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Likelier
Health · reviewed 2026-05-16

What are the odds of developing alcohol use disorder over a lifetime?

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
5/5
D4 Uncertainty
4/5
D5 Scope
5/5
D6 Prose
5/5
D7 Perception honesty
4/5
D8 Caveat completeness
5/5
Average 4.75/5
Direct evidence

Lifetime probability · lifetime, US adult

1 in 3.4

29% lifetime chance

Most people underestimate this.

range 1 in 4.5 to 1 in 2.5

lifetime, US adult each band = 10× rarer → zoomed to your factors See full scale →
certain 1 in 1K 1 in 1M 1 in 1B
1 in 1.1 1 in 34

● your factors — click this risk ▾ to reveal

≈ As likely as

An empty glass on a plain surface beside a small calendar showing years passed, flat vector illustration in muted tones.

Perceived

Most adults anchor their estimate of alcohol use disorder risk on the visible end of the spectrum: the person who has lost a job, a marriage, or a driver's license to drinking. That framing creates a population that looks much smaller than it is. The DSM-5 criteria for AUD span a wide severity range — from two or three symptoms (mild) to six or more (severe) — and the majority of the 29% lifetime prevalence is at the mild-to-moderate end, where the disorder is often invisible from the outside. Cultural normalization of heavy drinking in social, professional, and recreational contexts further compresses perceived risk: if most of the people around you drink heavily at times, the behavior stops registering as a marker of disorder. Public awareness campaigns have largely focused on drunk driving and fetal alcohol syndrome, leaving the population-level lifetime prevalence figure largely unknown outside clinical settings.

Rough estimate: ~5-10% of adults, perhaps

Source: editorial intuition, not polled

Actual

29.1% of US adults meet DSM-5 criteria for alcohol use disorder at some point in their lifetime (NESARC-III, 2012–2013)

US adults aged 18 and older (NESARC-III, N=36,309, face-to-face interviews 2012–2013)

Show derivation

The NESARC-III (Grant et al., JAMA Psychiatry 2015) conducted face-to-face structured psychiatric interviews with 36,309 US adults aged 18 and older, using the AUDADIS-5 instrument to assess DSM-5 criteria. Lifetime AUD prevalence was 29.1% (12-month prevalence was 13.9%). The lifetime figure is used directly as the normalized estimate: it already represents a US adult population and already encompasses the full adult lifespan captured by retrospective diagnostic interviews. No additional conversion is needed. The 29.1% figure is not a per-year or per-exposure rate but a lifetime cumulative prevalence. Severity distribution: approximately 17.5% mild (2-3 criteria), 6.3% moderate (4-5 criteria), and 5.3% severe (6+ criteria). The SAMHSA 2024 NSDUH (13.9M past-year AUD / ~260M adults) yields ~5.3% past-year prevalence among adults, consistent with the NESARC-III 13.9% figure when restricted to the same age range — the higher NESARC-III 12-month figure reflects differences in interview instrument and sampling. The 29.1% lifetime figure is the most widely cited and replicated estimate from the largest nationally representative study using DSM-5 criteria.

Caveats: The 29.1% figure is a lifetime prevalence estimate based on retrospective struct…

The 29.1% figure is a lifetime prevalence estimate based on retrospective structured diagnostic interviews with adults surveyed in 2012-2013. It captures disorder at any point in adulthood, including episodes that may have resolved decades earlier. The majority of lifetime AUD cases (roughly 60%) are mild (2-3 DSM-5 criteria), meeting the threshold for diagnosis but with substantially lower functional impairment than moderate-to-severe cases. DSM-5 collapsed the prior DSM-IV categories of "alcohol abuse" and "alcohol dependence" into a single disorder, which accounts for some of the elevation compared to earlier DSM-IV-based estimates. Only 19.8% of adults with lifetime AUD ever sought treatment, meaning the large majority of cases — including most mild cases — are never clinically identified. The prospective risk for a young adult just beginning to drink is not precisely the same as this retrospective lifetime prevalence; risk accumulates over the years of heaviest use (typically ages 18-35).

Risks at similar odds

Other risks with roughly the same likelihood — useful for calibration.

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Inheriting AUD risk

If a parent had alcohol use disorder, what are the odds you'll develop alcohol use disorder yourself?

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Cannabis use disorder

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Major depression

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Regular drinking

What are the odds of dying from alcohol-related disease as a regular drinker?

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Family caregiver probability

How likely am I to become an unpaid family caregiver — and what is the mental-health toll?

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Job loss & depression

What are the odds of developing depression after losing your job?

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Loneliness & health

What are the odds of chronic loneliness causing serious health harm over a lifetime?

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Menopause CV risk acceleration

How likely is a woman to develop cardiovascular disease after menopause — and how much does menopause accelerate that risk?

Compare to:

The 2012–2013 NESARC-III (the largest nationally representative diagnostic survey of alcohol and drug use ever conducted in the United States, with face-to-face structured interviews of 36,309 adults) found a 29.1% lifetime prevalence of DSM-5 alcohol use disorder. That is not a global or regional estimate; it is a US adult figure from a probability sample using clinical diagnostic criteria. The 12-month prevalence was 13.9%, meaning a substantial share of cases are active at any given time, not merely historical. Severity is distributed roughly as follows: about 17.5% mild (2–3 criteria), 6.3% moderate (4–5 criteria), and 5.3% severe (6 or more). SAMHSA’s 2024 National Survey on Drug Use and Health found 13.9 million Americans had past-year AUD, a lower absolute number but consistent with the NESARC-III structure when accounting for instrument differences — NSDUH uses a self-report questionnaire while NESARC-III used a clinician-level diagnostic interview, which consistently produces higher prevalence estimates.

The gap between perceived and actual risk here is large and in a consistent direction: nearly everyone underestimates it. The intuitive mental model of AUD centers on severe, visible cases (job loss, relationship breakdown, physical health collapse) which represent the top few percent of the severity spectrum. The DSM-5 deliberately collapsed what DSM-IV called “alcohol abuse” and “alcohol dependence” into a single disorder with a two-criterion floor, capturing a much wider range of problematic patterns. A person who repeatedly drinks more than intended, spends more time drinking than planned, and continues despite some interpersonal friction can meet the threshold for mild AUD without a single dramatic incident. That population is large and largely invisible. The NESARC-III data also showed that only 19.8% of adults with lifetime AUD ever sought treatment — meaning the vast majority of cases, especially at the mild end, are never clinically identified, further suppressing public awareness of the true prevalence.

The 29.1% figure describes what has happened to a representative sample of US adults as of 2012–2013; it is not a forecast for any individual. Men have substantially higher rates (36.0%) than women (22.7%), with younger adults and unmarried individuals also showing elevated prevalence in the NESARC-III data. Family history roughly triples risk, reflecting a heritability of around 50–60% from twin and adoption studies. Early onset of regular drinking (before age 21) is among the strongest individual predictors of lifetime disorder. Conversely, the large lifetime prevalence estimate includes many resolved cases: people who met criteria during their twenties, stopped or moderated their drinking, and would no longer meet the threshold today. The figure is a measure of exposure accumulated across the full adult life span, not a current snapshot.

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] Grant BF et al. — JAMA Psychiatry, 2015 — Epidemiology of DSM-5 Alcohol Use Disorder: Results From the National Epidemiologic Survey on Alcohol and Related Conditions III
    Epidemiology of DSM-5 Alcohol Use Disorder: Results From the National Epidemiologic Survey on Alcohol and Related Conditions III

    See all 2 Likelier entries citing this source →

    Statistic
    12-month and lifetime prevalences of DSM-5 AUD among US adults were 13.9% and 29.1%, respectively (NESARC-III, N=36,309)
    Excerpt
    “"In 2012-2013, US prevalences of DSM-5 12-month and lifetime AUD among adults 18 years and older were 13.9% and 29.1%, respectively. Prevalence was generally highest for men (17.6% and 36.0%, respectively), White and Native American respondents, and younger and never-married adults." ”
    Source data from
    2015-08-01
    Accessed
    2026-05-04 · archived copy
    Calculation
    The 29.1% lifetime prevalence is used directly as the native numerator (29.1 per 100 US adults). This is the primary calculation input. The study used DSM-5 diagnostic criteria applied via the AUDADIS-5 structured interview, making it the definitive DSM-5 AUD prevalence estimate for the US adult population.
    Independence
    NESARC-III was conducted by the National Institute on Alcohol Abuse and Alcoholism (NIAAA) using probability sampling of the US non-institutionalized civilian population. It is methodologically independent from SAMHSA NSDUH, which uses self-report questionnaires rather than structured diagnostic interviews.
  2. [2] Substance Abuse and Mental Health Services Administration (SAMHSA) — Key Substance Use and Mental Health Indicators in the United States: Results from the 2024 National Survey on Drug Use and Health
    Key Substance Use and Mental Health Indicators in the United States: Results from the 2024 National Survey on Drug Use and Health

    See all 3 Likelier entries citing this source →

    Statistic
    13.9 million Americans aged 12 or older had alcohol use disorder in the past year in 2024
    Excerpt
    “"In 2024, 13.9 million people aged 12 or older had a past year alcohol use disorder, representing approximately 5 percent of the population aged 12 or older. Marijuana use disorder was the most common drug use disorder (20.6 million), followed by opioid use disorder (4.8 million)." ”
    Source data from
    2025-07-14
    Accessed
    2026-05-04 · archived copy
    Calculation
    SAMHSA 2024 NSDUH past-year AUD figure (13.9M / ~260M US adults ≈ 5.3%) is used as a cross-validation anchor, not as the primary prevalence estimate. The lower 12-month figure relative to NESARC-III (13.9% vs 5.3%) reflects instrument differences: NSDUH uses a self-report questionnaire while NESARC-III used a full structured diagnostic interview, which produces systematically higher prevalence estimates. Both sources converge on the same conclusion: AUD is the most prevalent substance use disorder in the US.
    Independence
    SAMHSA NSDUH is conducted by an independent contractor (RTI International) and uses a different sampling and assessment methodology than NESARC-III, providing a genuinely independent cross-check on the scale of the disorder.
  3. [3] National Institute on Alcohol Abuse and Alcoholism (NIAAA) — National Epidemiologic Survey on Alcohol and Related Conditions III (NESARC-III) Publications List
    National Epidemiologic Survey on Alcohol and Related Conditions III (NESARC-III) Publications List
    Statistic
    NESARC-III is the largest and most comprehensive nationally representative survey of alcohol and drug use and related psychiatric conditions ever conducted in the United States
    Excerpt
    “"The National Epidemiologic Survey on Alcohol and Related Conditions III (NESARC-III) is the largest, most comprehensive, nationally representative survey of alcohol and drug use and related psychiatric conditions ever conducted in the United States. It consisted of in-person interviews with 36,309 adults aged 18 years and older conducted in 2012-2013." ”
    Source data from
    2016-08-10
    Accessed
    2026-05-04 · archived copy
    Calculation
    Used here to establish the methodological standing of NESARC-III as the definitive source for DSM-5 AUD prevalence. The face-to-face structured interview methodology and probability sampling of 36,309 adults make it the gold standard for US lifetime AUD prevalence.

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