Based on a longitudinal analysis of dried-bloodspot, physical-exam, and performance-test biomarkers in nearly 20,000 participants in the US Health and Retirement Study and English Longitudinal Study of Aging, Arun Balachandran and Daniel W Belsky show that the Pace of Aging varies widely among older adults and predicts risk of incident disability, multimorbidity, and mortality over 5-10 years of follow-up.
Global trends toward population aging have placed demography at the center of policy discussions. Planners and policy makers need information about how to protect the health of older people to preserve productivity and limit costs. However, demography’s current toolkit is focused on completed lifespans or healthspans (Balachandran, 2020). These metrics, including estimates of life expectancy, healthy life expectancy, disability adjusted life years, and so on, are effective in summarizing differences between populations accumulated across the full life courses of the individuals who contribute data. However, they do not distinguish health deficits established early in life from the ongoing changes in people’s bodies that are the essence of aging.
The Pace of Aging
For new policies and programs to mitigate societal burden related to population aging (Beard et al., 2016), they must slow or delay declines in health and function among older people. To provide optimally sensitive metrics for population surveillance and intervention evaluation, measurements are needed that can distinguish ongoing aging-related changes in organs, tissues, and capacities from differences in health that are legacies of early life.
We developed an approach, called Pace of Aging, to measure the rate of aging-related decline in the biological integrity of adult humans using longitudinal data tracking the health and function of multiple organ systems in the body (Belsky et al., 2015). In a recent study, we adapted our method to fit the data and populations included in two national-level studies of aging: the US Health and Retirement Study (HRS) and the English Longitudinal Study of Aging (ELSA) (Balachandran et al 2025). The measurements we derived are now publicly available to users of these datasets and the method can be applied to studies around the world as they begin to accumulate sufficient longitudinal data.
Measuring Pace of Aging for demographic analysis
Our original Pace of Aging method was developed within the New-Zealand-based Dunedin Longitudinal Study, a single-year birth cohort followed across the transition from young adulthood to midlife and including in-depth clinical exams at each wave of measurement (Belsky et al., 2015). We adapted this method to accommodate sparser data from a mixed-age sample of older people (Balachandran et al., 2025) with the goal of establishing new measurements and a methodological approach that can be useful for demographers. Our analysis included dried blood spot measurements of C-reactive protein, glycated hemoglobin, cystatin C (HRS only), and hemoglobin (ELSA only), physical exam measurements of blood pressure, waist circumference, and lung function, and performance test measurements of gait speed, grip strength, and balance. Changes in these biomarkers were modeled over an eight-year follow-up period to ascertain each individual’s rate of change on each biomarker. These changes were composited into a single index and normalized against the average rate for a reference group formed from participants below age 65. The resulting metric summarizes the average rate of change in a person’s physical state expressed as a ratio of “years” of biological decline experienced per 12 calendar months of follow-up.
Differences in rates of aging across population subgroups
Pace of Aging was highly variable in older adults in the United States and the United Kingdom. People who were older at study baseline exhibited faster Pace of Aging over follow-up, consistent with prior observations that the speed of aging accelerates towards the end of life. Population groups with shorter healthy lifespans, such as those with lower levels of education, also exhibited faster Pace of Aging.
We examined the significance of variation in Pace of Aging by testing differences in health risks between people who were aging slowly and those who were aging more rapidly. Follow-up for health outcomes extended beyond the Pace of Aging measurement interval by an additional 6-8 years. Across the US and UK samples, older people with faster Pace of Aging were more likely to accumulate new chronic diseases over follow-up, to become disabled, to become cognitively impaired and to develop dementia, and to die. Effect sizes for associations ranged from a ~10% increase in risk for incident chronic disease to a near doubling of mortality risk per standard deviation of Pace of Aging.
Implications
The adapted Pace of Aging method, along with specific measurements from US and UK aging studies, can enhance demographic research on healthy longevity at the population level. It offers a framework for demographers worldwide to measure the Pace of Aging in their own population studies (Balachandran et al., 2025). Many studies, within the Gateway of Global Aging initiative, already have or will soon gather the required data, i.e., three repeated measurements of blood, organ function, and performance tests. The Pace of Aging measure potentially supports diverse research areas: sociology and economics can explore how social factors affect healthy aging; medicine and gerontology can assess the impact of health events on aging; life-course epidemiology can distinguish early life influences from existing health issues; and health equity studies can identify disparities and the effects of economic and health shocks. These insights from the Pace of Aging analysis can support population monitoring projects to observe trends in healthy longevity and assist in identifying policies and social programs that promote a healthy lifespan among living individuals who have not yet developed disabling chronic conditions, in line with the goals of public health bodies.
References
AAVV (2025). Pace of aging matters for healthspan and lifespan in older adults. Nature Aging, 5(6), 964–965. https://doi.org/10.1038/s43587-025-00903-4
Balachandran, A. (2020). Population ageing in Europe and Asia: Beyond traditional perspectives. University of Groningen, The Netherlands. October. https://research.rug.nl/files/135497886/Complete_thesis.pdf
Balachandran, A., Pei, H., Shi, Y., Beard, J. R., Caspi, A., Cohen, A. A., Domingue, B. W., Eckstein Indik, C., Ferrucci, L., Furuya, A., Kothari, M., Moffitt, T. E., Ryan, C. P., Skirbekk, V., Zhang, Y. S., & Belsky, D. W. (2025). Pace of Aging analysis of healthspan and lifespan in older adults in the US and UK. Nature Aging. https://doi.org/10.1038/s43587-025-00866-6
Beard, J. R., Officer, A., de Carvalho, I. A., Sadana, R., Pot, A. M., Michel, J.-P., Lloyd-Sherlock, P., Epping-Jordan, J. E., Peeters, G. G., & Mahanani, W. R. (2016). The World report on ageing and health: A policy framework for healthy ageing. The Lancet, 387(10033), 2145–2154.
Belsky, D. W., Caspi, A., Houts, R., Cohen, H. J., Corcoran, D. L., Danese, A., Harrington, H., Israel, S., Levine, M. E., & Schaefer, J. D. (2015). Quantification of biological aging in young adults. Proceedings of the National Academy of Sciences, 112(30), E4104–E4110.