Skip to content
Likelier

Perceived fear vs. actual probability

What are the odds of a baby having a chromosomal disorder based on parental age?

Lifetime probability · subgroup

~1 in 200

per pregnancy at age 35 (any chromosomal abnormality)

0.5% lifetime chance

Most people overestimate this.

Scopes vary — shown as typical adult lifetime odds. See methodology.

Kids · reviewed 2026-04-19
Evidence quality 4.63/5

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
3/5
D4 Uncertainty
5/5
D5 Scope
5/5
D6 Prose
5/5
D7 Perception honesty
4/5
D8 Caveat completeness
5/5
Average 4.63/5
Source Peer-reviewed study · Nature
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 40 1 in 2,000

● your factors — click this risk ▾ to reveal

  1. Your factors
A single pair of small knitted booties resting on a plain light surface, flat vector illustration, muted colors.

Perceived

The phrase "geriatric pregnancy" — still used in clinical shorthand for anyone 35 or older — shapes perception more than any statistic. Surveys of pregnant women over 35 consistently find that most dramatically overestimate the probability of chromosomal abnormalities, with many believing the risk at 35 is "very high" or citing figures several times the actual rate. The cultural framing positions 35 as a cliff edge, when the underlying biology is a gentle, continuous slope that began climbing in the mid-20s.

Rough estimate: many women over 35 believe the risk is dramatically higher than it actually is

Source: editorial intuition, not polled

Actual

~1 in 350 live births with Down syndrome at maternal age 35

live births to mothers aged 35

Show derivation

Uses any clinically significant chromosomal abnormality at live birth for maternal age 35, estimated at approximately 1 in 200 (0.5%) from Hook 1981 and subsequent ACOG compilations. This is per pregnancy at that specific maternal age, not a lifetime cumulative figure. Down syndrome alone accounts for roughly 1 in 350 at age 35; the remainder includes trisomies 13 and 18, sex chromosome aneuploidies, and other structural abnormalities. The native rate (1 in 350) reflects Down syndrome specifically, which accounts for roughly half of all chromosomal abnormalities detected at age 35. The normalized figure (1 in 200) represents the combined probability of any chromosomal abnormality at this maternal age, as documented by Hook (1981). The figure applies to live births — many chromosomal abnormalities result in early miscarriage, so the conception rate is considerably higher.

Caveats: The age-35 threshold is a clinical convention from the 1970s when the risk of Do…

The age-35 threshold is a clinical convention from the 1970s when the risk of Down syndrome (~1/350) roughly equaled the procedural risk of amniocentesis-related miscarriage (~1/200-350). With modern NIPT offering >99% detection at <0.1% false positive, this cutoff is an artifact. Risk at any specific age applies to THAT pregnancy — it does not compound across pregnancies. Most chromosomal abnormalities result in early miscarriage, which is why miscarriage rates also rise with maternal age. Even at 45, the majority of live-born babies are chromosomally normal. Paternal age effects are real but much smaller than maternal age effects for chromosomal aneuploidies; paternal age primarily drives de novo point mutations (autism, achondroplasia) rather than nondisjunction. The figures here are for live births; midtrimester rates are approximately 20% higher because some affected pregnancies miscarry before term.

Related risks

Other risks on similar themes — for exploring related fears.

kids

Maternal mortality

What are the odds of dying from pregnancy-related causes?

kids

Baby walker injury

What are the odds an infant in a baby walker is treated in the emergency department for a walker-related injury?

kids

Walker stair fall

What are the odds an infant in a baby walker falls down a flight of stairs?

kids

Child death (<18)

What are the odds of a child dying before age 18 in the US?

kids

Child swallows object (ER)

What are the odds a young child swallows a non-food object and needs medical care?

kids

Infant fall

What are the odds of serious injury when an infant falls from furniture (sofa, bed, changing table)?

kids

Life-threatening birth (US)

What are the odds of a life-threatening complication during childbirth?

kids

Autism diagnosis

What are the odds of your child being diagnosed with autism spectrum disorder?

Compare to:

The risk of chromosomal abnormalities rises with maternal age, and the data behind the curve is among the best-characterized in clinical genetics. For Down syndrome specifically: roughly 1 in 1,250 at age 25, 1 in 350 at 35, 1 in 100 at 40, and 1 in 30 at 45. For all clinically significant chromosomal abnormalities combined, the figures are approximately twice as high — 1 in 200 at 35, 1 in 65 at 40. The curve is continuous, not a step function, climbing gradually from the early twenties with no biological cliff at any particular birthday. Even at 40, the probability that a given baby has Down syndrome is about 1% — which means 99% do not. At 45, where the fear is most acute, roughly 95% of live-born babies are chromosomally typical.

The perception gap traces largely to a single clinical threshold. In the 1970s, age 35 was chosen as the cutoff for offering amniocentesis because at that age the risk of Down syndrome (~1 in 350) roughly equaled the risk of the procedure itself causing a miscarriage (~1 in 200 to 1 in 350). The label “advanced maternal age” — and its blunter synonym, “geriatric pregnancy” — entered clinical vocabulary and never left. With the arrival of NIPT (non-invasive prenatal testing), which detects trisomy 21 with better than 99% sensitivity and a false-positive rate below 0.1%, the risk-benefit calculus that created the cutoff has evaporated. ACOG now recommends offering screening to all pregnant patients regardless of age. But the cultural residue persists: the number 35 looms larger in the popular imagination than any probability table warrants.

Paternal age is the quieter half of the story. Kong et al. demonstrated in 2012 that a father’s age at conception adds approximately two de novo point mutations per year to the offspring’s genome, with the mutation rate doubling roughly every 16.5 years. The conditions linked to this mechanism are different from the maternal-age trisomies: a 2017 meta-analysis put the adjusted autism spectrum disorder odds ratio at roughly 1.55 (95% CI 1.39-1.73) for the oldest paternal-age band, a 2010 meta-analysis found schizophrenia risk about two-thirds higher (RR 1.66, 95% CI 1.46-1.89) for fathers 50 and older versus fathers in their late twenties, and rare dominant conditions like achondroplasia and Apert syndrome are strongly paternal-age-dependent. The absolute risks remain small — the vast majority of children born to older fathers are unaffected — but the contrast with public awareness is stark. Maternal age dominates prenatal counseling conversations; paternal age is rarely mentioned at all.

At age 35, the probability of Down syndrome is about 1 in 350. That means 99.7% of pregnancies at that age are unaffected. The "geriatric pregnancy" label overstates what is, statistically, a small absolute risk.

The "35 cliff" originated from a 1970s cost-benefit analysis of amniocentesis, not biology. At 35, Down syndrome risk is 1 in 350. At 40, 99% of pregnancies are chromosomally normal. The cliff is administrative, not medical.

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.

4/6 sources independently verified verbatim against the cited source

  1. [1] American Academy of Family Physicians (AAFP) — Down Syndrome: Prenatal Risk Assessment and Diagnosis Verified
    Down Syndrome: Prenatal Risk Assessment and Diagnosis
    Statistic
    Risk of Down syndrome at age 25: 1/1,300; age 35: 1/365; age 45: 1/30. At age 35 the second-trimester prevalence of trisomy 21 (1/270) approaches the amniocentesis fetal-loss risk (1/200).
    Excerpt
    “"The risk of having a child with Down syndrome is 1/1,300 for a 25-year-old woman... at age 35, the risk increases to 1/365... At age 45, the risk of a having a child with Down syndrome increases to 1/30. At age 35, the second-trimester prevalence of trisomy 21 (1/270) approaches the estimated risk of fetal loss due to amniocentesis (1/200)." ”
    Source data from
    2000-08-15
    Accessed
    2026-04-19 · archived copy
    Verification
    Excerpt independently re-fetched and confirmed word-for-word against the cited source during our grounding audit.
    Calculation
    AAFP review article compiling Hook 1981 and Hecht & Hook 1996 age-specific rates. The article gives Down syndrome risk of 1/365 at age 35 (native headline rounded to ~1/350). Its 1/200 figure is the amniocentesis fetal-loss risk, NOT the chromosomal-abnormality rate — the normalized ~1/200 for any chromosomal abnormality at 35 comes from the Hook 1981 source below (5.6 per 1,000 = 1/179). These are livebirth rates; midtrimester amniocentesis rates are approximately 20% higher because some affected pregnancies miscarry between 16 weeks and term.
    Independence
    Review article synthesizing Hook 1981, Hecht & Hook 1996, and ACOG data. Dependent on the same upstream datasets as the Hook primary source below, but provides the clinical synthesis used in practice guidelines.
  2. [2] Obstetrics & Gynecology — Rates of chromosome abnormalities at different maternal ages
    Rates of chromosome abnormalities at different maternal ages
    Statistic
    Clinically significant chromosomal abnormalities rise from ~1/500 at age 20 to ~1/200 at 35, ~1/65 at 40, and ~1/20 at 45
    Excerpt
    “"The estimated rate of all clinically significant cytogenetic abnormalities rises from about 2 per 1000 at the youngest maternal ages to about 5.6 per 1000 at age 35, 15.8 per 1000 at age 40, and 53.7 per 1000 at age 45." ”
    Source data from
    1981-12-01
    Accessed
    2026-04-19 · archived copy
    Calculation
    Hook EB 1981 — the foundational dataset for maternal-age-specific chromosomal abnormality rates at livebirth, derived from large cytogenetic surveys. Rates per 1,000: age 20 ~2.0 (1/500), age 30 ~2.6 (1/385), age 35 ~5.6 (1/179), age 40 ~15.8 (1/63), age 45 ~53.7 (1/19). These remain the standard reference tables cited by ACOG and used in prenatal screening risk calculations.
    Independence
    Primary cytogenetic survey data — the upstream source for most subsequent compilations including ACOG practice bulletins and the AAFP review.
  3. [3] Nature — Rate of de novo mutations and the importance of father's age to disease risk
    Rate of de novo mutations and the importance of father's age to disease risk
    Statistic
    Each additional year of paternal age adds ~2 de novo mutations; rate doubles every 16.5 years
    Excerpt
    “"The diversity in mutation rate of single nucleotide polymorphisms is dominated by the age of the father at conception. The effect is an increase of about two mutations per year." ”
    Source data from
    2012-08-22
    Accessed
    2026-04-19 · archived copy
    Calculation
    Kong et al. 2012 — whole-genome sequencing of 78 Icelandic trios. Average de novo rate 1.20 x 10^-8 per nucleotide per generation at mean paternal age 29.7. Exponential model: paternal mutations double every 16.5 years. Used for the paternal age context in the body text. This study does not directly provide chromosomal abnormality rates but established the mechanistic basis for paternal-age effects on de novo point mutations.
    Independence
    Icelandic whole-genome sequencing study — entirely independent methodology and population from the maternal-age cytogenetic surveys. Addresses a different mutation mechanism (de novo SNVs vs. chromosomal nondisjunction).
  4. [4] Acta Psychiatrica Scandinavica (Wu S, Wu F, Ding Y, Hou J, Bi J, Zhang Z) — Advanced parental age and autism risk in children: a systematic review and meta-analysis Verified
    Advanced parental age and autism risk in children: a systematic review and meta-analysis
    Statistic
    Adjusted OR 1.55 (95% CI 1.39-1.73) for autism spectrum disorder in offspring in the oldest paternal-age category
    Excerpt
    “"The highest parental age category was associated with an increased risk of autism in the offspring, with adjusted ORs ... 1.55 (95% CI 1.39-1.73) for father." ”
    Source data from
    2017-01-01
    Accessed
    2026-07-03 · archived copy
    Verification
    Excerpt independently re-fetched and confirmed word-for-word against the cited source during our grounding audit.
    Calculation
    Meta-analysis pooling multiple cohort studies on parental age and autism risk. Grounds the body-text claim of a modestly elevated (~1.5x) autism odds ratio for children of older fathers — a mechanism (de novo point mutation burden) distinct from the maternal-age chromosomal-nondisjunction pathway that is this entry's primary subject.
    Independence
    Independent systematic review and meta-analysis of parental-age-and-autism cohort studies; unrelated methodologically to the Kong et al. 2012 de novo mutation-rate study also cited in this entry.
  5. [5] Schizophrenia Bulletin (Miller B, Messias E, Miettunen J, et al.) — Meta-analysis of Paternal Age and Schizophrenia Risk in Male Versus Female Offspring Verified
    Meta-analysis of Paternal Age and Schizophrenia Risk in Male Versus Female Offspring
    Statistic
    RR 1.66 (95% CI 1.46-1.89) for schizophrenia in offspring of fathers aged 50 or older versus fathers aged 25-29
    Excerpt
    “"The relative risk (RR) in the oldest fathers (aged 50 or older) was 1.66 [95% confidence interval (95% CI): 1.46-1.89, P < 0.01]." ”
    Source data from
    2010-01-01
    Accessed
    2026-07-03 · archived copy
    Verification
    Excerpt independently re-fetched and confirmed word-for-word against the cited source during our grounding audit.
    Calculation
    Meta-analysis of cohort and case-control studies on paternal age and schizophrenia risk in offspring. The pooled RR of 1.66 for the oldest father band is the figure used in the body text, replacing an earlier unsourced "risk roughly triples" claim that overstated the best available meta-analytic estimate.
    Independence
    Independent meta-analysis of paternal-age-and-schizophrenia cohort/case-control studies; distinct methodology and outcome from the Kong et al. 2012 mutation-rate study and the Wu et al. 2017 autism meta-analysis also cited in this entry.
  6. [6] Obstetrics & Gynecology (American College of Obstetricians and Gynecologists) — Screening for Fetal Chromosomal Abnormalities: ACOG Practice Bulletin, Number 226 Verified
    Screening for Fetal Chromosomal Abnormalities: ACOG Practice Bulletin, Number 226
    Statistic
    ACOG recommends that both screening and diagnostic testing options for fetal chromosomal abnormalities be offered to all pregnant patients regardless of maternal age or baseline risk
    Excerpt
    “"All patients should be offered both screening and diagnostic tests, and all patients have the right to accept or decline testing after counseling." ”
    Source data from
    2020-10-01
    Accessed
    2026-07-03 · archived copy
    Verification
    Excerpt independently re-fetched and confirmed word-for-word against the cited source during our grounding audit.
    Calculation
    ACOG Practice Bulletin No. 226 (Obstetrics & Gynecology, October 2020) formally updated prenatal aneuploidy screening guidance to recommend offering both screening and diagnostic testing to all pregnant patients regardless of maternal age, superseding the historical age-35 threshold discussed in the body text and caveats. Grounds the body-text claim that "ACOG now recommends offering screening to all pregnant patients regardless of age."
    Independence
    Professional-society clinical practice guideline; synthesizes but is methodologically distinct from the Hook 1981 cytogenetic survey and the AAFP review also cited in this entry.

434 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 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 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 Job loss & depression — 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 Silent hypertension — 1 in 2.7 Drug-resistant infection — 1 in 2.6 No marrow match — 1 in 2.4 Nursing home admission — 1 in 2.2 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 LTC need after 65 — 1 in 1.8 Widowhood probability — 1 in 1.7 Unprotected sex — 1 in 1.5 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 At-fault injury crash — 1 in 2.9 Deer collision — 1 in 2.7 Car-crash injury — 1 in 2.6 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 2.3 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 9.8 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 Iron gap (women) — 1 in 3.9 Vitamin D gap — 1 in 2.9 Magnesium gap — 1 in 1.9 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 Housing crash — 1 in 8.3 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 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 1.7 Identity theft — 1 in 1.7 Credit card fraud — 1 in 1.5 School bullying — 1 in 1.5 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 Problem-tenant loss — 1 in 1.8 LASIK complications — 1 in 100 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 Wisdom-tooth surgery — 1 in 22 Dental tourism complication — 1 in 20 Elderly abandonment — 1 in 20 Parkinson's — 1 in 20 Pet parasites — 1 in 20 Undiagnosed ADHD — 1 in 20 Adult-onset food allergy — 1 in 19 Non-Alzheimer's dementia — 1 in 17 Cannabis use disorder — 1 in 16 Stroke — 1 in 15 PTSD — 1 in 15 Severe hearing loss — 1 in 14 Type 2 diabetes — 1 in 13 Appendicitis — 1 in 13 Indoor cooking smoke — 1 in 13 Untreated depression — 1 in 13 Soda and diabetes — 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 Parent death/disability — 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 26 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 Unbelted crash death — 1 in 53 Speeding 20% over limit — 1 in 50 Motorcycle no helmet — 1 in 45 Spaceflight (astronaut) — 1 in 42 Video watching + driving — 1 in 32 Child crash injury — 1 in 27 Drowsy driving — 1 in 26 Cruise ship norovirus — 1 in 24 E-scooter injury — 1 in 10 Pickpocketed while traveling — 1 in 38 Catalytic converter theft — 1 in 37 Knife-involved 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 Restaurant food poisoning — 1 in 58 B12 deficiency — 1 in 28 Vegetarian deficiency — 1 in 14 Intimate deepfake — 1 in 25 Social media problematic use — 1 in 13 Child swallows object (ER) — 1 in 91 Life-threatening birth (US) — 1 in 61 Childbirth death (SSA) — 1 in 55 Toddler stair fall — 1 in 37 Co-sleeping death — 1 in 36 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 Dying without heir — 1 in 100 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 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 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 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 159 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 357 Homicide — 1 in 339 Pig-butchering scam — 1 in 106 Extreme heat — 1 in 333 Climate change death — 1 in 204 Bat bite & rabies — 1 in 278 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 Infant fall — 1 in 500 Baby walker injury — 1 in 455 Maternal mortality — 1 in 272 Maternal age & birth defects — 1 in 200 Child death (<18) — 1 in 103 Caving career death — 1 in 167 EMS duty death — 1 in 909 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 Lightning home fire — 1 in 461 Wildfire home destruction — 1 in 120 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 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 Fish bone injury — 1 in 1,429 Phone/laptop battery fire — 1 in 4,545 Laundry pod ingestion — 1 in 6,494 Pool drowning — 1 in 5,882 Untreated infant hip dysplasia — 1 in 5,000 SIDS — 1 in 2,398 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 45,662 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 Post-crash car fire — 1 in 25,000 Railroad crossing death — 1 in 20,576 Car submersion — 1 in 16,667 Child bike trailer — 1 in 14,286 Runway near-miss — 1 in 13,699 Acid attack — 1 in 94,340 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 Bee sting — 1 in 78,927 Swallowed bee/wasp — 1 in 29,155 Fatal scorpion sting — 1 in 26,110 Dog chocolate death — 1 in 13,889 Lead-tainted cinnamon pouch — 1 in 40,000 Plastic container leaching — 1 in 16,949 Infant car-seat asphyxia — 1 in 64,935 Bouncer chair fall — 1 in 60,606 Toddler choking — 1 in 50,000 Unsupervised infant choking — 1 in 50,000 Forward-facing toddler death — 1 in 26,738 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 Ferry sinking — 1 in 133,333 Turbulence injury — 1 in 114,943 School shooting — 1 in 192,308 Mass shooting — 1 in 113,636 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 Crocodile attack — 1 in 337,838 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 Infant swing death — 1 in 714,286 Whole-grape choking — 1 in 625,000 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 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
Lottery jackpot 1 in 95,238

Recently viewed on this device