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Health · reviewed 2026-05-16

What are the odds of developing cannabis use disorder?

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 16

6.3% lifetime chance

Most people underestimate this.

range 1 in 25 to 1 in 11

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 3.2 1 in 106

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≈ As likely as

A small calendar showing months accumulating beside a single leaf silhouette, flat vector illustration in muted green and grey tones.

Perceived

Cannabis occupies an unusual position in public risk perception: it is widely regarded as the drug least likely to cause dependence, often in explicit contrast to alcohol, opioids, or stimulants. The political framing of legalization debates has reinforced this view — advocates have emphasized relative safety compared to alcohol, and the term "marijuana use disorder" does not have the cultural salience of "alcoholism" or "opioid addiction." Many users and non-users alike believe cannabis is simply not addictive in any meaningful sense. That belief is incorrect for a substantial minority of users. The post-2018 legalization wave has also made high-potency products — concentrates, edibles, and vapes with THC concentrations far above what was available in prior decades — the norm in legal markets, changing the pharmacological exposure profile in ways that older survey data may not fully capture.

Rough estimate: ~1-2% of adults

Source: editorial intuition, not polled

Actual

6.3% of US adults meet DSM-5 criteria for cannabis 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

Hasin et al. (American Journal of Psychiatry, 2016) used the NESARC-III data (N=36,309 US adults, 2012–2013) with DSM-5 diagnostic criteria to estimate lifetime cannabis use disorder prevalence at 6.3% and 12-month prevalence at 2.5%. The lifetime figure is used directly as the normalized estimate: it already represents the US adult population and encompasses the full adult lifespan captured by retrospective structured interviews. Among adults who have ever used cannabis, the conditional probability of developing CUD is substantially higher. The Lopez-Quintero et al. (2011, Drug and Alcohol Dependence) analysis of NESARC-I data found that approximately 8.9% of ever-users transition to cannabis dependence — the per-user conditional rate. The NESARC-III all-adult 6.3% figure is used here because the question asks about population-level lifetime risk for a US adult, not conditional risk given use. SAMHSA 2024 NSDUH found 20.6 million past-year CUD among US residents 12+, consistent with the high end of prevalence estimates once cannabis use rates are applied.

Caveats: The 6.3% lifetime prevalence is drawn from 2012-2013 NESARC-III data, before leg…

The 6.3% lifetime prevalence is drawn from 2012-2013 NESARC-III data, before legalization in most US states. Since 2018, both cannabis use prevalence and use disorder rates have increased substantially; SAMHSA 2024 found 20.6 million past-year CUD cases, suggesting the lifetime prevalence for today's younger cohort will be higher than 6.3% by the time they reach the age of the NESARC-III respondents. The conditional risk among ever-users is substantially higher than the all-adult 6.3% — approximately 8.9% of ever-users develop dependence, per Lopez-Quintero et al. (2011, Drug and Alcohol Dependence, NESARC-I data). Post-legalization products — concentrates, vapes, and edibles with THC concentrations of 40-90% versus the 5-10% of typical cannabis sold in 2000 — represent a meaningfully different pharmacological exposure than the products used by most NESARC-III respondents. The 6.3% figure should be treated as a lower bound for current and future adult cohorts. DSM-5 CUD requires at least 2 of 11 criteria; tolerance and withdrawal are included but not required, meaning the disorder captures a wider range of problematic use patterns than colloquial "addiction."

Risks at similar odds

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Compare to:

The 2012–2013 NESARC-III (the same nationally representative study of 36,309 US adults that established the 29.1% lifetime prevalence of alcohol use disorder) found a 6.3% lifetime prevalence of DSM-5 cannabis use disorder (Hasin et al., American Journal of Psychiatry, 2016). The 12-month prevalence was 2.5%. SAMHSA’s 2024 National Survey on Drug Use and Health found 20.6 million Americans with past-year cannabis use disorder, making it the most common drug use disorder in the United States, more common than opioid use disorder (4.8 million) and stimulant use disorder (4.3 million) combined. The 6.3% lifetime figure is almost certainly a floor rather than a ceiling: it predates the 2018 legalization wave that transformed access and product potency across most of the country, and both cannabis use and cannabis use disorder rates have risen since 2012–2013.

The perception that cannabis is simply not addictive holds up poorly against the diagnostic data. The DSM-5 criteria for cannabis use disorder (which include tolerance, withdrawal, unsuccessful efforts to cut down, continued use despite interpersonal or occupational problems, and giving up important activities for cannabis) map directly onto the patterns that heavy daily users typically describe, often without having thought of themselves as disordered. Among ever-users, the conditional probability of developing disorder is approximately 8–9%, based on NESARC-I data (Lopez-Quintero et al., 2011). That per-user rate is lower than for nicotine (~67%) and heroin (~23%) but higher than alcohol (~15%) and cocaine (~17%), a ranking that conflicts sharply with the cultural hierarchy of drug danger. The post-legalization shift to high-potency concentrates and vapes (with THC concentrations of 40–90% versus the 5–10% typical of 2000-era cannabis) changes the exposure profile in ways that older survey data cannot capture.

The 6.3% all-adult lifetime figure encompasses a wide range of users. The disorder is far more common among those who begin using before age 18 (where adolescent brain development creates higher vulnerability), daily or near-daily users, and those with co-occurring anxiety or mood disorders — for whom cannabis is frequently used for self-medication of insomnia and anxiety. Occasional users (monthly or less) face a substantially lower conditional risk than the all-adult estimate implies. Men have higher rates than women in the NESARC-III data, consistent with higher rates of heavy use in male cohorts. The 6.3% figure also includes resolved cases: people who met criteria during periods of heavier use and later reduced or stopped without formal treatment, which is common. DSM-5 CUD requires only two of eleven criteria, spanning a severity range from mild functional impairment to severe dependence.

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] Hasin DS et al. — American Journal of Psychiatry, 2016 — Prevalence and Correlates of DSM-5 Cannabis Use Disorder, 2012–2013: Findings from the National Epidemiologic Survey on Alcohol and Related Conditions–III
    Prevalence and Correlates of DSM-5 Cannabis Use Disorder, 2012–2013: Findings from the National Epidemiologic Survey on Alcohol and Related Conditions–III
    Statistic
    Lifetime and 12-month prevalences of DSM-5 cannabis use disorder among US adults were 6.3% and 2.5%, respectively (NESARC-III, N=36,309)
    Excerpt
    “"The prevalences of 12-month and lifetime cannabis use disorder were 2.5% and 6.3%. Odds of 12-month and lifetime cannabis use disorder were higher for men, Native Americans, unmarried individuals, those with low incomes, and young adults; cannabis use disorder was associated with other substance use disorders, affective disorders, anxiety, and personality disorders." ”
    Source data from
    2016-03-01
    Accessed
    2026-05-04 · archived copy
    Calculation
    The 6.3% lifetime prevalence is used directly as the native numerator (6.3 per 100 US adults). This is the primary calculation input, representing the first nationally representative DSM-5 CUD prevalence estimate using structured diagnostic interviews. The 2.5% 12-month figure confirms the disorder is active for many adults at any given time, not merely historical.
    Independence
    NESARC-III was conducted by NIAAA using probability sampling and structured clinical interviews (AUDADIS-5), methodologically distinct from SAMHSA NSDUH self-report instruments.
  2. [2] Hasin DS et al. — JAMA Psychiatry, 2015 — Prevalence of Marijuana Use Disorders in the United States Between 2001-2002 and 2012-2013
    Prevalence of Marijuana Use Disorders in the United States Between 2001-2002 and 2012-2013
    Statistic
    Past-year prevalence of DSM-IV marijuana use disorder increased from 1.5% in 2001-2002 to 2.9% in 2012-2013; marijuana use more than doubled over the same period
    Excerpt
    “"The past-year prevalence of marijuana use was 4.1% in 2001-2002 and 9.5% in 2012-2013. The past-year prevalence of DSM-IV marijuana use disorder was 1.5% in 2001-2002 and 2.9% in 2012-2013 (P < .05). Significant increases were found across all demographic subgroups." ”
    Source data from
    2015-12-01
    Accessed
    2026-05-04 · archived copy
    Calculation
    This study uses DSM-IV criteria and past-year prevalence, so the absolute figures are lower than the DSM-5 lifetime estimates in Hasin et al. 2016. It is used here to establish the trend: both cannabis use and cannabis use disorder have increased substantially since 2001-2002, with disorder prevalence roughly doubling. The post-legalization era (2018 onward) is not captured in either NESARC study and likely represents a further increase in exposure and conditional disorder rates.
    Independence
    Both Hasin 2015 (JAMA Psychiatry) and Hasin 2016 (Am J Psychiatry) draw on NESARC wave data. They are not fully independent sources but use different diagnostic criteria (DSM-IV vs DSM-5) and different comparison years, providing genuine methodological triangulation on the trend.
  3. [3] 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
    20.6 million people aged 12 or older had past-year cannabis use disorder in 2024, making it the most common drug use disorder in the US
    Excerpt
    “"Marijuana use disorder was the most common drug use disorder (20.6 million), followed by opioid use disorder (4.8 million) and central nervous system stimulant use disorder (4.3 million). In 2024, 44.3 million individuals reported marijuana use in the past month." ”
    Source data from
    2025-07-14
    Accessed
    2026-05-04 · archived copy
    Calculation
    SAMHSA 2024 NSDUH: 20.6M past-year CUD / ~260M US adults ≈ 7.9% past-year CUD prevalence. This figure is notably higher than the NESARC-III 2.5% 12-month estimate, reflecting both the increase in cannabis use since 2012-2013 and instrument differences between NSDUH and NESARC. It is used here as a cross-validation anchor showing that post-legalization cannabis use disorder rates are higher than the NESARC-III figures, supporting the upper end of the uncertainty range. The 6.3% lifetime estimate from 2012-2013 is almost certainly an undercount for today's adult cohort.

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