United States · Ages 0–19 · 1968–2025
A unique story influenced by firearms, ethnicity, and urbvanicity.
Suicides are expressed as "# per 100,000 per year," but in some jurisdictions this means that we are converting very small numbers into rates (14/400,000 population, for example). Because of this, small changes in numbers of death can create 'bumpy' rate charts. The whole purpose of the confidence intervals and statistical significance on this page is to help you understand what is simply noise and what may be a true change.
This chart groups age "0-19" suicides, but it's important to note that 0-19 is really not what we are looking at. Suicides under 10 are extremely rare (<1 per million person years), and suicide rates increase with age all the way to age 19. So the "pool" of 0-19 is describing 19 year old suicides (12.3 per 100,000) more than it's describing 10 year old suicides (0.4 per 100,000), by a large margin. It is best to think of the "0-19" number as including young children but mostly being older adolescents.
Be cautious comparing jurisdictions like states or countries; there are huge differences in culture, methods available, ethnicity, poverty, and other variables. It's even been shown that religious coroners are less likely to adjudicate findings of suicide than non-religious coroners!
Female: In 2025, the rate was 2.18 per 100,000 per year. The fitted trend has been rising 2.1% a year since 2016 (95% CI +1.4% to +2.8%); across 2001–2025 the model finds 2 changes of direction. Male: In 2025, the rate was 4.89 per 100,000 per year. The fitted trend has been falling 2.3% a year since 2018 (95% CI −2.9% to −1.7%); across 2001–2025 the model finds 3 changes of direction.
I've created two maps here - one shows the raw rate of suicide for the full states. However, it's important to remember that urbanicity and ethnicity - two huge correlates with suicide rate - are variable state by state. the "Like for like" view extracts the suicide rate for all white, non-Hispanic, metro youth. If you are comparing states and want to control for known correlates, this is a much superior map.
Comparing very different demographics
White, non-Hispanic, metro only
Group states and test them against each other
Montana runs at 10.72 per 100,000 per year and New Jersey at 1.42 — a 7.5× difference between the highest and lowest states. The national figure over the same window is 3.35. A national number describes no state in particular, and the states at the top of this map are the ones with the largest American Indian and Alaska Native populations and the most children living outside metropolitan areas. Which raises the obvious question, and the next tab is the answer to it.
Holding demography still barely narrows the gap. Among White non-Hispanic children in metropolitan counties, Wyoming runs at 9.37 per 100,000 per year against Rhode Island at 1.48 — still a 6.3× spread, against 7.5× for all children. Restricting to a single demographic group removes only about 16% of the difference between the highest and lowest states. Whatever is driving the variation between American states, most of it is not the composition of their populations.
Not shown: Connecticut, District of Columbia, Hawaii. Connecticut is absent from the published table; the District of Columbia and Hawaii hold fewer than 10 deaths in this group across seven years and may not be displayed.
Choose a bucket, then click states to put them in it. Clicking a state already in that bucket takes it out; clicking one from another bucket moves it across.
Put some states in a bucket to compare them.
Its full record since 1999, with the trend fitted to whatever resolution the state's numbers support.
Choose a state on either map. The record shown is always all children, since the like-for-like table is a single pooled figure with no year detail.
CDC WONDER, ages 0–19, computed from counts and population.
The like-for-like map restricts the data rather than standardising it: 2018–2024, single-race White not Hispanic, metropolitan counties only, no weighting and no reference population. Denominators are smoothed over 9 years and projected one year past the published estimates, which stop at 2024; death counts never are. CDC will not show a cell under 10 deaths, so each state pools into the narrowest run of consecutive years that clears it — 14 of 51 need more than one — by summing counts and person-time, never by averaging rates.
Deaths through 2020 are counted by the state the child lived in and from 2021 by the state the death occurred in, which is what CDC publishes for those years; the national totals of the two extracts agree exactly, year for year, so no death is added or lost and only its attribution to a state can move. The population estimates change vintage at 2020 as well, and the earlier years are scaled onto the current vintage using the overlap year, so that a re-basing cannot appear as a change in the rate.
Boys are more likely to die by firearm suicide. Hence the sharpest urbanization trends are in boys. Exclude firearm suicides and most of the trend goes with them... what remains is about a quarter of the original association. Black non-Hispanic youth are the exception: they show no urbanization gradient at all, and Black non-Hispanic girls go the other way.
All children, all methods, 2018–2024
All children, firearm, 2018–2024
All children, other methods, 2018–2024
Boys, all methods, 2018–2024
Boys, firearm, 2018–2024
Boys, other methods, 2018–2024
Girls, all methods, 2018–2024
Girls, firearm, 2018–2024
Girls, other methods, 2018–2024
White non-Hispanic, 2018–2024
White non-Hispanic boys, 2018–2024
White non-Hispanic girls, 2018–2024
Black non-Hispanic, 2018–2024
Black non-Hispanic boys, 2018–2024
Black non-Hispanic girls, 2018–2024
Hispanic, 2018–2024
Hispanic boys, 2018–2024
Hispanic girls, 2018–2024
Suicide rate per 100,000 per year, ages 0–19, 2018–2025, by the child's county of residence. The line through each bar is its 95% confidence interval.
Children in the most rural counties die by suicide at 5.52 per 100,000 per year against 2.71 in big-city counties — 2.04× higher (95% CI 1.93–2.15). The gradient is monotonic: every step from city to country raises the rate, with no reversal anywhere along it. That is what a real effect looks like, as against a difference between two arbitrary groups. It also explains a good deal of the state map above, since the states at the top of it are the least urban — and it is the reason the like-for-like map holds urbanisation fixed as well as race.
| Urbanisation | What that means | Deaths | Rate | 95% CI | vs big-city counties |
|---|---|---|---|---|---|
| Large central metro | big-city counties, metro areas over 1 million | 5,428 | 2.71 | 2.64–2.78 | 1.00× |
| Large fringe metro | the suburbs of those same big cities | 5,054 | 3.01 | 2.92–3.09 | 1.11× |
| Medium metro | metro areas of 250,000 to 1 million | 4,878 | 3.55 | 3.46–3.66 | 1.31× |
| Small metro | metro areas under 250,000 | 2,449 | 4.25 | 4.08–4.42 | 1.57× |
| Micropolitan | a town of 10,000 to 50,000, no larger city | 2,520 | 4.60 | 4.43–4.79 | 1.70× |
| Non-core | rural counties with no town of 10,000 | 1,877 | 5.52 | 5.27–5.77 | 2.04× |
| Large central metro | big-city counties, metro areas over 1 million | 1,845 | 3.30 | 3.15–3.46 | 1.00× |
| Large fringe metro | the suburbs of those same big cities | 2,663 | 3.38 | 3.25–3.51 | 1.02× |
| Medium metro | metro areas of 250,000 to 1 million | 2,616 | 4.16 | 4.01–4.33 | 1.26× |
| Small metro | metro areas under 250,000 | 1,451 | 4.55 | 4.32–4.79 | 1.38× |
| Micropolitan | a town of 10,000 to 50,000, no larger city | 1,555 | 4.81 | 4.57–5.05 | 1.46× |
| Non-core | rural counties with no town of 10,000 | 1,159 | 5.39 | 5.08–5.71 | 1.63× |
| Large central metro | big-city counties, metro areas over 1 million | 1,340 | 4.68 | 4.43–4.94 | 1.00× |
| Large fringe metro | the suburbs of those same big cities | 1,934 | 4.77 | 4.56–4.99 | 1.02× |
| Medium metro | metro areas of 250,000 to 1 million | 1,964 | 6.09 | 5.83–6.37 | 1.30× |
| Small metro | metro areas under 250,000 | 1,118 | 6.84 | 6.45–7.26 | 1.46× |
| Micropolitan | a town of 10,000 to 50,000, no larger city | 1,214 | 7.31 | 6.91–7.73 | 1.56× |
| Non-core | rural counties with no town of 10,000 | 916 | 8.26 | 7.73–8.81 | 1.76× |
| Large central metro | big-city counties, metro areas over 1 million | 505 | 1.85 | 1.70–2.02 | 1.00× |
| Large fringe metro | the suburbs of those same big cities | 729 | 1.90 | 1.76–2.04 | 1.03× |
| Medium metro | metro areas of 250,000 to 1 million | 652 | 2.13 | 1.97–2.30 | 1.15× |
| Small metro | metro areas under 250,000 | 333 | 2.14 | 1.92–2.38 | 1.16× |
| Micropolitan | a town of 10,000 to 50,000, no larger city | 341 | 2.17 | 1.94–2.41 | 1.17× |
| Non-core | rural counties with no town of 10,000 | 243 | 2.33 | 2.05–2.65 | 1.26× |
| Large central metro | big-city counties, metro areas over 1 million | 876 | 2.87 | 2.68–3.06 | 1.00× |
| Large fringe metro | the suburbs of those same big cities | 602 | 3.04 | 2.80–3.29 | 1.06× |
| Medium metro | metro areas of 250,000 to 1 million | 504 | 3.24 | 2.96–3.53 | 1.13× |
| Small metro | metro areas under 250,000 | 184 | 3.37 | 2.90–3.89 | 1.17× |
| Micropolitan | a town of 10,000 to 50,000, no larger city | 146 | 3.45 | 2.91–4.05 | 1.20× |
| Non-core | rural counties with no town of 10,000 | 77 | 2.99 | 2.36–3.74 | 1.04× |
| Large central metro | big-city counties, metro areas over 1 million | 618 | 4.00 | 3.69–4.33 | 1.00× |
| Large fringe metro | the suburbs of those same big cities | 417 | 4.16 | 3.77–4.58 | 1.04× |
| Medium metro | metro areas of 250,000 to 1 million | 374 | 4.74 | 4.27–5.25 | 1.19× |
| Small metro | metro areas under 250,000 | 134 | 4.83 | 4.05–5.72 | 1.21× |
| Micropolitan | a town of 10,000 to 50,000, no larger city | 109 | 5.04 | 4.14–6.08 | 1.26× |
| Non-core | rural counties with no town of 10,000 | 66 | 4.97 | 3.85–6.33 | 1.24× |
| Large central metro | big-city counties, metro areas over 1 million | 258 | 1.71 | 1.51–1.93 | 1.00× |
| Large fringe metro | the suburbs of those same big cities | 185 | 1.90 | 1.63–2.19 | 1.11× |
| Medium metro | metro areas of 250,000 to 1 million | 130 | 1.69 | 1.42–2.01 | 0.99× |
| Small metro | metro areas under 250,000 | 50 | 1.86 | 1.38–2.45 | 1.09× |
| Micropolitan | a town of 10,000 to 50,000, no larger city | 37 | 1.78 | 1.26–2.46 | 1.04× |
| Non-core | rural counties with no town of 10,000 | 11 | 0.88 | 0.44–1.58 | 0.52× |
| Large central metro | big-city counties, metro areas over 1 million | 1,402 | 2.17 | 2.06–2.29 | 1.00× |
| Large fringe metro | the suburbs of those same big cities | 710 | 2.33 | 2.17–2.51 | 1.08× |
| Medium metro | metro areas of 250,000 to 1 million | 799 | 2.66 | 2.48–2.85 | 1.23× |
| Small metro | metro areas under 250,000 | 276 | 3.21 | 2.84–3.61 | 1.48× |
| Micropolitan | a town of 10,000 to 50,000, no larger city | 268 | 3.55 | 3.14–4.01 | 1.64× |
| Non-core | rural counties with no town of 10,000 | 131 | 3.92 | 3.27–4.65 | 1.81× |
| Large central metro | big-city counties, metro areas over 1 million | 977 | 2.97 | 2.78–3.16 | 1.00× |
| Large fringe metro | the suburbs of those same big cities | 484 | 3.12 | 2.85–3.41 | 1.05× |
| Medium metro | metro areas of 250,000 to 1 million | 558 | 3.64 | 3.35–3.96 | 1.23× |
| Small metro | metro areas under 250,000 | 200 | 4.56 | 3.95–5.24 | 1.54× |
| Micropolitan | a town of 10,000 to 50,000, no larger city | 192 | 4.98 | 4.30–5.74 | 1.68× |
| Non-core | rural counties with no town of 10,000 | 101 | 5.88 | 4.79–7.14 | 1.98× |
| Large central metro | big-city counties, metro areas over 1 million | 425 | 1.34 | 1.22–1.47 | 1.00× |
| Large fringe metro | the suburbs of those same big cities | 226 | 1.52 | 1.33–1.73 | 1.13× |
| Medium metro | metro areas of 250,000 to 1 million | 241 | 1.64 | 1.44–1.86 | 1.22× |
| Small metro | metro areas under 250,000 | 76 | 1.81 | 1.42–2.26 | 1.35× |
| Micropolitan | a town of 10,000 to 50,000, no larger city | 76 | 2.06 | 1.62–2.58 | 1.54× |
| Non-core | rural counties with no town of 10,000 | 30 | 1.85 | 1.24–2.63 | 1.38× |
CDC WONDER, 2018–2025, NCHS 2023 urbanisation classification by county of residence. Deaths are as published.
These views restrict the data; they do not standardise it. The gradient is partly a fact about who lives where, so each of these holds race, ethnicity and sex still and lets only urbanisation vary — no weighting, no reference population, no model. Each one is not the rate at which children die in rural America: it sets aside every child outside its own group, which is the point of it and also the danger of it. Every chart shares one scale, and rate ratios take large central metro as the comparator. The dashed outline behind each bar is all children in that category over the same years, so switching view shows the restriction and not a different window. Boys are the group total minus girls, which is exact rather than modelled.
The denominator stops before the deaths do. CDC publishes deaths for White non-Hispanic, Black non-Hispanic and Hispanic children by urbanisation through 2024 and population only through 2021. For 2022–2024 the last published denominator is carried forward rather than projected. Measured against each group's own trend that moves the affected years by 2.6% at worst and under 1% pooled, and it moves them downward for White non-Hispanic children — the highest-rate group — so it narrows the gaps between groups slightly rather than widening them. Counts CDC suppresses for holding fewer than ten deaths are recovered by differencing two exports of the same query, one with suicide included and one without: both sides run to the hundreds, so neither is suppressed. Those recovered annual counts are never shown. Only the pooled figures are, and the smallest of those is eleven deaths. The mechanism split is where the gradient lives. Firearm suicide runs 3.2 times higher in the emptiest counties than in the biggest cities; every other method together runs 1.3 times higher. That ratio of gradients is 2.49 (2.22 to 2.79), and it is the same in boys (2.45) and in girls (2.45). What differs between the sexes is not how steeply either component climbs — boys against girls gives 1.03 for firearm and 1.03 for everything else, both intervals sitting on 1 — but how much of each sex’s deaths sit in the steep component: firearms are 47 to 69 per cent of boys’ suicides across the gradient and 18 to 36 per cent of girls’. Give rural children the big-city firearm rate and change nothing else and 87 per cent of the boys’ gap closes, and 64 per cent of the girls’. This is an ecological comparison of rates, not a claim about any individual death; means restriction is where that inference is best supported and it is still an inference. One firearm cell — small metro, girls, 2024 — is suppressed by CDC and taken here as 9, which is the largest it can be. It is one year of a seven-year pool and moves that pooled figure by under two per cent.
The denominators are modelled, and the modelling is
the part to check. CDC publishes population for these categories only through
2021, four years against eight years of deaths. Rather
than projecting each category's population forward — which would have
carried the 2020/21 change of population vintage forward as though it were
demography — each category's share of the classified population
is projected and applied to the national person-time used elsewhere on this
page. A share is invariant to a change of vintage, because numerator and
denominator rescale together. The shares move about a tenth of a percentage
point a year, in one direction, and a straight line through the four
published years reproduces them with R² between
0.83 and 0.96 and
reconstructs every published category population to within a third of one per
cent. Figures from 2022 onward rest on that projection and are the
least certain on this page.
The six categories account for
98.99% of the national population, stable to
0.016 of a percentage point across the
published years; the remainder is children whose county CDC cannot classify.
They are excluded here along with their 146 deaths, so
the counts in this section sum to 22,206 rather than
the national total.
Guns are the story here. Firearm suicides account for the majority of suicides in America, and without them, we would likely see the same rates (generally) as in Canada.
Share of suicide deaths, ages 0–19, 2018–2025, with counts at the right.
Firearms account for 46.1% of suicide deaths among American children. The equivalent figure on the Canadian page is 12.1%. Two countries with comparable wealth, comparable health systems and comparable rates of adolescent depression differ by a factor of nearly four in how often a child's suicidal crisis ends in death by firearm. A firearm is the most lethal method available: the difference is not in how often children reach a crisis, it is in what is within reach when they do.
Firearm suicide rate per 100,000 per year, ages 0–19, 1968–2024. Girls purple, boys blue, both sexes black, each labelled at the end of its own line. The dotted rules mark changes of case definition: 1968–1978 counts ICD-8 E955, firearms and explosives, which is a wider category than the firearm mechanism of ICD-9 and ICD-10, so the line breaks there rather than running through. Denominators are the same smoothed, vintage-linked person-time every other rate on this page divides by, not the published estimate printed inside each extract.
The firearm rate in 2024 was 1.49 per 100,000 per year against 0.70 in 1968 — 112.6% higher. Over these eight years 10,302 American children aged 0–19 died by firearm suicide. Secure storage is the intervention with the strongest evidence base and the least controversy attached to it, and it is the one a story about these numbers can usefully name.
| Method | Deaths 2018–2025 | Share |
|---|---|---|
| Firearm | 10,302 | 46.1% |
| Suffocation | 8,545 | 38.3% |
| Poisoning | 1,806 | 8.1% |
| Falling or jumping from height | 679 | 3.0% |
| Other | 996 | 4.5% |
Grouped to match the Canadian page so the two can be read against each other. 4 cells were suppressed by CDC for holding fewer than 10 deaths; they fall in categories totalling well under one per cent and are counted in neither the named groups nor the total, so the shares here are of 22,328 deaths with a published mechanism. No method is described beyond these categories, and none is ranked by lethality.
The national rate is an average across groups whose rates differ by a factor of five. It should be important to note that most national suicide prevention organizations completely neglect American Indigenous suicide, and claim that "white rates" are the highest. They are not.
Suicide rate per 100,000 per year, ages 0–19, 2018–2025, with deaths at the right. The line through each bar is its 95% confidence interval. Race categories are non-Hispanic; Hispanic or Latino children of any race are counted in the final row.
American Indian and Alaska Native children die by suicide at 12.18 per 100,000 per year — 3.04× the rate for White children (95% CI 2.81–3.29), and nearly five times the lowest group on this chart. That is the same finding the Canadian page reports for First Nations and Inuit young people, in a different country with a different health system and a different data source. It is not a fact about being Indigenous; it is a fact about what was done to Indigenous communities on both sides of the border, and about what is and is not available to them now. Alaska is also the highest state on the map above, which is the same fact seen from another angle rather than a second one.
| Group | Deaths | Rate | 95% CI | vs White | 95% CI |
|---|---|---|---|---|---|
| American Indian or Alaska Native | 635 | 12.18 | 11.25–13.16 | 3.04× | 2.81–3.29 |
| Native Hawaiian or Other Pacific Islander | 62 | 4.44 | 3.40–5.69 | 1.11× | 0.86–1.42 |
| White | 12,901 | 4.01 | 3.94–4.08 | 1.00× | 0.98–1.02 |
| Black or African American | 2,841 | 3.15 | 3.04–3.27 | 0.79× | 0.76–0.82 |
| Asian | 932 | 2.60 | 2.44–2.78 | 0.65× | 0.61–0.69 |
| Hispanic or Latino, any race | 4,209 | 2.48 | 2.41–2.56 | 0.62× | 0.60–0.64 |
| More than one race | 738 | 2.47 | 2.30–2.66 | 0.62× | 0.57–0.66 |
Rates are crude, not age-standardised, and are computed from counts and population like everything else here. Groups are pooled across the whole period rather than shown by year: Native Hawaiian and Other Pacific Islander children account for 62 deaths across eight years, which cannot be split by year without falling below CDC's threshold of 10. Wide intervals on the smaller groups are the honest consequence of small numbers and should be read as such.
Every page on this site was looked at by me, one at a time, before it was published. This is exactly what that involved, and what it did not.
What I checked
What I did not
Automated checks ran over every page and I read their output. A language model was used on some pages to suggest things worth a second look; nothing it produced is published, and nothing it said stands as a finding on its own.
A review is a point in time. If the data behind a page changes afterwards, the page does not ship again until it has been looked at again — that rule is enforced when the site is deployed, not left to memory.
In the US and Canada, call or text 988 for the Suicide and Crisis Lifeline. The Trevor Project supports LGBTQ+ young people at 1-866-488-7386, or text START to 678-678.
In the United States, the 988 Suicide & Crisis Lifeline can be reached by call or text at 988. In Canada, 988 as well.
Disclaimer: The content on this website is provided for general informational and educational purposes only. It is not medical advice and is not a substitute for professional diagnosis, treatment, or care. Always seek the advice of a qualified health professional with any questions you may have regarding a medical or mental health condition. If you are in crisis or having thoughts of suicide, help is available now. Call or text 9-8-8 (Suicide Crisis Helpline — Canada & US, available 24/7), or go to your nearest emergency department. If you are in immediate danger, call 911.
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