ArticleJMIR aging2022
A Model for Estimating Biological Age From Physiological Biomarkers of Healthy Aging: Cross-sectional Study.
Article in JMIR aging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. It is linked to trial NCT03680768 (Development of a New Biological Age Technology Applicable in Public Health Promotion Interventions.), which is not on this map. Cited by 12 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Development of a New Biological Age Technology Applicable in Public Health Promotion Interventions.
Who cites it
12 citing papers in PubMed, 3 syntheses or guidelines pooled it, 19 citations in OpenAlex.
- Pooled it
- The Importance of Activating Factors in Physical Activity Interventions for Older Adults Using Information and Communication Technologies: Systematic Review.JMIR mHealth and uHealth · 2023Pooled it
- Age-Related Cognitive Decline, Focus on Microbiome: A Systematic Review and Meta-Analysis.International journal of molecular sciences · 2023Pooled it
- Multidimensional Physiological and Gut Microbiome Profiling Identifies Subtle Physiological Patterns in an Apparently Healthy Aging Indian Cohort: A Cross-Sectional Observational Study.Microorganisms · 2026Article
- Mortality associated biological age improves independently of weight loss after bariatric surgery.npj aging · 2026Article
- Multidimensional modeling of biological aging: integrating gait, eye movement, rest-state functional connectivity, and plasma biomarkers in non-dementia older adults.The journal of prevention of Alzheimer's disease · 2026Article
- A machine learning-derived biological age model for liver grafts provides a superior assessment of aging compared to chronological age in transplantation.Scientific reports · 2026Article
- Cultural Engagement Is Related to Decelerated Physiological Age: Doubly Robust Estimations in a National Cohort Study.Annals of the New York Academy of Sciences · 2026Article
- Social connections are differentially related to subjective age and physiological age acceleration amongst older adults.Nature communications · 2026Article
- Synergistic and heterogeneous aging using composite phenotypes and multiple organ systems aging clocks.Communications medicine · 2025Article
- Artificial Intelligence-Driven Biological Age Prediction Model Using Comprehensive Health Checkup Data: Development and Validation Study.JMIR aging · 2025Article
- A study on the development of a fitness age prediction model: the national fitness award cohort study 2017-2021.BMC public health · 2024Article
Corrections and comments
- Erratum issued
Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIndividual differences in the rate of aging and susceptibility to disease are not accounted for by chronological age alone. These individual differences are better explained by biological age, which may be estimated by biomarker prediction models. In the light of the aging demographics of the global population and the increase in lifestyle-related morbidities, it is interesting to invent a new biological age model to be used for health promotion.
objectiveThis study aims to develop a model that estimates biological age based on physiological biomarkers of healthy aging.
methodsCarefully selected physiological variables from a healthy study population of 100 women and men were used as biomarkers to establish an estimate of biological age. Principal component analysis was applied to the biomarkers and the first principal component was used to define the algorithm estimating biological age.
resultsThe first principal component accounted for 31% in women and 25% in men of the total variance in the biological age model combining mean arterial pressure, glycated hemoglobin, waist circumference, forced expiratory volume in 1 second, maximal oxygen consumption, adiponectin, high-density lipoprotein, total cholesterol, and soluble urokinase-type plasminogen activator receptor. The correlation between the corrected biological age and chronological age was r=0.86 (P<.001) and r=0.81 (P<.001) for women and men, respectively, and the agreement was high and unbiased. No difference was found between mean chronological age and mean biological age, and the slope of the regression line was near 1 for both sexes.
conclusionsEstimating biological age from these 9 biomarkers of aging can be used to assess general health compared with the healthy aging trajectory. This may be useful to evaluate health interventions and as an aid to enhance awareness of individual health risks and behavior when deviating from this trajectory.
trial registrationClinicalTrials.gov NCT03680768; https://clinicaltrials.gov/ct2/show/NCT03680768. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/19209.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.