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Scientists cannot directly measure a single maximum age that humans are capable of reaching. Instead, they study survival and death rates at very old ages, track the ages of the oldest people who die, and test statistical or biological models. Those approaches do not yet produce a universally accepted ceiling: studies disagree about what happens to mortality after age 105, and estimates such as 138 years are model-based proposals, not observed or agreed limits.
First, distinguish life expectancy from lifespan
“Life expectancy” is a population statistic calculated from a defined schedule of death rates. It summarizes how long people would live on average if those age-specific rates applied across their lives. It is not a prediction that every individual will reach that age, nor is it the oldest age a person could reach.
“Lifespan” can mean different things in different studies. It may refer to an individual’s age at death, the maximum age observed in a population, or a theoretical upper boundary inferred from a model. A claim about one of these outcomes cannot automatically answer questions about the others.
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- Life expectancy: an average under a specified population mortality schedule.
- Survival to a threshold: the probability or projected share of a population reaching an age such as 100.
- Age-specific mortality: the death rate among people at a particular age, including whether it continues to rise at extreme ages.
- Maximum lifespan: the oldest age a person might reach, either as an observed record or an inferred limit.
These distinctions matter because a study can find that life-expectancy gains are slowing, or project that relatively few people will reach 100, without establishing a hard maximum age at death.
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What scientists measure at extreme ages
Demographic researchers start with records of survival and death by age. They may compare age-specific mortality across populations or periods, examine the ages at which people die, or investigate whether mortality keeps increasing among people who survive into their late hundreds. These are related questions, but each has a different endpoint.
Age-specific mortality
Mortality at a given age describes the risk of dying among people who have reached that age, over a defined period or according to a specified statistical measure. A mortality-plateau study asks whether this risk stops rising, rises more slowly, or continues to rise at extreme ages. It does not ask directly for the oldest age any person can reach.
One framework used to describe the increase in mortality with age is the Gompertz model. In simplified terms, researchers examine how the model’s age-related mortality slope behaves. A slope that remains positive is evidence, under that model and in the analyzed data, that mortality continues to rise. It does not by itself establish a maximum possible human age.
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Observed maximum ages
Another approach tracks the oldest reported age at death. The maximum recorded in a population is an observation, not necessarily a biological boundary: it depends on how many people are observed, how long the observation period lasts, and whether the age records are reliable. A record that stops increasing over a period may be consistent with a constraint, but it does not alone prove that no one can live longer.
Biological-marker models
Some researchers analyze biological measurements over time rather than relying only on population death records. A 2021 longitudinal study of blood markers describes a progressive loss of resilience and cites a 138-year estimate for a limiting lifespan (Nature Communications, 2021). That figure is a model-based proposal discussed by the paper. It is neither an observed maximum age nor a consensus scientific ceiling, and it should not be read as a personal lifespan forecast.
Why the evidence becomes difficult to interpret at very old ages
Few people live to the ages that would be most informative about a putative limit. As a result, the statistical tail is based on sparse observations. With small numbers, a modest change in which individuals are included can substantially affect an estimated death rate or fitted trend.
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Age records also matter. A study of extreme-age mortality depends on correctly identifying both the person’s age and the timing of death. The available published summaries do not provide consistent detail on age-validation procedures across all of the studies discussed here, so their results should not be treated as if they were based on identical data-quality checks.
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Why researchers disagree about a mortality plateau
A plateau would mean that mortality stops increasing, or becomes approximately level, at the oldest ages examined. Whether such a pattern exists is contested; it is not a settled answer to the question of a maximum human lifespan.
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Evidence reported for a plateau
A 2018 paper on “longevity pioneers” described its finding as the best evidence to that point for a plateau in mortality at extreme ages. Its subject is the shape of late-life mortality in the population studied, not a direct measurement of a maximum age at death (Barbi et al., Science, 2018).
Evidence against a plateau in French data
A 2023 analysis by Dang and colleagues reached a different conclusion for French data. The authors report that their Gompertz slope estimate remained statistically different from zero across all of their model specifications, supporting the conclusion that mortality continued to increase beyond age 105 in that analysis (Dang et al., Demographic Research, 2023). This is a finding for the studied data and specifications, not proof that every population has the same mortality pattern.
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The contrast is useful because it shows what the dispute is about: how to infer a pattern from very few observations at extreme ages, and how choices about population, data, and model affect the result. Neither a plateau nor a continuing increase in mortality, on its own, supplies an agreed maximum possible age.
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What prominent lifespan and longevity estimates actually say
Several widely discussed results sound like estimates of a human lifespan limit but address different outcomes. Compare the endpoint, population, period, and model before treating any number as an answer to “How long can a human live?”
| Study | Outcome examined | Population and period stated | Reported result and what it does not establish |
|---|---|---|---|
| Dong, Milholland, and Vijg, 2016 | Changes in survival at older ages and the age at death of the oldest person | Global demographic data; the period is not stated in the available summary | The authors reported that survival improvements declined after age 100 and that the oldest person’s age at death had not increased since the 1990s. They interpreted this as evidence for a natural limit; this is the authors’ conclusion, not a consensus finding (Nature, 2016). |
| Barbi and colleagues, 2018 | Whether mortality reaches a plateau at extreme ages | “Longevity pioneers”; geography and observation period are not stated in the available summary | The authors reported evidence for a mortality plateau. This concerns late-life mortality patterns, not a numerical maximum lifespan (Science, 2018). |
| Dang and colleagues, 2023 | Whether mortality continues to rise beyond age 105 | French data; the observation period is not stated in the available summary | The estimated Gompertz slope remained statistically different from zero across the analyzed model specifications, supporting continued mortality increases in that analysis (Demographic Research, 2023). |
| Olshansky and colleagues, 2024 | Life-expectancy trends and survival to age 100 | Australia, France, Italy, Japan, South Korea, Spain, Sweden, and Switzerland, plus Hong Kong and the United States; vital-statistics data for 1990–2019 | The authors reported decelerating life-expectancy improvements. They estimated that survival to 100 was unlikely to exceed 15% for females and 5% for males unless biological aging is markedly slowed. These are study-specific projections about reaching 100, not a proposed maximum age (Nature Aging, 2024). |
| 2021 blood-marker study | Longitudinal changes in blood markers associated with resilience and lifespan | Study population and observation period are not stated in the available summary | The paper describes progressive loss of resilience and cites 138 years as a proposed limiting-lifespan estimate. It is a model-based figure, not an observed limit (Nature Communications, 2021). |
For the 2024 study, the percentages have a specific condition: the authors’ projection applies unless biological aging is markedly slowed. They should not be quoted as the chance that any particular person will reach 100, or as evidence that 100 is the maximum human age. Likewise, the 138-year figure belongs to a biological-marker model, while the mortality-plateau papers test a pattern in death rates. Putting these numbers on one scale would obscure what each study estimated.
How to evaluate a new claim about the human lifespan limit
When a headline says scientists have found a maximum lifespan, inspect the paper’s actual outcome before accepting that wording. These checks help separate evidence about ordinary longevity from a claim about the oldest possible age.
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- Check who was studied. Note the country or population, and whether the result is intended to describe that group or a broader human pattern.
- Check the period. A finding tied to particular years or cohorts may not describe mortality in another period. For example, the 2024 life-expectancy analysis covered vital-statistics data for 1990–2019 in its listed locations.
- Look for age-data and uncertainty information. Ask how extreme ages were verified and how uncertainty was reported. If those details are not provided, avoid interpreting a precise-looking estimate as exact.
- Read the model’s assumptions and scope. A fitted trend or proposed limiting age depends on the model and the data included. Check whether the authors frame the result as specific to their analysis or as a broader inference.
- Match the headline to the authors’ conclusion. A projection about survival to 100 is not a ceiling on age at death, and a mortality pattern is not itself a maximum lifespan estimate.
These studies describe populations and statistical patterns. They do not provide a method for calculating an individual reader’s lifespan.
So, is there a limit to how long humans can live?
The evidence summarized here does not establish one agreed numerical ceiling. Researchers have proposed constraints based on observed maximum ages, debated whether mortality plateaus at extreme ages, and developed models that produce upper-age estimates. Those approaches answer different questions, and the plateau findings themselves conflict. The most accurate reading is that a human lifespan limit remains an open, model-dependent question—not a number settled by current demographic or biological-marker evidence.
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