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Health · reviewed 2026-05-22

What are the odds of dying from a smokeless-tobacco-related disease as a regular user?

Evidence quality 4.13/5

Eight-dimension review score against the quality rubric . Each dimension scored 1–5.

D1 Source grounding
4/5
D2 Source authority
5/5
D3 Arithmetic
3/5
D4 Uncertainty
4/5
D5 Scope
5/5
D6 Prose
4/5
D7 Perception honesty
3/5
D8 Caveat completeness
5/5
Average 4.13/5

Lifetime probability · lifetime, subgroup

1 in 8.3

12% lifetime chance

Most people overestimate this.

range 1 in 20 to 1 in 4.0

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 2.1 1 in 12

● your factors — click this risk ▾ to reveal

≈ As likely as

A small tin container casting a soft shadow on a muted warm surface, flat vector illustration.

Perceived

Smokeless tobacco — snus, chewing tobacco, moist snuff — occupies an ambiguous space in public health perception. Many users treat it as a substantially safer substitute for cigarettes, citing the absence of combustion and the absence of lung cancer as the defining differences. Others assume the risk is comparable to smoking, equating "tobacco" with "similar hazard." Neither picture is accurate. The evidence points to a genuine but considerably smaller mortality risk than cigarette smoking — roughly a quarter to a third of smoking's attributable burden — concentrated mainly in cardiovascular disease and, for products higher in tobacco-specific nitrosamines (TSNA), oral and esophageal cancer. The headline figure is not zero, and it is substantially lower than the ~50% lifetime attributable mortality for a lifelong cigarette smoker.

Rough estimate: Many users believe the risk is negligible; others assume it matches cigarette smoking

Source: editorial intuition, not polled

Actual

Roughly 1 in 8 lifelong regular smokeless tobacco users die from a tobacco-attributable disease

lifelong regular smokeless tobacco users (primarily snus-type products in Scandinavia; US chewing tobacco users may have lower absolute mortality based on contemporaneous US data)

Show derivation

Reference subgroup: an adult who begins regular smokeless tobacco use in early adulthood and continues for decades, modelled primarily on Swedish snus data (the highest-quality long-term cohort evidence available). The 0.12 point estimate derives from the following reasoning. Shafey et al. (PMC7825961), a pooled analysis of eight Swedish prospective cohort studies (N=169,103 never-smoking men; 10,928 deaths over 2,857,312 person-years), found current snus users had an all-cause mortality adjusted HR of 1.28 (95% CI 1.20–1.35) and a cardiovascular mortality HR of 1.27 (95% CI 1.15–1.41) relative to never-users of tobacco. The population attributable fraction implied by an HR of 1.28 is (HR-1)/HR = 0.28/1.28 ≈ 22%. Applying that attributable fraction to the total lifetime mortality of a cohort (which asymptotically approaches 1.0 over a long enough follow-up) yields an approximate lifetime attributable mortality probability of ~12–18%. The 0.12 central estimate deliberately sits at the lower end of this range because: (1) US studies using NLMS and NHIS nationally representative cohorts (Rostron et al. 2018, PMC6458834) found null all-cause mortality (HR ≈ 1.0) for exclusive smokeless tobacco users in US populations, suggesting product-class differences (US chewing tobacco and moist snuff contain higher TSNAs than Swedish pasteurized snus); (2) modern US oral cancer incidence in smokeless tobacco users is only modestly elevated over non-users in the JMIR Cancer 2024 population-based study (HR 1.4, barely significant); (3) the Swedish pooled data represent heavy long-term male snus users who are older on average than US SLT users. Uncertainty range 0.05–0.25 reflects the genuine evidence conflict between Swedish cohort mortality data and US null-finding cohort data. Scope is declared subgroup_lifetime because this is a per-regular-user probability, not a general-population lifetime risk, and is not directly comparable to per-US-adult figures on other Likelier pages.

Caveats: This entry is anchored on Swedish snus cohort data, which provides the largest a…

This entry is anchored on Swedish snus cohort data, which provides the largest and most methodologically rigorous long-term mortality evidence. US cohort data (NLMS and NHIS) found null all-cause mortality for exclusive SLT users, which produces the wide uncertainty range (0.05–0.25). The discrepancy likely reflects product differences (Swedish snus is pasteurized with lower TSNA content than most US chewing tobacco and moist snuff), cohort composition, and follow-up duration differences. The headline 0.12 is an intermediate estimate designed to represent a typical long-term regular user of Western smokeless tobacco products, weighted toward the Swedish data as the longer-follow-up source, with downward adjustment for the US null findings. South and Southeast Asian smokeless tobacco products (gutkha, pan masala, betel quid with tobacco) carry substantially higher cancer risks and are in a different risk category entirely; this entry does not apply to those products. The oral cancer channel for modern US SLT users (primarily moist snuff) is substantially weaker than older literature suggested — contemporary incidence data show near-identical rates in SLT users and never-tobacco users. The primary remaining pathway is cardiovascular, particularly fatal myocardial infarction and heart failure in existing-CVD patients.

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Compare to:

The best available long-term evidence suggests that roughly 1 in 8 lifelong regular smokeless tobacco users will die from a tobacco-attributable disease — a figure that is substantially lower than the roughly 1 in 2 lifetime attributable mortality for cigarette smokers, yet clearly above zero. That estimate comes primarily from a pooled analysis of eight Swedish prospective cohort studies (Shafey et al. 2021, N=169,103 never-smoking men; 10,928 deaths), which found current snus users had an all-cause mortality adjusted hazard ratio of 1.28 (95% CI 1.20–1.35) and a cardiovascular mortality HR of 1.27 (1.15–1.41) compared to never-tobacco users. The attribution fraction implied by HR 1.28 is approximately 22% of deaths in the exposed cohort. An important qualifier: US nationally representative cohort studies (Rostron et al. 2019; NLMS and NHIS datasets) found essentially null all-cause mortality for exclusive US smokeless tobacco users, raising the real possibility that product formulation — Swedish pasteurized snus versus fermented US chewing tobacco and moist snuff — is the variable driving the Swedish-US divergence.

The oral cancer channel, historically the centrepiece of the smokeless-tobacco-health narrative, is now considerably weaker than it appeared in studies from the 1980s and 1990s. A 2024 population-based study of 19,536 US oral cancer cases (JMIR Cancer) found that exclusive smokeless tobacco users and never-tobacco users had nearly identical absolute oral cancer incidence rates — 20.6 versus 22.1 per 100,000 person-years — with only a borderline-significant relative risk of 1.4. This reflects the product shift away from dry snuff (the highest tobacco-specific nitrosamine product) toward moist snuff, which now accounts for roughly 80% of the US market. Older meta-analyses finding oral cancer relative risks of 2.6 to 4.7 for US smokeless tobacco were predominantly capturing dry-snuff users and South and Southeast Asian product users (where gutkha and betel quid products carry order- of-magnitude higher cancer risks). The cardiovascular pathway — primarily via nicotine-driven sympathetic activation, elevated blood pressure, and heart rate effects — is now the primary biological route through which the modest Swedish mortality excess likely operates, and is the mechanism most consistently supported across study populations.

The wide uncertainty band on this entry (0.05–0.25) is not a presentation failure but an accurate reflection of genuine evidence conflict. The Swedish data point to a meaningful absolute mortality elevation; the US data largely do not. Reconciling that conflict requires resolving questions about product formulation, follow-up length, background population health, and residual confounding by socioeconomic status — none of which have been fully resolved in the literature. What is clear from the data is what the entry is framed as: the risk is not zero, it is not equivalent to cigarette smoking, and the magnitude depends substantially on what specific product a user is consuming and whether they have pre-existing cardiovascular disease.

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] BMJ Open (Shafey et al.) — Swedish snus use is associated with mortality: a pooled analysis of eight prospective studies
    Swedish snus use is associated with mortality: a pooled analysis of eight prospective studies
    Statistic
    Current snus users: all-cause mortality aHR 1.28 (95% CI 1.20–1.35); cardiovascular mortality aHR 1.27 (1.15–1.41)
    Excerpt
    “"Current snus users had an increased risk of all-cause mortality (aHR 1.28, 95% CI 1.20 to 1.35), cardiovascular mortality (aHR 1.27, 95% CI 1.15 to 1.41), cancer mortality (aHR 1.12, 95% CI 1.00 to 1.26) and other cause mortality (aHR 1.37, 95% CI 1.24 to 1.52) compared with never-users of tobacco. Mortality from all causes except for cancer increased with duration of snus use at baseline, although there were no clear dose–response relationships with the amount of snus used." ”
    Source data from
    2021-01-27
    Accessed
    2026-05-22 · archived copy
    Calculation
    This pooled analysis of 169,103 never-smoking Swedish men provides the primary quantitative basis for the mortality hazard estimate. The HR 1.28 all-cause figure is the main anchor. Attributable fraction = (1.28-1)/1.28 = 0.219; applied to lifetime mortality (approaching 1.0 over a full adult lifespan) yields ~22% attributable in theory; adjusted to ~12% central estimate to account for US data showing null findings (see Rostron et al.). The Swedish cohort is male-only and drawn from a population using pasteurized snus with lower TSNA levels than most US products; this is both a strength (large, clean, never-smoking) and a limitation (product and population specificity).
    Independence
    This is the largest and most methodologically rigorous source for snus-specific mortality. It is independent from the Rostron US cohort study below. The two datasets point in different directions, which is why both are cited.
  2. [2] Tobacco Control (Rostron et al.) — Smokeless tobacco mortality risks: an analysis of two contemporary nationally representative longitudinal mortality studies
    Smokeless tobacco mortality risks: an analysis of two contemporary nationally representative longitudinal mortality studies
    Statistic
    Exclusive SLT users in US: all-cause mortality HR ≈ 1.0 in both NLMS and NHIS cohorts; no evidence of excess cancer mortality
    Excerpt
    “"No evidence of excess mortality risk among exclusive SLT users was found in either study. [...] Heart failure: NHIS HR 2.75 (95% CI 1.55–4.89). [...] No increased mortality risk from any of the major neoplasms often associated with SLT use. [...] Exclusive smokers showed 12-fold increased lung cancer risk versus 3 deaths in 1,863 SLT-user observations." ”
    Source data from
    2019-04-01
    Accessed
    2026-05-22 · archived copy
    Calculation
    Rostron et al. analysed two US nationally representative longitudinal mortality studies: NLMS (N=210,090, ~5-year follow-up) and NHIS (N=154,286, ~10-year follow-up). Among exclusive SLT users, all-cause mortality HR was approximately 1.0 in both datasets with overlapping confidence intervals, meaning no statistically significant excess all-cause mortality was found in US populations. This is the primary evidence underlying the downward adjustment from the Swedish HR-implied ~22% to the ~12% central estimate. The notable exception is heart failure (HR 2.75, 21 deaths in NHIS), which, while based on a small event count, is consistent with the cardiovascular signal in the Swedish data and is the biological mechanism most consistently associated with smokeless tobacco across study populations.
    Independence
    Rostron et al. use NLMS and NHIS — entirely different populations and time periods from the Swedish pooled analysis. This is a genuine independent replication attempt, and the null result is the principal reason for the wide uncertainty band (0.05–0.25) on this entry.
  3. [3] JMIR Cancer — Oral Cancer Incidence Among Adult Males With Current or Former Use of Cigarettes or Smokeless Tobacco: Population-Based Study
    Oral Cancer Incidence Among Adult Males With Current or Former Use of Cigarettes or Smokeless Tobacco: Population-Based Study
    Statistic
    ST-only users: oral cancer incidence 20.6 per 100,000 vs never-user 22.1 per 100,000; modest HR 1.4 (95% CI 1.1–1.9) for exclusive ST vs never-tobacco
    Excerpt
    “"Never Cig/Current ST (smokeless tobacco users): 20.6 per 100,000 (95% CI 18.3–23.3). Never Cig/Never ST (non-users): 22.1 per 100,000 (95% CI 21.5–22.6). [...] smokeless tobacco users had 1.4 times higher oral cancer risk compared to never users (95% CI 1.1–1.9, P=.02). [...] US smokeless tobacco predominantly consists of moist snuff (~80% market share) and chewing tobacco (~18% market share)." ”
    Source data from
    2024-01-15
    Accessed
    2026-05-22 · archived copy
    Calculation
    This 2024 population-based study of 19,536 US oral cancer cases is the most current direct evidence on oral cancer incidence for US SLT users. The absolute incidence rates are nearly identical between ST users (20.6) and never-tobacco users (22.1) per 100,000 person-years — a null result in absolute terms, with only a modest relative risk that is barely statistically significant. This substantially weakens the older oral-cancer-focused risk narrative for modern US smokeless tobacco users (primarily moist snuff) compared to 1980s studies that found higher RRs for dry snuff with higher TSNA content. The oral cancer channel contributes negligibly to the central estimate of 0.12, which is driven primarily by cardiovascular mortality signalled in the Swedish data.

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