# Overdose, alcohol and suicide: report

Chapter 8.2 of ZIP Code Destiny, by Vishal Singh (NYU Stern). Generated from the chapter's data files; the reading version is at https://vishalsingh.org/zipcode/overdose-alcohol-and-suicide. Table n of this report is figure n of the chapter.

## Identification

- Title: Overdose, alcohol and suicide
- Label: Two despairs
- Chapter: 8.2 (Part VIII, Early death; An American life)
- Question: Where are overdose, alcohol and suicide deaths highest, and how does each change with county deprivation?
- Dek: Across counties with a stable modeled rate for suicide, overdose and homicide in 2019 to 2023, suicide death rates are only weakly related to overdose and homicide rates (population-weighted correlations of +0.13 and −0.02).
- Grain: counties
- Status: published
- Published: 2026-10-09
- Updated: not revised
- Data sources:
  - CDC injury and violence mapping. CDC Mapping Injury, Overdose, and Violence county file: modeled overdose, suicide and homicide death rates, annual 2019 to 2023; years: 2019-2024 for counties, 2022-2024 for tracts (data as of 2026-05-14); weights: 2019-2023 ACS residents of each county, and every county once
  - CDC WONDER underlying cause of death. CDC WONDER underlying cause of death: drug poisoning (overdose), alcohol-induced causes and suicide, counties 2018 to 2024; years: 2018-2024; weights: none (crude rates from counts); WONDER county population
  - American Community Survey. Total population of 2020 tracts, 2019-2023, summed to counties as weights for the panel's county rates; years: 2019-2023 (5-year); weights: none (full count)
  - Area Deprivation Index. Neighborhood Atlas Area Deprivation Index 2023, tract national rank averaged to counties; years: 2023 release (version 4.0.1; built on ACS 2019-2023); weights: 2019-2023 tract population
  - Rural-Urban Continuum Codes. USDA Rural-Urban Continuum Codes 2023, county; years: 2023; weights: none (classification)
  - County Health Rankings. County Health Rankings 2024, share of residents who are American Indian or Alaska Native (Census Population Estimates 2022); years: 2024 release; weights: none (published county measure)
- Canonical URL: https://vishalsingh.org/zipcode/overdose-alcohol-and-suicide
- Report: https://vishalsingh.org/zipcode/overdose-alcohol-and-suicide/report
- Markdown: https://vishalsingh.org/zipcode/overdose-alcohol-and-suicide/report.md
- BibTeX key: singh2026overdosealcoholandsuicide

```bibtex
@misc{singh2026overdosealcoholandsuicide,
  author = {Singh, Vishal},
  title = {Overdose, alcohol and suicide},
  year = {2026},
  url = {https://vishalsingh.org/zipcode/overdose-alcohol-and-suicide},
  note = {In ZIP Code Destiny. Published 9 October 2026.}
}
```

## Principal estimates

The facts the dek and the opening prose cite, in order of appearance.

| Estimand | Population | Period | Value | Interval | n | Weights | Source | Fact id |
| --- | --- | --- | ---: | --- | ---: | --- | --- | --- |
| correlation of the county overdose and suicide rates, population-weighted; bootstrap over counties | counties with a stable rate for all three kinds of death | annual modeled rates for 2019 to 2023, averaged | +0.13 | 95% CI 0.05 to 0.21 | 1,899 counties | 2019-2023 ACS residents | CDC injury and violence mapping | p_corr_od_su |
| correlation of the county suicide and homicide rates, population-weighted; bootstrap over counties | counties with a stable rate for all three kinds of death | annual modeled rates for 2019 to 2023, averaged | −0.02 | 95% CI −0.10 to 0.06 | 1,899 counties | 2019-2023 ACS residents | CDC injury and violence mapping | p_corr_su_hm |
| count of counties | counties in CDC's county file with a stable rate for overdose, suicide and homicide in every year | 2019 to 2023 | 1,899 |   |   | none (full count) | CDC injury and violence mapping | p_common_n |
| share of residents living in counties with a stable rate for all three kinds of death | residents of the 50 states and DC | 2019-2023 ACS residents | 93.5% |   |   | 2019-2023 ACS residents | CDC injury and violence mapping | p_common_pop |
| correlation of the county overdose and homicide rates, population-weighted; bootstrap over counties | counties with a stable rate for all three kinds of death | annual modeled rates for 2019 to 2023, averaged | +0.48 | 95% CI 0.35 to 0.58 | 1,899 counties | 2019-2023 ACS residents | CDC injury and violence mapping | p_corr_od_hm |
| definition: WONDER withholds a county-year count above zero and below this number | county-years in CDC WONDER | deaths in 2018 to 2024 | 10 |   |   | none (definition) | CDC WONDER underlying cause of death | w_floor |
| count of mapped counties | counties complete for drug and alcohol with at least 20 pooled deaths of each | deaths in 2018 to 2024 | 545 |   |   | none (full count) | CDC WONDER underlying cause of death | dom_n |
| definition: the least number of pooled deaths for a county to be mapped | a county drawn on a map of WONDER counts | deaths in 2018 to 2024 | 20 |   |   | none (definition) | CDC WONDER underlying cause of death | map_floor |
| count of mapped counties with a higher crude overdose than alcohol-induced death rate | mapped counties | deaths in 2018 to 2024 | 479 |   | 545 counties | none (full count) | CDC WONDER underlying cause of death | dom_od_higher |
| count of mapped counties with a higher crude alcohol-induced than overdose death rate | mapped counties | deaths in 2018 to 2024 | 66 |   | 545 counties | none (full count) | CDC WONDER underlying cause of death | dom_alc_higher |

## Findings

Suicide, overdose and homicide death rates are highest in different counties, and suicide is the most separate. Across the 1,899 counties with a stable modeled rate for all three in 2019 to 2023, which hold 93.5% of residents, the county overdose rate has a population-weighted correlation of +0.13 (95% CI 0.05 to 0.21) with the suicide rate. The suicide rate has a correlation of −0.02 (95% CI −0.10 to 0.06) with the homicide rate. Overdose and homicide rates are more closely related, with a correlation of +0.48 (95% CI 0.35 to 0.58).

Drug and alcohol deaths separate as well, but the counts behind that result come from a selected set of counties. CDC WONDER publishes a county's count in every year only when the count is zero or at least 10 each year, which favors larger counties with high rates for their size. In the 545 such counties where each cause has at least 20 deaths, the overdose death rate is higher than the alcohol-induced death rate in 479 counties and lower in 66.

Case and Deaton found that mortality among middle-aged white non-Hispanic Americans rose between 1999 and 2013, mostly through drug and alcohol poisonings, suicide and chronic liver disease.[1] They later grouped suicide, drug overdose and alcoholic liver disease as deaths of despair.[2] The grouping treats three kinds of death as one problem. This chapter asks whether they share an address, using death rates for counties. A county rate is deaths per hundred thousand residents, crude and not adjusted for age, and it says nothing about who died or why. Whether people in these places feel despair is a person-level question, taken up in Chapter 6.3, Life evaluation and daily feelings (https://vishalsingh.org/zipcode/life-evaluation-and-daily-feelings).

### Suicide, overdose and homicide rates peak in different counties

The first three figures use the county file of CDC's injury and violence dashboard, which carries modeled estimates of death rates and is the only source in this chapter that also covers homicide. A model borrows strength across counties where deaths are few, so the maps can show counties that CDC WONDER's public counts leave blank. A county is drawn when CDC publishes a stable rate in each year from 2019 to 2023, and its rate is the mean of the five annual rates. That leaves 2,714 counties with an overdose rate, 2,273 with a suicide rate and 2,807 with a homicide rate, holding 97.7%, 94.9% and 97.6% of residents. CDC's file has 3,135 counties and leaves out Connecticut's. The suicide map has the fewest counties because CDC marks more small-county suicide rates unstable.

Table 1. Across counties, the population-weighted correlation of suicide rates is +0.13 with overdose rates and −0.02 with homicide rates, against +0.48 between overdose and homicide rates

The counties with the highest rates lie in different places. In the highest tenth of overdose rates, 68.0% of the counties are in the South, which holds 45.7% of counties with an overdose rate. The South also holds 85.8% of the highest tenth for homicide, against 47.7% of counties with a homicide rate. The highest tenth for suicide lies elsewhere, with 50.0% of its counties in the West, which holds 13.7% of counties with a suicide rate.

The correlations in the opening paragraph give the same picture county by county. Counting every county once, the three correlations are smaller and in the same order: +0.19, +0.02 and +0.27. The suicide rate shares little with the overdose rate or the homicide rate, and the interval for its correlation with the homicide rate includes zero under both weightings. Overdose and homicide share more, but much less when every county counts once than when large counties carry their weight. The panel counts only unintentional and undetermined-intent drug poisonings as overdose, so an overdose recorded as a suicide appears in the suicide rate and not in the overdose rate. Homicide counts every method. Gun homicide is the subject of Chapter 8.1, Gun homicide and the causes of early death (https://vishalsingh.org/zipcode/gun-homicide-and-causes-of-early-death).

### Homicide, suicide and overdose are higher in the most deprived tenth of counties

Weighted by population, all three rates are higher in the most deprived tenth than in the least, and the homicide and overdose lines do not rise steadily in between. Rank counties by the Area Deprivation Index of their residents and cut the ranking into tenths with equal numbers of counties (Table 2). A county's rank is the population-weighted mean of the national ranks of its tracts. Weighted by population, the homicide rate is 4.8 (95% CI 4.2 to 5.4) deaths per hundred thousand residents in the least deprived tenth and 13.6 (95% CI 11.1 to 16.2) in the most deprived, a ratio of 2.83 (95% CI 2.24 to 3.58). Suicide goes from 12.2 (95% CI 11.3 to 13.2) to 17.4 (95% CI 15.7 to 19.4), a ratio of 1.43 (95% CI 1.25 to 1.63), and the line is level over the more deprived tenths.

Overdose goes from 23.8 (95% CI 22.2 to 25.6) to 31.1 (95% CI 25.7 to 36.5), a ratio of 1.30 (95% CI 1.07 to 1.55). Across all counties with a rate, the population-weighted correlation with deprivation is +0.46 (95% CI 0.37 to 0.53) for suicide, +0.30 (95% CI 0.25 to 0.36) for homicide and +0.22 (95% CI 0.15 to 0.28) for overdose.

Homicide and overdose do not climb steadily. The point estimates of the homicide line fall in 4 of the nine steps between tenths, and those of the overdose line in 4. The overdose line reaches 36.1 (95% CI 30.6 to 42.0) in tenth 4, which is 5.0 (95% CI −2.6 to 13.2) above the most deprived tenth. The interval for that difference includes zero, and a peak chosen from ten noisy means overstates its lead, so the data do not show that overdose rates are higher in the middle of the ranking than at the deprived end.

Table 2. Weighted by population, homicide rates in the most deprived tenth of counties are 2.83 times those in the least deprived, suicide rates 1.43 times and overdose rates 1.30 times, but the homicide and overdose lines do not rise steadily

Counting every county once changes the picture for two of the three. Homicide is 3.4 (95% CI 3.1 to 3.7) in the least deprived tenth and 9.5 (95% CI 8.2 to 10.9) in the most deprived, a ratio of 2.78 (95% CI 2.34 to 3.30), close to the weighted ratio. Suicide is 15.3 (95% CI 14.6 to 16.1) in the least deprived tenth and 14.2 (95% CI 13.2 to 15.3) in the most deprived, a ratio of 0.93 (95% CI 0.85 to 1.02).

Overdose is 22.2 (95% CI 21.1 to 23.2) and 23.0 (95% CI 19.5 to 26.4), a ratio of 1.03 (95% CI 0.88 to 1.20). Neither the suicide ratio's interval nor the overdose ratio's excludes equal rates in the two tenths. The correlation with deprivation is −0.01 (95% CI −0.04 to 0.03) for overdose and +0.01 (95% CI −0.04 to 0.05) for suicide, against +0.18 (95% CI 0.16 to 0.21) for homicide. The weighted rise in suicide and overdose comes from the larger counties, and the small counties that make up most of the most deprived tenth do not show it.

Three features of the tenths limit what they show. The tenths cover the 3,120 counties with a deprivation rank and hold equal numbers of counties, so the most deprived tenth is mostly small rural counties. A county without a stable rate for a kind of death is left out of that line. Those counties are also small ones, and the suicide line has the fewest counties in its most deprived tenth for that reason. The Area Deprivation Index understates deprivation in high-cost cities (Chapter 1.1, What the deprivation index measures (https://vishalsingh.org/zipcode/anatomy-of-deprivation)), so a high-cost county can sit in a less deprived tenth than its tracts would suggest. The homicide correlation with deprivation here differs from the one in Chapter 8.1, Gun homicide and the causes of early death (https://vishalsingh.org/zipcode/gun-homicide-and-causes-of-early-death), which uses County Health Rankings' homicide rates, available only for counties with enough homicides, and a different set of counties.

### Suicide is higher in more urban nonmetro counties, homicide in large metro counties

Table 3 groups counties by the 2023 Rural-Urban Continuum Code. Weighted by population, suicide is 19.7 (95% CI 19.2 to 20.2) deaths per hundred thousand residents in nonmetro counties with an urban population of 5,000 or more (more urban nonmetro counties) and 12.2 (95% CI 11.6 to 12.9) in large metro counties, those in metro areas of 1 million or more. The ratio is 1.6 (95% CI 1.5 to 1.7).

Homicide runs the other way, 7.6 (95% CI 6.7 to 8.7) in large metro counties against 4.6 (95% CI 4.2 to 5.1) in nonmetro counties with a smaller urban population (least urban nonmetro counties), a ratio of 1.6 (95% CI 1.4 to 1.9). The overdose rate is 27.8 (95% CI 25.7 to 30.0) in large metro counties and 21.8 (95% CI 20.2 to 23.5) in least urban nonmetro counties, a ratio of 1.3 (95% CI 1.1 to 1.4).

Table 3. Weighted by population, suicide rates in more urban nonmetro counties are 1.6 times those in large metro counties, and homicide rates in large metro counties are 1.6 times those in the least urban nonmetro counties

Counting every county once, suicide is 19.6 (95% CI 19.2 to 20.0) in more urban nonmetro counties against 14.6 (95% CI 14.1 to 15.0) in large metro counties, a ratio of 1.3 (95% CI 1.3 to 1.4). Homicide is 6.2 (95% CI 5.6 to 6.9) in large metro counties against 3.5 (95% CI 3.2 to 3.9) in least urban nonmetro counties, a ratio of 1.8 (95% CI 1.5 to 2.0). Both contrasts hold.

Two other comparisons do not hold. Suicide is no higher in least urban nonmetro counties than in large metro counties when every county counts once. The overdose ratio is 1.8 (95% CI 1.6 to 2.0), with 28.3 (95% CI 26.8 to 29.9) in large metro counties and 16.0 (95% CI 14.8 to 17.2) in least urban nonmetro counties, a larger gap than the weighted one. Overdose rates are lower in least urban nonmetro counties under both weightings, and they differ more by county type than the weighted figures suggest.

These are crude rates. Age structure differs between rural and urban counties and suicide rates differ by age, so part of a gap between county types can reflect who lives in the county and not a different risk at the same age. The panel's rates are also modeled for small counties, which can borrow strength from neighboring areas, so a nonmetro county's rate may partly reflect its neighbors.

### Overdose deaths exceed alcohol-induced deaths in most counties where both can be mapped

Alcohol-induced deaths appear in this chapter's data only through CDC WONDER, which counts deaths by the underlying cause on the death certificate. Here drug means drug poisoning of any intent (unintentional, suicide, homicide or undetermined). Alcohol-induced means WONDER's category of alcohol-induced deaths, which includes alcoholic liver disease and alcohol poisoning, and suicide means intentional self-harm by any method. A suicide by drug poisoning is in both the drug count and the suicide count. All three are crude rates per hundred thousand residents.

WONDER withholds any county-year count above zero and below 10, and it publishes a count of zero, so a rate pooled over the published years of a county is biased. This chapter does not impute, bound or back out the withheld counts. It uses the counties whose count is published in every year, which it calls complete counties, for which the rate pooled over 2018 to 2024 is exact. Complete counties are selected on the outcome as well as on size. Among counties of 30,000 to 60,000 residents, the mean overdose rate in CDC's modeled panel is 50.9 (95% CI 46.1 to 56.4) in counties with a published count in every year and 22.5 (95% CI 21.5 to 23.4) in the rest. The maps and gradient of WONDER counts therefore describe these counties and not counties in general. Chapter 10.3, Suppressed counties in death data (https://vishalsingh.org/zipcode/suppressed-counties-in-death-data) covers how many county-years are withheld, which counties lose their counts and what the selection does to comparisons.

Table 4 maps the ratio of the two rates, on a log scale, for the 545 counties that are complete for both and have at least 20 pooled deaths of each. They hold 76.6% of residents outside Connecticut. The overdose rate is the higher one in 479 of them and the alcohol-induced rate in 66.

Each class of the key is a doubling of the ratio. The overdose rate is at least 2 times the alcohol-induced rate in 234 mapped counties, and the alcohol-induced rate is at least 2 times the overdose rate in 6. Across the 569 counties that publish both counts every year, the two rates have a correlation of +0.25 (95% CI 0.16 to 0.35), and +0.30 (95% CI 0.20 to 0.43) counting every county once.

The counties where alcohol is higher are mostly in the West and Midwest, which hold 78.8% of them. Alcohol is the higher rate in 28.0% of mapped counties in the West and 16.4% in the Midwest, against 6.5% in the South and 0.0% in the Northeast.

Table 4. Overdose deaths exceed alcohol-induced deaths in 479 of 545 mapped counties, and the 66 counties where alcohol is higher lie mostly in the West and Midwest

Several of the counties with the highest alcohol-induced rates have large American Indian and Alaska Native populations. Of the ten mapped counties with the highest alcohol-induced rate, 6 are counties where American Indian or Alaska Native residents are at least 10% of residents, by County Health Rankings' figures from the American Community Survey. Only 10 of the 133 counties in WONDER of that kind are mapped, and alcohol is the higher rate in 6 of those.

Those counties' pooled alcohol-induced rate is 57.3 deaths per hundred thousand residents, against 13.6 in the other mapped counties. The cutoff matters. At 5% instead, there are 27 such counties and alcohol is the higher rate in 8 of them. These county totals are not divided by race, so the comparison describes counties and not the people who died.

### Weighted by population, suicide and overdose rates correlate more with deprivation than alcohol-induced rates

Table 5 repeats the gradient for the WONDER rates, in the 525 counties whose drug, alcohol and suicide counts are published in every year, which hold 76.0% of residents outside Connecticut. The tenths are tenths of these counties, which are selected as described above, so they do not line up with the tenths of Table 2. The correlation of the county rate with the deprivation rank, weighted by person-years, is +0.42 (95% CI 0.30 to 0.51) for suicide, +0.35 (95% CI 0.24 to 0.44) for overdose and +0.13 (95% CI 0.04 to 0.22) for alcohol-induced deaths.

Counting every county once, the correlations are +0.28 (95% CI 0.19 to 0.36), +0.26 (95% CI 0.19 to 0.34) and +0.15 (95% CI 0.05 to 0.22). From the same bootstrap draws, the weighted correlation for overdose is higher than the one for alcohol by +0.21 (95% CI 0.09 to 0.33), and the one for suicide by +0.28 (95% CI 0.18 to 0.39).

In the least deprived tenth the rates are 22.0 (95% CI 20.0 to 24.8), 12.5 (95% CI 10.8 to 14.0) and 9.9 (95% CI 9.1 to 11.1) for overdose, alcohol-induced deaths and suicide. In the most deprived tenth they are 32.3 (95% CI 25.2 to 40.0), 17.6 (95% CI 13.9 to 22.7) and 16.5 (95% CI 14.2 to 18.9).

The overdose rate is higher in the most deprived tenth than in the least deprived by 10.3 (95% CI 2.5 to 18.3) deaths per hundred thousand residents and the suicide rate by 6.6 (95% CI 4.0 to 9.2). These are differences between the two tenths' pooled rates, with intervals from bootstrap draws that the two tenths share.

Table 5. Among counties with published counts in every year, the population-weighted correlation of deprivation is +0.42 with suicide and +0.35 with overdose death rates, against +0.13 with alcohol-induced death rates

The overdose line here keeps rising into more deprived tenths than the panel's line in Table 2, which is a different set of counties ranked in a different way. In all counties with a modeled rate the population-weighted correlation with deprivation for overdose is +0.22 (95% CI 0.15 to 0.28), below the +0.35 (95% CI 0.24 to 0.44) here, so the selection matters for the overdose result. The alcohol-induced line is level until the most deprived tenth, and the jump there depends on a few counties. 5 of the tenth's counties are ones where American Indian or Alaska Native residents are at least 10% of residents, and without them the tenth's rate is 14.4 (95% CI 12.1 to 16.6), in line with the other tenths.

The panel and WONDER give the same county rates where both can be compared. Across counties whose WONDER counts are published in every year, the county rate in the two sources has a correlation of +0.995 (95% CI 0.993 to 0.996) for overdose and +0.995 (95% CI 0.994 to 0.996) for suicide. The overdose agreement holds although WONDER's overdose count includes overdoses recorded as suicides and the panel's does not.

In those counties the panel's rates are modeled in 0.6% of overdose county-years and 0.0% of suicide county-years, against 44.9% and 54.0% in all counties. The agreement therefore checks the processing of the same death records where the panel's rates are direct and does not validate the modeled rates for small counties behind the first three figures.

### Change over time is in the chapter on mortality trends

Chapter 8.3, Mortality trends, 2018 to 2024 (https://vishalsingh.org/zipcode/mortality-trends-2018-2024) follows the national overdose, alcohol-induced and suicide rates from 2018 to 2024, including the size of the overdose peak and the fall since. It also checks WONDER's crude series against CDC's modeled panel, which gives a different size for the rise. A study of death records describes the fall in overdose deaths from 2023 to 2024 as concentrated in deaths involving illicit fentanyl. The study also reports that deaths involving stimulants without fentanyl and deaths involving xylazine continued to make up a growing share of overdose deaths.[3] That study is descriptive, and a fall in a national rate says nothing about which counties it reached. This chapter does not map change over time.

Explaining the fall is a causal question, and the maps cannot answer it. One policy lever has been studied with designs that compare states by when they adopted it.

> Causal evidence: Naloxone access laws and opioid deaths (Difference-in-differences, staggered state adoption)
>
> Two studies use the staggered timing of state laws that widened access to naloxone, the drug that reverses an opioid overdose. Abouk, Pacula and Powell compared states before and after they adopted each type of law with states that had not adopted it, using state and time fixed effects and the years since adoption, for 2005 to 2016.[4] Laws that gave pharmacists direct authority to dispense naloxone were followed by fewer fatal opioid overdoses, and laws of other types showed no association with deaths. Doleac and Mukherjee used the same variation in timing and found more opioid-related emergency room visits and more opioid-related theft, with no net reduction in opioid-related deaths.[5] The two studies disagree about the same kind of policy, so the evidence on naloxone laws is mixed, and both studies end well before 2024, so neither can say how much of the fall after 2023 naloxone, treatment or changes in the drug supply account for.

### Only the income ranking separates the two ends of the overdose gradient

Over the 2,699 counties that have a stable overdose rate and all four rankings, the ADI baseline gives 24.0 (95% CI 22.3 to 25.7) overdose deaths per hundred thousand residents in the least deprived tenth of counties and 30.0 (95% CI 24.8 to 35.3) in the most deprived, with a rank correlation of +0.14 between tenth and rate, and on this common sample the two end intervals overlap, unlike those in Table 2 (Table 6). The standardized index, which applies the ADI's coefficients after standardizing each measure, gives 21.7 (95% CI 20.3 to 23.2) and 27.0 (95% CI 20.3 to 34.6), with a correlation of +0.28, and its end intervals overlap as well. Ranked by median household income the tenths run from 22.7 (95% CI 21.2 to 24.4) to 33.1 (95% CI 28.7 to 37.6), intervals that do not overlap, with a correlation of +0.43, and ranked by the bachelor's degree share they run from 24.3 (95% CI 22.3 to 26.3) to 29.4 (95% CI 26.0 to 33.0), with overlapping ends. Under the book's rule the income ranking counts as a change, since its ends differ and the baseline's do not, while the standardized index and the degree share leave the gradient unchanged (Chapter 9.1, How far one ranking goes (https://vishalsingh.org/zipcode/how-far-one-ranking-goes)).

Table 6. The overdose death rate does not differ detectably between the least and the most deprived places under the ADI; it is worse at the more deprived end but uneven along the way under the income ranking

### What these data cannot show

Every figure describes counties. A county rate is an average over all of its residents, so it cannot say who died, and a correlation across counties does not describe the people in them (ecological inference). The data do not measure despair. Deaths from suicide, overdose and alcohol are counted, and whether the people who live in these counties feel despair is a person-level question for Chapter 6.3, Life evaluation and daily feelings (https://vishalsingh.org/zipcode/life-evaluation-and-daily-feelings). Survey measures of drinking are in Chapter 7.2, Health behaviors, person by person (https://vishalsingh.org/zipcode/health-behaviors-person-by-person).

The WONDER figures cover a selected set of counties. Counties whose counts are published in every year hold most residents but are a minority of counties, they are larger, and they have higher rates than other counties of similar size. The correlations with deprivation among the 525 complete counties, +0.42 (95% CI 0.30 to 0.51) for suicide, +0.35 (95% CI 0.24 to 0.44) for overdose and +0.13 (95% CI 0.04 to 0.22) for alcohol-induced deaths, describe those counties only. Most counties where American Indian or Alaska Native residents are at least 10% of residents are outside the maps, as are other small counties with high rates. Withheld counts could hold up to the shares given in the methods note, and no method in this chapter recovers them.

North Carolina's drug-poisoning count for 2023 in WONDER predates the state's amended death certificates and is low. It is 15.8% of the published deaths of the 48 complete North Carolina counties in the window. Raising each of their published 2023 counts by 10% to 19% raises their pooled overdose rate by 1.6% to 3.0%.

At the larger increase the correlation of overdose with deprivation is +0.35 (95% CI 0.24 to 0.44) and the overdose gap between the most and least deprived tenths is 10.4 (95% CI 2.6 to 18.4), and no comparison in this chapter changes direction. The modeled panel covers nearly every county but borrows strength across them, so its rate for a small county is partly its neighbors' rate, and its agreement with WONDER is checked only where its rates are direct. Alcohol-induced deaths are deaths whose underlying cause is alcohol, such as alcoholic liver disease, and they leave out deaths from other conditions in which alcohol was involved.

Several results depend on the weighting. In all counties with a modeled rate, the population-weighted correlations with deprivation are +0.46 (95% CI 0.37 to 0.53) for suicide and +0.22 (95% CI 0.15 to 0.28) for overdose, and counting every county once they are +0.01 (95% CI −0.04 to 0.05) and −0.01 (95% CI −0.04 to 0.03). Weighted by population, suicide and overdose rates are higher in the most deprived tenth of counties and suicide rates are higher outside large metro counties. Counting every county once, the first holds for homicide only and the second for smaller metro and more urban nonmetro counties only. Rates are crude, so a county with an older population has a higher rate for the same risk at each age, and comparisons of rural and urban counties carry that difference. The Area Deprivation Index understates deprivation in high-cost cities. The tenths of counties are relative to the counties in each figure. The three kinds of death also overlap a little, since a suicide by drug poisoning is counted as both a suicide and a drug death. Outside the box above, nothing in this chapter supports a claim about what lowers any of these death rates.

## Tables

### Table 1. Across counties, the population-weighted correlation of suicide rates is +0.13 with overdose rates and −0.02 with homicide rates, against +0.48 between overdose and homicide rates

CDC modeled death rates per 100,000 residents, mean of annual rates for 2019 to 2023, by county: overdose, suicide and homicide in three views

No inline rows: the values of Table 1 are in https://vishalsingh.org/zipcode/data/overdose-alcohol-and-suicide/three_causes_overdose.json.

Views: Overdose (every row); Suicide (every row); Homicide (every row).

Note: Each map plots a county's mean annual modeled rate for 2019 to 2023. A county is drawn when CDC publishes a stable rate in each of the five years; gray hatched counties have a year in which CDC marks the rate unstable (fewer than 10 deaths and no stable model) or, for two Alaska areas that did not exist in 2019, no row, and the tooltip says which. The overdose map has 2,714 counties with a rate, the suicide map 2,273 and the homicide map 2,807, and they hold 97.7%, 94.9% and 97.6% of residents.

Note: These are CDC modeled estimates, which borrow strength across counties where deaths are few, so the WONDER floor of 20 pooled deaths does not apply here; it applies to the maps of WONDER counts in Figure 4. CDC publishes counts under 10 as ranges, and the tooltip gives the lowest and highest five-year totals those ranges allow. Overdose is unintentional or undetermined-intent drug overdose, so it leaves out overdoses recorded as suicides; suicide and homicide include every method. Rates are crude, not age-adjusted. The panel's 2024 values are provisional and left out.

Note: Connecticut's eight counties are gray because CDC's county file does not carry them. Puerto Rico is not drawn. Alaska is drawn.

Source: CDC Mapping Injury, Overdose, and Violence county file, 2019-2023; modeled estimates, crude rates

Data: https://vishalsingh.org/zipcode/report/overdose-alcohol-and-suicide/figures/three_causes_maps.json

### Table 2. Weighted by population, homicide rates in the most deprived tenth of counties are 2.83 times those in the least deprived, suicide rates 1.43 times and overdose rates 1.30 times, but the homicide and overdose lines do not rise steadily

CDC modeled death rates per 100,000 residents by tenth of counties ranked by Area Deprivation Index, mean of annual rates for 2019 to 2023, county rates weighted by population

| cause | conf_high | conf_low | decile | estimate | n_units | weighting |
| --- | ---: | ---: | ---: | ---: | ---: | --- |
| Overdose | 25.58 | 22.17 | 1 | 23.84 | 302 | Population-weighted |
| Overdose | 29.93 | 24.57 | 2 | 27.28 | 296 | Population-weighted |
| Overdose | 34.96 | 26.90 | 3 | 30.74 | 289 | Population-weighted |
| Overdose | 42.01 | 30.60 | 4 | 36.13 | 283 | Population-weighted |
| Overdose | 35.49 | 27.61 | 5 | 31.86 | 270 | Population-weighted |
| Overdose | 31.25 | 24.58 | 6 | 27.90 | 268 | Population-weighted |
| Overdose | 35.13 | 27.89 | 7 | 31.39 | 270 | Population-weighted |
| Overdose | 33.13 | 21.71 | 8 | 27.17 | 260 | Population-weighted |
| Overdose | 30.12 | 23.86 | 9 | 26.83 | 248 | Population-weighted |
| Overdose | 36.49 | 25.66 | 10 | 31.09 | 215 | Population-weighted |
| Suicide | 13.16 | 11.31 | 1 | 12.18 | 267 | Population-weighted |
| Suicide | 15.20 | 13.23 | 2 | 14.15 | 255 | Population-weighted |
| Suicide | 17.11 | 14.83 | 3 | 15.83 | 247 | Population-weighted |
| Suicide | 17.04 | 15.09 | 4 | 16.03 | 239 | Population-weighted |
| Suicide | 17.94 | 16.04 | 5 | 16.91 | 243 | Population-weighted |
| Suicide | 18.76 | 16.57 | 6 | 17.63 | 225 | Population-weighted |
| Suicide | 19.09 | 17.60 | 7 | 18.32 | 214 | Population-weighted |
| Suicide | 18.94 | 14.20 | 8 | 16.62 | 211 | Population-weighted |
| Suicide | 18.83 | 17.33 | 9 | 18.10 | 183 | Population-weighted |
| Suicide | 19.41 | 15.71 | 10 | 17.37 | 179 | Population-weighted |
| Homicide | 5.44 | 4.19 | 1 | 4.82 | 301 | Population-weighted |
| Homicide | 9.17 | 5.65 | 2 | 7.31 | 292 | Population-weighted |
| Homicide | 9.02 | 6.40 | 3 | 7.86 | 281 | Population-weighted |
| Homicide | 14.24 | 8.53 | 4 | 11.44 | 282 | Population-weighted |
| Homicide | 12.33 | 7.48 | 5 | 9.89 | 277 | Population-weighted |
| Homicide | 9.99 | 6.87 | 6 | 8.45 | 275 | Population-weighted |
| Homicide | 10.00 | 6.19 | 7 | 7.86 | 275 | Population-weighted |
| Homicide | 7.73 | 5.66 | 8 | 6.63 | 280 | Population-weighted |
| Homicide | 10.31 | 7.40 | 9 | 8.79 | 273 | Population-weighted |
| Homicide | 16.17 | 11.14 | 10 | 13.63 | 257 | Population-weighted |
| Overdose | 23.25 | 21.05 | 1 | 22.19 | 302 | Each county counted once |
| Overdose | 25.61 | 22.63 | 2 | 24.07 | 296 | Each county counted once |
| Overdose | 25.72 | 22.45 | 3 | 24.04 | 289 | Each county counted once |
| Overdose | 27.06 | 22.97 | 4 | 25.01 | 283 | Each county counted once |
| Overdose | 24.59 | 20.70 | 5 | 22.56 | 270 | Each county counted once |
| Overdose | 23.20 | 19.55 | 6 | 21.40 | 268 | Each county counted once |
| Overdose | 26.06 | 21.64 | 7 | 23.81 | 270 | Each county counted once |
| Overdose | 25.14 | 20.33 | 8 | 22.68 | 260 | Each county counted once |
| Overdose | 23.62 | 19.26 | 9 | 21.33 | 248 | Each county counted once |
| Overdose | 26.39 | 19.55 | 10 | 22.96 | 215 | Each county counted once |
| Suicide | 16.12 | 14.57 | 1 | 15.34 | 267 | Each county counted once |
| Suicide | 18.19 | 16.75 | 2 | 17.46 | 255 | Each county counted once |
| Suicide | 18.63 | 17.09 | 3 | 17.85 | 247 | Each county counted once |
| Suicide | 18.27 | 16.91 | 4 | 17.58 | 239 | Each county counted once |
| Suicide | 18.45 | 16.62 | 5 | 17.46 | 243 | Each county counted once |
| Suicide | 18.36 | 16.64 | 6 | 17.49 | 225 | Each county counted once |
| Suicide | 18.40 | 16.95 | 7 | 17.66 | 214 | Each county counted once |
| Suicide | 17.53 | 15.88 | 8 | 16.72 | 211 | Each county counted once |
| Suicide | 16.89 | 15.09 | 9 | 16.04 | 183 | Each county counted once |
| Suicide | 15.33 | 13.24 | 10 | 14.22 | 179 | Each county counted once |
| Homicide | 3.74 | 3.11 | 1 | 3.41 | 301 | Each county counted once |
| Homicide | 4.88 | 3.94 | 2 | 4.34 | 292 | Each county counted once |
| Homicide | 4.76 | 3.86 | 3 | 4.29 | 281 | Each county counted once |
| Homicide | 5.48 | 4.14 | 4 | 4.79 | 282 | Each county counted once |
| Homicide | 5.48 | 4.17 | 5 | 4.79 | 277 | Each county counted once |
| Homicide | 5.10 | 3.90 | 6 | 4.48 | 275 | Each county counted once |
| Homicide | 6.06 | 4.63 | 7 | 5.31 | 275 | Each county counted once |
| Homicide | 5.55 | 4.23 | 8 | 4.91 | 280 | Each county counted once |
| Homicide | 7.24 | 5.54 | 9 | 6.36 | 273 | Each county counted once |
| Homicide | 10.86 | 8.16 | 10 | 9.47 | 257 | Each county counted once |

Views: Population-weighted (weighting = Population-weighted); Each county counted once (weighting = Each county counted once).

Note: The deprivation rank of a county is the population-weighted mean of the Area Deprivation Index national ranks of its tracts, so a county ranked as least deprived can contain deprived tracts. The index understates deprivation in high-cost areas.

Note: Counties without a stable rate in all five years are left out of that cause's line: 2,714 counties for overdose, 2,273 for suicide and 2,807 for homicide, out of 3,120 counties with a deprivation rank. The suicide line is thinnest in the most deprived tenth, where CDC marks the most small-county rates unstable. Connecticut is not in CDC's county file.

Note: The weighted and unweighted views differ for suicide and overdose: counting every county once, the ratio of the most deprived tenth to the least deprived is 0.93 for suicide and 1.03 for overdose, against 2.78 for homicide, so the weighted rise comes from the larger counties.

Note: Across all the counties in the comparison, weighted by population, the rate is 27.7 per hundred thousand residents for overdose, 14.3 for suicide and 7.1 for homicide.

Source: CDC Mapping Injury, Overdose, and Violence county file, 2019-2023, and Area Deprivation Index 2023; modeled estimates, crude rates, population-weighted and unweighted

Data: https://vishalsingh.org/zipcode/report/overdose-alcohol-and-suicide/figures/three_causes_by_decile.json

### Table 3. Weighted by population, suicide rates in more urban nonmetro counties are 1.6 times those in large metro counties, and homicide rates in large metro counties are 1.6 times those in the least urban nonmetro counties

CDC modeled death rates per 100,000 residents by 2023 Rural-Urban Continuum Code group of county, mean of annual rates for 2019 to 2023, county rates weighted by population

| cause | conf_high | conf_low | county_type | estimate | n_units | weighting |
| --- | ---: | ---: | --- | ---: | ---: | --- |
| Overdose | 30.00 | 25.67 | Large metro | 27.79 | 428 | Population-weighted |
| Overdose | 29.93 | 26.91 | Smaller metro | 28.41 | 702 | Population-weighted |
| Overdose | 27.72 | 25.21 | Nonmetro, more urban | 26.45 | 851 | Population-weighted |
| Overdose | 23.48 | 20.20 | Nonmetro, least urban | 21.77 | 733 | Population-weighted |
| Suicide | 12.88 | 11.57 | Large metro | 12.21 | 387 | Population-weighted |
| Suicide | 17.15 | 16.00 | Smaller metro | 16.58 | 629 | Population-weighted |
| Suicide | 20.19 | 19.23 | Nonmetro, more urban | 19.69 | 668 | Population-weighted |
| Suicide | 18.54 | 17.01 | Nonmetro, least urban | 17.74 | 589 | Population-weighted |
| Homicide | 8.69 | 6.65 | Large metro | 7.62 | 431 | Population-weighted |
| Homicide | 7.29 | 6.15 | Smaller metro | 6.69 | 704 | Population-weighted |
| Homicide | 6.30 | 5.24 | Nonmetro, more urban | 5.76 | 846 | Population-weighted |
| Homicide | 5.13 | 4.19 | Nonmetro, least urban | 4.65 | 826 | Population-weighted |
| Overdose | 29.92 | 26.84 | Large metro | 28.34 | 428 | Each county counted once |
| Overdose | 27.02 | 24.61 | Smaller metro | 25.81 | 702 | Each county counted once |
| Overdose | 24.96 | 22.88 | Nonmetro, more urban | 23.88 | 851 | Each county counted once |
| Overdose | 17.23 | 14.75 | Nonmetro, least urban | 15.96 | 733 | Each county counted once |
| Suicide | 15.03 | 14.14 | Large metro | 14.59 | 387 | Each county counted once |
| Suicide | 17.86 | 17.08 | Smaller metro | 17.47 | 629 | Each county counted once |
| Suicide | 20.02 | 19.15 | Nonmetro, more urban | 19.58 | 668 | Each county counted once |
| Suicide | 14.99 | 13.69 | Nonmetro, least urban | 14.34 | 589 | Each county counted once |
| Homicide | 6.87 | 5.62 | Large metro | 6.20 | 431 | Each county counted once |
| Homicide | 6.34 | 5.50 | Smaller metro | 5.90 | 704 | Each county counted once |
| Homicide | 6.00 | 5.08 | Nonmetro, more urban | 5.53 | 846 | Each county counted once |
| Homicide | 3.89 | 3.16 | Nonmetro, least urban | 3.53 | 826 | Each county counted once |

Views: Population-weighted (weighting = Population-weighted); Each county counted once (weighting = Each county counted once).

Note: The groups follow the Rural-Urban Continuum Code: large metro is counties in metro areas of 1 million or more, smaller metro is the other metro counties, more urban nonmetro counties have an urban population of 5,000 or more, and least urban nonmetro counties have fewer. Connecticut is not in CDC's county file.

Note: Rates are crude, not age-adjusted. Age structure differs between rural and urban counties, and suicide rates differ by age, so part of a difference between types of county can reflect age structure and not the same risk at every age.

Source: CDC Mapping Injury, Overdose, and Violence county file, 2019-2023, and USDA Rural-Urban Continuum Codes 2023; modeled estimates, crude rates, population-weighted and unweighted

Data: https://vishalsingh.org/zipcode/report/overdose-alcohol-and-suicide/figures/rate_by_county_type.json

### Table 4. Overdose deaths exceed alcohol-induced deaths in 479 of 545 mapped counties, and the 66 counties where alcohol is higher lie mostly in the West and Midwest

Crude alcohol-induced death rate relative to crude overdose death rate, log base 2 of the ratio, counties with a published count in every year and at least 20 pooled deaths of each cause, 2018 to 2024

No inline rows: the values of Table 4 are in https://vishalsingh.org/zipcode/data/overdose-alcohol-and-suicide/drug_vs_alcohol_dominance.json.

Note: A county is drawn when WONDER publishes its drug and alcohol counts in every year from 2018 to 2024 and it has at least 20 pooled deaths of each. WONDER withholds county-year counts above zero and below 10, so a rate built from the published years of a county with withheld years would leave out its low-count years; the map uses only counties with no withheld year. That leaves 545 of the counties, which hold 76.6% of residents outside Connecticut, and the tooltip gives the reason for every gray county.

Note: Those counties are selected on the outcome as well as on size. Among counties of 30,000 to 60,000 residents, the mean overdose rate in CDC's modeled panel is 50.9 in counties whose WONDER overdose count is published in every year and 22.5 in the rest: a county whose deaths reach 10 or more in every year has a high rate for its size. The map describes those counties and not counties in general.

Note: Rates are crude, not age-adjusted. Drug deaths are drug poisonings of any intent (unintentional, suicide, homicide and undetermined), alcohol-induced deaths are WONDER's alcohol-induced category, and the county ratio compares counts and populations from the same WONDER query. Connecticut's counties have no population in WONDER for 2022 to 2024, so they are gray. Valdez-Cordova AK is coded by its old code and draws on both successor areas; Kusilvak AK and Oglala Lakota SD are drawn under their current codes. Puerto Rico is not drawn.

Source: CDC WONDER underlying cause of death, 2018-2024; crude rates, counties with a published count in every year

Data: https://vishalsingh.org/zipcode/report/overdose-alcohol-and-suicide/figures/drug_vs_alcohol_dominance.json

### Table 5. Among counties with published counts in every year, the population-weighted correlation of deprivation is +0.42 with suicide and +0.35 with overdose death rates, against +0.13 with alcohol-induced death rates

Crude death rates per 100,000 residents by tenth of counties ranked by Area Deprivation Index, counties with a published count in every year for all three kinds of death, 2018 to 2024, weighted by person-years

| cause | conf_high | conf_low | decile | estimate | n_units |
| --- | ---: | ---: | ---: | ---: | ---: |
| Overdose | 24.80 | 20.04 | 1 | 21.99 | 52 |
| Overdose | 27.34 | 20.94 | 2 | 24.01 | 53 |
| Overdose | 31.36 | 23.49 | 3 | 27.64 | 52 |
| Overdose | 29.42 | 23.00 | 4 | 26.06 | 53 |
| Overdose | 30.54 | 22.71 | 5 | 27.06 | 52 |
| Overdose | 39.78 | 26.38 | 6 | 32.06 | 53 |
| Overdose | 41.98 | 27.94 | 7 | 34.55 | 52 |
| Overdose | 45.37 | 30.72 | 8 | 37.26 | 53 |
| Overdose | 39.62 | 29.73 | 9 | 34.91 | 52 |
| Overdose | 40.00 | 25.20 | 10 | 32.29 | 53 |
| Alcohol-induced causes | 14.04 | 10.78 | 1 | 12.54 | 52 |
| Alcohol-induced causes | 15.52 | 11.99 | 2 | 13.76 | 53 |
| Alcohol-induced causes | 16.56 | 12.24 | 3 | 14.44 | 52 |
| Alcohol-induced causes | 14.22 | 10.93 | 4 | 12.30 | 53 |
| Alcohol-induced causes | 15.58 | 12.07 | 5 | 13.42 | 52 |
| Alcohol-induced causes | 17.39 | 11.97 | 6 | 14.30 | 53 |
| Alcohol-induced causes | 15.22 | 12.22 | 7 | 13.48 | 52 |
| Alcohol-induced causes | 16.86 | 14.36 | 8 | 15.57 | 53 |
| Alcohol-induced causes | 16.05 | 13.60 | 9 | 14.71 | 52 |
| Alcohol-induced causes | 22.74 | 13.88 | 10 | 17.57 | 53 |
| Suicide | 11.05 | 9.07 | 1 | 9.90 | 52 |
| Suicide | 14.56 | 11.76 | 2 | 13.07 | 53 |
| Suicide | 16.09 | 12.55 | 3 | 14.35 | 52 |
| Suicide | 14.53 | 12.38 | 4 | 13.27 | 53 |
| Suicide | 15.88 | 11.98 | 5 | 13.72 | 52 |
| Suicide | 16.51 | 13.24 | 6 | 14.61 | 53 |
| Suicide | 16.50 | 14.06 | 7 | 15.08 | 52 |
| Suicide | 17.56 | 15.05 | 8 | 16.27 | 53 |
| Suicide | 16.99 | 14.71 | 9 | 15.73 | 52 |
| Suicide | 18.93 | 14.24 | 10 | 16.50 | 53 |

Note: The figure uses the 525 counties whose drug, alcohol and suicide counts WONDER publishes in every year from 2018 to 2024, which hold 76.0% of residents outside Connecticut. WONDER withholds county-year counts above zero and below 10, which would drop the low-count years of a small county and bias its rate. The tenths are tenths of these counties ranked by deprivation, with equal numbers of counties, so the most deprived tenth here is not the most deprived tenth of all counties.

Note: These counties are selected on the outcome as well as on size (see Figure 4), so the correlations describe them and not counties in general. In all counties with a modeled rate, the population-weighted correlation with deprivation is +0.46 for suicide and +0.22 for overdose (Figure 2), and +0.01 and −0.01 counting every county once.

Note: Rates are crude, not age-adjusted. A suicide by drug poisoning is counted in both the overdose and the suicide rate. The most deprived tenth includes counties with large American Indian and Alaska Native populations, where alcohol-induced death rates are high.

Source: CDC WONDER underlying cause of death, 2018-2024, and Area Deprivation Index 2023; crude rates, population-weighted (person-years)

Data: https://vishalsingh.org/zipcode/report/overdose-alcohol-and-suicide/figures/despair_gradient.json

### Table 6. The overdose death rate does not differ detectably between the least and the most deprived places under the ADI; it is worse at the more deprived end but uneven along the way under the income ranking

Overdose deaths per 100,000 residents by tenth of counties ranked four ways, over the 2,699 counties that have all four rankings

| bin | conf_high | conf_low | estimate | n_units | ranking |
| ---: | ---: | ---: | ---: | ---: | --- |
| 1 | 25.73 | 22.32 | 23.98 | 301 | Area Deprivation Index |
| 2 | 29.71 | 24.37 | 27.05 | 294 | Area Deprivation Index |
| 3 | 37.57 | 27.61 | 32.22 | 290 | Area Deprivation Index |
| 4 | 39.38 | 29.56 | 34.01 | 281 | Area Deprivation Index |
| 5 | 33.46 | 26.73 | 30.04 | 272 | Area Deprivation Index |
| 6 | 34.52 | 25.38 | 30.27 | 269 | Area Deprivation Index |
| 7 | 34.66 | 27.24 | 30.94 | 268 | Area Deprivation Index |
| 8 | 34.44 | 22.27 | 28.15 | 261 | Area Deprivation Index |
| 9 | 30.71 | 24.25 | 27.22 | 242 | Area Deprivation Index |
| 10 | 35.31 | 24.80 | 30.05 | 221 | Area Deprivation Index |
| 1 | 23.20 | 20.29 | 21.74 | 300 | Standardized index |
| 2 | 30.97 | 25.61 | 28.42 | 296 | Standardized index |
| 3 | 34.32 | 26.26 | 30.03 | 273 | Standardized index |
| 4 | 29.67 | 23.00 | 25.92 | 260 | Standardized index |
| 5 | 37.89 | 29.35 | 33.55 | 283 | Standardized index |
| 6 | 40.27 | 31.70 | 36.37 | 265 | Standardized index |
| 7 | 48.75 | 26.81 | 37.39 | 261 | Standardized index |
| 8 | 30.39 | 24.17 | 27.13 | 271 | Standardized index |
| 9 | 36.80 | 24.06 | 30.61 | 247 | Standardized index |
| 10 | 34.57 | 20.33 | 26.97 | 243 | Standardized index |
| 1 | 24.36 | 21.19 | 22.68 | 300 | Median household income |
| 2 | 29.37 | 24.46 | 27.04 | 295 | Median household income |
| 3 | 33.05 | 25.53 | 28.89 | 284 | Median household income |
| 4 | 33.50 | 25.01 | 29.39 | 275 | Median household income |
| 5 | 40.44 | 32.14 | 36.53 | 267 | Median household income |
| 6 | 47.88 | 29.17 | 38.58 | 264 | Median household income |
| 7 | 35.61 | 28.82 | 32.13 | 262 | Median household income |
| 8 | 33.75 | 23.00 | 28.01 | 259 | Median household income |
| 9 | 31.52 | 26.39 | 28.87 | 246 | Median household income |
| 10 | 37.60 | 28.75 | 33.15 | 247 | Median household income |
| 1 | 26.33 | 22.27 | 24.29 | 298 | Bachelor's degree share |
| 2 | 31.45 | 26.22 | 28.93 | 295 | Bachelor's degree share |
| 3 | 35.98 | 25.74 | 30.09 | 285 | Bachelor's degree share |
| 4 | 33.74 | 27.06 | 30.26 | 266 | Bachelor's degree share |
| 5 | 32.82 | 25.50 | 29.05 | 249 | Bachelor's degree share |
| 6 | 29.74 | 22.80 | 25.95 | 277 | Bachelor's degree share |
| 7 | 32.85 | 26.02 | 29.49 | 258 | Bachelor's degree share |
| 8 | 32.12 | 26.81 | 29.38 | 263 | Bachelor's degree share |
| 9 | 30.65 | 24.86 | 27.68 | 257 | Bachelor's degree share |
| 10 | 32.97 | 25.96 | 29.41 | 251 | Bachelor's degree share |

Note: Least and most deprived tenth: ADI 24.0 and 30.0, rank correlation +0.14; standardized index 21.7 and 27.0, +0.28; median household income 22.7 and 33.1, +0.43; bachelor's degree share 24.3 and 29.4, +0.14.

Note: The standardized index applies the ADI's coefficients to its measures after standardizing each one, so home value and income carry less weight than in the ADI. Income and degree share are single census measures, each ranked from the highest value to the lowest.

Source: CDC Mapping Injury, Overdose, and Violence county file, 2019-2023, and Area Deprivation Index 2023; modeled estimates, crude rates, population-weighted; ADI 2023 and ACS 2019-2023 tract tables (B19013, B15003 and the 15 rebuilt ADI measures)

Data: https://vishalsingh.org/zipcode/report/overdose-alcohol-and-suicide/figures/alt_rankings.json

### Table 7. Weighted by residents, the county overdose rate rises weakly with deprivation (+0.22), and counted once each, counties show no relation (−0.01)

Overdose deaths per 100,000 residents, 2019 to 2023 average, modeled county rates, against county Area Deprivation Index; dot area is residents

No inline rows: the values of Table 7 are in https://vishalsingh.org/zipcode/data/overdose-alcohol-and-suicide/overdose_map_scatter.json.

Note: Counties without a stable modeled rate in every year from 2019 to 2023 are gray on the map and have no dot; Connecticut's counties are not in CDC's county file.

Source: CDC Mapping Injury, Overdose, and Violence county file, 2019-2023, and Area Deprivation Index 2023; modeled estimates, crude rates

Data: https://vishalsingh.org/zipcode/report/overdose-alcohol-and-suicide/figures/overdose_map_scatter.json

## All estimates

Every fact in facts.json (162), sorted by id.

| Fact id | Value | Unit | Estimand | Population | Period | Interval | n | Weights | Source | Note |
| --- | ---: | --- | --- | --- | --- | --- | ---: | --- | --- | --- |
| a_n | 3,120 | counties | count of counties | counties in CDC's county file with an Area Deprivation Index rank | ADI 2023 |   |   | none (full count) | Area Deprivation Index |   |
| aian5_alc_higher | 8 | counties | count with a higher crude alcohol-induced than overdose death rate | mapped counties where American Indian or Alaska Native residents are at least the lower cutoff share | deaths in 2018 to 2024 |   | 27 counties | none (full count) | CDC WONDER underlying cause of death |   |
| aian5_cut | 5% | percent of residents who are American Indian or Alaska Native | definition: the lower cutoff used to check how the counts change | counties | Census Population Estimates 2022 as reported by County Health Rankings 2024 |   |   | none (definition) | County Health Rankings |   |
| aian5_n | 27 | counties | count of counties | mapped counties where American Indian or Alaska Native residents are at least the lower cutoff share | Census Population Estimates 2022 as reported by County Health Rankings 2024 |   |   | none (full count) | County Health Rankings |   |
| aian_alc_higher | 6 | counties | count with a higher crude alcohol-induced than overdose death rate | mapped counties where American Indian or Alaska Native residents are at least the cutoff share | deaths in 2018 to 2024 |   | 10 counties | none (full count) | CDC WONDER underlying cause of death |   |
| aian_all_n | 133 | counties | count of counties | counties in CDC WONDER where American Indian or Alaska Native residents are at least the cutoff share (Alaska and South Dakota codes mapped to their successors) | Census Population Estimates 2022 as reported by County Health Rankings 2024 |   |   | none (full count) | County Health Rankings |   |
| aian_cut | 10% | percent of residents who are American Indian or Alaska Native | definition: a county counts as American Indian or Alaska Native heavy at this share of residents | counties | Census Population Estimates 2022 as reported by County Health Rankings 2024 |   |   | none (definition) | County Health Rankings |   |
| aian_n | 10 | counties | count of counties | mapped counties where American Indian or Alaska Native residents are at least the cutoff share | Census Population Estimates 2022 as reported by County Health Rankings 2024 |   |   | none (full count) | County Health Rankings |   |
| aian_rate | 57.3 | alcohol-induced deaths per 100,000 residents | pooled crude rate | residents of mapped counties where American Indian or Alaska Native residents are at least the cutoff share | deaths in 2018 to 2024 |   | 10 counties | none (crude rate from counts) | CDC WONDER underlying cause of death |   |
| aian_rate_other | 13.6 | alcohol-induced deaths per 100,000 residents | pooled crude rate | residents of the other mapped counties | deaths in 2018 to 2024 |   | 535 counties | none (crude rate from counts) | CDC WONDER underlying cause of death |   |
| aian_top10 | 6 | counties | count of those counties where American Indian or Alaska Native residents are at least the cutoff share | the ten mapped counties with the highest crude alcohol-induced death rate | deaths in 2018 to 2024 |   | 10 counties | none (full count) | CDC WONDER underlying cause of death |   |
| all_hm | 47.7% | percent of counties | share of counties with a stable homicide rate in the South region (Census regions) | counties in CDC's county file with a stable modeled rate in each year 2019 to 2023 | annual modeled rates for 2019 to 2023, averaged |   | 2,807 counties | none (each county counts once) | CDC injury and violence mapping |   |
| all_od | 45.7% | percent of counties | share of counties with a stable overdose rate in the South region (Census regions) | counties in CDC's county file with a stable modeled rate in each year 2019 to 2023 | annual modeled rates for 2019 to 2023, averaged |   | 2,714 counties | none (each county counts once) | CDC injury and violence mapping |   |
| all_su | 13.7% | percent of counties | share of counties with a stable suicide rate in the West region (Census regions) | counties in CDC's county file with a stable modeled rate in each year 2019 to 2023 | annual modeled rates for 2019 to 2023, averaged |   | 2,273 counties | none (each county counts once) | CDC injury and violence mapping |   |
| alt_adi_least | 24.0 | Overdose deaths per 100,000 residents | population-weighted mean of county modeled overdose rates; 95% intervals from a bootstrap over counties | the least deprived tenth of counties ranked by Area Deprivation Index, among the counties with all four rankings | annual modeled rates for 2019 to 2023, averaged; rankings from ACS 2019-2023 | 95% CI 22.3 to 25.7 | 301 counties | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| alt_adi_most | 30.0 | Overdose deaths per 100,000 residents | population-weighted mean of county modeled overdose rates; 95% intervals from a bootstrap over counties | the most deprived tenth of counties ranked by Area Deprivation Index, among the counties with all four rankings | annual modeled rates for 2019 to 2023, averaged; rankings from ACS 2019-2023 | 95% CI 24.8 to 35.3 | 221 counties | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| alt_adi_rho | +0.14 | rank correlation | Spearman rank correlation between bin order and bin mean, each bin counted once | the bins of counties ranked by Area Deprivation Index | annual modeled rates for 2019 to 2023, averaged; rankings from ACS 2019-2023 |   |   | each bin counted once | CDC injury and violence mapping |   |
| alt_degree_least | 24.3 | Overdose deaths per 100,000 residents | population-weighted mean of county modeled overdose rates; 95% intervals from a bootstrap over counties | the least deprived tenth of counties ranked by Bachelor's degree share, among the counties with all four rankings | annual modeled rates for 2019 to 2023, averaged; rankings from ACS 2019-2023 | 95% CI 22.3 to 26.3 | 298 counties | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| alt_degree_most | 29.4 | Overdose deaths per 100,000 residents | population-weighted mean of county modeled overdose rates; 95% intervals from a bootstrap over counties | the most deprived tenth of counties ranked by Bachelor's degree share, among the counties with all four rankings | annual modeled rates for 2019 to 2023, averaged; rankings from ACS 2019-2023 | 95% CI 26.0 to 33.0 | 251 counties | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| alt_degree_rho | +0.14 | rank correlation | Spearman rank correlation between bin order and bin mean, each bin counted once | the bins of counties ranked by Bachelor's degree share | annual modeled rates for 2019 to 2023, averaged; rankings from ACS 2019-2023 |   |   | each bin counted once | CDC injury and violence mapping |   |
| alt_income_least | 22.7 | Overdose deaths per 100,000 residents | population-weighted mean of county modeled overdose rates; 95% intervals from a bootstrap over counties | the least deprived tenth of counties ranked by Median household income, among the counties with all four rankings | annual modeled rates for 2019 to 2023, averaged; rankings from ACS 2019-2023 | 95% CI 21.2 to 24.4 | 300 counties | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| alt_income_most | 33.1 | Overdose deaths per 100,000 residents | population-weighted mean of county modeled overdose rates; 95% intervals from a bootstrap over counties | the most deprived tenth of counties ranked by Median household income, among the counties with all four rankings | annual modeled rates for 2019 to 2023, averaged; rankings from ACS 2019-2023 | 95% CI 28.7 to 37.6 | 247 counties | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| alt_income_rho | +0.43 | rank correlation | Spearman rank correlation between bin order and bin mean, each bin counted once | the bins of counties ranked by Median household income | annual modeled rates for 2019 to 2023, averaged; rankings from ACS 2019-2023 |   |   | each bin counted once | CDC injury and violence mapping |   |
| alt_n_places | 2,699 | counties | count of counties in the common sample of the ranking comparison | counties with the outcome and all four rankings | annual modeled rates for 2019 to 2023, averaged; rankings from ACS 2019-2023 |   |   | none (full count) | CDC injury and violence mapping |   |
| alt_rho_cut | 0.9 | absolute rank correlation | threshold between a steady and an uneven gradient | the rule for changed gradients (docs/RANKING_SWITCH_RULE.md) | annual modeled rates for 2019 to 2023, averaged; rankings from ACS 2019-2023 |   |   | none (a fixed rule) | CDC injury and violence mapping |   |
| alt_rho_margin | 0.1 | absolute rank correlation | smallest move in the rank correlation that counts as a change of shape | the rule for changed gradients (docs/RANKING_SWITCH_RULE.md) | annual modeled rates for 2019 to 2023, averaged; rankings from ACS 2019-2023 |   |   | none (a fixed rule) | CDC injury and violence mapping |   |
| alt_std_least | 21.7 | Overdose deaths per 100,000 residents | population-weighted mean of county modeled overdose rates; 95% intervals from a bootstrap over counties | the least deprived tenth of counties ranked by Standardized index, among the counties with all four rankings | annual modeled rates for 2019 to 2023, averaged; rankings from ACS 2019-2023 | 95% CI 20.3 to 23.2 | 300 counties | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| alt_std_most | 27.0 | Overdose deaths per 100,000 residents | population-weighted mean of county modeled overdose rates; 95% intervals from a bootstrap over counties | the most deprived tenth of counties ranked by Standardized index, among the counties with all four rankings | annual modeled rates for 2019 to 2023, averaged; rankings from ACS 2019-2023 | 95% CI 20.3 to 34.6 | 243 counties | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| alt_std_rho | +0.28 | rank correlation | Spearman rank correlation between bin order and bin mean, each bin counted once | the bins of counties ranked by Standardized index | annual modeled rates for 2019 to 2023, averaged; rankings from ACS 2019-2023 |   |   | each bin counted once | CDC injury and violence mapping |   |
| dom_alc_2x | 6 | counties | count of mapped counties with an alcohol-induced rate at least twice the overdose rate | mapped counties | deaths in 2018 to 2024 |   | 545 counties | none (full count) | CDC WONDER underlying cause of death |   |
| dom_alc_higher | 66 | counties | count of mapped counties with a higher crude alcohol-induced than overdose death rate | mapped counties | deaths in 2018 to 2024 |   | 545 counties | none (full count) | CDC WONDER underlying cause of death |   |
| dom_alc_midwest | 16.4% | percent of mapped counties | share of mapped counties with a higher crude alcohol-induced than overdose death rate | mapped counties in the Midwest Census region | deaths in 2018 to 2024 |   | 116 counties | none (each county counts once) | CDC WONDER underlying cause of death |   |
| dom_alc_ne | 0.0% | percent of mapped counties | share of mapped counties with a higher crude alcohol-induced than overdose death rate | mapped counties in the Northeast Census region | deaths in 2018 to 2024 |   | 94 counties | none (each county counts once) | CDC WONDER underlying cause of death |   |
| dom_alc_south | 6.5% | percent of mapped counties | share of mapped counties with a higher crude alcohol-induced than overdose death rate | mapped counties in the South Census region | deaths in 2018 to 2024 |   | 217 counties | none (each county counts once) | CDC WONDER underlying cause of death |   |
| dom_alc_west | 28.0% | percent of mapped counties | share of mapped counties with a higher crude alcohol-induced than overdose death rate | mapped counties in the West Census region | deaths in 2018 to 2024 |   | 118 counties | none (each county counts once) | CDC WONDER underlying cause of death |   |
| dom_both | 569 | counties | count of counties | counties whose drug and alcohol counts are both published in every year | deaths in 2018 to 2024 |   |   | none (full count) | CDC WONDER underlying cause of death |   |
| dom_corr | +0.25 | correlation coefficient | correlation of the county crude overdose and alcohol-induced death rates, weighted by county population; bootstrap over counties | counties whose drug and alcohol counts are both published in every year | deaths in 2018 to 2024 | 95% CI 0.16 to 0.35 | 569 counties | WONDER county population | CDC WONDER underlying cause of death |   |
| dom_corr_u | +0.30 | correlation coefficient | correlation of the county crude overdose and alcohol-induced death rates, counting every county once; bootstrap over counties | counties whose drug and alcohol counts are both published in every year | deaths in 2018 to 2024 | 95% CI 0.20 to 0.43 | 569 counties | none (each county counts once) | CDC WONDER underlying cause of death |   |
| dom_f2 | 2 | times | definition: the ratio at which the first class boundaries of the dominance map fall | county overdose and alcohol-induced death rates | deaths in 2018 to 2024 |   |   | none (definition) | CDC WONDER underlying cause of death |   |
| dom_f4 | 4 | times | definition: the ratio at which the second class boundaries of the dominance map fall | county overdose and alcohol-induced death rates | deaths in 2018 to 2024 |   |   | none (definition) | CDC WONDER underlying cause of death |   |
| dom_n | 545 | counties | count of mapped counties | counties complete for drug and alcohol with at least 20 pooled deaths of each | deaths in 2018 to 2024 |   |   | none (full count) | CDC WONDER underlying cause of death |   |
| dom_od_2x | 234 | counties | count of mapped counties with an overdose rate at least twice the alcohol-induced rate | mapped counties | deaths in 2018 to 2024 |   | 545 counties | none (full count) | CDC WONDER underlying cause of death |   |
| dom_od_higher | 479 | counties | count of mapped counties with a higher crude overdose than alcohol-induced death rate | mapped counties | deaths in 2018 to 2024 |   | 545 counties | none (full count) | CDC WONDER underlying cause of death |   |
| dom_pop | 76.6% | percent of residents | share of those residents (person-years) living in the mapped counties | residents of the 49 states and DC outside Connecticut, which has no WONDER county population for 2022 to 2024 | WONDER population, 2018 to 2024 |   |   | WONDER county population | CDC WONDER underlying cause of death |   |
| dom_wm_share | 78.8% | percent of mapped counties with a higher alcohol-induced rate | share in the West and Midwest Census regions | mapped counties with a higher alcohol-induced than overdose rate | deaths in 2018 to 2024 |   | 66 counties | none (each county counts once) | CDC WONDER underlying cause of death |   |
| g_adi_alc | +0.13 | correlation coefficient | correlation of the county crude alcohol-induced rate with the Area Deprivation Index rank, weighted by person-years; bootstrap over counties | counties in the gradient | deaths in 2018 to 2024 | 95% CI 0.04 to 0.22 | 525 counties | person-years in the county | CDC WONDER underlying cause of death |   |
| g_adi_alc_u | +0.15 | correlation coefficient | correlation of the county crude alcohol-induced rate with the Area Deprivation Index rank, counting every county once; bootstrap over counties | counties in the gradient | deaths in 2018 to 2024 | 95% CI 0.05 to 0.22 | 525 counties | none (each county counts once) | CDC WONDER underlying cause of death |   |
| g_adi_od | +0.35 | correlation coefficient | correlation of the county crude overdose rate with the Area Deprivation Index rank, weighted by person-years; bootstrap over counties | counties in the gradient | deaths in 2018 to 2024 | 95% CI 0.24 to 0.44 | 525 counties | person-years in the county | CDC WONDER underlying cause of death |   |
| g_adi_od_u | +0.26 | correlation coefficient | correlation of the county crude overdose rate with the Area Deprivation Index rank, counting every county once; bootstrap over counties | counties in the gradient | deaths in 2018 to 2024 | 95% CI 0.19 to 0.34 | 525 counties | none (each county counts once) | CDC WONDER underlying cause of death |   |
| g_adi_su | +0.42 | correlation coefficient | correlation of the county crude suicide rate with the Area Deprivation Index rank, weighted by person-years; bootstrap over counties | counties in the gradient | deaths in 2018 to 2024 | 95% CI 0.30 to 0.51 | 525 counties | person-years in the county | CDC WONDER underlying cause of death |   |
| g_adi_su_u | +0.28 | correlation coefficient | correlation of the county crude suicide rate with the Area Deprivation Index rank, counting every county once; bootstrap over counties | counties in the gradient | deaths in 2018 to 2024 | 95% CI 0.19 to 0.36 | 525 counties | none (each county counts once) | CDC WONDER underlying cause of death |   |
| g_alc_d1 | 12.5 | deaths per 100,000 residents | pooled crude alcohol-induced rate; bootstrap over counties | residents of the least deprived tenth of the counties in the gradient | deaths in 2018 to 2024 | 95% CI 10.8 to 14.0 | 52 counties | none (crude rate from counts) | CDC WONDER underlying cause of death |   |
| g_alc_d10 | 17.6 | deaths per 100,000 residents | pooled crude alcohol-induced rate; bootstrap over counties | residents of the most deprived tenth of the counties in the gradient | deaths in 2018 to 2024 | 95% CI 13.9 to 22.7 | 53 counties | none (crude rate from counts) | CDC WONDER underlying cause of death |   |
| g_alc_d10_ex | 14.4 | deaths per 100,000 residents | pooled crude alcohol-induced rate; bootstrap over counties | residents of the most deprived tenth of the gradient, without its counties where American Indian or Alaska Native residents are at least the cutoff share | deaths in 2018 to 2024 | 95% CI 12.1 to 16.6 | 48 counties | none (crude rate from counts) | CDC WONDER underlying cause of death |   |
| g_d10_aian_n | 5 | counties | count of counties | counties in the most deprived tenth of the gradient where American Indian or Alaska Native residents are at least the cutoff share | deaths in 2018 to 2024 |   | 53 counties | none (full count) | CDC WONDER underlying cause of death |   |
| g_diff_od_alc | +0.21 | difference between two correlation coefficients | correlation with deprivation for overdose minus that for alcohol-induced causes, weighted by person-years, from one set of bootstrap draws over counties | counties in the gradient | deaths in 2018 to 2024 | 95% CI 0.09 to 0.33 | 525 counties | person-years in the county | CDC WONDER underlying cause of death |   |
| g_diff_su_alc | +0.28 | difference between two correlation coefficients | correlation with deprivation for suicide minus that for alcohol-induced causes, weighted by person-years, from one set of bootstrap draws over counties | counties in the gradient | deaths in 2018 to 2024 | 95% CI 0.18 to 0.39 | 525 counties | person-years in the county | CDC WONDER underlying cause of death |   |
| g_n | 525 | counties | count of counties in the gradient | counties whose drug, alcohol and suicide counts are published in every year and that have a deprivation rank | deaths in 2018 to 2024 |   |   | none (full count) | CDC WONDER underlying cause of death |   |
| g_od_d1 | 22.0 | deaths per 100,000 residents | pooled crude overdose rate; bootstrap over counties | residents of the least deprived tenth of the counties in the gradient | deaths in 2018 to 2024 | 95% CI 20.0 to 24.8 | 52 counties | none (crude rate from counts) | CDC WONDER underlying cause of death |   |
| g_od_d10 | 32.3 | deaths per 100,000 residents | pooled crude overdose rate; bootstrap over counties | residents of the most deprived tenth of the counties in the gradient | deaths in 2018 to 2024 | 95% CI 25.2 to 40.0 | 53 counties | none (crude rate from counts) | CDC WONDER underlying cause of death |   |
| g_od_diff | 10.3 | deaths per 100,000 residents | pooled crude overdose rate of the most deprived tenth minus that of the least deprived tenth, weighted by person-years; bootstrap over counties with draws shared by the two tenths | residents of the most deprived tenth of the gradient relative to the least deprived tenth | deaths in 2018 to 2024 | 95% CI 2.5 to 18.3 | 525 counties | person-years in the county | CDC WONDER underlying cause of death |   |
| g_pop | 76.0% | percent of residents | share of those residents (person-years) living in the counties of the gradient | residents of the 49 states and DC outside Connecticut, which has no WONDER county population for 2022 to 2024 | WONDER population, 2018 to 2024 |   |   | WONDER county population | CDC WONDER underlying cause of death |   |
| g_su_d1 | 9.9 | deaths per 100,000 residents | pooled crude suicide rate; bootstrap over counties | residents of the least deprived tenth of the counties in the gradient | deaths in 2018 to 2024 | 95% CI 9.1 to 11.1 | 52 counties | none (crude rate from counts) | CDC WONDER underlying cause of death |   |
| g_su_d10 | 16.5 | deaths per 100,000 residents | pooled crude suicide rate; bootstrap over counties | residents of the most deprived tenth of the counties in the gradient | deaths in 2018 to 2024 | 95% CI 14.2 to 18.9 | 53 counties | none (crude rate from counts) | CDC WONDER underlying cause of death |   |
| g_su_diff | 6.6 | deaths per 100,000 residents | pooled crude suicide rate of the most deprived tenth minus that of the least deprived tenth, weighted by person-years; bootstrap over counties with draws shared by the two tenths | residents of the most deprived tenth of the gradient relative to the least deprived tenth | deaths in 2018 to 2024 | 95% CI 4.0 to 9.2 | 525 counties | person-years in the county | CDC WONDER underlying cause of death |   |
| map_floor | 20 | pooled deaths | definition: the least number of pooled deaths for a county to be mapped | a county drawn on a map of WONDER counts | deaths in 2018 to 2024 |   |   | none (definition) | CDC WONDER underlying cause of death |   |
| nc_adi_od_hi | +0.35 | correlation coefficient | correlation of the county crude overdose rate with the Area Deprivation Index rank, weighted by person-years, with the larger rise applied to North Carolina's published 2023 counts | counties in the gradient | deaths in 2018 to 2024 | 95% CI 0.24 to 0.44 | 525 counties | person-years in the county | CDC WONDER underlying cause of death |   |
| nc_diff_od_hi | 10.4 | deaths per 100,000 residents | pooled crude overdose rate of the most deprived tenth minus that of the least deprived tenth, with the larger rise applied to North Carolina's published 2023 counts; bootstrap over counties with shared draws | residents of the most deprived tenth of the gradient relative to the least deprived tenth | deaths in 2018 to 2024 | 95% CI 2.6 to 18.4 | 525 counties | person-years in the county | CDC WONDER underlying cause of death |   |
| nc_hi | 19% | percent of the published count | definition: the larger rise, which brings North Carolina's 2022-to-2023 change in the state file in line with the nation's | published 2023 drug counts of those counties | deaths in 2023 |   |   | none (definition) | CDC WONDER underlying cause of death |   |
| nc_lo | 10% | percent of the published count | definition: the smaller rise applied to each published county count in the sensitivity check (a withheld cell is never changed) | published 2023 drug counts of those counties | deaths in 2023 |   |   | none (definition) | CDC WONDER underlying cause of death |   |
| nc_n | 48 | counties | count of counties | North Carolina counties whose WONDER drug count is published in every year | deaths in 2018 to 2024 |   |   | none (full count) | CDC WONDER underlying cause of death |   |
| nc_share23 | 15.8% | percent of deaths | share of their published deaths in 2018 to 2024 that fall in 2023 | drug-poisoning deaths in those counties | deaths in 2018 to 2024 |   |   | none (full count) | CDC WONDER underlying cause of death |   |
| nc_shift_hi | 3.0% | percent change in the pooled rate | change in the pooled overdose rate of those counties if each published 2023 count were raised by the larger rise | North Carolina counties whose WONDER drug count is published in every year | deaths in 2018 to 2024 |   |   | none (crude rate from counts) | CDC WONDER underlying cause of death |   |
| nc_shift_lo | 1.6% | percent change in the pooled rate | change in the pooled overdose rate of those counties if each published 2023 count were raised by the smaller rise | North Carolina counties whose WONDER drug count is published in every year | deaths in 2018 to 2024 |   |   | none (crude rate from counts) | CDC WONDER underlying cause of death |   |
| p_adi_hm | +0.30 | correlation coefficient | correlation of the county homicide rate with the county Area Deprivation Index rank, population-weighted; bootstrap over counties | counties with a stable modeled homicide rate and a deprivation rank | annual modeled rates for 2019 to 2023, averaged | 95% CI 0.25 to 0.36 | 2,793 counties | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| p_adi_hm_u | +0.18 | correlation coefficient | correlation of the county homicide rate with the county Area Deprivation Index rank, counting every county once; bootstrap over counties | counties with a stable modeled homicide rate and a deprivation rank | annual modeled rates for 2019 to 2023, averaged | 95% CI 0.16 to 0.21 | 2,793 counties | none (each county counts once) | CDC injury and violence mapping |   |
| p_adi_od | +0.22 | correlation coefficient | correlation of the county overdose rate with the county Area Deprivation Index rank, population-weighted; bootstrap over counties | counties with a stable modeled overdose rate and a deprivation rank | annual modeled rates for 2019 to 2023, averaged | 95% CI 0.15 to 0.28 | 2,701 counties | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| p_adi_od_u | −0.01 | correlation coefficient | correlation of the county overdose rate with the county Area Deprivation Index rank, counting every county once; bootstrap over counties | counties with a stable modeled overdose rate and a deprivation rank | annual modeled rates for 2019 to 2023, averaged | 95% CI −0.04 to 0.03 | 2,701 counties | none (each county counts once) | CDC injury and violence mapping |   |
| p_adi_su | +0.46 | correlation coefficient | correlation of the county suicide rate with the county Area Deprivation Index rank, population-weighted; bootstrap over counties | counties with a stable modeled suicide rate and a deprivation rank | annual modeled rates for 2019 to 2023, averaged | 95% CI 0.37 to 0.53 | 2,263 counties | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| p_adi_su_u | +0.01 | correlation coefficient | correlation of the county suicide rate with the county Area Deprivation Index rank, counting every county once; bootstrap over counties | counties with a stable modeled suicide rate and a deprivation rank | annual modeled rates for 2019 to 2023, averaged | 95% CI −0.04 to 0.05 | 2,263 counties | none (each county counts once) | CDC injury and violence mapping |   |
| p_common_n | 1,899 | counties | count of counties | counties in CDC's county file with a stable rate for overdose, suicide and homicide in every year | 2019 to 2023 |   |   | none (full count) | CDC injury and violence mapping |   |
| p_common_pop | 93.5% | percent of residents | share of residents living in counties with a stable rate for all three kinds of death | residents of the 50 states and DC | 2019-2023 ACS residents |   |   | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| p_corr_od_hm | +0.48 | correlation coefficient | correlation of the county overdose and homicide rates, population-weighted; bootstrap over counties | counties with a stable rate for all three kinds of death | annual modeled rates for 2019 to 2023, averaged | 95% CI 0.35 to 0.58 | 1,899 counties | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| p_corr_od_hm_u | +0.27 | correlation coefficient | correlation of the county overdose and homicide rates, counting every county once; bootstrap over counties | counties with a stable rate for all three kinds of death | annual modeled rates for 2019 to 2023, averaged | 95% CI 0.20 to 0.33 | 1,899 counties | none (each county counts once) | CDC injury and violence mapping |   |
| p_corr_od_su | +0.13 | correlation coefficient | correlation of the county overdose and suicide rates, population-weighted; bootstrap over counties | counties with a stable rate for all three kinds of death | annual modeled rates for 2019 to 2023, averaged | 95% CI 0.05 to 0.21 | 1,899 counties | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| p_corr_od_su_u | +0.19 | correlation coefficient | correlation of the county overdose and suicide rates, counting every county once; bootstrap over counties | counties with a stable rate for all three kinds of death | annual modeled rates for 2019 to 2023, averaged | 95% CI 0.14 to 0.23 | 1,899 counties | none (each county counts once) | CDC injury and violence mapping |   |
| p_corr_su_hm | −0.02 | correlation coefficient | correlation of the county suicide and homicide rates, population-weighted; bootstrap over counties | counties with a stable rate for all three kinds of death | annual modeled rates for 2019 to 2023, averaged | 95% CI −0.10 to 0.06 | 1,899 counties | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| p_corr_su_hm_u | +0.02 | correlation coefficient | correlation of the county suicide and homicide rates, counting every county once; bootstrap over counties | counties with a stable rate for all three kinds of death | annual modeled rates for 2019 to 2023, averaged | 95% CI −0.02 to 0.06 | 1,899 counties | none (each county counts once) | CDC injury and violence mapping |   |
| p_hm_n | 2,807 | counties | count of counties with a stable modeled homicide rate in each of the five years | counties in CDC's county file | 2019 to 2023 |   |   | none (full count) | CDC injury and violence mapping |   |
| p_hm_pop | 97.6% | percent of residents | share of residents living in counties with a stable modeled homicide rate in each year | residents of the 50 states and DC | 2019-2023 ACS residents |   |   | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| p_n | 3,135 | counties | count of counties in the file | counties and county equivalents in CDC's county file (Connecticut's eight counties are absent) | 2019 to 2023 |   |   | none (full count) | CDC injury and violence mapping |   |
| p_od_n | 2,714 | counties | count of counties with a stable modeled overdose rate in each of the five years | counties in CDC's county file | 2019 to 2023 |   |   | none (full count) | CDC injury and violence mapping |   |
| p_od_pop | 97.7% | percent of residents | share of residents living in counties with a stable modeled overdose rate in each year | residents of the 50 states and DC | 2019-2023 ACS residents |   |   | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| p_su_n | 2,273 | counties | count of counties with a stable modeled suicide rate in each of the five years | counties in CDC's county file | 2019 to 2023 |   |   | none (full count) | CDC injury and violence mapping |   |
| p_su_pop | 94.9% | percent of residents | share of residents living in counties with a stable modeled suicide rate in each year | residents of the 50 states and DC | 2019-2023 ACS residents |   |   | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| pd_hm_d1 | 4.8 | deaths per 100,000 residents | mean of county homicide rates, population-weighted; bootstrap over counties | residents of the least deprived tenth of counties by deprivation with a stable homicide rate | annual modeled rates for 2019 to 2023, averaged | 95% CI 4.2 to 5.4 | 301 counties | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| pd_hm_d10 | 13.6 | deaths per 100,000 residents | mean of county homicide rates, population-weighted; bootstrap over counties | residents of the most deprived tenth of counties by deprivation with a stable homicide rate | annual modeled rates for 2019 to 2023, averaged | 95% CI 11.1 to 16.2 | 257 counties | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| pd_hm_falls | 4 | steps between adjacent tenths | count of steps where the population-weighted mean homicide rate is lower in the more deprived tenth (point estimates) | the nine steps between ten tenths of counties | annual modeled rates for 2019 to 2023, averaged |   |   | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| pd_od_d1 | 23.8 | deaths per 100,000 residents | mean of county overdose rates, population-weighted; bootstrap over counties | residents of the least deprived tenth of counties by deprivation with a stable overdose rate | annual modeled rates for 2019 to 2023, averaged | 95% CI 22.2 to 25.6 | 302 counties | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| pd_od_d10 | 31.1 | deaths per 100,000 residents | mean of county overdose rates, population-weighted; bootstrap over counties | residents of the most deprived tenth of counties by deprivation with a stable overdose rate | annual modeled rates for 2019 to 2023, averaged | 95% CI 25.7 to 36.5 | 215 counties | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| pd_od_falls | 4 | steps between adjacent tenths | count of steps where the population-weighted mean overdose rate is lower in the more deprived tenth (point estimates) | the nine steps between ten tenths of counties | annual modeled rates for 2019 to 2023, averaged |   |   | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| pd_od_peak | 36.1 | deaths per 100,000 residents | population-weighted mean of county overdose rates; bootstrap over counties | residents of the tenth of counties with the highest overdose rate among the ten tenths | annual modeled rates for 2019 to 2023, averaged | 95% CI 30.6 to 42.0 | 283 counties | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| pd_od_peak_dec | 4 | tenth of counties by deprivation (1 = least deprived) | number of the tenth with the highest population-weighted mean overdose rate | tenths of counties in CDC's county file ranked by deprivation | annual modeled rates for 2019 to 2023, averaged |   |   | none (position in the ranking) | CDC injury and violence mapping |   |
| pd_od_peak_gap | 5.0 | deaths per 100,000 residents | difference of the two population-weighted means; bootstrap over counties with shared draws (the peak is chosen after seeing the data, so the contrast can only overstate) | residents of the tenth of counties with the highest overdose rate, relative to the most deprived tenth | annual modeled rates for 2019 to 2023, averaged | 95% CI −2.6 to 13.2 | 2,701 counties | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| pd_ratio_hm | 2.83 | ratio of rates | ratio of the mean county homicide rates in the two tenths, population-weighted; bootstrap over counties | the most deprived tenth of counties relative to the least deprived tenth | annual modeled rates for 2019 to 2023, averaged | 95% CI 2.24 to 3.58 | 2,793 counties | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| pd_ratio_od | 1.30 | ratio of rates | ratio of the mean county overdose rates in the two tenths, population-weighted; bootstrap over counties | the most deprived tenth of counties relative to the least deprived tenth | annual modeled rates for 2019 to 2023, averaged | 95% CI 1.07 to 1.55 | 2,701 counties | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| pd_ratio_su | 1.43 | ratio of rates | ratio of the mean county suicide rates in the two tenths, population-weighted; bootstrap over counties | the most deprived tenth of counties relative to the least deprived tenth | annual modeled rates for 2019 to 2023, averaged | 95% CI 1.25 to 1.63 | 2,263 counties | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| pd_su_d1 | 12.2 | deaths per 100,000 residents | mean of county suicide rates, population-weighted; bootstrap over counties | residents of the least deprived tenth of counties by deprivation with a stable suicide rate | annual modeled rates for 2019 to 2023, averaged | 95% CI 11.3 to 13.2 | 267 counties | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| pd_su_d10 | 17.4 | deaths per 100,000 residents | mean of county suicide rates, population-weighted; bootstrap over counties | residents of the most deprived tenth of counties by deprivation with a stable suicide rate | annual modeled rates for 2019 to 2023, averaged | 95% CI 15.7 to 19.4 | 179 counties | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| pu_hm_d1 | 3.4 | deaths per 100,000 residents | mean of county homicide rates, counting every county once; bootstrap over counties | counties of the least deprived tenth of counties by deprivation with a stable homicide rate | annual modeled rates for 2019 to 2023, averaged | 95% CI 3.1 to 3.7 | 301 counties | none (each county counts once) | CDC injury and violence mapping |   |
| pu_hm_d10 | 9.5 | deaths per 100,000 residents | mean of county homicide rates, counting every county once; bootstrap over counties | counties of the most deprived tenth of counties by deprivation with a stable homicide rate | annual modeled rates for 2019 to 2023, averaged | 95% CI 8.2 to 10.9 | 257 counties | none (each county counts once) | CDC injury and violence mapping |   |
| pu_od_d1 | 22.2 | deaths per 100,000 residents | mean of county overdose rates, counting every county once; bootstrap over counties | counties of the least deprived tenth of counties by deprivation with a stable overdose rate | annual modeled rates for 2019 to 2023, averaged | 95% CI 21.1 to 23.2 | 302 counties | none (each county counts once) | CDC injury and violence mapping |   |
| pu_od_d10 | 23.0 | deaths per 100,000 residents | mean of county overdose rates, counting every county once; bootstrap over counties | counties of the most deprived tenth of counties by deprivation with a stable overdose rate | annual modeled rates for 2019 to 2023, averaged | 95% CI 19.5 to 26.4 | 215 counties | none (each county counts once) | CDC injury and violence mapping |   |
| pu_ratio_hm | 2.78 | ratio of rates | ratio of the mean county homicide rates in the two tenths, counting every county once; bootstrap over counties | the most deprived tenth of counties relative to the least deprived tenth | annual modeled rates for 2019 to 2023, averaged | 95% CI 2.34 to 3.30 | 2,793 counties | none (each county counts once) | CDC injury and violence mapping |   |
| pu_ratio_od | 1.03 | ratio of rates | ratio of the mean county overdose rates in the two tenths, counting every county once; bootstrap over counties | the most deprived tenth of counties relative to the least deprived tenth | annual modeled rates for 2019 to 2023, averaged | 95% CI 0.88 to 1.20 | 2,701 counties | none (each county counts once) | CDC injury and violence mapping |   |
| pu_ratio_su | 0.93 | ratio of rates | ratio of the mean county suicide rates in the two tenths, counting every county once; bootstrap over counties | the most deprived tenth of counties relative to the least deprived tenth | annual modeled rates for 2019 to 2023, averaged | 95% CI 0.85 to 1.02 | 2,263 counties | none (each county counts once) | CDC injury and violence mapping |   |
| pu_su_d1 | 15.3 | deaths per 100,000 residents | mean of county suicide rates, counting every county once; bootstrap over counties | counties of the least deprived tenth of counties by deprivation with a stable suicide rate | annual modeled rates for 2019 to 2023, averaged | 95% CI 14.6 to 16.1 | 267 counties | none (each county counts once) | CDC injury and violence mapping |   |
| pu_su_d10 | 14.2 | deaths per 100,000 residents | mean of county suicide rates, counting every county once; bootstrap over counties | counties of the most deprived tenth of counties by deprivation with a stable suicide rate | annual modeled rates for 2019 to 2023, averaged | 95% CI 13.2 to 15.3 | 179 counties | none (each county counts once) | CDC injury and violence mapping |   |
| rucc_big | 1 million | residents | definition: the metro area size of code 1 | metro areas in the 2023 Rural-Urban Continuum Code | 2023 |   |   | none (definition) | Rural-Urban Continuum Codes |   |
| rucc_town | 5,000 | residents | definition: the urban population that separates codes 4 to 7 from codes 8 and 9 | nonmetro counties in the 2023 Rural-Urban Continuum Code | 2023 |   |   | none (definition) | Rural-Urban Continuum Codes |   |
| sel_hi | 60,000 | residents | definition: upper end of the county size band | counties in the comparison of complete counties with the rest | 2019-2023 ACS residents |   |   | none (definition) | American Community Survey |   |
| sel_lo | 30,000 | residents | definition: lower end of the county size band | counties in the comparison of complete counties with the rest | 2019-2023 ACS residents |   |   | none (definition) | American Community Survey |   |
| sel_od_in | 50.9 | deaths per 100,000 residents | mean of the CDC panel's modeled county overdose rates, counting every county once; bootstrap over counties | counties of 30,000 to 60,000 residents whose WONDER overdose count is published in every year | annual modeled rates for 2019 to 2023, averaged | 95% CI 46.1 to 56.4 | 73 counties | none (each county counts once) | CDC injury and violence mapping |   |
| sel_od_out | 22.5 | deaths per 100,000 residents | mean of the CDC panel's modeled county overdose rates, counting every county once; bootstrap over counties | counties of 30,000 to 60,000 residents whose WONDER overdose count is not published in every year | annual modeled rates for 2019 to 2023, averaged | 95% CI 21.5 to 23.4 | 480 counties | none (each county counts once) | CDC injury and violence mapping |   |
| top_hm | 85.8% | percent of counties | share of those counties in the South region (Census regions) | counties in the highest tenth of homicide rates among counties with a stable rate | annual modeled rates for 2019 to 2023, averaged |   | 281 counties | none (each county counts once) | CDC injury and violence mapping |   |
| top_od | 68.0% | percent of counties | share of those counties in the South region (Census regions) | counties in the highest tenth of overdose rates among counties with a stable rate | annual modeled rates for 2019 to 2023, averaged |   | 272 counties | none (each county counts once) | CDC injury and violence mapping |   |
| top_su | 50.0% | percent of counties | share of those counties in the West region (Census regions) | counties in the highest tenth of suicide rates among counties with a stable rate | annual modeled rates for 2019 to 2023, averaged |   | 228 counties | none (each county counts once) | CDC injury and violence mapping |   |
| ty_hm_large | 7.6 | deaths per 100,000 residents | mean of county homicide rates, population-weighted; bootstrap over counties | residents of large metro counties with a stable modeled homicide rate | annual modeled rates for 2019 to 2023, averaged | 95% CI 6.7 to 8.7 | 431 counties | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| ty_hm_least | 4.6 | deaths per 100,000 residents | mean of county homicide rates, population-weighted; bootstrap over counties | residents of least urban nonmetro counties with a stable modeled homicide rate | annual modeled rates for 2019 to 2023, averaged | 95% CI 4.2 to 5.1 | 826 counties | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| ty_hm_ratio | 1.6 | ratio of rates | ratio of mean county homicide rates between the two types, population-weighted; bootstrap over counties | the two county types compared | annual modeled rates for 2019 to 2023, averaged | 95% CI 1.4 to 1.9 | 2,807 counties | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| ty_od_large | 27.8 | deaths per 100,000 residents | mean of county overdose rates, population-weighted; bootstrap over counties | residents of large metro counties with a stable modeled overdose rate | annual modeled rates for 2019 to 2023, averaged | 95% CI 25.7 to 30.0 | 428 counties | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| ty_od_least | 21.8 | deaths per 100,000 residents | mean of county overdose rates, population-weighted; bootstrap over counties | residents of least urban nonmetro counties with a stable modeled overdose rate | annual modeled rates for 2019 to 2023, averaged | 95% CI 20.2 to 23.5 | 733 counties | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| ty_od_ratio | 1.3 | ratio of rates | ratio of mean county overdose rates between the two types, population-weighted; bootstrap over counties | the two county types compared | annual modeled rates for 2019 to 2023, averaged | 95% CI 1.1 to 1.4 | 2,714 counties | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| ty_su_large | 12.2 | deaths per 100,000 residents | mean of county suicide rates, population-weighted; bootstrap over counties | residents of large metro counties with a stable modeled suicide rate | annual modeled rates for 2019 to 2023, averaged | 95% CI 11.6 to 12.9 | 387 counties | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| ty_su_more | 19.7 | deaths per 100,000 residents | mean of county suicide rates, population-weighted; bootstrap over counties | residents of more urban nonmetro counties with a stable modeled suicide rate | annual modeled rates for 2019 to 2023, averaged | 95% CI 19.2 to 20.2 | 668 counties | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| ty_su_ratio | 1.6 | ratio of rates | ratio of mean county suicide rates between the two types, population-weighted; bootstrap over counties | the two county types compared | annual modeled rates for 2019 to 2023, averaged | 95% CI 1.5 to 1.7 | 2,273 counties | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| tyu_hm_large | 6.2 | deaths per 100,000 residents | mean of county homicide rates, counting every county once; bootstrap over counties | counties of large metro counties with a stable modeled homicide rate | annual modeled rates for 2019 to 2023, averaged | 95% CI 5.6 to 6.9 | 431 counties | none (each county counts once) | CDC injury and violence mapping |   |
| tyu_hm_least | 3.5 | deaths per 100,000 residents | mean of county homicide rates, counting every county once; bootstrap over counties | counties of least urban nonmetro counties with a stable modeled homicide rate | annual modeled rates for 2019 to 2023, averaged | 95% CI 3.2 to 3.9 | 826 counties | none (each county counts once) | CDC injury and violence mapping |   |
| tyu_hm_ratio | 1.8 | ratio of rates | ratio of mean county homicide rates between the two types, counting every county once; bootstrap over counties | the two county types compared | annual modeled rates for 2019 to 2023, averaged | 95% CI 1.5 to 2.0 | 2,807 counties | none (each county counts once) | CDC injury and violence mapping |   |
| tyu_od_large | 28.3 | deaths per 100,000 residents | mean of county overdose rates, counting every county once; bootstrap over counties | counties of large metro counties with a stable modeled overdose rate | annual modeled rates for 2019 to 2023, averaged | 95% CI 26.8 to 29.9 | 428 counties | none (each county counts once) | CDC injury and violence mapping |   |
| tyu_od_least | 16.0 | deaths per 100,000 residents | mean of county overdose rates, counting every county once; bootstrap over counties | counties of least urban nonmetro counties with a stable modeled overdose rate | annual modeled rates for 2019 to 2023, averaged | 95% CI 14.8 to 17.2 | 733 counties | none (each county counts once) | CDC injury and violence mapping |   |
| tyu_od_ratio | 1.8 | ratio of rates | ratio of mean county overdose rates between the two types, counting every county once; bootstrap over counties | the two county types compared | annual modeled rates for 2019 to 2023, averaged | 95% CI 1.6 to 2.0 | 2,714 counties | none (each county counts once) | CDC injury and violence mapping |   |
| tyu_su_large | 14.6 | deaths per 100,000 residents | mean of county suicide rates, counting every county once; bootstrap over counties | counties of large metro counties with a stable modeled suicide rate | annual modeled rates for 2019 to 2023, averaged | 95% CI 14.1 to 15.0 | 387 counties | none (each county counts once) | CDC injury and violence mapping |   |
| tyu_su_more | 19.6 | deaths per 100,000 residents | mean of county suicide rates, counting every county once; bootstrap over counties | counties of more urban nonmetro counties with a stable modeled suicide rate | annual modeled rates for 2019 to 2023, averaged | 95% CI 19.2 to 20.0 | 668 counties | none (each county counts once) | CDC injury and violence mapping |   |
| tyu_su_ratio | 1.3 | ratio of rates | ratio of mean county suicide rates between the two types, counting every county once; bootstrap over counties | the two county types compared | annual modeled rates for 2019 to 2023, averaged | 95% CI 1.3 to 1.4 | 2,273 counties | none (each county counts once) | CDC injury and violence mapping |   |
| us_homicide_cty | 7.1 | deaths per 100,000 residents | mean of county homicide rates, population-weighted; bootstrap over counties | residents of all counties with a stable modeled homicide rate and a deprivation rank | annual modeled rates for 2019 to 2023, averaged | 95% CI 6.5 to 7.7 | 2,793 counties | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| us_overdose | 27.7 | deaths per 100,000 residents | mean of county overdose rates, population-weighted; bootstrap over counties | residents of all counties with a stable modeled overdose rate and a deprivation rank | annual modeled rates for 2019 to 2023, averaged | 95% CI 26.4 to 29.0 | 2,701 counties | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| us_suicide | 14.3 | deaths per 100,000 residents | mean of county suicide rates, population-weighted; bootstrap over counties | residents of all counties with a stable modeled suicide rate and a deprivation rank | annual modeled rates for 2019 to 2023, averaged | 95% CI 13.8 to 14.9 | 2,263 counties | 2019-2023 ACS residents | CDC injury and violence mapping |   |
| w_cell_max | 9 | deaths in a county-year | definition: the largest county-year count that WONDER withholds | county-years in CDC WONDER | deaths in 2018 to 2024 |   |   | none (definition) | CDC WONDER underlying cause of death |   |
| w_floor | 10 | deaths in a county-year | definition: WONDER withholds a county-year count above zero and below this number | county-years in CDC WONDER | deaths in 2018 to 2024 |   |   | none (definition) | CDC WONDER underlying cause of death |   |
| w_max_alc | 29.0% | percent of deaths in the county files | largest share of the county file's alcohol-induced deaths that the withheld cells could hold, at the largest withheld count each | deaths in county-years in CDC WONDER | 2018 to 2024 |   |   | none (bound from the public threshold) | CDC WONDER underlying cause of death |   |
| w_max_od | 13.7% | percent of deaths in the county files | largest share of the county file's drug overdose deaths that the withheld cells could hold, at the largest withheld count each | deaths in county-years in CDC WONDER | 2018 to 2024 |   |   | none (bound from the public threshold) | CDC WONDER underlying cause of death |   |
| w_max_su | 28.3% | percent of deaths in the county files | largest share of the county file's suicide deaths that the withheld cells could hold, at the largest withheld count each | deaths in county-years in CDC WONDER | 2018 to 2024 |   |   | none (bound from the public threshold) | CDC WONDER underlying cause of death |   |
| w_wh_alc | 57.9% | percent of county-years | share of county-years whose alcohol-induced count WONDER withholds | county-years in CDC WONDER | 2018 to 2024 |   | 12,729 county-years | none (full count) | CDC WONDER underlying cause of death |   |
| w_wh_od | 47.3% | percent of county-years | share of county-years whose drug overdose count WONDER withholds | county-years in CDC WONDER | 2018 to 2024 |   | 10,405 county-years | none (full count) | CDC WONDER underlying cause of death |   |
| w_wh_su | 57.4% | percent of county-years | share of county-years whose suicide count WONDER withholds | county-years in CDC WONDER | 2018 to 2024 |   | 12,616 county-years | none (full count) | CDC WONDER underlying cause of death |   |
| xc_mod_all_od | 44.9% | percent of county-years that are modeled | share of county-years with a rate that CDC marks as modeled and not direct | county-years of the panel's overdose rates in all counties | 2019 to 2023 |   | 15,109 county-years | none (full count) | CDC injury and violence mapping |   |
| xc_mod_all_su | 54.0% | percent of county-years that are modeled | share of county-years with a rate that CDC marks as modeled and not direct | county-years of the panel's suicide rates in all counties | 2019 to 2023 |   | 14,432 county-years | none (full count) | CDC injury and violence mapping |   |
| xc_mod_od | 0.6% | percent of county-years that are modeled | share of county-years with a rate that CDC marks as modeled and not direct | county-years of the panel's overdose rates in counties whose WONDER count is published in every year | 2019 to 2023 |   | 4,445 county-years | none (full count) | CDC injury and violence mapping |   |
| xc_mod_su | 0.0% | percent of county-years that are modeled | share of county-years with a rate that CDC marks as modeled and not direct | county-years of the panel's suicide rates in counties whose WONDER count is published in every year | 2019 to 2023 |   | 3,590 county-years | none (full count) | CDC injury and violence mapping |   |
| xc_od | +0.995 | correlation coefficient | correlation of the county WONDER crude rate with the CDC panel's county rate, weighted by county population; bootstrap over counties | counties whose WONDER overdose count is published in every year | WONDER 2018 to 2024 against the panel's 2019 to 2023 | 95% CI 0.993 to 0.996 | 889 counties | WONDER county population | CDC WONDER underlying cause of death |   |
| xc_su | +0.995 | correlation coefficient | correlation of the county WONDER crude rate with the CDC panel's county rate, weighted by county population; bootstrap over counties | counties whose WONDER suicide count is published in every year | WONDER 2018 to 2024 against the panel's 2019 to 2023 | 95% CI 0.994 to 0.996 | 718 counties | WONDER county population | CDC WONDER underlying cause of death |   |

## Definitions

- Crude rate: Deaths or births divided by the population, with no adjustment for age. A place with older residents has a higher crude death rate even if health at each age is the same.
- Modeled estimate: A figure produced by a statistical model instead of a direct count or measurement, usually for small areas where direct data are thin, borrowing strength from surveys, neighboring areas or other data. Neighboring areas can share errors, so single extremes call for caution.
- Area Deprivation Index (ADI): A score that ranks neighborhoods by income, education, employment and housing conditions drawn from the American Community Survey. In this book a higher national percentile means a more deprived neighborhood.
- Population-weighted: Averaged so that each place counts in proportion to its number of residents, which lets a large county move the result more than a small one. An unweighted average counts every place equally.
- Suppression: The withholding of a number because the count behind it is too small to publish without risking the identification of a person. A suppressed value is missing, not zero.
- Ecological inference: Drawing conclusions about individuals from data about places or groups. A pattern across counties need not hold for the people inside them.

## Methods

The chapter compares death rates across counties from two sources: the CDC injury and violence panel, which carries modeled overdose, suicide and homicide rates for 2019 to 2023, and CDC WONDER counts for 2018 to 2024. WONDER withholds small nonzero counts, so the WONDER results use only counties whose counts are published in every year; these are larger counties, selected on the outcome as well as on size, with higher rates than other counties of similar size. Statistics across counties are computed twice, weighted by residents and counting every county once, and several results differ between the two. The panel and WONDER are compared only in the counties that are complete in WONDER.

### How the panel's county rates are built

Two sources serve different jobs. The CDC injury and violence panel (county file, data as of May 2026) carries modeled overdose, suicide and homicide death rates for every county except Connecticut's.

A county's rate is the mean of its annual rates for 2019 to 2023 and is kept only if CDC publishes a stable rate in each of the five years; 2024 is provisional and left out.

Overdose in the panel is unintentional or undetermined-intent drug overdose; suicide and homicide include every method.

Explains Table 1, Table 2 and Table 3.

### Why the WONDER results use only complete counties

CDC WONDER underlying cause of death supplies drug poisoning (overdose, any intent), alcohol-induced causes and suicide, all crude rates per 100,000 residents.

WONDER withholds a county-year count above zero and below 10 and publishes a count of 0, so the published years of a county leave out its low-count years and keep its zero years; a rate pooled over those years is biased. Nothing is imputed, bounded or derived from totals.

The chapter instead uses counties whose count is published in every year 2018 to 2024 (complete counties), for which the pooled rate is exact, and it reports how many counties and how many residents that leaves.

Complete counties are larger counties and are selected on the outcome as well as on size: among counties of 30,000 to 60,000 residents the panel's mean overdose rate is 50.9 in complete counties and 22.5 in the rest.

Withheld county-years are 47.3% of county-years for overdose, 57.9% for alcohol-induced causes and 57.4% for suicide; at 9 deaths each, they could hold at most 13.7%, 29.0% and 28.3% of the deaths in the county files.

Explains Table 4 and Table 5.

### How counties are ranked, grouped and mapped

County deprivation is the mean of the Area Deprivation Index national ranks of a county's tracts, weighted by 2019-2023 ACS tract population, with Connecticut tracts assigned to the eight legacy counties; tenths of counties hold equal numbers of counties.

County types follow the 2023 Rural-Urban Continuum Code: large metro (code 1), smaller metro (2 and 3), more urban nonmetro with an urban population of 5,000 or more (4 to 7) and least urban nonmetro with fewer (8 and 9).

Connecticut's counties have no WONDER population for 2022 to 2024 and are left out, and the shares of residents that the maps and the gradient hold divide by the residents of the other 49 states and DC.

WONDER codes Valdez-Cordova AK, Kusilvak AK and Oglala Lakota SD by their old codes, so tracts are merged to those codes for deprivation and county type, and County Health Rankings rows are reached through the successor codes. Maps need at least 20 pooled deaths.

The share of residents who are American Indian or Alaska Native comes from County Health Rankings (Census Population Estimates 2022).

Explains Table 1, Table 2, Table 3, Table 4 and Table 5.

### How counties are weighted and the two sources compared

Statistics across counties are computed twice, weighted by 2019-2023 ACS residents and counting every county once, and both are reported where they differ.

The panel and WONDER are compared only in complete counties, where the panel's rates are modeled in 0.6% of overdose county-years and 0.0% of suicide county-years, against 44.9% and 54.0% in all counties.

Explains Table 2, Table 3 and Table 5.

### How North Carolina's low 2023 drug count is handled

North Carolina's 2023 drug count in WONDER predates amended death certificates and is low; it is 15.8% of the published deaths of its 48 complete counties in the window.

Raising each of their published 2023 counts by 10% to 19% (a withheld cell is never changed) raises their pooled overdose rate by 1.6% to 3.0%, and every comparison asserted in this build holds at both increases.

Explains Table 4 and Table 5.

### How uncertainty is measured

Intervals for means, ratios, correlations and differences are 95% percentile intervals from a bootstrap that resamples whole counties (2,000 replicates, seed 12345), with shared draws for ratios and differences.

### Four rankings of the same places

The comparison follows the book's ranking switch rule, fixed on October 28, 2026 before any of these gradients was computed. The main gradient of the chapter is recomputed under four rankings of the same places, with the outcome, period, weights, bins and intervals unchanged: the published ADI; a standardized index that applies the ADI's coefficients to its measures after standardizing each one across tracts; median household income; and the share of adults 25 and older with a bachelor's degree or more. The three alternatives come from ACS tract estimates for 2019 to 2023, the period of the ADI.

All four rankings use the same places, the 2,699 counties that have the outcome and all four rankings, so the ADI panel can differ slightly from the chapter's main figure. Tracts enter only if they have every input of the standardized index, which leaves out tracts without a median rent, home value or mortgage cost. A county takes the population-weighted mean of the ranks of its common-sample tracts under the county codes of CDC's county file, which does not carry Connecticut, and the tenths are cut among the panel counties with all four rankings before those without a stable overdose rate are set aside, as in the chapter's figure.

A pattern counts as changed when the worse end switches sides, when the two ends differ under one ranking and not the other, or when the rank correlation of bin order and bin mean falls on the other side of 0.9 and moves by at least 0.1.

Explains Table 6.

## What these data cannot show

Every figure describes counties. A county rate is an average over all of its residents, so it cannot say who died, and a correlation across counties does not describe the people in them (ecological inference). The data do not measure despair. Deaths from suicide, overdose and alcohol are counted, and whether the people who live in these counties feel despair is a person-level question for Chapter 6.3, Life evaluation and daily feelings (https://vishalsingh.org/zipcode/life-evaluation-and-daily-feelings). Survey measures of drinking are in Chapter 7.2, Health behaviors, person by person (https://vishalsingh.org/zipcode/health-behaviors-person-by-person).

The WONDER figures cover a selected set of counties. Counties whose counts are published in every year hold most residents but are a minority of counties, they are larger, and they have higher rates than other counties of similar size. The correlations with deprivation among the 525 complete counties, +0.42 (95% CI 0.30 to 0.51) for suicide, +0.35 (95% CI 0.24 to 0.44) for overdose and +0.13 (95% CI 0.04 to 0.22) for alcohol-induced deaths, describe those counties only. Most counties where American Indian or Alaska Native residents are at least 10% of residents are outside the maps, as are other small counties with high rates. Withheld counts could hold up to the shares given in the methods note, and no method in this chapter recovers them.

North Carolina's drug-poisoning count for 2023 in WONDER predates the state's amended death certificates and is low. It is 15.8% of the published deaths of the 48 complete North Carolina counties in the window. Raising each of their published 2023 counts by 10% to 19% raises their pooled overdose rate by 1.6% to 3.0%.

At the larger increase the correlation of overdose with deprivation is +0.35 (95% CI 0.24 to 0.44) and the overdose gap between the most and least deprived tenths is 10.4 (95% CI 2.6 to 18.4), and no comparison in this chapter changes direction. The modeled panel covers nearly every county but borrows strength across them, so its rate for a small county is partly its neighbors' rate, and its agreement with WONDER is checked only where its rates are direct. Alcohol-induced deaths are deaths whose underlying cause is alcohol, such as alcoholic liver disease, and they leave out deaths from other conditions in which alcohol was involved.

Several results depend on the weighting. In all counties with a modeled rate, the population-weighted correlations with deprivation are +0.46 (95% CI 0.37 to 0.53) for suicide and +0.22 (95% CI 0.15 to 0.28) for overdose, and counting every county once they are +0.01 (95% CI −0.04 to 0.05) and −0.01 (95% CI −0.04 to 0.03). Weighted by population, suicide and overdose rates are higher in the most deprived tenth of counties and suicide rates are higher outside large metro counties. Counting every county once, the first holds for homicide only and the second for smaller metro and more urban nonmetro counties only. Rates are crude, so a county with an older population has a higher rate for the same risk at each age, and comparisons of rural and urban counties carry that difference. The Area Deprivation Index understates deprivation in high-cost cities. The tenths of counties are relative to the counties in each figure. The three kinds of death also overlap a little, since a suicide by drug poisoning is counted as both a suicide and a drug death. Outside the box above, nothing in this chapter supports a claim about what lowers any of these death rates.

## References

1. Case, Anne; Deaton, Angus (2015). Rising morbidity and mortality in midlife among white non-Hispanic Americans in the 21st century. Proceedings of the National Academy of Sciences 112(49): 15078-15083. https://doi.org/10.1073/pnas.1518393112
2. Case, Anne; Deaton, Angus (2020). Deaths of Despair and the Future of Capitalism. Princeton University Press.
3. Friedman, Joseph R.; Palamar, Joseph J.; Ciccarone, Daniel; Gaines, Tommi L.; Borquez, Annick; Shover, Chelsea L.; Strathdee, Steffanie A. (2026). Charting the decline of the fourth wave: US overdose deaths by race, ethnicity and substance involvement. Addiction 121(9): 2552-2558. https://doi.org/10.1111/add.70472
4. Abouk, Rahi; Pacula, Rosalie Liccardo; Powell, David (2019). Association between state laws facilitating pharmacy distribution of naloxone and risk of fatal overdose. JAMA Internal Medicine 179(6): 805-811. https://doi.org/10.1001/jamainternmed.2019.0272
5. Doleac, Jennifer L.; Mukherjee, Anita (2022). The effects of naloxone access laws on opioid abuse, mortality, and crime. Journal of Law and Economics 65(2): 211-238. https://doi.org/10.1086/719588

## Provenance

- Pipeline version: 0.1.0
- Build script: book2/chapters/overdose-alcohol-and-suicide/build.py (sha256 5d8c87039fd8fd14bafa06333bbff92057aec1ab1a0f84d76553e726b2db2dbe)
- Built on: 2026-10-07
- Site commit: c2b1ff3309cb4a10833f884da91ac0057a66ad0a

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| data/staged/crosswalks/ers_rucc_county_2023.parquet | 67,278 | ad01d36a53664a2bfafbcbebb0f5a921f5b81122ffa80cf96333db23b41c191e | ad01d36a53664a2bfafbcbebb0f5a921f5b81122ffa80cf96333db23b41c191e |
| data/staged/health/chr_county_2024.parquet | 8,776,933 | 619795f7ecfec8aff10694b649eaee5e421dbeffbe4be47af4161b51ceefa5cd | c69357f1bcf630407bb9716cb445618838999558c019aaaf77d4681b6bf45c56 |
| data/staged/mortality/injury_violence_county.parquet | 722,427 | d0dfd060a3ab9eaa3a87b35d1b24b5a1e9f21af3513c10367edb651c46f40403 | d0dfd060a3ab9eaa3a87b35d1b24b5a1e9f21af3513c10367edb651c46f40403 |
| data/staged/mortality/wonder_ucd_alcohol_county_2018_2024.parquet | 289,631 | 478b6b5f8ffa061bcca1df84162d1e169babeb7832bc9818379af9be382a778f | 478b6b5f8ffa061bcca1df84162d1e169babeb7832bc9818379af9be382a778f |
| data/staged/mortality/wonder_ucd_alcohol_state_2018_2024.parquet | 16,162 | 94c821fe0bce60f99f2a300acf8e929b857a8b0f780f5634cadce0698fd665a4 | 94c821fe0bce60f99f2a300acf8e929b857a8b0f780f5634cadce0698fd665a4 |
| data/staged/mortality/wonder_ucd_drug_county_2018_2024.parquet | 308,988 | b0e5cb6dfb44fc1ce53a192faf74cb84277bb5d601a3fc32b65078a7ec03bbf1 | b0e5cb6dfb44fc1ce53a192faf74cb84277bb5d601a3fc32b65078a7ec03bbf1 |
| data/staged/mortality/wonder_ucd_drug_state_2018_2024.parquet | 17,336 | 72a7ecbb0c49a8ba9b90b22f6fad1a6d19c025c256c72799a7acf2369ebabe44 | 72a7ecbb0c49a8ba9b90b22f6fad1a6d19c025c256c72799a7acf2369ebabe44 |
| data/staged/mortality/wonder_ucd_suicide_county_2018_2024.parquet | 290,192 | 448558540a3f42296acf7f66a945f7c6794fd6f4dc9c7032a18a3d105d0541f1 | 448558540a3f42296acf7f66a945f7c6794fd6f4dc9c7032a18a3d105d0541f1 |
| data/staged/mortality/wonder_ucd_suicide_state_2018_2024.parquet | 15,948 | 7588fe51ddda48e57e88852172442b4d2bf64689882e600ebf342668ff79ea1a | 7588fe51ddda48e57e88852172442b4d2bf64689882e600ebf342668ff79ea1a |
| data/staged/ses/acs5_tract2020_2019_2023.parquet | 7,232,424 | 5fe6f730a35225f14d5d8abfc6b9bce58b52e545f309a7eac74f1dae74d7a31c | 7b4a2475b3852d3f91804716a04566ef8ceadacec2be9fb85f5eb642078efac6 |
| data/staged/svi/svi_tract2020_2022.parquet | 17,740,415 | cb3860d8edc2aaf1f2a02211a58f7a0b80457eb6ad9a37b5ec8abb2d5da9da10 | e371a4a696d5bed05d54ad7c5b6ca2504508805b847ec415c2322be7f66ec2b2 |

Outputs:

| File | SHA-256 |
| --- | --- |
| facts.json | 63d63863e78931b4e81f3b1a9139d7c8f996c5de86982d97219967944bc2f0e4 |
| figures/alt_rankings.json | d65045934802ba7de6c7fac3a6b91557460db6f900774a99b519294cb9fe8c5f |
| figures/despair_gradient.json | c5c1c87291b998d6bcb231aa0ee1f74b912268eecc99fda0d2f3f3145fc796ca |
| figures/drug_vs_alcohol_dominance.json | c81916df228a9b72d8c295da0e569c7e589a99a5204439e4a892798ac0886fca |
| figures/overdose_map_scatter.json | c42a48640410c56392168f48bbbcfb8e4e26f353e035d82429c486e86f5d9d64 |
| figures/rate_by_county_type.json | 075430d88ebd37427085b6604a1505e781377290ad9c32a3f730c27149c02187 |
| figures/three_causes_by_decile.json | 92ef9f8f26ff64531896da0f23322aae3d67e8acc808bdc546fa5587efa9bbd9 |
| figures/three_causes_maps.json | 4542cdc2b9468265db8f773c2f3c0d845887100f9876eb58b0a751aab7afb971 |
| meta.json | 8bd9610c5b742da958e023caf9204247185872271d0e2c342567f9f86816e85b |
| public/data/overdose-alcohol-and-suicide/drug_vs_alcohol_dominance.json | ff08aed3fb3b7f71f78ad152bec4c5c58ded87ff20aff2116156db2abe11caf7 |
| public/data/overdose-alcohol-and-suicide/overdose_map_scatter.json | 677dad3020d8c19fc6cac8822f5da06c0002e9828c99822d6a8fbd3a223b0f7f |
| public/data/overdose-alcohol-and-suicide/three_causes_homicide.json | c00726c24312e475ffe280f22184cbbb038fdb74ef43f5b9c9b1c679af0c8f4f |
| public/data/overdose-alcohol-and-suicide/three_causes_overdose.json | 9278d4edcf9a442668529049c116b5a08df06c6eb83859f48415fb2faccb13da |
| public/data/overdose-alcohol-and-suicide/three_causes_suicide.json | 8b54afc2684c642847b373c3268f60a35db95773d5b01d563361b4ded230a524 |
| refs.json | 4b62041a65570f9e671d959231c1e3654d5860b40f4924928183eebb7a7b8a70 |

## Machine formats

- Report (HTML): https://vishalsingh.org/zipcode/overdose-alcohol-and-suicide/report
- Report (Markdown): https://vishalsingh.org/zipcode/overdose-alcohol-and-suicide/report.md
- Every estimate (JSON): https://vishalsingh.org/zipcode/report/overdose-alcohol-and-suicide/facts.json
- Table 1, figure "three_causes_maps" (JSON): https://vishalsingh.org/zipcode/report/overdose-alcohol-and-suicide/figures/three_causes_maps.json
- Table 2, figure "three_causes_by_decile" (JSON): https://vishalsingh.org/zipcode/report/overdose-alcohol-and-suicide/figures/three_causes_by_decile.json
- Table 3, figure "rate_by_county_type" (JSON): https://vishalsingh.org/zipcode/report/overdose-alcohol-and-suicide/figures/rate_by_county_type.json
- Table 4, figure "drug_vs_alcohol_dominance" (JSON): https://vishalsingh.org/zipcode/report/overdose-alcohol-and-suicide/figures/drug_vs_alcohol_dominance.json
- Table 5, figure "despair_gradient" (JSON): https://vishalsingh.org/zipcode/report/overdose-alcohol-and-suicide/figures/despair_gradient.json
- Table 6, figure "alt_rankings" (JSON): https://vishalsingh.org/zipcode/report/overdose-alcohol-and-suicide/figures/alt_rankings.json
- Table 7, figure "overdose_map_scatter" (JSON): https://vishalsingh.org/zipcode/report/overdose-alcohol-and-suicide/figures/overdose_map_scatter.json
- Payload of "three_causes_maps" (JSON): https://vishalsingh.org/zipcode/data/overdose-alcohol-and-suicide/three_causes_overdose.json
- Payload of "drug_vs_alcohol_dominance" (JSON): https://vishalsingh.org/zipcode/data/overdose-alcohol-and-suicide/drug_vs_alcohol_dominance.json
- Payload of "overdose_map_scatter" (JSON): https://vishalsingh.org/zipcode/data/overdose-alcohol-and-suicide/overdose_map_scatter.json
- Index of every report: https://vishalsingh.org/zipcode/llms.txt; all reports in one file: https://vishalsingh.org/zipcode/llms-full.txt