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Perceived fear vs. actual probability

What are the odds that microplastics in food, water, or air will harm your health?

Health · reviewed 2026-06-14

What are the odds that microplastics in food, water, or air will harm your health?

Evidence quality 4.88/5

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
5/5
D4 Uncertainty
5/5
D5 Scope
5/5
D6 Prose
5/5
D7 Perception honesty
5/5
D8 Caveat completeness
5/5
Average 4.88/5
Direct evidence
Source No reliable estimate
A single water glass on a plain surface with faint translucent particles suspended inside, flat vector illustration.
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The gap between fear and evidence on microplastics is wide, but it runs in an unusual direction: the fear is not that the science says microplastics are safe — it is that the science does not yet say much of anything actionable. The WHO’s 2019 review of microplastics in drinking water found “no reliable evidence” of health risk at current exposure levels. EFSA, after reviewing over 100 studies, has not issued a quantified risk figure and does not expect to complete its formal opinion until end of 2027. No epidemiological cohort has measured attributable human disease from dietary or airborne microplastic exposure at general-population levels. The entry carries no_reliable_estimate not because the risk is known to be zero, but because no one has measured it well enough to put a number on it.

What drives the fear is a detection-equals-danger heuristic. Leslie et al. (2022) found microplastic particles in 77% of human blood samples — a genuine and striking finding that proves systemic exposure. Ragusa et al. found them in placentas. Marfella et al. (2024), published in the NEJM, reported that patients with detectable micro- and nanoplastics in carotid artery plaque had a 4.5-fold higher rate of cardiovascular events than those without. But Marfella’s cohort was pre-selected (all had asymptomatic carotid disease requiring surgery), the study lacked anticontamination controls in the operating environment, and association in a diseased population is not causation in the general public. Meanwhile, the “credit card per week” exposure claim that anchored public perception has been shown to overestimate actual ingestion by one to two orders of magnitude — realistic estimates land around 0.01-0.1 grams per week, not 5 grams.

The number does not exist yet, and that matters more than any placeholder would. Occupational exposure (textile and plastics workers inhaling synthetic fibers at industrial concentrations) has a thin but real evidence base for respiratory effects, though confounded by co-exposures. Heavy seafood consumers ingest more particles via shellfish bioaccumulation. Bottled water delivers roughly 10-100x more particles per liter than tap water. None of these exposure gradients have been tied to measurable health outcomes in humans. The field is pre-epidemiological: we know exposure is universal, we suspect biological plausibility from animal and in-vitro models, and we have one provocative but methodologically contested association study. That is not nothing, but it is not a probability either.

Microplastics turn up in human blood, lungs, and placentas, and a majority of adults rank them among top food-safety worries. But the WHO found no reliable evidence that microplastics at current exposure levels harm health. Detection is not the same as a measured 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 — Microplastics in Drinking-Water
    Microplastics in Drinking-Water

    See all 3 Likelier entries citing this source →

    Statistic
    No reliable evidence that microplastics in drinking water at current exposure levels pose a risk to human health
    Excerpt
    “"Based on the limited information we have, microplastics in drinking water don't appear to pose a health risk at current levels. But we need to find out more." ”
    Source data from
    2019-08-22
    Accessed
    2026-04-18 · archived copy
    Calculation
    WHO reviewed all available evidence on microplastic occurrence in drinking water (tap and bottled) and assessed potential health impacts from ingestion. The report concluded that particles larger than 150 micrometres are unlikely to be absorbed, uptake of smaller particles is expected to be limited, and no epidemiological data link drinking-water microplastic exposure to adverse health outcomes. WHO called for more research but did not identify a quantifiable risk, supporting the no_reliable_estimate classification.
    Independence
    WHO review synthesised global evidence independently of the Marfella, Leslie, and EFSA analyses cited below.
  2. [2] New England Journal of Medicine / Marfella et al. — Microplastics and Nanoplastics in Atheromas and Cardiovascular Events
    Microplastics and Nanoplastics in Atheromas and Cardiovascular Events
    Statistic
    Patients with detectable MNPs in carotid plaque had HR 4.53 (95% CI 2.00-10.27) for composite cardiovascular endpoint vs those without
    Excerpt
    “"Patients in whom microplastics and nanoplastics were detected within the atheroma had a higher risk of a composite of myocardial infarction, stroke, or death from any cause than those in whom microplastics and nanoplastics were not detected." ”
    Source data from
    2024-03-07
    Accessed
    2026-04-18 · archived copy
    Calculation
    Marfella et al. prospectively followed 257 patients who underwent carotid endarterectomy and analyzed excised plaque for MNPs via pyrolysis-GC/MS. Polypropylene was detected in 58.4% of plaques; PVC in 12.1%. After 34 months, the MNP-positive group had significantly higher cardiovascular events. However, this is an observational study in a high-risk surgical cohort (all had asymptomatic carotid disease), and critics note no pre-analytical anticontamination procedures were used — the surgical environment itself contains PE and PVC. The study demonstrates association in a diseased population, not causation in the general public, and cannot be converted to a population-level attributable risk.
    Independence
    Prospective clinical cohort study by Italian researchers using pyrolysis-GC/MS on excised plaque tissue; independent of WHO review and Leslie blood-detection study.
  3. [3] Environment International / Leslie et al. — Discovery and quantification of plastic particle pollution in human blood
    Discovery and quantification of plastic particle pollution in human blood
    Statistic
    Microplastics detected in 17 of 22 (77%) healthy adult blood samples at mean concentration of 1.6 µg/mL
    Excerpt
    “"This is the first study to report quantitative data on plastic particle pollution in human blood, showing that plastic particles are bioavailable for uptake into the human bloodstream." ”
    Source data from
    2022-03-24
    Accessed
    2026-04-18 · archived copy
    Calculation
    Leslie et al. analyzed blood from 22 healthy Dutch volunteers using pyrolysis-GC/MS for five high-production polymers. PET was the most prevalent (50% of samples), followed by polystyrene (36%) and PE (23%). The study proves systemic exposure (detection) but does not measure health outcomes. No dose-response relationship, no disease endpoint, no follow-up. Detection of a substance in blood is a necessary but not sufficient condition for harm — the dose, persistence, and biological activity all remain unquantified for general-population microplastic exposure. This study is included because it is the most-cited driver of public fear, illustrating the detection-equals-danger heuristic.
    Independence
    Dutch laboratory study using independent pyrolysis-GC/MS methodology on volunteer blood samples; no overlap with the Marfella clinical cohort or WHO/EFSA reviews.
  4. [4] Nature Medicine / Nihart et al. — Bioaccumulation of microplastics in decedent human brains
    Bioaccumulation of microplastics in decedent human brains
    Statistic
    MNP concentration 7-30x higher in brain (median ~4900 µg/g) than liver/kidney; rose ~50% from 2016 to 2024; up to 10x higher in brains with documented dementia
    Excerpt
    “"Concentrations in decedent brain samples were 7 to 30 times higher than in the liver or kidney... brain tissue from people who had been diagnosed with dementia had up to 10 times as much plastic in their brains as everyone else... the study design cannot show whether higher levels of plastic in the brain caused the dementia symptoms — they may simply accumulate more due to the disease process itself." ”
    Source data from
    2025-02-03
    Accessed
    2026-06-14
    Calculation
    Nihart et al. applied pyrolysis-GC/MS (corroborated by FTIR and electron microscopy) to >50 autopsy samples from the Albuquerque medical examiner, from decedents in 2016 and 2024. Brain MNP load (predominantly polyethylene, largely nanoscale shard-like fragments) far exceeded liver and kidney, and rose ~50% across the eight-year window. Brains with a documented dementia diagnosis showed up to 10x more plastic, concentrated in cerebrovascular walls and immune cells. This is a cross-sectional autopsy series: the dementia association is explicitly correlation, not causation, and the authors flag reverse causation (impaired clearance / blood-brain-barrier breakdown in dementia could increase deposition). It quantifies tissue burden and its temporal rise, not attributable disease risk, so it does not change the no_reliable_estimate classification.
    Independence
    US autopsy-tissue study using pyrolysis-GC/MS plus FTIR and electron microscopy; methodologically independent of the WHO review, the Marfella plaque cohort, the Leslie blood study, and the EFSA assessment.
  5. [5] European Food Safety Authority — Microplastics and nanoplastics in food
    Microplastics and nanoplastics in food
    Statistic
    EFSA risk assessment on microplastics in food scheduled for completion by end of 2027; no quantified health risk established as of 2025
    Excerpt
    “"The European Parliament has requested EFSA to deliver a scientific opinion on the potential health risks posed by microplastics in food, water and air." ”
    Source data from
    2025-10-28
    Accessed
    2026-04-18 · archived copy
    Calculation
    EFSA's 2025 literature review of micro- and nanoplastic release from food contact materials analyzed over 100 studies (2015-2025) and concluded that while microplastic release from FCMs is real, current studies likely overestimate quantities, and nanoplastic data remain insufficient for reliable exposure estimates. EFSA has not issued a quantified risk figure. Their formal scientific opinion is not expected until end of 2027. The absence of an EFSA opinion after years of review is itself evidence of the epistemic gap — not of safety, but of insufficient data to quantify risk in either direction.
    Independence
    EFSA risk assessment is an independent EU regulatory review, methodologically separate from the WHO 2019 review and from individual primary studies.
  6. [6] Current Opinion in Food Science / Hussain et al. — Ingested Microplastics: Do Humans Eat One Credit Card per Week?
    Ingested Microplastics: Do Humans Eat One Credit Card per Week?
    Statistic
    The widely cited 5g/week estimate overestimates ingestion by several orders of magnitude; realistic estimates are 0.01-0.1g/week
    Excerpt
    “"Our analysis suggests that the widely reported figure of 5 g per week overestimates microplastic ingestion by several orders of magnitude." ”
    Source data from
    2022-12-01
    Accessed
    2026-04-18 · archived copy
    Calculation
    Hussain et al. critically reviewed the 2019 University of Newcastle/WWF study that generated the "credit card per week" claim. The 5g figure was the extreme upper bound of a 0.1-5g range, and the underlying methodology conflated particle counts with mass in ways that inflate estimates. More careful analyses suggest typical adult ingestion is roughly 0.01-0.1g per week — still nonzero, but 50-500x lower than the headline figure. This matters because the perceived threat level is anchored to an exposure estimate that is almost certainly wrong by orders of magnitude.
    Independence
    Critical reanalysis of the WWF/Newcastle exposure estimate by independent food-science researchers; not affiliated with WHO, EFSA, or the original 2019 study authors.

443 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 Skipping care over ICE fear — 1 in 7.1 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 Anxiety disorder — 1 in 3.2 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 Child head lice — 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 Currency collapse — 1 in 5.6 Visa overstay deportation — 1 in 5.6 Subprime auto-loan repossession — 1 in 5.0 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 BNPL missed payment — 1 in 2.4 Divorce — 1 in 2.4 Burst pipe damage — 1 in 2.2 Workplace bullying — 1 in 2.1 Prolonged grid blackout — 1 in 2.0 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 Drug overdose — 1 in 56 Gas-stove asthma in a child — 1 in 50 Cat litter toxoplasmosis — 1 in 48 Mental health LTD claim — 1 in 45 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 PTSD — 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 Keyless relay car theft — 1 in 13 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 Child swallows object (ER) — 1 in 91 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 Losing SNAP under 2025 work rules — 1 in 18 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 NAION (Ozempic) — 1 in 909 Infant pool submersion — 1 in 800 MS — 1 in 769 Workplace fatality — 1 in 690 Typhoid fever — 1 in 654 GLP-1 anesthesia aspiration — 1 in 613 Unsafe imported products — 1 in 565 Brain aneurysm — 1 in 400 COVID-19 — 1 in 400 Fireworks injury — 1 in 385 Too much caffeine — 1 in 366 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 Heat-triggered preterm birth — 1 in 200 Skipping daily showers — 1 in 200 Not scrubbing feet — 1 in 200 Marrow donation risk — 1 in 167 Tick-borne encephalitis — 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 109 HIV diagnosis — 1 in 105 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 709 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 Homicide — 1 in 339 Police duty death — 1 in 313 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 Student visa revocation — 1 in 263 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 Child nicotine-pouch ingestion — 1 in 7,937 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 Listeria from deli meat — 1 in 6,061 Serious E. coli from fresh produce — 1 in 4,831 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 Flu brain swelling in a child (IAE/ANE) — 1 in 100,000 Fatal bee/wasp sting — 1 in 76,923 Locally-acquired dengue (continental US) — 1 in 66,667 Anesthesia death — 1 in 50,000 Dog hot car death — 1 in 41,667 Vibrio vulnificus wound infection — 1 in 32,051 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 Post-crash car fire — 1 in 25,000 Railroad crossing death — 1 in 20,704 Car submersion — 1 in 16,667 Child bike trailer — 1 in 14,286 Runway near-miss — 1 in 13,699 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 Post-hurricane heat death — 1 in 20,000 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 Lead-tainted cinnamon pouch — 1 in 40,000 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 Death in ICE custody — 1 in 17,065 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

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