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Likelier
Health · reviewed 2026-05-28

What are the odds of an emergency-room visit from a high-heel-related injury over a lifetime of wearing heels?

Evidence quality 4.88/5

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
5/5
D4 Uncertainty
4/5
D5 Scope
5/5
D6 Prose
5/5
D7 Perception honesty
5/5
D8 Caveat completeness
5/5
Average 4.88/5
Direct evidence

Lifetime probability · lifetime, subgroup

1 in 79

1.3% lifetime chance

Most people underestimate this.

range 1 in 167 to 1 in 50

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 20 1 in 262

● your factors — click this risk ▾ to reveal

≈ As likely as

A single high-heeled shoe lying on its side on a flat stone step, viewed from a low angle, calm muted palette.

Perceived

The folk model of high-heel risk is chronic and cosmetic: bunions, Morton's neuroma, a sore lower back, eventually maybe a podiatrist. Acute, hospital-visit-grade injury on a single night out is not typically what most heel wearers consciously weigh. Women who wear heels regularly have almost all rolled an ankle or scraped a heel at some point and counted it as a near-miss. There is no good survey isolating the perceived probability of an ER visit specifically attributable to heels, so we mark this as editorial intuition. The interesting property of the fear is that the acute rate is roughly what the chronic-foot-pain rate would predict if you assumed a small fraction of bad steps reached an ER — but very few wearers carry that as the headline risk in their head.

Rough estimate: Most heel wearers would guess the lifetime ER-visit risk at well under 1 in 1,000

Source: editorial intuition, not polled

Actual

~16,000 ED visits/year among ~50 million US women who regularly wear heels (~1 in 3,100/year)

US adult women who regularly wear high-heeled shoes

Avg. lifetime encounters:  ~59 (1/yr × 59 yr)

Show derivation

Scope is subgroup_lifetime: US adult women who regularly wear high-heeled shoes across an approximate 40-year heel-wearing window (roughly ages 18 to 58). Starting from a per-year baseline of approximately 16,000 ED visits attributed to high-heel- related injury (Cohen 2022, pre-pandemic 2016 to 2019 average for women aged 15 to 69) and a US heel-wearer base of approximately 50 million (about 130 million US adult women times the APMA 2014 estimate that roughly 49 percent wear heels, rounded down to account for "wear" not being operationalised by frequency), the per-wearer annual risk is roughly 1 in 3,125. Compounded across 40 years: 1 minus (1 minus 1/3125) to the 40th power equals approximately 0.0127, or about 1 in 79. The uncertainty band is wide on both sides because (a) the wearer-prevalence number is a single trade- association survey with no frequency cut, and (b) the NEISS narrative filter is a known undercount — many sprains caused by heels never mention heels in the chart note. The headline is therefore better read as a lower bound on "heel-attributable acute injury serious enough to be medically attended" rather than the full burden.

Caveats: Three structural uncertainties make this entry's number a lower bound. First, th…

Three structural uncertainties make this entry's number a lower bound. First, the NEISS narrative filter that produces the 16,000 per year figure captures only ED visits where the discharge or triage narrative explicitly names "high heel" or a close synonym — sprains caused by heels but coded only as "fall" or "ankle injury" are missed. Second, the wearer base of approximately 50 million is anchored on a single 2014 APMA survey that does not distinguish daily wearers from women who own a pair worn twice a year; the true denominator for the "at-risk" population could be half this size, in which case the per-wearer rate (and the cumulative lifetime figure) is roughly double. Third, "high heel" is itself a broad category — stiletto versus block heel versus 2-inch pump have meaningfully different fall and sprain rates, but no national surveillance system separates them. The headline is best read as "any acute injury attributed to a high-heeled shoe and serious enough to be medically attended" rather than the full burden of heel-related musculoskeletal harm, which includes chronic foot pain, Morton's neuroma, and bunion surgery that this page does not cover. The cumulative figure also excludes the much larger number of falls that happen in heels but are reported simply as falls. The fear's gap is in the other direction from many entries on this site: the acute headline (~1 in 80 lifetime ED visit) is *higher* than most heel wearers would intuit, while the catastrophic-outcome version of the fear (heel fall causing serious head injury or death) is genuinely rare.

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
Per year (US heel-wearing woman, 2016 to 2019 baseline) 1 in 3,125 Cohen 2022 pre-pandemic figure: ~16,000 ED visits / ~50M heel-wearers. Roughly 1 in 3,100 per year. Drops to about 1 in 8,000 per year in 2020 under pandemic conditions.
Per year, ages 20 to 29 (US heel-wearing woman) 1 in 1,250 Moore 2015 reports 18.38 per 100,000 women in this age band, roughly 2.5x the all-female average. Heel use is concentrated in this group and the rate scales accordingly.
Per year, ages 50+ (US heel-wearing woman) 1 in 10,000 Order-of-magnitude estimate. Moore 2015 shows steep age decline after 40; heel use drops sharply and so does the absolute rate. Population at risk is much smaller, so per-wearer risk does not fall by the same factor.
Per 40-year heel-wearing career (cumulative) 1 in 79 Headline subgroup_lifetime figure: about 1 in 80 women who wear heels regularly across their adult life will visit an ED with a heel-attributed injury at least once.

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Compare to:

The useful number is the one per heel-wearing year, not the headline lifetime figure. A US woman who regularly wears heels has roughly a 1 in 3,100 chance per year of an ED visit attributed to her shoes — about 16,000 such visits a year across the roughly 50 million US heel wearers, per the Cohen (2022) extension of the Moore (2015) NEISS series. Compounded across a 40-year heel-wearing adult life, that becomes about 1 in 80. The peak age band is 20 to 29 at roughly 2.5 times the average rate, where heel height, frequency of wear, and the at-risk contexts (clubs, weddings, unfamiliar venues) all stack. Most of the injuries are sprains and strains to the foot and ankle, with about one in five being fractures.

What is interesting about this fear is the direction of the perceived-versus-actual gap. The chronic, cosmetic harms of heels — bunions, back pain, podiatry visits — are the version most wearers carry in their head, and they are well-understood. The acute, hospital-visit-grade harm is less salient: most women have rolled an ankle in heels at some point and counted it as a near-miss rather than the upper tail of the same distribution that produces 16,000 ED visits a year. The Moore series also documented that the rate roughly doubled between 2002 and 2012, in a period when neither US adult female population nor the share of women wearing heels obviously doubled — most likely a mix of higher heels coming back into fashion and more attentive coding at sentinel NEISS hospitals.

The headline figure is meaningfully heterogeneous. A daily heel wearer in a workplace dress code accumulates roughly five times the exposure of an occasional wearer, and per-year rate scales with exposure approximately linearly. Alcohol substantially elevates per-event risk: the NEISS narrative often flags evening events even though the surveillance system does not code intoxication directly. After about age 50, both the share of women wearing heels and the absolute ED visit rate drop steeply, though the case-fatality of a fall from a heel rises with age in line with the broader geriatric-fall literature. And the number itself is best read as a lower bound: NEISS captures only injuries whose discharge note names the shoe, and a meaningful share of heel-attributable sprains and falls reach the ED coded only as “fall” or “ankle injury.”

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] Journal of Foot and Ankle Surgery (Moore JX, Lambert B, Jenkins GP, McGwin G Jr) — Epidemiology of High-Heel Shoe Injuries in U.S. Women: 2002 to 2012
    Epidemiology of High-Heel Shoe Injuries in U.S. Women: 2002 to 2012
    Statistic
    123,355 estimated ED visits over 11 years (2002 to 2012); overall rate 7.32 per 100,000 females (95% CI 7.08 to 7.56); rate roughly doubled across the period; ages 20 to 29 highest at 18.38 per 100,000, ages 30 to 39 at 11.07 per 100,000; over 80 percent foot or ankle injuries; ~19 percent fractures; 49.5 percent of injuries occurred at home
    Excerpt
    “"A total of 3294 injuries, representing an estimated 123,355 high-heel-related injuries, were treated in emergency departments within the United States from 2002 to 2012." [Paraphrase from abstract — full text paywalled] "The overall rate of high-heel-related injuries was 7.32 per 100,000 females (95% confidence interval 7.08 to 7.56)." "Our results suggest that high-heel-related injuries have nearly doubled during the 11-year period from 2002 to 2012." "Most injuries occurring as sprains and strains to the foot and ankle." ”
    Source data from
    2015-07-01
    Accessed
    2026-05-28 · archived copy
    Calculation
    Moore et al. is the foundational US epidemiology of acute high-heel injury, built on a NEISS narrative search across 100 US sentinel emergency departments 2002 to 2012. Two figures anchor this page: the long-run all-female rate of 7.32 per 100,000 (used as the floor of the per-year-per-woman range, not the per- wearer rate), and the age-banding (ages 20 to 29 at 2.5 times the average rate), which drives the personal factor multipliers below. The paper's 123,355 / 11 = ~11,200 ED visits per year average is *lower* than Cohen 2022's 2016 to 2019 figure (~16,000) because the rate was rising across the Moore window — the headline calculation uses Cohen's more recent baseline, with Moore's older figure setting the low end of the uncertainty band.
    Independence
    Both Moore 2015 and Cohen 2022 use the same NEISS national surveillance system, so they are method-correlated, not fully independent measurements. The two are cited together because they cover non-overlapping time windows (2002 to 2012 vs 2016 to 2020) and Cohen explicitly extends Moore's series.
  2. [2] Social Determinants of Health (Cohen PN, University of Maryland) — Pandemic-related decline in injuries related to women wearing high-heeled shoes: Analysis of U.S. data for 2016 to 2020
    Pandemic-related decline in injuries related to women wearing high-heeled shoes: Analysis of U.S. data for 2016 to 2020
    Statistic
    2016 to 2019 baseline approximately 16,000 ED visits per year among US women aged 15 to 69; 2020 dropped to 6,290 visits (5.40 per 100,000, 95% CI 3.95 to 6.86) after COVID shutdowns; no significant change in fracture share or hospital-admission share
    Excerpt
    “"There were an estimated 6,290 high-heel related emergency department visits involving women ages 15 to 69 in 2020, compared with approximately 16,000 per year in 2016 to 2019." "The 2020 rate of 5.40 HHSRIs per 100,000 women ages 15 to 69 was significantly below the peak in 2017." ”
    Source data from
    2022-01-01
    Accessed
    2026-05-28 · archived copy
    Calculation
    Cohen 2022 provides the most current pre-pandemic baseline (~16,000 ED visits per year), which we use as the numerator for the headline calculation. The 2020 pandemic figure (6,290) is informative but suppressed by behaviour change — most women were not commuting in heels in 2020 and we treat that year as not representative of a steady-state denominator. Using 16,000 / 50 million heel- wearing women equals roughly 1 in 3,125 per year, which compounds over 40 years to approximately 1 in 79. If the pre-pandemic 16,000 is replaced by Moore's older 11,000 (still inside the same NEISS series), the per-year rate becomes 1 in 4,545 and the 40-year cumulative is approximately 1 in 113 — this is the low end of our uncertainty band.
    Independence
    Shares the NEISS surveillance backbone with Moore 2015. Treat as a temporal extension and methodological cross-check, not an independent measurement.
  3. [3] American Podiatric Medical Association (APMA), via PR Newswire — New Study Shows High Heels are Biggest Culprit of Female Foot Pain
    New Study Shows High Heels are Biggest Culprit of Female Foot Pain
    Statistic
    Nearly half of US adult women (49 percent) wear high heels; 71 percent of heel wearers report the shoes hurt their feet; survey of 1,000 US adults aged 18 and over (2014)
    Excerpt
    “"Nearly half of all women (49 percent) wear high heels, even though the majority of heel wearers (71 percent) complain these shoes hurt their feet." "The study, which surveyed 1,000 US adults ages 18 and older..." ”
    Source data from
    2014-05-19
    Accessed
    2026-05-28 · archived copy
    Calculation
    The APMA survey is the denominator anchor for the per-wearer calculation: approximately 130 million US adult women times 49 percent equals roughly 64 million heel wearers. We round down to 50 million in the headline because "wear high heels" in APMA's survey is not operationalised by frequency — a respondent who owns heels and wears them twice a year answers yes, and they are not really the population the per-year ED-visit denominator should be built from. The 30 to 50 percent prevalence range maps directly into the uncertainty band: at 30 percent prevalence the per-wearer annual rate would be roughly 1 in 2,400, giving a 40-year cumulative of approximately 1 in 60 (high end of the band).
    Independence
    Independent of NEISS — different research design, different question, different population. Trade-association survey is the weakest of the three sources on method, but no peer-reviewed prevalence study with a frequency cut exists.
  4. [4] Sports Medicine (Doherty C, Delahunt E, Caulfield B, Hertel J, Ryan J, Bleakley C) — The Incidence and Prevalence of Ankle Sprain Injury: A Systematic Review and Meta-Analysis of Prospective Epidemiological Studies
    The Incidence and Prevalence of Ankle Sprain Injury: A Systematic Review and Meta-Analysis of Prospective Epidemiological Studies
    Statistic
    Pooled ankle sprain incidence 13.6 per 1,000 exposures in females vs 6.94 per 1,000 in males across prospective studies; ankle sprain is one of the most common musculoskeletal injuries
    Excerpt
    “"A higher incidence of ankle sprain in females compared with males (13.6 vs 6.94 per 1,000 exposures), in children compared with adolescents (2.85 vs 1.94 per 1,000 exposures)." [Paraphrase from abstract — full text paywalled] ”
    Source data from
    2014-01-01
    Accessed
    2026-05-28 · archived copy
    Calculation
    Doherty et al. is not a high-heel study; it is the meta-analytic anchor for the background female-vs-male ankle-sprain rate ratio (roughly 2x). Used here only as context for the personal factor multipliers and to underline that the heel- attributable ED-visit count is one slice of the much larger female ankle-sprain burden — most sprains, including some caused by heels, never reach an ED at all. We do not derive any headline number from this source.
    Independence
    Independent of NEISS, independent of the APMA survey. Cited as method context, not as a per-wearer rate measurement.

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 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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