10, with higher values indicating worse aging. The HAI predicts mortality and was shown to be heritable, supporting its interpretation as a phenotype of biological aging. Its appeal lies in being inexpensive, transparent, and built from routine clinical measurements rather than specialized assays.

Key highlights

  • Captures aging as a multisystem process by combining vascular, metabolic, cognitive, renal, and pulmonary markers into one score.
  • Built from inexpensive, routine clinical and cognitive measurements rather than specialized assays.
  • Transparent and easy to compute, with an unweighted 0-to-10 scale that requires no model fitting.
  • Predicts mortality in a graded fashion and is heritable, supporting its interpretation as a biological-aging phenotype.

Intuition

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How it works

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When to use it

Use the Healthy Aging Index when you want an inexpensive, transparent summary of multisystem biological aging that can be computed from routine clinical and cognitive measurements in an older population. It is well suited to epidemiological cohorts and aging studies that already collect blood pressure, fasting glucose, cognitive screening, serum creatinine, and spirometry, and where the goal is to characterize subclinical physiologic burden, stratify mortality risk, or study the heritability and determinants of biological aging. The index is appropriate when a single, interpretable composite is preferred over more complex biological-age algorithms and when comparability with the original five-marker construction is desired. It is less appropriate when the required measurements, particularly spirometry or fasting glucose, are unavailable, when the population is too young or too ill for the markers to discriminate, or when a continuous, finely calibrated estimate of biological age is needed, in which case methods such as the Klemera-Doubal biological-age estimator or epigenetic clocks are better suited. The index complements rather than replaces frailty measures.

Strengths & limitations

Strengths
  • Captures aging as a multisystem process by combining vascular, metabolic, cognitive, renal, and pulmonary markers into one score.
  • Built from inexpensive, routine clinical and cognitive measurements rather than specialized assays.
  • Transparent and easy to compute, with an unweighted 0-to-10 scale that requires no model fitting.
  • Predicts mortality in a graded fashion and is heritable, supporting its interpretation as a biological-aging phenotype.
Limitations
  • Tertile-based cutpoints depend on the reference population, so scores may not be directly comparable across cohorts.
  • Equal weighting of the five systems is a simplifying assumption that may not reflect their true relative importance.
  • Categorizing continuous markers into three levels discards information and can misclassify people near cutpoints.
  • The fixed five-marker set omits other systems, such as inflammation or musculoskeletal function, relevant to aging.

Common pitfalls

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Applications

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Frequently asked

Which five markers make up the Healthy Aging Index and why these?

The index uses systolic blood pressure for the vascular system, fasting glucose for metabolic function, the Mini-Mental State Examination for cognition, serum creatinine for renal function, and forced vital capacity for pulmonary function. These were chosen because each represents a distinct physiologic system that declines with age and because all can be measured with routine, inexpensive methods. Together they capture aging as a multisystem process rather than the failure of any single organ, which is the central idea behind the index.

How is the 0-to-10 score computed and interpreted?

Each of the five markers is scored 0, 1, or 2 according to which risk category, typically a tertile, the individual falls into, with the least healthy category scoring 2. The five scores are summed without weighting to give a total from 0 to 10. A low score means most systems remain healthy, while a high score signals that many systems show subclinical decline at once. Higher scores are associated with greater mortality risk, so the total serves as a graded summary of multisystem biological aging.

How does the Healthy Aging Index differ from a frailty index or a biological-age estimate?

The HAI is a five-marker physiologic composite focused on subclinical organ-system decline, scored 0 to 10. A deficit-accumulation frailty index counts many clinical deficits of any kind and expresses frailty as a proportion, while methods like the Klemera-Doubal estimator or epigenetic clocks produce a continuous biological age in years from biomarker or methylation data. The HAI is simpler and cheaper than biological-age algorithms and more physiologically specific than a broad frailty index. The measures correlate but capture different facets of aging and are often studied together.

Sources

  1. 1.
    Sanders, J. L., Minster, R. L., Barmada, M. M., Matteini, A. M., Boudreau, R. M., Christensen, K., Walston, J. D., Newman, A. B. (2014). Heritability of and mortality prediction with a longevity phenotype: the healthy aging index. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, 69(4), 479-485.

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ScholarGate. (2026, June 23). Healthy Aging Index Construction. ScholarGate. https://scholargate.app/social-gerontology/healthy-aging-index