Published on: May 28, 2025
A newly enhanced method for assessing the Pace of Aging in population-based studies is providing researchers and policymakers with a powerful tool to predict aging-related risks, including chronic diseases, cognitive decline, disability, and mortality. Developed by scientists at Columbia University's Mailman School of Public Health, this refined approach allows for a more precise measurement of how quickly individuals and populations undergo age-related health deterioration.
Traditional metrics in population health research have struggled to distinguish between health differences rooted in early-life conditions—such as prenatal care and nutrition—and those resulting from the biological processes of aging. The findings, now published in Nature Aging, address this limitation.
The Pace of Aging method offers a crucial advancement in how we study population aging,” said Arun Balachandran, PhD, postdoctoral researcher at the Columbia Aging Center and lead author of the study. “Until now, our tools haven’t been able to separate the effects of early life from the physiological changes due to aging itself,” added Daniel Belsky, PhD, associate professor of Epidemiology at Columbia Mailman School and a faculty member at the Robert N. Butler Columbia Aging Center.
Originally designed to evaluate anti-aging interventions, the method has now been adapted to assess the impact of social policies and public health initiatives. According to the researchers, this allows for a deeper understanding of how various societal and environmental factors influence the trajectory of aging across populations.
The study analyzed data from two major, long-running, nationally representative cohorts: the U.S. Health and Retirement Study (HRS) and the English Longitudinal Study of Aging (ELSA). These studies track adults aged 50 and above, gathering comprehensive information on health, cognition, socioeconomic factors, and family life over time.
Researchers used data from dried blood samples, physical assessments, and performance-based tests, collected up to three times across eight years. In total, 19,045 participants were included between 2006 and 2016, with follow-up through 2022 to examine outcomes like disease, disability, and mortality. Key biomarkers in the U.S. cohort included C-reactive protein (CRP), Cystatin-C, glycated hemoglobin (HbA1C), diastolic blood pressure, waist circumference, lung function, balance, grip strength, and walking speed.
Our study shows that meaningful differences in how fast people age can be measured with a fairly limited set of indicators, said Belsky. This opens up new opportunities to study aging trajectories globally, added Balachandran. The metrics consistently forecast future health outcomes and highlight disparities among different population groups—for example, individuals with lower educational attainment showed signs of accelerated aging.
The original version of the Pace of Aging tool was based on the Dunedin Study, which followed individuals born in 1972–73 from childhood through midlife. This updated version now enables its use in broader, population-based aging research, offering valuable insights for health planners and policymakers aiming to improve public health and longevity.
“This research extends beyond the medical and gerontological fields,” Belsky noted. “It has major implications for sociology and economics by helping us understand how life changes—like retirement, caregiving responsibilities, or bereavement—affect the aging process. These insights can guide more effective social and public health policies.”
Crucially, the differences in aging pace revealed by the study were not only statistically significant but also practically impactful. “Individuals who aged faster were more likely to become ill, disabled, or die sooner—even if their chronological age was the same,” Belsky said.
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