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Perceived fear vs. actual probability

What are the odds of sudden permanent vision loss (NAION) from taking semaglutide (Ozempic/Wegovy)?

Lifetime probability · subgroup

~1 in 900

over a 5-year course (total on-drug); excess attributable ~1 in 1,400

0.1% lifetime chance

Scopes vary — shown as typical adult lifetime odds. See methodology.

Health · reviewed 2026-06-12

What are the odds of sudden permanent vision loss (NAION) from taking semaglutide (Ozempic/Wegovy)?

Evidence quality 4.75/5

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
5/5
D5 Scope
5/5
D6 Prose
5/5
D7 Perception honesty
4/5
D8 Caveat completeness
5/5
Average 4.75/5
Direct evidence
Source Government statistic · European Medicines Agency (Pharmacovigilance Risk Assessment Committee)
lifetime, subgroup each band = 10× rarer → See full scale →
certain 1 in 1K 1 in 1M 1 in 1B
A single abstract eye shape with one half dimmed to grey, rendered in muted teal and pale sand tones, flat vector illustration.

Perceived

NAION entered public awareness abruptly in mid-2024, when a Harvard referral-clinic study tied semaglutide to a several-fold higher rate of sudden one-eye vision loss, and again in June 2025 when the European Medicines Agency formally added it to the label as a "very rare" side effect. Most people taking these drugs have never heard the term, and the coverage that did reach them swung between "blindness warning" headlines and reassurance that the absolute risk is tiny. The result is a fear that is either absent or wildly miscalibrated, rarely sitting at the actual order of magnitude.

Rough estimate: Perception ranges from unaware to headline-driven 'blindness' alarm; no published survey of NAION awareness or perceived likelihood exists

Source: editorial intuition, not polled

Actual

~1 in 10,000 semaglutide users (EMA 'very rare' frequency band)

adults taking semaglutide (Ozempic/Wegovy/Rybelsus)

Show derivation

Scope is the subgroup of adults taking semaglutide; "lifetime" here is the treatment-course duration, NOT the site-default 59-year adult horizon. EMA's headline "very rare / up to 1 in 10,000" is the EU SmPC frequency-category band (a label tier), not a measured cumulative incidence, so we do not normalize on it. We normalize on the population-based per-person-year rate that EMA and the Simonsen 2025 Danish-Norwegian cohort independently agree on. Simonsen reports an excess of +1.41 NAION events per 10,000 person-years (incidence-rate difference) and a pooled hazard ratio of 2.81; EMA gives "approximately one additional case per 10,000 person-years." Implied diabetic baseline = IRD / (HR - 1) = 1.41 / 1.81 ≈ 0.78 per 10,000 PY; total on-drug rate = baseline × HR ≈ 0.78 × 2.81 ≈ 2.2 per 10,000 PY. Over a central 5-year course: 2.2 × 5 / 10,000 ≈ 1.1e-3 ≈ 1 in 900 (total). The drug-attributable EXCESS over the same course is 1.41 × 5 / 10,000 ≈ 7e-4 ≈ 1 in 1,400. The headline 0.0011 is TOTAL on-drug risk; the excess is reported in caveats. The cumulative figure exceeds the "1 in 10,000" label band precisely because that band is a per-exposure frequency tier while this is cumulative across a multi-year course. The Hathaway 2024 hazard ratios (4.28 in diabetics, 7.64 in overweight patients) are from a neuro-ophthalmology referral cohort and are used only for the association signal, not for absolute risk.

Caveats: The headline 1-in-900 is the TOTAL risk of NAION over a ~5-year course for a dia…

The headline 1-in-900 is the TOTAL risk of NAION over a ~5-year course for a diabetic semaglutide user, reconciled from the population-based Danish-Norwegian rate (Simonsen 2025: +1.41 excess events per 10,000 person-years, pooled HR 2.81) and the EMA's matching "~1 additional case per 10,000 person-years." The drug-attributable EXCESS over the same course is lower, roughly 1 in 1,400. EMA's "very rare / up to 1 in 10,000" is a regulatory frequency-category band, not a cumulative incidence, and is reported as the native figure for recognizability only. The Hathaway 2024 hazard ratios (4.28 in diabetics, 7.64 in overweight patients) come from a neuro-ophthalmology referral clinic and overstate the population effect through selection; they are cited for the association, not the absolute rate. NAION is usually permanent and irreversible, typically affects one eye, and the second eye carries elevated but not certain subsequent risk. The risk is conditional on remaining on the drug — it accrues per year of treatment and does not apply to people not taking semaglutide. General-population background NAION incidence is far lower (2.3-10.2 per 100,000/year in adults over 50). Whether the association is causal remains debated; the regulatory and cohort evidence is consistent but observational, not randomized.

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Compare to:

A diabetic adult taking semaglutide faces roughly a 1-in-900 chance of non-arteritic anterior ischemic optic neuropathy — sudden, usually permanent loss of vision in one eye — over a five-year course of treatment. That figure is reconciled from two sources that arrived at the same place by different routes: a Danish-Norwegian registry of 61,377 users found an excess of 1.41 NAION cases per 10,000 person-years (pooled hazard ratio 2.81), and the European Medicines Agency, reviewing the same body of evidence in June 2025, put it at “approximately one additional case per 10,000 person-years” and a roughly two-fold increase in risk. The drug-attributable share of that 1-in-900 is smaller — about 1 in 1,400 over the same period — because diabetics carry some baseline NAION risk with or without the drug.

The number most people have actually heard is the EMA’s “very rare, up to 1 in 10,000.” That is a regulatory frequency band, not a measured cumulative risk, and it appears here only because it is the figure on the label. Over a multi-year course the cumulative total runs higher than the per-exposure band suggests, which is the ordinary arithmetic of a small annual rate compounded across years on a chronic medication. The discovery study, a 2024 Harvard analysis out of Massachusetts Eye and Ear, reported far larger hazard ratios — 4.28 in diabetics, 7.64 in overweight patients — but those came from a neuro-ophthalmology referral clinic, where patients with eye problems are precisely who shows up. They are good evidence that an association exists and poor evidence of how large the absolute risk is.

The risk is conditional on being on the drug, and it accrues per year of exposure rather than landing in a single moment, which is why this entry is scoped to semaglutide users rather than the general adult population. Background NAION is genuinely rare — 2.3 to 10.2 cases per 100,000 people per year in adults over 50, and well under that across all ages. Diabetes and sleep apnea already raise that baseline before any drug enters the picture. Whether semaglutide causes NAION or merely travels with it remains observationally unsettled: the registry and regulatory evidence point the same direction and the effect is consistent, but none of it is a randomized trial. What can be said cleanly is the order of magnitude — a rare event made a few times less rare, over years, in a population already predisposed.

Across a 5-year course of semaglutide, the total risk of the rare optic-nerve condition NAION is about ~1 in 900, of which roughly 1 in 1,400 is excess attributable to the drug. The EMA classes it in the "very rare" band, well below the alarm in some headlines.

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] European Medicines Agency (Pharmacovigilance Risk Assessment Committee) — PRAC concludes eye condition NAION is a very rare side effect of semaglutide medicines Ozempic, Rybelsus and Wegovy
    PRAC concludes eye condition NAION is a very rare side effect of semaglutide medicines Ozempic, Rybelsus and Wegovy
    Statistic
    NAION classified a 'very rare' side effect of semaglutide (may affect up to 1 in 10,000 people taking it); ~2-fold increased risk in type 2 diabetes; ~1 additional case per 10,000 person-years of treatment
    Excerpt
    “"NAION is a very rare side effect of semaglutide (meaning it may affect up to 1 in 10,000 people taking semaglutide). [...] Exposure to semaglutide in adults with type 2 diabetes is associated with an approximately two-fold increase in the risk of developing NAION compared with people not taking the medicine. This corresponds to approximately one additional case of NAION per 10,000 person-years of treatment; one person-year corresponds to one person taking semaglutide for one year." ”
    Source data from
    2025-06-06
    Accessed
    2026-06-12
    Calculation
    EMA's "very rare / 1 in 10,000" is the EU SmPC frequency-category band (a regulatory label tier), not a measured cumulative incidence. The robust quantitative anchor is the per-person-year rate (~1 additional case per 10,000 PY), which matches the Simonsen IRD. The "~2-fold" matches Simonsen's pooled HR 2.81 in order of magnitude.
  2. [2] Diabetes, Obesity and Metabolism (Wiley); Simonsen et al. — Use of semaglutide and risk of non-arteritic anterior ischemic optic neuropathy: A Danish-Norwegian cohort study
    Use of semaglutide and risk of non-arteritic anterior ischemic optic neuropathy: A Danish-Norwegian cohort study
    Statistic
    Pooled HR 2.81 (95% CI 1.67-4.75); incidence-rate difference +1.41 (95% CI +0.53 to +2.29) per 10,000 person-years; 61,377 semaglutide users, 32 NAION events
    Excerpt
    “"the pooled hazard ratio (HR) was 2.81 (95% confidence interval [CI] 1.67-4.75) [...] the incidence rate difference (IRD) was +1.41 (95% CI +0.53 to +2.29) per 10 000 person-years [...] the use of semaglutide for managing type 2 diabetes is associated with an increased risk of NAION compared with the use of SGLT-2is. However, the absolute risk remains low." ”
    Source data from
    2025-03-17
    Accessed
    2026-06-12
    Calculation
    Active-comparator new-user design (semaglutide vs SGLT-2 inhibitors) on Danish + Norwegian national registries — population-based, so usable for absolute risk. IRD +1.41/10,000 PY is the drug-attributable excess. Combined with HR 2.81, implied diabetic baseline ≈ IRD/(HR-1) = 1.41/1.81 ≈ 0.78 per 10,000 PY; implied total on-drug ≈ 0.78 × 2.81 ≈ 2.2 per 10,000 PY. This is the population anchor for the normalized model. Published Wiley/PubMed version cited, not the medRxiv preprint.
    Independence
    Independent of EMA's review population (different national registries, different analytic team), though EMA's pharmacovigilance conclusion drew on the same broad body of cohort evidence. Treat Simonsen as the primary quantitative cohort and EMA as the regulatory synthesis.
  3. [3] JAMA Ophthalmology 2024;142(8):732-739; Hathaway JT et al., Massachusetts Eye and Ear / Harvard Medical School — Risk of Nonarteritic Anterior Ischemic Optic Neuropathy in Patients Prescribed Semaglutide
    Risk of Nonarteritic Anterior Ischemic Optic Neuropathy in Patients Prescribed Semaglutide
    Statistic
    Diabetes cohort HR 4.28 (95% CI 1.62-11.29), 17 vs 6 NAION events; overweight/obese cohort HR 7.64 (95% CI 2.21-26.36), 20 vs 3 events
    Excerpt
    “"hazard ratio [HR], 4.28; 95% CI, 1.62-11.29 [...] HR, 7.64; 95% CI, 2.21-26.36 [...] 20 NAION events occurred in the prescribed semaglutide cohort vs 3 in the non-GLP-1 RA cohort." ”
    Source data from
    2024-08-01
    Accessed
    2026-06-12
    Calculation
    Neuro-ophthalmology referral-clinic cohort (710 diabetic + 979 overweight patients) — the discovery study that first flagged the association. Its absolute event rates are inflated by referral selection and are NOT usable as a base rate; used only for the relative/association signal and as the discovery citation. The larger relative effect vs Simonsen's 2.81 reflects this selection.
  4. [4] American Academy of Ophthalmology (EyeNet) — Semaglutide, Weight-Loss Drugs, and Vision Loss (NAION): Current Thinking
    Semaglutide, Weight-Loss Drugs, and Vision Loss (NAION): Current Thinking
    Statistic
    Background NAION incidence 2.3-10.2 per 100,000/yr in adults over 50, 0.54 per 100,000/yr across all ages; type 2 diabetes is a risk factor
    Excerpt
    “"The condition is rare, with the estimated annual incidence of NAION ranging from 2.3 to 10.2 per 100,000 people in adults over the age of 50, and 0.54 per 100,000 people in all age groups. [...] NAION is more common in individuals with certain health issues, such as type 2 diabetes and sleep apnea." ”
    Source data from
    2025-10-01
    Accessed
    2026-06-12
    Calculation
    Supplies the general-population baseline for comparison and a sanity check. The diabetic on-drug rate implied by Simonsen (~2.2 per 10,000 PY = ~22 per 100,000/yr) sits above the general-population over-50 ceiling of 10.2 per 100,000/yr — consistent, since diabetics plus a drug effect should exceed the all-comer over-50 rate.

443 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 Skipping care over ICE fear — 1 in 7.1 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 Anxiety disorder — 1 in 3.2 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 Child head lice — 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 Currency collapse — 1 in 5.6 Visa overstay deportation — 1 in 5.6 Subprime auto-loan repossession — 1 in 5.0 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 BNPL missed payment — 1 in 2.4 Divorce — 1 in 2.4 Burst pipe damage — 1 in 2.2 Workplace bullying — 1 in 2.1 Prolonged grid blackout — 1 in 2.0 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 Drug overdose — 1 in 56 Gas-stove asthma in a child — 1 in 50 Cat litter toxoplasmosis — 1 in 48 Mental health LTD claim — 1 in 45 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 PTSD — 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 Keyless relay car theft — 1 in 13 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 Child swallows object (ER) — 1 in 91 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 Losing SNAP under 2025 work rules — 1 in 18 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 NAION (Ozempic) — 1 in 909 Infant pool submersion — 1 in 800 MS — 1 in 769 Workplace fatality — 1 in 690 Typhoid fever — 1 in 654 GLP-1 anesthesia aspiration — 1 in 613 Unsafe imported products — 1 in 565 Brain aneurysm — 1 in 400 COVID-19 — 1 in 400 Fireworks injury — 1 in 385 Too much caffeine — 1 in 366 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 Heat-triggered preterm birth — 1 in 200 Skipping daily showers — 1 in 200 Not scrubbing feet — 1 in 200 Marrow donation risk — 1 in 167 Tick-borne encephalitis — 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 109 HIV diagnosis — 1 in 105 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 709 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 Homicide — 1 in 339 Police duty death — 1 in 313 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 Student visa revocation — 1 in 263 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 Child nicotine-pouch ingestion — 1 in 7,937 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 Listeria from deli meat — 1 in 6,061 Serious E. coli from fresh produce — 1 in 4,831 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 Flu brain swelling in a child (IAE/ANE) — 1 in 100,000 Fatal bee/wasp sting — 1 in 76,923 Locally-acquired dengue (continental US) — 1 in 66,667 Anesthesia death — 1 in 50,000 Dog hot car death — 1 in 41,667 Vibrio vulnificus wound infection — 1 in 32,051 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 Post-crash car fire — 1 in 25,000 Railroad crossing death — 1 in 20,704 Car submersion — 1 in 16,667 Child bike trailer — 1 in 14,286 Runway near-miss — 1 in 13,699 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 Post-hurricane heat death — 1 in 20,000 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 Lead-tainted cinnamon pouch — 1 in 40,000 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 Death in ICE custody — 1 in 17,065 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

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