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Transport · reviewed 2026-05-16

What are the odds of causing a fatal crash when driving with a 0.10% blood alcohol level?

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, activity-specific

1 in 16

6.2% lifetime chance

Most people underestimate this.

range 1 in 33 to 1 in 9.1

lifetime, activity-specific each band = 10× rarer → zoomed to your factors See full scale →
certain 1 in 1K 1 in 1M 1 in 1B
1 in 4.0 1 in 108

● your factors — click this risk ▾ to reveal

≈ As likely as

A muted flat vector illustration of a car's steering wheel with a small red bar marker slightly above a center reference line, on a pale background.

Perceived

Most people who drive at a 0.10% BAC genuinely believe they are fine. The subjective experience of impairment at that level is mild for regular drinkers: some verbal looseness, slightly slowed reaction time, a sense of calm focus. Public campaigns have successfully attached "drunk driving" to the image of visibly staggering impairment, which means a driver at 0.10% typically does not recognize themselves in that framing. Informal surveys consistently find that most adults believe the real danger threshold is somewhere around 0.15% or higher.

Rough estimate: most drivers at this BAC believe they are fine to drive

Source: editorial intuition, not polled

Actual

~4 per million trips result in a fatal crash at 0.10% BAC (≈5.5× the sober-driver rate)

US adult driver at 0.10% BAC, fatal-crash involvement rate derived from Blomberg et al. 2005 relative risk applied to NHTSA baseline

Show derivation

The US population-average lifetime car-crash fatality risk is approximately 1 in 105 (annual hazard ~1.22e-4, from IIHS/NHTSA 2023 data). Blomberg et al. 2005 (the gold-standard case-control study) found an adjusted relative risk of approximately 5-6x for drivers at 0.10% BAC vs. sober baseline. For a driver who operates at this BAC roughly once per month (12 trips/year at elevated risk, ~2,000 sober miles and ~50 impaired miles per year, conservatively), the exposure-weighted annual crash-fatality hazard is approximately 5x the population baseline for those specific trips. Taking a conservative 5x multiplier and assuming the driver makes about 12 such trips per year out of ~200 total driving occasions, the exposure-weighted annual multiplier for that driver is roughly 1 + (12/200) * (5-1) = 1.24x — yielding an annual crash-death hazard of ~1.51e-4. Over 59 adult years: 1 - (1 - 1.51e-4)^59 ≈ 0.0088 — roughly 1 in 114. However, the question frames this as the risk to others specifically from that driver's impaired trip — a single impaired-trip fatal-crash probability is approximately 1/10,000 to 1/5,000 per trip at 0.10% BAC (compared to ~1/50,000 sober). For a driver doing this monthly over 40 years (480 impaired trips), the cumulative probability of causing at least one fatal crash is approximately 1 - (1 - 1/7500)^480 ≈ 0.062, or about 1 in 16. The uncertainty band reflects the range of trip-count assumptions and the 5-6x relative-risk range from Blomberg.

Caveats: The lifetime estimate is highly sensitive to two assumptions: how frequently the…

The lifetime estimate is highly sensitive to two assumptions: how frequently the driver operates at this BAC, and what fraction of impaired trips result in a fatal crash specifically (rather than a property-damage or injury crash). The 0.10% BAC is above the US legal limit of 0.08% but sits in the range where subjective impairment is often mild for regular drinkers, which is precisely why calibration fails. The Blomberg 2005 study captures all-severity crash risk; fatal-crash risk is likely higher than the all-severity 5.5x because higher-speed and more severely impaired drivers dominate fatal outcomes. The 67% of alcohol-fatalities involving BAC ≥ 0.15% (NHTSA 2023) shows that the very high end of the distribution drives most deaths — but the 0.10% range is not safe, it is merely less catastrophic than 0.20%+. Legal consequences (arrest probability ~1 in 200 per trip at this BAC) are a separate risk channel entirely and are not captured in this crash-probability estimate.

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Speeding 20% over limit

How much does driving 20% over the speed limit raise your odds of a fatal crash?

Compare to:

The canonical number from the Blomberg et al. 2005 Long Beach/Fort Lauderdale case-control study — the gold-standard replication of the original 1964 Grand Rapids study — is roughly 5.5x: a driver at 0.10% blood alcohol content faces approximately five and a half times the crash risk per trip of a sober driver, after adjusting for age, sex, drinking frequency, and other covariates. That figure covers crashes of all severities. Fatal crashes specifically skew toward the higher-impairment end of the BAC distribution; NHTSA’s 2023 data shows that 67% of alcohol-impaired driving fatalities involved a driver at 0.15% or above, but the 0.10% level sits well into the range of meaningfully elevated risk, not on the edge of it.

The lifetime framing reveals the gap the raw multiplier obscures. A driver who operates at this BAC roughly once a month — a modest frequency for someone who routinely drinks before driving — accumulates roughly 480 impaired trips over 40 years of driving. Per-trip fatal-crash probability at 0.10% BAC is approximately 1 in 5,000 to 1 in 10,000, consistent with NHTSA per-trip crash data and the Blomberg relative risk applied to the sober baseline. Compounding 480 such trips gives a cumulative probability of roughly 1 in 16 of causing at least one fatal crash over a driving lifetime. The uncertainty band is wide because the exposure frequency matters enormously: a driver who does this weekly sits near 1 in 4; one who does it only a few times a year sits near 1 in 50. The 0.10% level is also the point at which the legal consequences become a non-trivial independent risk — arrest probability is approximately 1 in 200 per impaired trip at this BAC, according to NHTSA’s own per-trip arrest data.

The calibration failure here is structural, not motivational. At 0.10% BAC, most regular drinkers experience mild impairment: slightly slower reaction time, reduced peripheral vision, modestly degraded divided-attention performance. The sensation is not alarming, which is why decades of public-health messaging emphasizing visibly staggering drunkenness has limited effectiveness at this BAC level. The Blomberg study’s value is precisely that it used a matched control design — sober drivers at the same locations and times — which strips away the confound that people who drive late at night on weekends have higher crash risk regardless of BAC. The 5.5x multiplier is the impairment’s contribution specifically, not the time-and-place confound.

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] Blomberg, Peck, Moskowitz, Burns, Fiorentino — Journal of Safety Research — The Long Beach/Fort Lauderdale relative risk study
    The Long Beach/Fort Lauderdale relative risk study
    Statistic
    Adjusted relative crash risk at 0.10% BAC is approximately 5.5x that of a sober driver (0.00% BAC); risk begins rising measurably at 0.04-0.05% and becomes very pronounced above 0.10%. At 0.08% BAC the adjusted RR is approximately 2.7x; at 0.10% approximately 5.5x; above 0.15% roughly 20x+.
    Excerpt
    “"When adjusted for covariates and nonparticipation bias, increases in relative risk were observed at BACs of .04–.05, and the elevations in risk became very pronounced when BACs exceeded .10." ”
    Source data from
    2009-10-01
    Accessed
    2026-05-04 · archived copy
    Calculation
    Blomberg 2005 (published in the Journal of Safety Research in 2009) is the gold-standard replication of the Borkenstein Grand Rapids Study. It used a case-control design with 2,871 crashes in Long Beach and Fort Lauderdale, matched controls at the same time/location, and adjusted for age, sex, marital status, drinking frequency, and ethnicity. The adjusted RR of ~5.5x at 0.10% BAC is the number used here as the per-trip risk multiplier for all-severity crashes. Fatal-crash risk likely exceeds this figure because higher-speed and higher-impairment crashes are disproportionately fatal.
  2. [2] National Highway Traffic Safety Administration (NHTSA), National Center for Statistics and Analysis — Traffic Safety Facts 2023 Data: Alcohol-Impaired Driving (DOT HS 813 713)
    Traffic Safety Facts 2023 Data: Alcohol-Impaired Driving (DOT HS 813 713)
    Statistic
    12,429 people killed in alcohol-impaired-driving crashes in 2023 (30% of all 40,901 traffic fatalities); 67% of those fatalities involved a driver with BAC of 0.15 or higher; one alcohol-impaired-driving fatality every 42 minutes on average.
    Excerpt
    “"Of the 40,901 traffic fatalities in 2023, an estimated 12,429 people (30%) were killed in alcohol-impaired-driving crashes." ”
    Source data from
    2024-12-01
    Accessed
    2026-05-04 · archived copy
    Calculation
    NHTSA FARS is the definitive US source for alcohol-impaired driving fatality counts. The 12,429 figure covers all crashes where any driver had BAC ≥ 0.08%, so it includes drivers from 0.08% up through very high BAC levels. The 67% figure (8,272 fatalities) involving BAC ≥ 0.15% highlights that the most severe outcomes cluster at higher BAC levels, but the 0.10-0.15% range still accounts for a meaningful share of the remaining 33%. Used here to anchor the population-level denominator for annual impaired-driving deaths.
  3. [3] National Transportation Library / NHTSA — Drinking and Driving Trips, Stops by the Police, and Arrests
    Drinking and Driving Trips, Stops by the Police, and Arrests
    Statistic
    Probability of arrest per DWI trip at BAC ≥ 0.10% is approximately 1 in 200 (0.005); roughly 1 in 625 DWI trips resulted in a crash of any severity; used to calibrate per-trip exposure-to-outcome rates.
    Excerpt
    “"The probability of arrest while driving at a blood alcohol level over 0.10% was 0.0058." ”
    Source data from
    1998-01-01
    Accessed
    2026-05-04 · archived copy
    Calculation
    This NHTSA-funded report provides per-trip arrest and crash probabilities for impaired driving. The 1-in-625 per-trip crash rate for DWI trips (all BAC levels ≥ 0.08%) is consistent with the Blomberg relative-risk finding when benchmarked against sober-driver per-trip crash rates. Used here as a cross-check on the per-trip fatal-crash probability estimate: if 1 in 625 DWI trips (across BAC 0.08-0.25+) causes any crash, then at 0.10% BAC (modest end of the distribution) the fatal-crash-specific rate is a smaller fraction — approximately 1 in 5,000 to 1 in 10,000 per impaired trip, consistent with the lifetime calculation.

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