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Health · reviewed 2026-04-11

What are the odds of developing CTE as a former football player?

Evidence quality 4.63/5

Eight-dimension review score against the quality rubric . Each dimension scored 1–5.

D1 Source grounding
5/5
D2 Source authority
5/5
D3 Arithmetic
4/5
D4 Uncertainty
4/5
D5 Scope
5/5
D6 Prose
5/5
D7 Perception honesty
4/5
D8 Caveat completeness
5/5
Average 4.63/5
Direct evidence

Lifetime probability · lifetime, subgroup

1 in 5.0

20% lifetime chance

range 1 in 10 to 1 in 2.0

lifetime, subgroup each band = 10× rarer → zoomed to your factors See full scale →
certain 1 in 1K 1 in 1M 1 in 1B
1 in 1.7 1 in 5.0

● your factors — click this risk ▾ to reveal

≈ As likely as

A single scuffed leather football laces detail resting on a pale neutral surface, flat vector illustration in muted colors.

Perceived

Until roughly 2015, chronic traumatic encephalopathy was a niche term inside sports medicine and a courtroom word inside NFL concussion litigation. The 2017 Mez et al. JAMA paper — CTE neuropathology in 110 of 111 donated NFL brains — moved it into the mainstream, and the headline number was vivid enough that it reshaped how former players, parents of youth athletes, and the general public talk about the risk. The current intuition among former career football players is no longer that CTE is a rare unlucky tail event; it is closer to "something that happens to a meaningful share of us, and we do not yet know which share." That intuition is roughly the right shape, even though the 99% figure is not the population rate and the true rate is still unmeasurable in living brains.

Rough estimate: Former career players now treat CTE as a meaningful personal risk rather than a rare tail event

Source: editorial intuition, not polled

Actual

~1 in 5 former NFL career players (wide uncertainty)

former NFL career players (order-of-magnitude estimate)

Show derivation

The headline 1-in-5 for a former NFL career player is an order-of-magnitude estimate, not a measured rate. It cannot be measured directly because as of 2026 there is no validated in-vivo biomarker for CTE — the neuropathological diagnosis requires post-mortem tau immunohistochemistry, and most former players will never have their brain examined. Two data points anchor the estimate from opposite directions. The upper bound comes from Mez et al. (JAMA 2017), which reported CTE neuropathology in 177 of 202 donated brains from former football players (87%), including 110 of 111 former NFL players (99%) and 48 of 53 former college players (91%). This is almost certainly a massive overestimate of the population rate: the Boston University brain bank receives donations preferentially from families of former players with symptoms, and Mez and colleagues explicitly warn against interpreting the 99% figure as a prevalence rate. The lower bound is hard to pin down because no large unselected cohort of former players has been followed to autopsy. The Nguyen et al. (American Journal of Epidemiology 2022) formal selection-bias analysis of the Mez dataset estimates that college-level and professional football players face roughly 2.4-2.5 times the CTE risk of high-school-only players after adjustment — a dose-response relationship that is stronger, not weaker, once selection bias is modelled. Working backward from plausible high-school-only population rates and applying that multiplier puts a career NFL player's lifetime CTE probability somewhere in the low tens of percent, with a wide band. Best-guess point estimate 0.2 (1 in 5) with an uncertainty interval of 0.1 to 0.5 that reflects the genuine gap between the lowest plausible population rate and the highest plausible selection-bias-adjusted rate. Scope is subgroup_lifetime because this number describes former NFL career players specifically, not US adults, and not former football players of all levels.

Caveats: The central methodological fact on this page is that CTE cannot be reliably diag…

The central methodological fact on this page is that CTE cannot be reliably diagnosed in a living brain as of 2026. The diagnostic gold standard is post-mortem tau immunohistochemistry on specific brain regions; tau PET imaging is progressing in research cohorts but has not produced a validated clinical test. Every published CTE prevalence number therefore comes from a brain bank, which is by construction a self-selected sample. The Boston University VA-BU-CLF brain bank — the source of the Mez et al. 2017 JAMA paper and most subsequent CTE neuropathology research — receives donations preferentially from families of former players with cognitive, mood, or behavioural symptoms, because those are the families motivated to donate. The 99%-of-NFL-brains figure is not a population rate and the paper’s authors say so explicitly. The second caveat is the distinction between CTE neuropathology (a specific tau protein deposition pattern) and CTE clinical syndrome (the cognitive, behavioural, and mood symptoms attributed to that pathology). The two overlap but are not the same. Neuropathologically-diagnosed CTE can be severe without obvious ante-mortem symptoms, and cognitive decline meeting symptomatic criteria for CTE can occur without the neuropathology on autopsy. This entry is scoped to neuropathological CTE because that is what the cited studies actually measure. Third: the dose-response with total years of contact play is reasonably well-established across Mez 2017, Nguyen 2022, and related work, and is the most load-bearing quantitative finding in the CTE literature. What is not established is the shape of that curve at low exposure, which is why the high-school-only row in the regional_breakdown is so uncertain. A single season of youth flag football is almost certainly low-risk; a career of NFL linemen play is almost certainly elevated. The middle of that range — one or two years of high school tackle, a single college season — is not well-measured in either direction. Finally, this entry will update as in-vivo biomarkers mature. If and when a validated tau PET or blood-based CTE biomarker reaches clinical deployment, the denominators on this page become measurable rather than estimated, and the 1-in-5 headline could move substantially in either direction.

Regional breakdown

The headline figure averages across very different populations. Here’s how the probability varies by geography or context:

Region / context Lifetime probability Notes
Former NFL career player 1 in 5.0 Order-of-magnitude estimate with wide uncertainty. The raw autopsy-series figure is 110 of 111 donated NFL brains (99%) per Mez et al. JAMA 2017, but that cohort is a self-selected symptomatic donor population. The true population rate is unmeasurable in 2026 because there is no validated in-vivo biomarker for CTE. Working from the Nguyen et al. 2022 selection-bias-adjusted dose-response (career NFL vs high school ~2.5×) and a plausible high-school-only base rate, a career NFL player’s lifetime CTE probability lands somewhere in the low-tens-of-percent range. 1 in 5 is the headline, with genuine uncertainty from 1 in 10 to 1 in 2.
Former college football player (D1, career) 1 in 20 Mez 2017 found CTE neuropathology in 48 of 53 former college players donated to the BU brain bank (91%), again with the same massive selection bias. Nguyen et al. 2022 dose-response puts college career players at ~2.4× the CTE risk of high school-only players. The 5% figure is an order-of-magnitude estimate for a D1 career player — four years of contact football at the highest amateur level, multiple diagnosed concussions typical, thousands of subconcussive impacts.
Former high school-only player 1 in 100 Mez 2017 found CTE in 3 of 14 donated brains from former high-school-only players (21%), which — even accounting for selection bias — suggests a non-zero population rate. Any specific percentage here is a guess; 1% is the order-of-magnitude placeholder and could be meaningfully higher or lower. The key qualitative finding from Nguyen et al. 2022 is that the dose-response with total years of contact play is real and monotonic, so a single high school career is genuinely lower-risk than a college career, which is genuinely lower-risk than an NFL career.
Never played contact sport 1 in 1,000 CTE neuropathology is occasionally reported in individuals with no documented repetitive head impact history, but it is genuinely rare. The 0.1% figure is a baseline placeholder representing the tail of the risk distribution — people with undiagnosed impact histories, military blast exposure outside a formal record, or unusual susceptibility. The population rate in never-exposed adults is not well-characterized.

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Compare to:

The headline on this page is roughly 1 in 5 for a former NFL career player, with genuine uncertainty from about 1 in 10 to about 1 in 2. That is an order-of-magnitude estimate, not a measured rate, and the reason is simple: as of 2026 there is no validated in-vivo biomarker for CTE, and the neuropathological diagnosis requires post-mortem tau immunohistochemistry on a donated brain. The most-cited data point in the entire literature — Mez et al. JAMA 2017 finding CTE neuropathology in 110 of 111 donated NFL brains (99%) and 177 of 202 donated brains from former football players at all levels — comes from the Boston University VA-BU-CLF brain bank, which receives donations preferentially from families of players with symptoms. The 99% figure is an upper bound on the population rate, not an estimate of it. The 1-in-5 headline is what you get when you work backward from the selection-bias-adjusted dose-response multipliers in Nguyen et al. (American Journal of Epidemiology 2022) and a plausible high-school-only base rate. It could be meaningfully wrong.

What the literature is confident about is the dose-response with total years of contact play. Career NFL players have roughly 2.5× the CTE risk of high-school-only players in the Nguyen et al. selection-bias-adjusted analysis; career college players are roughly 2.4× the high-school rate. The curve is monotonic and the effect sizes are larger, not smaller, once selection bias is properly modelled — which weighs against the interpretation that the Mez findings are purely a donor-selection artefact. Position matters independently of career length: offensive and defensive linemen absorb the highest per-play head impact counts in the sport and carry elevated risk even when they never had a concussion formally diagnosed. Stamm et al. (Neurology 2015) additionally found that former NFL players who began tackle football before age 12 performed worse on cognitive tests than those who started later, independent of total years of play, suggesting a developmental window effect on top of the cumulative-exposure effect.

Where the number does not apply: the 1-in-5 figure is specifically for a former NFL career player. A former college career player sits lower, perhaps 1 in 20 as an order-of-magnitude guess. A former high-school-only player sits lower still. An adult who never played contact sport is closer to a small non-zero baseline than to any of the football numbers. And every one of those estimates will move as the field develops in-vivo diagnostics — tau PET imaging is progressing in research cohorts, and a validated clinical biomarker would convert this entire page from order-of-magnitude estimates anchored on brain bank convenience samples into something actually measurable. This entry is flagged calibrated rather than underrated because the Mez 2017 finding already moved public perception substantially; former players now take the risk seriously, and the cultural framing of the fear is roughly in the right neighbourhood even though the precise number still is not.

Claim ledger

Every number below is what each source reported, with the verbatim quote we relied on and how we arrived at our figure. Click any link to verify directly.

  1. [1] JAMA (Mez, Daneshvar, Kiernan, Abdolmohammadi, Alvarez, Huber, Alosco et al. 2017) — Clinicopathological Evaluation of Chronic Traumatic Encephalopathy in Players of American Football
    Clinicopathological Evaluation of Chronic Traumatic Encephalopathy in Players of American Football
    Statistic
    CTE was neuropathologically diagnosed in 177 of 202 (87%) deceased former football players donated to the VA-BU-CLF brain bank, including 110 of 111 former National Football League (NFL) players (99%), 48 of 53 college players (91%), and 3 of 14 high school players (21%)
    Excerpt
    “"CTE was neuropathologically diagnosed in 177 players (87%... 110 of 111 National Football League (99%) players." ”
    Source data from
    2017-07-25
    Accessed
    2026-04-11 · archived copy
    Calculation
    Mez et al. 2017 is the single most-cited data point on CTE in football players and is the source of the 99%-of-NFL-brains figure. It is NOT the source of the headline 1-in-5 normalized estimate, because the Mez sample is a brain bank convenience sample, not a population cohort. The paper’s authors explicitly warn that selection bias makes the 99% figure an upper bound on the true population rate among former NFL players. The regional_breakdown rows for subgroup level (NFL career, D1 college career, high school only) are order-of-magnitude estimates informed by, but not derived directly from, the Mez numerators — they also incorporate the dose-response multipliers from Nguyen et al. 2022 below.
    Independence
    All post-2013 CTE neuropathology in the United States flows through a small number of brain banks, with the VA-BU-CLF bank (Boston University CTE Center) the dominant source for former football players. Mez et al. and the follow-up selection-bias analysis (Nguyen et al. 2022) share that underlying cohort, so treat the two citations as one dataset with two different analytic frames rather than as independent measurements.
  2. [2] American Journal of Epidemiology (Nguyen, Alosco, Mez, Tripodis et al. 2022) — Relationship Between Level of American Football Playing and Diagnosis of Chronic Traumatic Encephalopathy in a Selection Bias Analysis
    Relationship Between Level of American Football Playing and Diagnosis of Chronic Traumatic Encephalopathy in a Selection Bias Analysis
    Statistic
    After adjustment for selection bias in the VA-BU-CLF brain bank cohort, college-level and professional football players had 2.38 (95% simulation interval: 1.16, 5.94) and 2.47 (95% simulation interval: 1.46, 4.79) times the risk of a CTE diagnosis, respectively, compared to high-school-level players
    Excerpt
    “"After adjustment for selection bias, college-level and professional football players had 2.38 (95% simulation interval (SI): 1.16, 5.94) and 2.47 (95% SI: 1.46, 4.79) times the risk of being diagnosed with CTE as high-school-level players, respectively; these estimates are larger than estimates with no selection bias adjustment." ”
    Source data from
    2022-04-19
    Accessed
    2026-04-11 · archived copy
    Calculation
    Nguyen et al. 2022 is the methodologically important follow-up to Mez 2017: it takes the same brain bank cohort and applies quantitative bias analysis to the selection process. The key finding for this entry is that the dose-response relationship between total football exposure and CTE diagnosis is stronger after adjusting for selection bias, not weaker — i.e. the data do not support the hypothesis that the Mez findings are entirely a selection artefact. A career college player has ~2.4× the CTE risk of a high-school-only player, and a career NFL player has ~2.5×. Those multipliers feed the regional_breakdown rows directly and are the basis for estimating that a career NFL player’s lifetime CTE probability sits in the low-tens-of-percent range even after the most aggressive reasonable adjustment for Boston University brain bank selection bias.
    Independence
    Uses the same VA-BU-CLF brain bank cohort as Mez et al. 2017. Not an independent measurement; included as the authoritative methodological correction to the raw Mez numbers and the source of the dose-response multipliers used in this entry.
  3. [3] Neurology (Stamm, Bourlas, Baugh, Fritts, Daneshvar, Martin, McClean, Tripodis, Stern 2015) — Age of First Exposure to Football and Later-Life Cognitive Impairment in Former NFL Players
    Age of First Exposure to Football and Later-Life Cognitive Impairment in Former NFL Players
    Statistic
    Former NFL players who began playing tackle football before age 12 performed significantly worse on measures of executive function, memory, and estimated verbal IQ than former NFL players who began playing at age 12 or later; the effect was independent of total years of play and age at testing
    Excerpt
    “"There is an association between participation in tackle football prior to age 12 and greater later-life cognitive impairment measured using objective neuropsychological tests." ”
    Source data from
    2015-01-28
    Accessed
    2026-04-11 · archived copy
    Calculation
    Stamm et al. 2015 is the source for the "youth football before age 12" factor in the personal_factor_multipliers block below. The paper does not directly produce a CTE incidence number; it shows that the age window during which repetitive head impacts are received matters independently of total exposure, which supports a non-linear dose-response structure rather than a simple hours-of-contact-play model. Subsequent work (notably Caccese et al. 2020 and follow-up work from the same BU group) has replicated the age-12 effect on some cognitive outcomes and failed to replicate it on others; it is well-established enough to cite as a multiplier but not strong enough to anchor a population probability.
    Independence
    Same VA-BU-CLF / DETECT research pipeline as Mez et al. 2017 and Nguyen et al. 2022. Partially dependent, used for the age-of-first-exposure multiplier rather than as an independent population measurement.
  4. [4] Boston University (Barlow 2017) — BU Researchers Find CTE in 99% of Former NFL Players Studied
    BU Researchers Find CTE in 99% of Former NFL Players Studied
    Statistic
    177 of 202 deceased football players donated to the VA-BU-CLF brain bank had CTE (87%); 110 of 111 former NFL players had CTE (99%). The researchers explicitly warned the numbers should not be interpreted as a population prevalence rate
    Excerpt
    “"The study has several important limitations, most notably the lack of a control group, and selection bias in the brain collection itself — families of players with symptoms of CTE are far more likely to donate brains to research than those without signs of the disease." ”
    Source data from
    2017-07-25
    Accessed
    2026-04-11 · archived copy
    Calculation
    The Boston University communications article accompanying the Mez 2017 JAMA paper is the source of the verbatim selection-bias caveat that anchors the caveats block below. It is included specifically because the methodological warning it contains — that the 99% figure reflects a self-selected donor population, not all former NFL players — is routinely dropped from secondary coverage of the Mez findings, and readers of this page need that context to understand why the normalized figure is 1 in 5 rather than the raw 99%.
    Independence
    Boston University is the institutional home of the CTE Center, the VA-BU-CLF brain bank, and the authors of Mez 2017, Nguyen 2022, and Stamm 2015. This page is a university communications piece covering its own researchers and shares the same upstream cohort as the other three citations. Included for the verbatim caveat wording rather than as an independent measurement.
  5. [5] Brain Pathology / Bieniek KF et al. (Mayo Clinic) — Association between contact sports participation and chronic traumatic encephalopathy: a retrospective cohort study
    Association between contact sports participation and chronic traumatic encephalopathy: a retrospective cohort study
    Statistic
    Among 300 contact sport athletes in the Mayo Clinic Tissue Registry, American football had the highest CTE frequency (15%) with OR 2.62 (P=0.005); zero of 450 non-athletes had CTE
    Excerpt
    “"For contact sports, American football had the highest frequency of chronic traumatic encephalopathy pathology (15% of cases) and an odds ratio of 2.62 (P-value = 0.005)." ”
    Source data from
    2020-01-01
    Accessed
    2026-04-12 · archived copy
    Calculation
    Mayo Clinic brain bank finding of 15% CTE in football players is substantially lower than the BU brain bank's 99% (Mez 2017), consistent with the selection bias caveat in the BU work (symptomatic families donate disproportionately). The 15% figure from a population-based autopsy registry is a more conservative anchor for the true prevalence.
    Independence
    Fully independent of the BU/VA-BU-CLF brain bank — different institution (Mayo Clinic), different tissue registry, different geographic catchment, population-based rather than self-referred.
  6. [6] Medical Journal of Australia / Suter CM, Affleck AJ, Lee M, Pearce AJ, Iles LE, Buckland ME — Chronic traumatic encephalopathy in Australia: the first three years of the Australian Sports Brain Bank
    Chronic traumatic encephalopathy in Australia: the first three years of the Australian Sports Brain Bank
    Statistic
    12 of 21 completed donations had pathognomonic CTE lesions; mean age at death 48 years for CTE donors vs 75 for non-CTE
    Excerpt
    “"The most frequent neuropathology was CTE: 12 donors had pathognomonic CTE lesions." ”
    Source data from
    2022-05-01
    Accessed
    2026-04-12 · archived copy
    Calculation
    Australian Sports Brain Bank confirms CTE is not limited to American football or the US. Found CTE in Australian Rules football, rugby league, and rugby union players, broadening the evidence base beyond the BU/VA-BU-CLF pipeline.
    Independence
    Fully independent of both BU and Mayo — different country, different sports, different brain bank, different research group.

412 risks with measured probability
1 in 10 1 in 100 1 in 1K 1 in 10K 1 in 100K 1 in 1M 1 in 10M 1 in 100M 1 in 1B certain rarer → Cosmetic surgery abroad risk — 1 in 10 Infant sugar/salt and adult disease — 1 in 10 Endometriosis — 1 in 10 Hair transplant Turkey risk — 1 in 10 Knee replacement — 1 in 10 Chronic painkillers — 1 in 10 Elderly abandonment — 1 in 9.1 Complete tooth loss — 1 in 9.1 Alzheimer's — 1 in 8.3 Sleep deprivation — 1 in 8.3 Smokeless tobacco — 1 in 8.3 Cycling w/o helmet — 1 in 8.0 Bruxism tooth damage — 1 in 7.7 Vision loss — 1 in 6.7 Hernia from lifting — 1 in 6.7 Hip fracture risk — 1 in 6.7 Regular drinking — 1 in 6.7 First heart attack — 1 in 5.9 Infertility — 1 in 5.7 5+ years paid LTC — 1 in 5.6 CTE (football) — 1 in 5.0 Major depression — 1 in 4.9 Hiking injury — 1 in 4.8 Infection from sharing food with child — 1 in 4.2 Lyme disease — 1 in 4.0 Loneliness & health — 1 in 3.8 Job loss & depression — 1 in 3.7 Inheriting AUD risk — 1 in 3.5 Alcohol use disorder — 1 in 3.4 Menopause CV risk acceleration — 1 in 3.0 Silent diabetes — 1 in 3.0 Flying with cold — 1 in 2.9 Tick illness (forest) — 1 in 2.9 Silent high cholesterol — 1 in 2.9 Grandparent loss in childhood — 1 in 2.8 Pacifier floor drop — 1 in 2.8 Drug-resistant infection — 1 in 2.6 No marrow match — 1 in 2.4 Nursing home admission — 1 in 2.2 Skipping dental checkups — 1 in 2.1 False-positive mammogram — 1 in 2.0 Regular smoking — 1 in 2.0 Travelers' diarrhea — 1 in 2.0 Adventure sports — 1 in 1.8 Family caregiver probability — 1 in 1.8 LTC need after 65 — 1 in 1.8 Widowhood probability — 1 in 1.7 Unprotected sex — 1 in 1.5 Silent hypertension — 1 in 1.3 Chronic back pain — 1 in 1.3 Hand hygiene — 1 in 1.0 Cancer (any) — 1 in 7.1 E-scooter no helmet — 1 in 4.5 E-bike no helmet — 1 in 4.0 Mishandled luggage — 1 in 3.7 Deer collision — 1 in 2.7 At-fault injury crash — 1 in 2.5 Flight cancellation — 1 in 1.8 Trip disruption: war or disaster — 1 in 1.7 Home burglary (global) — 1 in 9.1 Hitchhiking assault — 1 in 8.8 Mail check fraud — 1 in 7.7 Child sexual abuse — 1 in 6.8 Stalking — 1 in 6.2 Student sexual assault — 1 in 5.7 Domestic violence — 1 in 3.7 Night walk assault — 1 in 3.6 Bicycle theft — 1 in 2.9 Sexual assault — 1 in 2.9 Home burglary — 1 in 2.6 Sexual harassment (lifetime) — 1 in 1.6 Water scarcity — 1 in 2.5 Carrington-class solar storm — 1 in 1.9 WAIS tipping point — 1 in 1.1 Indoor cat escape harm — 1 in 10 Off-leash dog bite — 1 in 8.9 Rabbit dies in 4 years — 1 in 3.3 Dog bite (non-fatal) — 1 in 1.8 Hamster dies before teenager — 1 in 1.0 Vitamin D gap — 1 in 2.9 Undercooked food — 1 in 1.6 Raw meat cross-contamination — 1 in 1.4 Food left out — 1 in 1.2 AI voice scam — 1 in 2.9 Online scam loss — 1 in 2.5 Teen cyberbullying — 1 in 2.0 Kids & explicit content — 1 in 1.9 Data breach — 1 in 1.1 Miscarriage — 1 in 6.7 Teen suicide attempt — 1 in 5.6 Postpartum depression — 1 in 4.8 Painkiller before infant vaccination — 1 in 3.8 Excessive pregnancy weight — 1 in 2.6 Unvaxxed child & measles — 1 in 2.0 Elder fraud loss — 1 in 10 Pension fund collapse — 1 in 10 Personal bankruptcy — 1 in 10 Housing crash — 1 in 8.3 Crypto total loss — 1 in 6.7 IRS audit — 1 in 6.7 Visa overstay deportation — 1 in 5.6 Long term disability working age — 1 in 4.0 Student loan default — 1 in 3.8 Whistleblower retaliation — 1 in 3.2 Career obsolescence — 1 in 2.9 Forced job exit before retirement — 1 in 2.9 Retirement shortfall — 1 in 2.6 Divorce — 1 in 2.4 Burst pipe damage — 1 in 2.2 Workplace bullying — 1 in 2.1 Deportation (undocumented) — 1 in 1.8 Funeral cost shock — 1 in 1.8 Identity theft — 1 in 1.7 Credit card fraud — 1 in 1.5 School bullying — 1 in 1.5 Insurance claim denial — 1 in 1.4 Frontline soldier casualty — 1 in 1.3 Economic recession — 1 in 1.0 Stock market crash — 1 in 1.0 Hail roof damage — 1 in 3.0 Dry toilet paper harm — 1 in 100 Secondhand smoke — 1 in 91 Gaming disorder (adults) — 1 in 83 High-heel ER visit — 1 in 79 Child throwing object — 1 in 67 Medication reaction — 1 in 58 Cat litter toxoplasmosis — 1 in 48 Mental health LTD claim — 1 in 45 Drug overdose — 1 in 42 Benzo dependence — 1 in 40 Tap water lead — 1 in 40 Medication misuse — 1 in 35 Traumatic brain injury — 1 in 33 Hospital infection — 1 in 31 Air pollution — 1 in 29 End-stage kidney disease — 1 in 29 Traveler's diarrhea (water) — 1 in 26 Skiing injury — 1 in 26 Bipolar disorder — 1 in 23 Dental tourism complication — 1 in 20 Pet parasites — 1 in 20 Undiagnosed ADHD — 1 in 20 Adult-onset food allergy — 1 in 19 Indoor cooking smoke — 1 in 18 Non-Alzheimer's dementia — 1 in 17 Working-age disabling stroke — 1 in 17 Cannabis use disorder — 1 in 16 Stroke — 1 in 15 Parent death/disability — 1 in 14 Severe hearing loss — 1 in 14 Type 2 diabetes — 1 in 13 Appendicitis — 1 in 13 Untreated depression — 1 in 13 Untreated back pain disability — 1 in 13 Heart disease — 1 in 12 Medical error death — 1 in 12 Compulsive sexual behavior — 1 in 12 Eating disorder — 1 in 11 Hip replacement — 1 in 11 Kidney stones — 1 in 11 Sedentary lifestyle — 1 in 11 Salon infection — 1 in 11 Ovarian cancer — 1 in 91 Colorectal cancer — 1 in 77 Breast cancer — 1 in 59 Liver cancer — 1 in 59 Lung cancer — 1 in 56 Prostate cancer — 1 in 50 Melanoma (UV) — 1 in 29 Low-fiber CRC risk — 1 in 23 Red meat & CRC — 1 in 21 Charred meat & cancer — 1 in 20 Maintenance crash — 1 in 83 Driving on sedating meds — 1 in 77 Texting + driving — 1 in 56 Driving after cannabis — 1 in 53 Eating while driving — 1 in 53 Unbelted crash death — 1 in 53 Speeding 20% over limit — 1 in 48 Motorcycle no helmet — 1 in 45 Spaceflight (astronaut) — 1 in 42 Video watching + driving — 1 in 32 Drowsy driving — 1 in 26 E-scooter injury — 1 in 26 Cruise ship norovirus — 1 in 24 Driving at 0.10% BAC — 1 in 16 Catalytic converter theft — 1 in 83 Pickpocketed while traveling — 1 in 38 Stabbed in an assault — 1 in 37 Vehicle theft — 1 in 34 Street robbery / mugging — 1 in 26 Wrongful conviction — 1 in 24 Drink spiking — 1 in 17 Protest under autocracy — 1 in 12 AMOC collapse — 1 in 20 Sting anaphylaxis — 1 in 50 Cat collar injury — 1 in 25 Fish bone injury — 1 in 68 Restaurant food poisoning — 1 in 58 Vegetarian deficiency — 1 in 25 Intimate deepfake — 1 in 25 Social media problematic use — 1 in 13 Infant fall — 1 in 100 Childbirth death (SSA) — 1 in 55 Co-sleeping death — 1 in 43 Toddler stair fall — 1 in 37 Play swing & slide injury — 1 in 33 Autism diagnosis — 1 in 31 C-section complications — 1 in 29 Toy injury requiring ER (child) — 1 in 21 Preeclampsia — 1 in 20 Severe birth tearing — 1 in 17 Gestational diabetes — 1 in 13 Child fall head injury — 1 in 12 Sports betting financial ruin — 1 in 100 Fighter pilot death — 1 in 48 Commercial fishing career death — 1 in 45 Logging career death — 1 in 34 Dying without heir — 1 in 33 Medical bankruptcy — 1 in 25 Compulsive buying disorder — 1 in 20 Rental listing scam loss — 1 in 20 Mortgage foreclosure — 1 in 14 Musculoskeletal LTD claim — 1 in 14 Day-trading losses — 1 in 13 Extremist govt catastrophe — 1 in 13 Hurricane home destruction — 1 in 17 LASIK complications — 1 in 1,000 Infant pool submersion — 1 in 800 MS — 1 in 769 Workplace fatality — 1 in 690 Typhoid fever — 1 in 654 Unsafe imported products — 1 in 565 Brain aneurysm — 1 in 400 COVID-19 — 1 in 400 Fireworks injury — 1 in 385 Sickle cell disease — 1 in 365 Counterfeit medicine — 1 in 361 Spinal cord injury — 1 in 313 Childhood cancer diagnosis — 1 in 285 Next pandemic death — 1 in 208 Dengue (travel) — 1 in 200 Skipping daily showers — 1 in 200 Not scrubbing feet — 1 in 200 Marrow donation risk — 1 in 167 Schizophrenia — 1 in 143 Accidental fall — 1 in 135 Parkinson's — 1 in 125 Sudden death during exercise — 1 in 123 Suicide (US) — 1 in 121 Opioid addiction — 1 in 114 Tuberculosis (global) — 1 in 108 Radon cancer — 1 in 435 Testicular cancer — 1 in 250 Cervical cancer — 1 in 167 Pancreatic cancer — 1 in 125 Pedestrian death — 1 in 806 Motorcycle crash — 1 in 694 Boating drowning — 1 in 685 Driver kills pedestrian — 1 in 552 Phone-distracted walking injury — 1 in 400 EV battery fire — 1 in 333 Cyclist killed by car — 1 in 196 Hand-held phone call + driving — 1 in 143 Petrol car fire — 1 in 125 Self-driving car fatality — 1 in 115 Car crash — 1 in 105 Firefighter duty death — 1 in 455 Police duty death — 1 in 313 Homicide — 1 in 287 Pig-butchering scam — 1 in 106 Extreme heat — 1 in 333 Climate change death — 1 in 204 Swallowed bee/wasp — 1 in 500 Bat bite & rabies — 1 in 238 Mosquito-borne disease — 1 in 190 Food poisoning (global) — 1 in 317 Solar panel fire — 1 in 667 Untreated childhood scoliosis — 1 in 1,000 Child window fall — 1 in 855 Walker stair fall — 1 in 625 Baby walker injury — 1 in 455 Maternal mortality — 1 in 272 Untreated childhood flat feet — 1 in 250 Maternal age & birth defects — 1 in 200 Child death (<18) — 1 in 143 Caving career death — 1 in 167 EMS duty death — 1 in 794 Civilian war casualty — 1 in 499 Soldier in combat — 1 in 270 Mining career death — 1 in 214 Gambling financial ruin — 1 in 159 Wildfire home destruction — 1 in 120 Lightning home fire — 1 in 105 Malaria (travel) — 1 in 10,000 Infection from shared drink — 1 in 10,000 Chagas disease — 1 in 8,475 Wild berry fox tapeworm — 1 in 8,475 Schistosomiasis death — 1 in 6,667 Sudden death (young adult) — 1 in 3,922 Unsafe wiring — 1 in 3,390 Sepsis from wound — 1 in 2,857 Anesthesia awareness — 1 in 2,500 Heat stroke (outdoor) — 1 in 1,905 House fire — 1 in 1,818 Rabies from dogs — 1 in 1,449 Drowning — 1 in 1,379 Shallow-water diving SCI — 1 in 1,111 Choking — 1 in 1,099 EVALI vaping hospitalization — 1 in 1,064 Betel nut cancer — 1 in 1,290 Blood clot (flight) — 1 in 4,651 Killing a cyclist — 1 in 3,937 Teen road-crash death — 1 in 3,030 Child rear bike seat — 1 in 2,500 Child without restraint — 1 in 2,000 Fatal police encounter — 1 in 4,739 Honor killing — 1 in 2,381 Intimate-partner homicide — 1 in 1,767 Hurricane — 1 in 8,929 Drought famine death — 1 in 6,536 Blizzard death — 1 in 4,367 Earthquake — 1 in 3,802 Dog chocolate death — 1 in 2,000 Food poisoning (US) — 1 in 1,862 Fish mercury — 1 in 1,695 Phone/laptop battery fire — 1 in 1,136 SIDS — 1 in 7,143 Laundry pod ingestion — 1 in 6,494 Untreated infant hip dysplasia — 1 in 5,000 Pool drowning — 1 in 2,299 War (civilian) — 1 in 2,000 Fatal bee/wasp sting — 1 in 76,923 Anesthesia death — 1 in 50,000 Dog hot car death — 1 in 41,667 Anaphylaxis — 1 in 27,548 Chiropractic neck manipulation — 1 in 16,667 CO poisoning — 1 in 14,006 Hepatitis A (travel) — 1 in 12,500 Skipping allergy immunotherapy — 1 in 11,111 Acrylamide & cancer — 1 in 16,667 Bus crash — 1 in 100,000 Plane crash — 1 in 58,824 Child pedestrian (residential) — 1 in 45,455 Railroad crossing death — 1 in 20,704 Child bike trailer — 1 in 14,286 Acid attack — 1 in 89,286 Terrorism — 1 in 77,519 Child stranger abduction — 1 in 38,760 Stranger kidnapping — 1 in 35,211 Dowry death — 1 in 13,158 Accidental gun death — 1 in 11,299 Wildfire — 1 in 100,000 Tornado — 1 in 80,645 Tsunami — 1 in 52,632 Ocean drowning — 1 in 29,155 Flood — 1 in 20,202 Landslide death — 1 in 18,416 Supervolcano eruption — 1 in 12,376 Crocodile attack — 1 in 84,746 Bee sting — 1 in 78,927 Fatal scorpion sting — 1 in 26,110 Plastic container leaching — 1 in 16,949 Infant in car seat — 1 in 64,935 Bouncer chair fall — 1 in 60,606 Toddler choking — 1 in 50,000 Unsupervised infant choking — 1 in 50,000 Magnet ingestion — 1 in 12,048 Snorkeling death — 1 in 21,739 Pet in transport — 1 in 20,000 Landmine or UXO injury — 1 in 14,728 Vaccine reaction — 1 in 763,359 Aluminum & Alzheimer's — 1 in 169,492 Residential gas leak — 1 in 140,845 Child hot car death — 1 in 102,041 Glyphosate & cancer — 1 in 1,000,000 Teflon cookware cancer — 1 in 169,492 Roller coaster injury — 1 in 312,500 Cruise ship accident — 1 in 188,679 Ferry sinking — 1 in 133,333 Turbulence injury — 1 in 114,943 School shooting — 1 in 192,308 Mass shooting — 1 in 113,636 Nuclear accident — 1 in 833,333 Avalanche — 1 in 210,526 Lightning — 1 in 209,205 Snake bite — 1 in 884,956 Spider bite — 1 in 833,333 Hippo attack — 1 in 564,972 Dog bite — 1 in 142,045 Pesticide residue — 1 in 1,000,000 Dirty can illness — 1 in 200,000 PLA bioplastic harm — 1 in 169,492 Charger left plugged in — 1 in 200,000 Infant swing death — 1 in 714,286 Child blind cord strangulation — 1 in 416,667 Child plastic bag suffocation — 1 in 263,158 Button battery — 1 in 250,000 Inclined sleeper death — 1 in 238,095 Elevator/escalator death — 1 in 188,324 Japanese encephalitis (travel) — 1 in 2,000,000 Kid + front airbag — 1 in 10,000,000 Asteroid impact — 1 in 1,351,351 Banana spider eggs — 1 in 10,000,000 Shark attack — 1 in 5,681,818 Bear attack — 1 in 3,787,879 Wild berry poisoning — 1 in 2,222,222 Space debris hits property — 1 in 10,000,000 Piranha attack — 1 in 135,135,135 Phone at gas pump — 1 in 1,000,000,000 Phone on plane — 1 in 1,000,000,000 Alien contact — 1 in 169,491,525
Lottery jackpot 1 in 95,238