An observational study in Aging, Mortality and All-cause Mortality, sponsored by Longevity Metrics, Inc.. Recruiting at 1 site in United States. Open to participants aged 18 Years and older, including healthy volunteers. Per ClinicalTrials.gov, last updated 2026-09-08.
Sponsored by Longevity Metrics, Inc. · Observational
The Human Observatory Study is a prospective observational and ecological surveillance study building a continuously-updating world model for human health, disease, and death at the individual and population level. Individual multi-system clinical data from enrolled participants are linked to a continuously-ingested ecological data infrastructure spanning environmental exposures, social determinants, genealogical and family history records, mortality data, and population health databases at geographic resolutions from home address to global scale and beyond. The resulting model generates individual screening recommendations informed by population-level causal estimates, and population-level causal forecasts anchored by present-timepoint individual clinical biology. This linkage creates a feedback architecture designed to improve both simultaneously.
Existing approaches to human health prediction face a structural limitation: individual clinical studies measure biology without capturing the environment, while population epidemiology captures the environment without individual biological ground truth. The Human Observatory Study resolves this by operating at both levels simultaneously through a linked dual-layer architecture.
At the individual level, participants enrolled in the 100-Year Human Aging Study contribute comprehensive multi-system health measurements. This includes clinical, physiological, cognitive, behavioral, social, occupational, and environmental data collected at fixed and mobile clinical sites. These measurements provide the biological present timepoint that historical population data alone cannot supply.
At the population level, the Observatory continuously ingests ecological data from public and private registries across multiple input domains. This includes air quality, water and chemical contaminants, wildfire and smoke exposure, altitude and terrain, climate, satellite earth observation, occupational and industrial exposure, mortality and vital statistics, demographics and social determinants, and clinical data networks at geographic resolutions from home address to global scale and beyond. This ecological layer captures the environmental and social causal structure of health and disease continuously and does not require individual enrollment.
A foundational input domain is genealogy and family history. Health and disease run in families across generations. The Observatory is designed to build and continuously expand a linked genealogical database connecting living and historical individuals to their family health histories. Information is obtained from public genealogical records, death registries, family history self-report, and genetic data where available. The long-term vision is a genealogical infrastructure of sufficient depth and breadth to trace familial health patterns across the full recorded human family tree. Therefore connecting individual present-timepoint biology to multigenerational patterns of disease, longevity, and environmental exposure that no existing biobank or longitudinal study has attempted to capture at this scale.
The linked architecture enables a feedback loop with two outputs: population-level causal estimates that inform individual screening recommendations, and individual clinical data that give population models a present biological anchor for prospective forecasting. The degree to which each input domain, alone and in combination, predicts health, disease, and death across geographic scales from neighborhood to global and beyond is the central scientific question the Observatory is designed to answer.
The Observatory launches in Colorado, chosen as the founding site for its exceptional natural variation in altitude, wildfire smoke corridors, mining and industrial chemical geographies, and frontier-to-urban socioeconomic gradient all within a compact, well-characterized geography with established academic research infrastructure. Colorado proves the model. The architecture then replicates geographically, with each new location enriching the world model for every other. The long-term vision is global coverage and beyond. Every geography will contribute its environmental, social, and biological signal to a world model that gets more accurate with every geography studied, every participant enrolled, every dataset ingested, and every causal analysis conducted.
The Human Observatory Study is conducted across all Longevity Metrics participation pathways, current and future: the Boulder fixed laboratory; all current and future fixed clinical sites; mobile screening units including the Health Ahead Bus; and an online participation pathway through which participants enroll and contribute structured data without in-person screening. Ecological data are ingested continuously from public and private registries independent of individual enrollment. All pathways operate under a single protocol with identical procedures, data management, informed consent, and safety standards.
This study is one of four that compound into one system. The 100-Year Human Aging Study (NCT07563777) supplies the clinical data and validates what it means for health, disease, disability, and death. The Health Ahead Comparative Effectiveness Study (NCT07669168) moves the screening toward increasing automation and mobility while maintaining quality. The Longevity Metrics AI/ML Development Study (NCT pending approval) builds the models that make automation, prediction, and broad utilization possible, and returns each model's geographic residuals here. This study does with sociodemographic and environmental data what the 100-Year study does with clinical data, and defines the validated envelope within which each model's output is labeled.
5,368 studies on the registry are indexed under Cardiovascular Diseases; 939 are open to participants now.
This study's planned enrollment of 1,000,000 is above the median of 506 across 1,572 observational studies indexed under Cardiovascular Diseases.
Browse Cardiovascular Diseases studies →Longevity Metrics, Inc. is the lead sponsor of 3 studies on the registry; 3 are open to participants now.
Counted across the registry records on this site, refreshed daily.
Participants of all ages, health statuses, and demographic backgrounds enrolled in the 100-Year Human Aging Study at any fixed or mobile clinical site, plus participants completing the online health screener. No exclusions based on health status, geographic location, language, or population group. The ecological surveillance layer requires no individual enrollment.
Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.
Exclusion Criteria:
Linkage of individual multi-system clinical health measurements to continuously-ingested ecological data from public and private registries spanning environmental, social, genealogical, and population health domains at geographic resolutions from home address to global scale and beyond. The linked dataset feeds a continuously-updating causal inference engine generating life expectancy estimates, disease cluster detection, individual screening recommendations, and population health intelligence.
Life Expectancy Estimates by Geography
Continuously-updated life expectancy point estimates with credible intervals generated at individual, neighborhood, ZIP code, county, state, national, global, and beyond-earth scales using individual clinical data linked to population mortality records, environmental context, and ecological data.
Time frame: From enrollment until death, assessed periodically, up to 100 years
Geographic Disease Cluster and Outbreak Detection
Statistically anomalous concentrations of incident disease, mortality spikes, or shared symptom patterns at neighborhood and community resolution.
Time frame: From enrollment until death, assessed periodically, up to 100 years
Individual Screening Recommendation Accuracy
Concordance between population-level causal estimates used to generate individualized screening recommendations and actual individual health outcomes at longitudinal follow-up, assessed periodically as outcomes accrue.
Time frame: From enrollment until death, assessed periodically, up to 100 years
Causal Effect Estimates for Modifiable Exposures
Estimated attributable life-years gained or lost per unit change in modifiable environmental, occupational, and social exposures.
Time frame: From enrollment until death, assessed periodically, up to 100 years
Geographic Variation in Disability-Free Life Expectancy
Disability-free life expectancy stratified by geography, ascertained via the functional independence and disability survey instrument used across all three associated protocols.
Time frame: From enrollment until death, assessed periodically, up to 100 years
Health Equity Characterization
Life expectancy gaps and chronic disease disparities stratified by geography, income, race and ethnicity, educational attainment, and rural-urban classification.
Time frame: From enrollment until death, assessed periodically, up to 100 years
Human Tree of Life Growth
Total participants linked to genealogical record; multigenerational depth achieved; proportion of enrolled participants with identified biological relatives in the registry; total historical individuals linked across all genealogical databases.
Time frame: From enrollment until death, assessed periodically, up to 100 years
Population Biological Age Acceleration
Mean difference between chronological age and biological age estimate for repeat-visit participants, stratified by geographic and demographic characteristics.
Time frame: From enrollment until death, assessed periodically, up to 100 years
Multi-Domain Predictor Modeling
Assessment of individual and composite clinical, biological, behavioral, environmental, social, occupational, genealogical, and geographic measurements as predictors of all-cause mortality, life expectancy, and incident serious disease at population scale; analyses evaluate which domains are independently predictive, which are redundant, and which combinations provide additive or synergistic predictive value.
Time frame: From enrollment until death, assessed periodically, up to 100 years
Incident Serious Health Events and Chronic Disease
New diagnosis of myocardial infarction, stroke, cancer, dementia, heart failure, atrial fibrillation, sepsis, venous thromboembolism, COPD, chronic hypoxia, major fracture, type 2 diabetes, hypertension, chronic kidney disease, metabolic syndrome, or osteoporosis ascertained via periodic follow-up contact and health data network linkage.
Time frame: From enrollment until death, assessed periodically, up to 100 years
Plan to share: No — Individual participant data are not shared. The complete participant record includes facial and voice recordings, genomic data, and neighborhood-resolution geography, and cannot be de-identified; it is never released. Identifiable data are accessed only by approved researchers working within Longevity Metrics secure facilities under data use agreements, with no data removed. Specific derived, aggregate, and statistical outputs are de-identified to HIPAA Safe Harbor standards and may be published, shared with collaborators, or contributed to open-access research databases. Models, risk estimates, and analytic findings derived from the research data may be provided to external organizations or used commercially; no participant record and no dataset containing participant data is transferred.
Started Apr 2026 (actual). Primary completion is estimated for Dec 2099, 884 months after the start.
Of 84 industry-sponsored observational studies under Cardiovascular Diseases, half reached primary completion within 31 months of starting (the median), counting those still running; a quarter within 15 and three quarters within 48. This study's planned 884 months is above that.
Counting every sponsor, half of 664 studies reached it within 61 months; a quarter within 24 and three quarters within 192.
Cardiovascular Diseases covers many different conditions, not one, so the studies compared here vary widely. Read these figures as a rough guide.
How these figures are worked out, and which studies are left out of them.
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