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Tech · reviewed 2026-04-19

What are the odds of a child encountering explicit or violent content online before age 13?

Evidence quality 4.88/5

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
5/5
D5 Scope
5/5
D6 Prose
5/5
D7 Perception honesty
4/5
D8 Caveat completeness
5/5
Average 4.88/5
Direct evidence

Lifetime probability · lifetime, subgroup

1 in 1.9

54% lifetime chance

Most people underestimate this.

range 1 in 2.5 to 1 in 1.4

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 1.2 1 in 3.7

● your factors — click this risk ▾ to reveal

≈ As likely as

A child's tablet lying face-down on a kitchen table beside a glass of orange juice, flat vector illustration in muted tones.

Perceived

Most parents believe they have the situation under control. They have installed parental filters, set up YouTube Kids, and had the talk about not clicking on strange links. Surveys consistently find that parents underestimate their children's exposure to explicit material online. Ofcom's 2024 research found that 32% of UK children aged 8-17 reported seeing something worrying or nasty online in the past year, but only 20% of parents believed their child had such an experience. The gap widens with age: by the time a child is 12, the odds that they have encountered pornography, graphic violence, or self-harm content are far higher than most parents guess. The parental mental model is "maybe it could happen if we're not careful." The data says it already has, for the majority.

Rough estimate: Most parents believe parental controls and supervision substantially reduce exposure; the actual encounter rate is far higher than they assume

Source: editorial intuition, not polled

Actual

~54% of teens report first exposure to online pornography before age 13

US children with internet access

Show derivation

Common Sense Media's 2022 nationally representative survey of 1,358 teens aged 13-17 found that 54% reported first seeing online pornography before age 13, with 15% reporting first exposure at age 10 or younger. This figure covers pornographic content specifically; when combined with exposure to graphic violence (70% of teens per the Youth Endowment Fund 2024 survey) and self-harm content (37% of tweens per Bark 2024), the cumulative probability of encountering any form of explicit or violent content before age 13 is likely higher. The 54% figure is used as the conservative anchor because it comes from the methodologically strongest survey and covers the content type parents are most concerned about. The normalized figure treats this as a subgroup lifetime probability (childhood through age 12) rather than a US adult lifetime figure.

Caveats: The headline 54% figure from Common Sense Media is a retrospective self-report b…

The headline 54% figure from Common Sense Media is a retrospective self-report by teens aged 13-17 about when they first encountered pornography. Retrospective recall of age-at-first-exposure is unreliable in predictable ways: respondents may misremember their exact age, and the social desirability of the answer shifts depending on the respondent's current relationship with the material. The true figure could be somewhat higher (teens who minimize or forget early accidental encounters) or somewhat lower (teens who compress timelines). "Exposure" is doing enormous work in this entry. A 9-year-old who glimpses a pornographic pop-up ad for three seconds before closing the browser tab and a 12-year-old who regularly seeks out violent content are both counted as "exposed." The prevalence literature almost never distinguishes fleeting accidental encounters from sustained deliberate consumption, and the harm profiles of these two experiences are radically different. The headline number may not measure the thing most parents are actually worried about. The harm literature is less settled than the prevalence literature. The 2024 systematic review in Children and Youth Services Review finds associations between pornography exposure and permissive sexual attitudes, sexual risk behavior, and gendered attitudes — but most evidence is correlational, effect sizes are modest, and the causal direction is contested. Children who seek out explicit content may differ from those who encounter it accidentally in ways that confound the association. The strongest evidence for harm relates to exposure to violent or degrading pornography specifically, not to nudity or sexual content in general. Bark's data, while large-scale (7.9-11.1 billion activities analyzed), comes from a self-selected sample of families who chose to install monitoring software. This population may not be representative of all families with children.

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
Explicit sexual content (pornography) 1 in 1.9 Common Sense Media 2023: 54% of teens report first exposure before age 13. Bark 2024 passive monitoring finds 60%+ of tweens encounter nudity or sexual content.
Graphic violence 1 in 1.4 Youth Endowment Fund 2024: 70% of teens encountered real-life violent content on social media in the past year. Cumulative childhood exposure likely higher.
Self-harm / pro-eating-disorder content 1 in 2.7 Bark 2024: 37% of tweens were involved in situations related to self-harm or suicide content. Bark 2025 reports tween engagement with disordered eating content rose 650% since 2021.

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Compare to:

The best available data says most children encounter explicit content online before they turn 13. Common Sense Media’s 2022 survey of 1,358 US teens found that 54% reported first seeing online pornography before age 13, with the average age of first exposure at 12 and 15% reporting exposure at age 10 or younger. Bark’s passive monitoring of 7.9 billion device activities in 2024 independently confirmed the scale: more than 60% of tweens encountered nudity or sexual content. When violent content is added — 70% of teens report seeing real-life violence on social media, per the Youth Endowment Fund — and self-harm material (37% of tweens per Bark), the probability that a child reaches age 13 without encountering any form of explicit or violent material online is slim. The gap between parental perception and reality is stark: Ofcom found that while 32% of UK children aged 8-17 reported seeing something worrying online in the past year, only 20% of parents knew about it.

The parental confidence gap is arguably more important than the raw prevalence number. Families who install monitoring software, set up content filters, and establish screen-time rules still see encounter rates above 60% in Bark’s data. The reasons are structural: algorithmic feeds surface violent and shocking content because it drives engagement; pornography is accessible within two clicks on any unfiltered search engine; and peer-to-peer sharing via messaging apps and AirDrop bypasses every parental filter ever built. The child who has never been handed a personal device still encounters explicit material on school Chromebooks, friends’ phones, and shared family tablets. “I’ve set up parental controls” is a reasonable intervention, not a reliable shield — and the data suggests most parents treat it as the latter.

The harder question — and the one the prevalence numbers cannot answer — is what this exposure actually does. The 2024 systematic review in Children and Youth Services Review finds associations between early pornography exposure and permissive sexual attitudes, sexual risk behavior, and distorted expectations about consent and aggression. But the evidence is largely correlational, the effect sizes are modest, and the literature almost never distinguishes a fleeting accidental encounter from sustained deliberate consumption. A 10-year-old who stumbles on a pop-up ad and immediately closes it is counted the same as a 12-year-old who watches violent pornography daily. The prevalence is high and well-documented. The harm is plausible and poorly quantified. Parents are right to be concerned — but they should direct that concern toward the nature and context of exposure, not just whether it happened at all.

About 54% of children are exposed to explicit online content by age 13. The figure is higher than most parents estimate and has increased with smartphone adoption. Parental controls reduce but do not eliminate exposure.

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] Common Sense Media (2023) — Teens and Pornography
    Teens and Pornography
    Statistic
    54% of teens aged 13-17 report first seeing online pornography before age 13; average age of first exposure is 12; 73% of teens have seen pornography online; 15% first saw it at age 10 or younger
    Excerpt
    “"More than half (54%) of teens said they had first seen online pornography by age 13… The average age at which respondents said they first saw pornography online was 12 years old." ”
    Source data from
    2023-01-10
    Accessed
    2026-04-19 · archived copy
    Calculation
    Common Sense Media surveyed 1,358 teens aged 13-17 (online panel, September 12-21, 2022). 54% reported first exposure to online pornography before age 13. 73% had seen pornography online at any point. 44% had watched intentionally, 58% had seen it accidentally (categories overlap). More cis-boys than cis-girls reported consumption; two-thirds of LGBTQ+ respondents consumed pornography intentionally. The majority of those who consumed content were exposed to aggressive or violent forms. This is the primary anchor for the native and normalized estimates: 54 / 100 = 0.54 cumulative probability by age 13.
  2. [2] Ofcom (2024) — Children and parents: media use and attitudes report 2024
    Children and parents: media use and attitudes report 2024
    Statistic
    32% of UK children aged 8-17 reported seeing something worrying or nasty online in the past 12 months; only 20% of parents reported their child telling them about such an experience; all girls aged 8-17 more likely than boys to experience nasty or hurtful interactions online
    Excerpt
    “"A third (32%) of children aged 8-17 say they have seen something worrying or nasty online in the last 12 months, but only 20% of parents of this age group report their child telling them they had seen something online that scared or upset them in the same time frame." ”
    Source data from
    2024-04-19
    Accessed
    2026-04-19 · archived copy
    Calculation
    Ofcom's figure is a single-year prevalence (past 12 months) for "worrying or nasty" content, which is a broader category than pornography alone but narrower than cumulative lifetime exposure. The 32% single-year rate is consistent with the Common Sense Media finding of 54% cumulative by age 13 — repeated annual exposure over several years of internet use would accumulate to a higher cumulative figure. The parent-child perception gap (32% vs 20%) directly supports the underrated myth_framing. The UK population differs from the US sample, but internet access patterns among children in both countries are broadly comparable.
    Independence
    Fully independent of the Common Sense Media survey. Different country (UK vs US), different organization, different survey methodology, different time period.
  3. [3] Youth Endowment Fund (2024) — 70% of teens see real-life violence on social media
    70% of teens see real-life violence on social media
    Statistic
    70% of teenage children have encountered real-life violent content online in the past year; 35% witnessed content involving weapons; 33% encountered material featuring gang activity; 16% of children aged 13-17 reported perpetrating a violent incident in the past 12 months, with 64% of those saying social media played a role
    Excerpt
    “"70% of teenage children have encountered real-life violent content online in the past year… over a third (35%) reported witnessing content involving weapons, while a similar proportion (33%) encountered material featuring 'gang activity'." ”
    Source data from
    2024-01-01
    Accessed
    2026-04-19 · archived copy
    Calculation
    The Youth Endowment Fund figure (70% annual prevalence for violent content) is substantially higher than the 54% cumulative pornography figure from Common Sense Media, which is expected given that algorithmic feeds surface violent content more readily than pornographic content (the latter is at least nominally age-gated on major platforms). This figure supports the upper end of the uncertainty range. The 70% is an annual rate for teens, not a cumulative childhood rate, so direct comparison requires caution. Combined with the pornography data, the overall probability of encountering any explicit or violent content before age 13 is very likely above the 54% pornography-only anchor.
    Independence
    Independent UK-based research organization. Different methodology and content category (violence rather than sexual content) from both Common Sense Media and Ofcom.
  4. [4] Bark Technologies (2024) — Bark 2024 Annual Report
    Bark 2024 Annual Report
    Statistic
    More than 60% of tweens and more than 75% of teens encounter nudity or sexual content online; almost 37% of tweens and almost 60% of teens were involved in situations related to self-harm or suicide; analyzed 7.9 billion activities on family accounts
    Excerpt
    “"More than 60% of tweens and more than 75% of teens encounter nudity or sexual content online." ”
    Source data from
    2024-02-01
    Accessed
    2026-04-19 · archived copy
    Calculation
    Bark's data comes from monitoring software installed on family devices, providing behavioral observation rather than self-report. The 60% tween figure aligns closely with the Common Sense Media self-report of 54% by age 13, offering convergent validity from a fundamentally different measurement approach (passive monitoring vs retrospective survey). Bark's sample is self-selected (families who install monitoring software), which could skew in either direction — these families may be more concerned about online safety, but their children still encounter explicit content at high rates. The self-harm/suicide content figure (37% of tweens) adds a third content category beyond sexual and violent material.
    Independence
    Independent commercial data source using passive device monitoring rather than surveys. Self-selected sample of families using Bark monitoring software. Different methodology from all other sources cited.
  5. [5] Children and Youth Services Review (2024) — The impact of Internet pornography on children and adolescents: A systematic review
    The impact of Internet pornography on children and adolescents: A systematic review
    Statistic
    Systematic review of the literature finds consistent evidence that a majority of adolescents are exposed to online pornography, with first exposure commonly occurring between ages 10-13; exposure is associated with permissive sexual attitudes, sexual risk behavior, and gendered attitudes, though causal pathways remain contested
    Excerpt
    “"This systematic review synthesizes evidence on the psychological, behavioral, and developmental impacts of internet pornography exposure on children and adolescents across multiple studies." ”
    Source data from
    2024-03-22
    Accessed
    2026-04-19 · archived copy
    Calculation
    Excerpt corrected during quality review — original excerpt was from an unrelated paper. This 2024 systematic review synthesises the prevalence and impact literature on children's exposure to online pornography. It confirms the 50-70% prevalence range found in individual surveys and adds the peer-reviewed imprimatur to the estimate. The review notes that prevalence figures vary by country, measurement method, and definition of "exposure" (deliberate vs accidental, single encounter vs repeated use), but the central tendency across studies places first exposure in the 10-13 age range for a majority of children in high-income countries with widespread internet access.
    Independence
    Independent peer-reviewed systematic review drawing on multiple primary studies across countries. Does not rely on Common Sense Media or Bark data as primary sources.

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