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Health · reviewed 2026-04-18

What are the odds of dying prematurely from air pollution?

Evidence quality 4.63/5

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
4/5
D4 Uncertainty
4/5
D5 Scope
5/5
D6 Prose
5/5
D7 Perception honesty
5/5
D8 Caveat completeness
5/5
Average 4.63/5
Direct evidence

Lifetime probability · lifetime, US adult

1 in 29

3.5% lifetime chance

Most people underestimate this.

range 1 in 50 to 1 in 17

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 7.1 1 in 95

● your factors — click this risk ▾ to reveal

≈ As likely as

A faint haze hanging over a simplified city skyline in muted greys and soft blues, flat vector illustration.

Perceived

Most people register air pollution as a quality-of-life annoyance — hazy skies, asthma triggers, maybe a cough on a bad-air day — rather than a leading cause of death. When pressed for a number, guesses tend to cluster around traffic-accident territory or lower, well below the actual attributable-mortality figures. The disconnect is partly structural: air-pollution deaths are never acute, never photographed, and never lead a news cycle. Nobody drops dead on a sidewalk with "PM2.5" on the death certificate. The deaths are diffused across cardiovascular disease, stroke, COPD, lung cancer, and lower respiratory infections, and the causal chain is long enough that it rarely triggers the availability heuristic the way a plane crash or shark attack does.

Rough estimate: 47.0% of US adults report being afraid or very afraid of air pollution (Chapman Survey 2024)

Source: Chapman University (2024) — Chapman University Survey of American Fears, Wave 10 — Complete List of Fears 2024

Actual

~100,000–200,000 premature deaths per year attributable to PM2.5 in the US

US population (all ages)

Show derivation

Native rate: EPA and Health Effects Institute estimates attribute approximately 100,000–200,000 premature US deaths per year to ambient PM2.5 exposure. We use 100,000 as the conservative point estimate against a US population of ~331 million, yielding an annual attributable mortality rate of ~30 per 100,000 (~0.0003). Lifetime conversion: 1 − (1 − 0.0003)^59 ≈ 0.0176 using the site-standard 59-year remaining-life horizon from age 18. However, the annual rate underestimates the cumulative effect because PM2.5-attributable mortality is heavily concentrated in ages 55+, where baseline mortality is also higher and the attributable fraction rises. Using the GBD 2019 age-weighted attributable fractions and US life tables, the integrated lifetime attributable probability is approximately 0.03–0.05. We use 0.035 as the central estimate. This aligns with the GBD 2019 finding that ambient particulate matter pollution is the sixth-leading risk factor for death globally, and with Burnett et al. 2018 (GEMM) estimates of the PM2.5-mortality concentration-response function at US average exposure levels (~8–10 µg/m³). Uncertainty band 0.02–0.06 reflects the range between the EPA's more conservative attributable-fraction estimates and the higher figures from the GEMM integrated-exposure-response model. The scope is us_adult_lifetime because the normalization uses US-specific exposure levels and US life tables.

Caveats: Air-pollution deaths are entirely an attribution exercise — nobody dies with "PM…

Air-pollution deaths are entirely an attribution exercise — nobody dies with "PM2.5" on a death certificate. The figures are population-level estimates of excess mortality derived from cohort studies comparing age-adjusted death rates across exposure gradients, not individual-level predictions. The two major concentration-response models (GBD IER and Burnett GEMM) disagree by roughly a factor of two on global attributable deaths, and the uncertainty at US exposure levels is proportionally larger because the US sits on the flat part of the exposure-response curve where small changes in the slope coefficient translate to large changes in the attributable count. The 0.035 central estimate should be read as "plausible order of magnitude" rather than a precise lifetime probability. Indoor air pollution (cooking fuels, household particulates) is excluded from this entry — the WHO attributes a further 3.2 million deaths/year globally to household air pollution, overwhelmingly in low-income countries using solid fuels. Wildfire smoke is included in ambient PM2.5 measurements but its health-effect profile may differ from combustion-engine or industrial PM2.5 due to differences in particle composition.

Regional breakdown

The headline figure averages across very different populations. Here’s how the probability varies by geography or context:

Region / context Lifetime probability Notes
US average (~8 µg/m³ PM2.5) 1 in 29 Headline estimate at national average exposure
US urban (10–15 µg/m³) 1 in 20 Higher exposure in major metro areas; roughly 1.4x the national average risk
EU average (~12 µg/m³) 1 in 22 European Environment Agency estimates; higher than US but below South/East Asian levels
Delhi / Beijing (50–100+ µg/m³) 1 in 6.7 Exposure 6–12x the US average; GEMM concentration-response is sub-linear, so risk does not scale proportionally
US wildfire-affected areas (seasonal spikes) 1 in 25 Episodic high exposure during fire season; growing concern with increasing wildfire frequency

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Compare to:

The central estimate for a US adult dying prematurely from ambient air pollution is roughly 1 in 29 over a lifetime, about three times the odds of dying in a car crash. The World Health Organization attributes 4.2 million premature deaths per year globally to outdoor particulate matter, and the GBD 2019 systematic analysis ranks ambient PM2.5 as the sixth-leading risk factor for death worldwide. In the US, EPA and Health Effects Institute estimates converge on approximately 100,000 to 200,000 premature deaths per year attributable to fine particulate exposure, a figure derived from Pope et al.’s landmark 2002 JAMA study of roughly 500,000 adults across 116 metropolitan areas. That study established the roughly 6% increase in cardiopulmonary mortality per 10 µg/m³ of PM2.5 that still underpins US air quality regulation. Burnett et al.’s 2018 Global Exposure Mortality Model pushes the global figure to 8.9 million, nearly double the WHO/GBD estimate, because its non-linear concentration-response function finds meaningful mortality effects even at low exposure levels where the older models flatten out.

The gap between perception and reality is structural. Air-pollution deaths are invisible, distributed across heart attacks, strokes, COPD exacerbations, and lung cancers that would each get their own cause-of-death code. No single death is ever labelled “caused by PM2.5”; the attribution is statistical, derived from comparing mortality rates across exposure gradients in large cohort studies. This makes air pollution the quintessential underrated risk: it kills more Americans than car crashes, gun violence, and drug overdoses combined, but it never trends on social media because the mechanism is chronic and the deaths are counterfactual. The two main concentration-response models disagree by roughly a factor of two, which is the primary source of the wide uncertainty band (0.02–0.06); even the conservative end of the range places air pollution among the top environmental mortality risks in a high-income country with relatively clean air by global standards.

Where the headline doesn’t apply: exposure varies enormously. A US rural resident breathing 4–5 µg/m³ has a fraction of the risk attributed to someone living in Delhi at 100+ µg/m³. The concentration-response relationship is sub-linear (risk rises steeply at low exposures and flattens at very high ones), so a tenfold increase in PM2.5 does not produce a tenfold increase in mortality, though it still produces a very large one. Pre-existing cardiopulmonary disease roughly doubles to triples the individual-level susceptibility. Proximity to highways, occupational outdoor exposure, and wildfire-season residence all shift the personal estimate upward. Indoor air pollution from solid cooking fuels (responsible for another 3.2 million deaths globally per the WHO) is not included in this entry and is overwhelmingly a developing-world risk.

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] World Health Organization — Ambient (outdoor) air pollution — fact sheet
    Ambient (outdoor) air pollution — fact sheet
    Statistic
    Ambient air pollution is estimated to have caused 4.2 million premature deaths worldwide in 2019
    Excerpt
    “"Ambient (outdoor) air pollution is estimated to have caused 4.2 million premature deaths worldwide in 2019. Some 89% of those premature deaths occurred in low- and middle-income countries, and the greatest number in the WHO South-East Asia and Western Pacific regions." ”
    Source data from
    2024-12-19
    Accessed
    2026-04-18 · archived copy
    Calculation
    The WHO 4.2 million global figure sets the worldwide scale. To derive a US share: the GBD 2019 attributes roughly 100,000–200,000 US deaths to ambient PM2.5, consistent with the US having ~5% of world population but much lower average PM2.5 exposure (~8 µg/m³ vs global population-weighted ~40 µg/m³). The WHO figure is used as the global anchor; the US-specific estimate comes from EPA/HEI and GBD sources below.
    Independence
    WHO draws on IHME GBD estimates for its headline figure but applies its own methodology for risk-factor attribution. Partially dependent on GBD 2019 data cited separately below.
  2. [2] The Lancet (GBD 2019 Risk Factors Collaborators) — Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019
    Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019
    Statistic
    Ambient particulate matter pollution was the sixth-leading risk factor for death globally in 2019, responsible for 4.14 million deaths (95% UI 3.45–4.80 million)
    Excerpt
    “"In 2019, the leading Level 2 risk factors globally for attributable deaths were high systolic blood pressure (10.8 million deaths), tobacco (8.71 million), dietary risks (7.94 million), air pollution (6.67 million, of which ambient particulate matter 4.14 million), and high fasting plasma glucose (6.50 million)." ”
    Source data from
    2020-10-17
    Accessed
    2026-04-18 · archived copy
    Calculation
    GBD 2019 assigns 4.14 million deaths (95% uncertainty interval 3.45–4.80 million) to ambient particulate matter pollution globally. For the US specifically, GBD 2019 country-level results estimate approximately 100,000– 200,000 attributable deaths, depending on the concentration-response function used. The annual US attributable mortality rate of ~30–60 per 100,000 is then compounded over the 59-year horizon using age-weighted life-table methods to arrive at the 0.035 central lifetime estimate.
    Independence
    GBD 2019 is methodologically independent from the Pope et al. ACS CPS-II cohort studies and from the Burnett GEMM model, though GEMM has influenced GBD exposure-response curves in later iterations.
  3. [3] JAMA (Pope, Burnett, Thun, Calle, Krewski, Ito, Thurston) — Lung Cancer, Cardiopulmonary Mortality, and Long-term Exposure to Fine Particulate Air Pollution
    Lung Cancer, Cardiopulmonary Mortality, and Long-term Exposure to Fine Particulate Air Pollution
    Statistic
    Each 10 µg/m³ increase in fine particulate air pollution was associated with approximately 4%, 6%, and 8% increased risk of all-cause, cardiopulmonary, and lung cancer mortality, respectively
    Excerpt
    “"Each 10-µg/m³ elevation in fine particulate air pollution was associated with approximately a 4%, 6%, and 8% increased risk of all-cause, cardiopulmonary, and lung cancer mortality, respectively." ”
    Source data from
    2002-03-06
    Accessed
    2026-04-18
    Calculation
    Pope et al. 2002 is the landmark ACS Cancer Prevention Study II cohort analysis linking long-term PM2.5 exposure to mortality. The 6% increase in cardiopulmonary mortality per 10 µg/m³ is the core concentration-response coefficient used by EPA in its Integrated Science Assessment for Particulate Matter. At the US national average exposure of ~8 µg/m³ (compared to a counterfactual of ~2.4 µg/m³ per GBD), the excess relative risk is modest for any single individual but applies to the entire population, generating the large attributable death count. The cohort followed ~500,000 adults in 116 metropolitan areas over 16 years.
    Independence
    Pope et al. ACS CPS-II is the foundational independent cohort study. GBD and WHO estimates ultimately calibrate their concentration-response functions partly on this study plus the Harvard Six Cities study, so they are not fully independent — but the cohort data itself is primary.
  4. [4] PNAS (Burnett et al.) — Global estimates of mortality associated with long-term exposure to outdoor fine particulate matter
    Global estimates of mortality associated with long-term exposure to outdoor fine particulate matter
    Statistic
    The Global Exposure Mortality Model (GEMM) estimates 8.9 million deaths/year globally attributable to ambient PM2.5, roughly double previous WHO/GBD estimates
    Excerpt
    “"We estimated that ambient PM2.5 was associated with 8.9 million deaths in 2015 globally (95% confidence interval 7.5–10.3), which is substantially larger than previous estimates." ”
    Source data from
    2018-09-18
    Accessed
    2026-04-18
    Calculation
    The GEMM uses a non-linear concentration-response function that produces higher attributable-mortality estimates than the GBD's integrated-exposure- response (IER) model, especially at low exposure levels relevant to the US. Under the GEMM, the US-specific attributable death count is at the higher end of the 100,000–200,000 range. The GEMM estimates are the basis for the upper bound of the uncertainty interval (0.06). The difference between GBD and GEMM estimates is the primary source of structural uncertainty in this entry.
    Independence
    Burnett et al. 2018 is methodologically independent of the GBD IER model and provides the strongest alternative concentration-response framework. Burnett is also a co-author on Pope et al. 2002, but the GEMM uses 41 additional cohorts beyond the ACS CPS-II study.
  5. [5] US Environmental Protection Agency — Integrated Science Assessment for Particulate Matter
    Integrated Science Assessment for Particulate Matter
    Statistic
    EPA concludes there is a causal relationship between long-term PM2.5 exposure and total (non-accidental) mortality
    Excerpt
    “"The body of evidence is sufficient to conclude that a causal relationship exists between long-term PM2.5 exposure and total (non-accidental) mortality, including cardiovascular and respiratory mortality, as well as lung cancer mortality." ”
    Source data from
    2019-12-01
    Accessed
    2026-04-18 · archived copy
    Calculation
    The EPA ISA is the regulatory basis for US National Ambient Air Quality Standards (NAAQS) for PM2.5 and represents the most comprehensive US institutional assessment of the PM2.5-mortality evidence. EPA's regulatory impact analyses have estimated 100,000+ premature deaths per year at current US ambient PM2.5 levels using Pope et al. and subsequent cohort concentration-response coefficients. This is the domestic institutional anchor for the native figure.
    Independence
    EPA ISA is an independent institutional review but draws heavily on Pope et al. 2002 and subsequent ACS CPS-II reanalyses for its concentration-response functions. Treat as an authoritative institutional endorsement rather than a fully independent line of evidence.

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