Figure gallery

Every figure in the book, with its chart type and a link to the chapter that shows it.

236 figures in 35 chapters. county-map 26, tabs 45, dot 41, bar 15, dumbbell 14, line 47, heatmap 8, scatter 21, table 10, ridgeline 2, tract-map 3, beeswarm 2, slope 1, histogram 1.

Birthweight and preterm birth

Chapter 1.1 in Part I

Figure 1. Low birthweight is most common in the South, where 89% of the counties in the highest tenth of shares lie, against 47% of mapped countiescounty-mapShare of live births under 2,500 grams by county, County Health Rankings 2024, births in 2016 to 2022
Figure 2. Low birthweight rises from 7.4% of births in the least deprived tenth of large counties to 9.7% in the most deprivedtabsShare of live births under 2,500 grams (and before 37 weeks in the second tab) by county deprivation, 2018 to 2024
Figure 3. Non-Hispanic Black mothers had low-birthweight births at 14.0% against 6.7% for non-Hispanic white mothers, a ratio of 2.1dotFirst panel: share of live births under 2,500 grams in the large counties, by mother's race and ethnicity, County Health Rankings, births in 2016 to 2022. Second panel: infant deaths per 1,000 live births in the United States by mother's single race, any ethnicity, 2018 and 2019
Figure 4. Low birthweight is more common for non-Hispanic Black mothers in the least deprived quartile of counties (12.4%) than for non-Hispanic white mothers in the most deprived (7.6%)barLow birthweight (share of live births under 2,500 grams, births in 2016 to 2022) or infant mortality (deaths per 1,000 live births, 2018 and 2019) by quartile of county deprivation rank and mother's race

Infant mortality

Chapter 1.2 in Part I

Figure 1. Infant mortality ran from 3.7 per 1,000 in Massachusetts and New Hampshire to 8.7 in MississippitabsInfant deaths per 1,000, by state and DC, 2018 to 2022; the first tab maps the rates and the second ranks them with intervals
Figure 2. 85.1% of the counties in the highest tenth of infant mortality rates are in the South, which holds 49.3% of the 1,206 counties that publish a ratecounty-mapInfant deaths per 1,000, by county, County Health Rankings 2024, infant deaths and live births in 2015 to 2021
Figure 3. Infant mortality rises from 3.9 per 1,000 in the least deprived quarter of large counties to 7.2 in the most deprivedtabsInfant deaths per 1,000 by county deprivation, WONDER 2018 to 2022 for the large counties and County Health Rankings 2015 to 2021 for all counties with a rate
Figure 4. The rise with county deprivation holds within states and for births to white mothers and to Black mothers, at 0.63 deaths per 1,000 for each 10-point step across all birthsdotChange in infant deaths per 1,000 for each 10-point rise in county deprivation rank (births-weighted slope) with 95% intervals, counties of 250,000 residents or more
Figure 5. Infant mortality in 2018 and 2019 was 10.3 per 1,000 for Black mothers and 4.7 for white mothers, a ratio of 2.2dotInfant deaths per 1,000 by mother's single race, any ethnicity, United States, 2018 and 2019, with 95% intervals
Figure 6. Black mothers' infants died at a higher rate than white mothers' in all 36 states that publish both, by a median ratio of 2.1dumbbellInfant deaths per 1,000 by mother's single race, any ethnicity, 36 states, 2018 and 2019, with 95% intervals, ordered by the Black-white difference
Figure 7. Neonatal deaths made up 68.7% of infant deaths in the 14 counties that publish every age group, and both rates are higher where deprivation is higherdotInfant deaths per 1,000 by age at death, 14 counties of 250,000 residents or more, 2018 to 2022, ordered from the least to the most deprived county rank

Where births are falling

Chapter 1.3 in Part I

Figure 1. Births in the named counties fell 4.6% from 2018 to 2024 with a low in 2023, a larger fall than the 3.0% in all other countieslineLive births by year in the 578 counties that CDC WONDER identifies (counties with 100,000 or more residents in WONDER's population vintage) and in all other counties, which WONDER pools by state, 2018 to 2024, indexed to 2018 or as counts
Figure 2. Of the 58 counties with the largest gains in births, 43 are in the South, which holds 40.1% of the named countiescounty-mapPercent change in live births from 2018 to 2024 by county, for the 578 counties that CDC WONDER identifies (counties with 100,000 or more residents in WONDER's population vintage)
Figure 3. The ten largest gains in births are all in the South, and the ten largest declines are spread across every Census regiondotPercent change in live births from 2018 to 2024 for the ten named counties with the largest gains and the ten with the largest declines, of the 578 named counties
Figure 4. Births in 2024 were below 2018 in all four quartiles of counties, by 5.6% in the least deprived and 7.3% in the most deprived, and in 2021 the other three quartiles rose by more than the most deprivedlinePooled live births in each quartile of the 578 named counties by Area Deprivation Index rank, indexed to 2018 = 100, 2018 to 2024, with 95% intervals from a bootstrap over counties
Figure 5. The most deprived quartile of counties lost births in every Census region, and in the South the other three quartiles show no clear lossheatmapPooled change in live births from 2018 to 2024 by Census region and quartile of county deprivation rank, named counties, with 95% intervals from a bootstrap over counties
Figure 6. Births fell for mothers aged 15 to 29, changed little for mothers aged 30 to 34 and rose for mothers aged 35 to 44 from 2018 to 2024barPooled change in live births by mother's age band, 2018 to 2024, in the 578 named counties, with 95% intervals from a bootstrap over counties
Figure 7. In every quartile of county deprivation the share of births to older mothers rose and the share to younger mothers fell, and the differences between quartiles are larger than those changesdumbbellShare of births to mothers aged 15 to 24 and to mothers aged 35 to 44, among births to mothers aged 15 to 44, by quartile of county deprivation rank, 2018 and 2024, with 95% intervals from a bootstrap over counties
Figure 8. Counties with the largest declines in births lost births at every age under 35, and counties with the largest gains added births at every age from 25linePooled change in live births from 2018 to 2024 by mother's age band, in four equal-sized groups of the 578 named counties formed by the change in their total births

Smoking in pregnancy

Chapter 1.4 in Part I

Figure 1. Smoking in pregnancy fell from 8.2% to 3.3% of births in the lowest-income third of large counties and from 3.6% to 1.1% in the highest-income thirdlineShare of births to mothers who reported smoking, among births with a known tobacco answer, by third of the 530 large counties ranked on median household income, 2018 to 2024, with 95% intervals from a bootstrap over counties
Figure 2. The share of births to mothers who smoked is 0.8% in the county at the 5th percentile and 13.2% at the 95th percentile of large counties, and the highest shares cluster in Pennsylvania, Ohio, Michigan, New York, Indiana and Missouricounty-mapShare of births to mothers who reported smoking among births with a known tobacco answer, 2018 to 2024, 530 large counties (counties of 100,000 residents or more)
Figure 3. Large counties with higher median household income have a lower share of births to mothers who smoked, from 5.7% in the lowest-income tenth to 1.7% in the highestscatterShare of births to mothers who reported smoking, 2018 to 2024, against county median household income (SAIPE 2022, log scale), one dot per county, with pooled shares for tenths of counties
Figure 4. Within a state, a doubling of county income goes with a smoking share 3.9 points lower when counties are weighted by births, and 6.6 points lower when each county counts oncedotChange in the share of births to mothers who smoked, in percentage points per doubling of county median household income (SAIPE 2022), across all counties, within states and between states, 2018 to 2024, with 95% intervals from a bootstrap over states
Figure 5. In all 26 states with a slope of their own the estimated slope is below zero, and the 95% interval lies below zero in 10 when counties are weighted by birthsdotChange in the share of births to mothers who smoked per doubling of county median household income (SAIPE 2022), one dot per state with at least 8 complete large counties, 2018 to 2024, with 95% intervals; four views by scale and by weighting
Figure 6. States with a higher share of births to mothers who smoked have steeper slopes in points, a correlation of −0.62, with no detectable relation in proportion, where the correlation is −0.19scatterSlope of the smoking share on county median household income against the state's pooled smoking share, one dot per state with a slope of its own, 2018 to 2024; slopes in percentage points per doubling of income or as a percent difference per 10% higher income
Figure 7. Raising the minimum number of counties from 3 to 10 leaves 9 to 11 states with an interval below zero and none above it, and the test of equal proportional slopes never rejectstableStates with a slope of their own, states with an interval below or above zero, and wild-bootstrap p-values for equal slopes in percentage points and in proportion, by the fewest complete counties a state needs, 2018 to 2024
Figure 8. The within-state slope in points shrank from 4.9 to 2.4 points per doubling of county income from 2018 to 2024 while the slope in proportion grew from 10.1% to 14.7%lineWithin-state slope of the smoking share on county median household income (SAIPE 2022), by year of birth, 2018 to 2024, in percentage points per doubling of income or as a percent difference per 10% higher income, with 95% intervals from a bootstrap over states

Test scores, class and race

Chapter 2.1 in Part II

Figure 1. 74% of the counties in the lowest tenth for average achievement are in the South, which holds 43% of countiescounty-mapAverage of math and reading achievement in third through eighth grade, in grade levels above or below the national average, by county, 2009 to 2019 pooled
Figure 2. Average achievement is higher in counties with higher median household income, a correlation of +0.59 with log income across 2,999 countiesscatterAverage of math and reading achievement (grade levels from the national average) against median household income (dollars, log scale), one dot per county; dot area is the tests counted
Figure 3. The slope of county average achievement on county median income is positive in 45 of 45 states, with a 95% interval above zero in 40dotWithin-state slope of the county average of math and reading on county median household income (grade levels per doubling of income), states with 10 or more counties
Figure 4. Within the same districts, white students score 0.64 standard deviations above Black students in math, and the other gaps shown are smaller or negativedotMean gap in math achievement between two groups of students in the same geographic school district, in standard deviations of the national cohort, averaged over the districts that report each gap, with the spread of district gaps as a bar
Figure 5. In math, Asian students average +0.66 standard deviations from the national average and Black students −0.53dotMean math achievement of each group of students relative to the national average of all students, in standard deviations of the national cohort, over counties that report the group
Figure 6. The white–Black math gap is wider in counties with more school segregation, a correlation of +0.59 across 2,101 countiesscatterWhite minus Black math gap (standard deviations of the national cohort) against the school segregation index (Theil's index across racial and ethnic groups), one dot per county; dot area is the tests counted
Figure 7. Counties with a wider income gap have a wider white–Black gap, a correlation of +0.80 across 2,092 counties, and the two gaps are of similar sizescatterWhite minus Black math gap against the gap between students who are not and are economically disadvantaged, standard deviations of the national cohort, one dot per county; dot area is the tests counted
Figure 8. Relative to its average size, the white–Black math gap varies 1.34 times as much across counties as the boys minus girls reading gapbarStandard deviation across counties of each gap divided by the average gap, counties with all four gaps, weighted by the tests of the two groups in each gap

Gender gaps in reading and math

Chapter 2.2 in Part II

Figure 1. Girls scored higher than boys in reading in 99.9% of districts, while math gaps fall on both sides of zeroridgelineDistribution across school districts of the male minus female mean test score gap in grade levels, reading and math, third through eighth grade pooled over 2009 to 2019
Figure 2. The reading gap is below zero in all 48 states, while the math gap is above zero in 20 of themdotTest-weighted mean male minus female gap in grade levels by state, reading and math, districts with both gaps and an income, third through eighth grade pooled over 2009 to 2019
Figure 3. The math gap rises from −0.20 grade levels in the lowest-income tenth of districts to +0.08 in the highest, while the reading gap stays below zerolineTest-weighted mean male minus female gap in grade levels by tenth of district median household income, reading and math, third through eighth grade pooled over 2009 to 2019
Figure 4. Districts at one income level differ widely in their math gap, and the decile means rise with income, a correlation of +0.40 with income rankscatterMale minus female math gap in grade levels against district median household income in dollars (log scale), one dot per district, with test-weighted decile means
Figure 5. Boys scored higher in math than girls in 34.8% of counties, and those counties cluster in the Plains, the Great Lakes states and the Mountain Westcounty-mapMale minus female mean math score gap in grade levels, county, third through eighth grade pooled over 2009 to 2019

School discipline and incarceration

Chapter 3.1 in Part III

Figure 1. Out-of-school suspensions were more common in more deprived districts, at 3.1 per thousand students in the least deprived tenth of districts against 23.6 in the most deprivedscatterStudents suspended out of school at least once per 1,000 students enrolled, by the district's deprivation rank (mean Area Deprivation Index national rank of its tracts), one dot per district, 2020-21 school year
Figure 2. Every stage of school exclusion was more common in the most deprived third of districts than in the least deprived thirdtabsFour stages of exclusion from out-of-school suspension to school-related arrest, districts ranked on deprivation, 2020-21 school year
Figure 3. The Black suspension rate was higher than the white rate in 20 of the 24 districts with the most Black studentsdumbbellStudents suspended out of school at least once per 1,000 enrolled, white and Black students in the same district, the districts with the most Black students among those compared, 2020-21 school year
Figure 4. Counties in the highest tenth of suspension rates were concentrated in 6 states, which hold 61.0% of themcounty-mapStudents suspended out of school at least once per 1,000 students enrolled, school districts assigned to the county that holds most of their population, 2020-21 school year
Figure 5. Incarceration of children from low-income families rose with tract deprivation and was higher for Black than for white children in the same tractstabsPercent incarcerated on April 1, 2010, among children from low-income families born 1978 to 1983, by the deprivation of the tract where they grew up, ranked on 2019-2023 data

College access, price and earnings

Chapter 3.2 in Part III

Figure 1. At the median for-profit college, former students' median earnings a decade after entry were $28,330, against $42,014 at the median public college and $53,848 at the median private nonprofit collegeridgelineDistribution across colleges of the median earnings of former students who received federal aid, a decade after entry (thousands of 2022 dollars), by sector; entering classes of 2009 to 2010 and 2010 to 2011
Figure 2. The median net price rises with family income, but at public four-year colleges it falls from 62% of an assumed income in the lowest band to 13% in the highestlineMedian across colleges of the average net price after grants for full-time, first-time students who received federal aid, by family-income band, public and private nonprofit four-year colleges, academic year 2021 to 2022
Figure 3. Former students of costlier colleges tend to earn more, a correlation of +0.63, but 56% of plotted for-profit colleges cost more than the median and have median earnings at or below itscatterMedian earnings a decade after entry (2022 dollars) against the average annual cost of attendance (academic year 2021 to 2022), one dot per college, dot area is undergraduate enrollment
Figure 4. Among high-Pell colleges, the 15 highest-earning have a median of $72,282 a decade after entry and the 15 lowest-earning $31,902tabsPublic and private nonprofit four-year colleges in the top third by Pell share, with at least 1,000 undergraduates; median earnings of former students who received federal aid and net price for the lowest income band
Figure 5. The average resident in the country lives 9.6 miles from a four-year college, and the state averages are longest in Alaska, Wyoming, Montana and Mississippicounty-mapDistance in miles from the average resident of each county to the nearest four-year campus (great-circle, from each census tract's internal point, weighted by tract population), campuses of 2023, residents of 2019 to 2023
Figure 6. Distance to a four-year college rises with county deprivation, from 6.1 miles in the least deprived tenth of counties to 29.3 in the most deprived, and with ruralitytabsMiles from the average resident to the nearest four-year campus, and the share of counties with no four-year campus, by tenth of county Area Deprivation Index rank and by Rural-Urban Continuum Code, residents of 2019 to 2023

Race, income and mobility

Chapter 3.3 in Part III

Figure 1. Children from low-income families reach the highest adult income ranks in the Plains and Mountain West and the lowest in the Southeastcounty-mapMean adult household income rank (percentile) of children born 1978 to 1983 to parents at the 25th income percentile, by county of childhood
Figure 2. White children from low-income families reached a higher adult income rank than Black children from the same tract in 92.5% of 30,997 tractsscatterAdult household income rank (percentile) of Black children against white children raised in the same census tract by parents at the 25th income percentile, one dot per tract
Figure 3. Black children ranked 10.3 points below white children in the same tracts, Hispanic children 2.6 points below and Asian children 9.4 points abovedotMean adult household income rank of each group minus that of white children raised in the same tract by parents at the 25th income percentile, tracts where both are estimated
Figure 4. Children raised at the 75th income percentile reach adult ranks 13.6 points above those raised at the 25th in the same tract, a difference that is smaller where the latter do betterscatterAdult household income rank (percentile) of children raised at the 75th income percentile against those raised at the 25th, one dot per tract, races pooled
Figure 5. Across counties, economic connectedness correlates +0.69 with upward mobility, more than any civic or cohesion measuredotPopulation-weighted correlation of each Social Capital Atlas county measure with the mean adult income rank of children from low-income families
Figure 6. In each of the 20 most populous counties, white residents live longer than Black residents, by 1.1 to 9.9 yearsdumbbellLife expectancy at birth in years, non-Hispanic Black and non-Hispanic white residents, for the most populous counties with both estimates, deaths in 2019 to 2021
Figure 7. Place accounts for 53% of the variance in county life expectancy by race, race for 31% and their interaction for 16%barShares of the variance of county-by-race life expectancy (a non-Hispanic white and a non-Hispanic Black estimate for each county), percent, deaths in 2019 to 2021

Teen births

Chapter 3.4 in Part III

Figure 1. Predicted teen birth shares are higher in the South than in any other region, 33.5% against 21.7% in the Northeastcounty-mapPredicted share of women with a teen birth, percent, by county of childhood, women born 1978 to 1983 whose parents were at the 25th income percentile (teen births in the 1990s and early 2000s, not a current rate), races pooled
Figure 2. Predicted teen birth shares rise from 12.9% in the least deprived tenth of tracts to 38.5% in the most deprivedscatterPredicted share of women with a teen birth (percent) against the Area Deprivation Index national rank, one dot per 2010 tract, women born 1978 to 1983 whose parents were at the 25th income percentile (teen births in the 1990s and early 2000s, not a current rate), races pooled
Figure 3. Every group's predicted teen birth share is higher in the most deprived tenth of tracts than in the least deprivedlinePredicted share of women with a teen birth (percent) by tenth of the Area Deprivation Index, tracts where each group is estimated, women born 1978 to 1983 whose parents were at the 25th income percentile (teen births in the 1990s and early 2000s, not a current rate)
Figure 4. Black women's predicted teen birth share was 17.6 points above white women's in the same tracts, Hispanic women's 10.9 points above and Asian women's 7.1 points belowdotMean predicted share of women with a teen birth for each group minus the share for white women raised in the same tract, percentage points, tracts where both are estimated, women born 1978 to 1983 whose parents were at the 25th income percentile (teen births in the 1990s and early 2000s, not a current rate)
Figure 5. The Black-white gap in predicted teen birth shares shows no detectable change from the least to the most deprived tenth of tracts, −0.7 points with an interval that includes zerodumbbellPredicted share of women with a teen birth (percent) for white and Black women raised in the same tracts, by tenth of the Area Deprivation Index, women born 1978 to 1983 whose parents were at the 25th income percentile (teen births in the 1990s and early 2000s, not a current rate)
Figure 6. Across counties, Black women's predicted teen birth share rises 0.85 points for each point of white women's, against 0.26 among tracts within the same countiesscatterMean predicted share of women with a teen birth (percent) for Black women against white women, counties with at least a minimum number of tracts where both are estimated, women born 1978 to 1983 whose parents were at the 25th income percentile (teen births in the 1990s and early 2000s, not a current rate)
Figure 7. The Black-white gap in predicted teen birth shares has an interval above zero under all nine floors on tracts per county and on tract populationdotMean predicted share of women with a teen birth for Black women minus white women raised in the same places, percentage points, by floor, women born 1978 to 1983 whose parents were at the 25th income percentile (teen births in the 1990s and early 2000s, not a current rate)

Home value, income and redlining

Chapter 4.1 in Part IV

Figure 1. Life expectancy is 2.2 years higher for each doubling of ZIP-area home value, and a year of life costs $18 thousand in housing dollars in Cincinnati and $140 thousand in San Francisco-OaklandtabsLife expectancy at birth (deaths in 2010 to 2015) against median home value (ACS 2019 to 2023) across ZIP code areas, and the housing dollars per year of life in each large metro
Figure 2. The share of tax returns that claim the EITC rises from 12.0% to 28.9% across tenths of counties by deprivation, while the share with adjusted gross income of $200,000 or more falls from 11.1% to 1.9%tabsShares of individual income tax returns by tenth of counties on the Area Deprivation Index, and the distribution of returns across five income groups by fifth of counties, tax year 2022
Figure 3. Tracts graded A on the 1930s HOLC maps have a life expectancy of 80.9 years, against 76.8 years in tracts graded D, for deaths in 2010 to 2015tabsTract outcomes by 1930s HOLC grade: means of five measures, the spread of life expectancy, and the gap between grade A and grade D tracts city by city

Mortgage denials

Chapter 4.2 in Part IV

Figure 1. Decided home-purchase applications were denied 9.0% of the time, against 20.7% for refinance and 35.8% for cash-out refinance loanstableDenied share of decided applications, tracts of the 50 states and DC with a published cell, 2024, by loan purpose
Figure 2. The denial rate was 7.8% in the least deprived tenth of tracts and 13.8% in the most deprived, and it is level across the three least deprived tenthsscatterDenied share of decided home-purchase applications, 2024, against the tract's Area Deprivation Index national rank: sampled tracts with at least 30 decided applications as dots and pooled rates for tenths of tracts as the line
Figure 3. In every tenth of tracts with enough applications, Black and Hispanic applicants were denied more often than white applicantslineDenied share of decided home-purchase applications, 2024, by applicant group and tenth of tracts on the Area Deprivation Index (1 = least deprived), points on at least 100 tracts
Figure 4. In the tracts that hold both groups, Black applicants were denied 16.2% of the time and white applicants 6.2%dumbbellDenied share of decided home-purchase applications, 2024, for each applicant group and for non-Hispanic white applicants in the same tracts, tracts where both cells are published
Figure 5. The same-tract gap between Black and white applicants stays between 8.6 and 10.4 percentage points across tenths of tract deprivationtabsBlack minus white denied share of decided home-purchase applications, 2024, in tracts where both cells are published, by tenth of tracts on the deprivation index and by fifth of tracts on median applicant income
Figure 6. Denial rates rise from 7.9% in grade A tracts to 11.3% in grade D tracts, and no grade differs detectably from grade A among tracts of the same city and the same tenth of the deprivation indextabsDenied share of decided home-purchase applications, 2024, in tracts graded on the 1930s HOLC maps: by grade, as a difference from grade A under three adjustments, and by applicant group
Figure 7. In Cook County, 53.0% of the tracts in the top fifth of denial rates and 57.7% of those in the bottom fifth lie in the part of the county that the 1930s map graded, a difference these data cannot tell from zerotract-mapDenied share of decided home-purchase applications, 2024, in Cook County tracts with at least 20 decided applications, and the HOLC grade covering most of each tract

Work, wages and access to jobs

Chapter 4.3 in Part IV

Figure 1. Unemployment among residents was 3.6% across counties in 2023, differed little between county types, and reached 10% or more in 6 countiescounty-mapUnemployment rate, percent of the civilian labor force, annual average 2023, residents of each county, modeled estimates
Figure 2. Metropolitan counties went from a lower unemployment rate than nonmetropolitan counties with smaller towns in 2019 (3.6% against 4.3%) to a higher one in 2020 (8.2% against 6.7%)lineUnemployment rate, percent of the civilian labor force, pooled over the counties of each type, annual averages 2000 to 2024, residents of each county, modeled estimates
Figure 3. Jobs located in metropolitan counties paid $73,585 a year on average in 2023, against $48,786 in nonmetropolitan counties with smaller towns or nonecounty-mapAverage annual pay per job, current dollars, for jobs located in each county and covered by unemployment insurance, 2023, jobs at the workplace
Figure 4. In 2019, 62.4% of the jobs held by residents of nonmetropolitan counties with smaller towns or none were in another county, against 44.1% for residents of metropolitan countieslinePercent of jobs held by a county's residents that are located in a different county, pooled over the counties of each type, 2010, 2015 and 2019, jobs counted by home county
Figure 5. In the fifth of counties with the fewest jobs per resident job, 45.4% of jobs held by residents were in the top earnings band against 39.5% of the jobs located theredumbbellPercent of jobs paying more than $3,333 a month, jobs held by a county's residents against jobs located in the county, fifths of counties ranked by jobs located per job held by residents, 2019
Figure 6. In 66.0% of counties the jobs held by residents were more often in the top earnings band than the jobs located in the countyscatterPercent of jobs paying more than $3,333 a month, jobs held by a county's residents against jobs located in the county, one dot per county, 2019
Figure 7. In the most deprived tenth of tracts, 30.4% of jobs held by residents were in the top earnings band against 60.1% in the least deprived tenth, and unemployment was 8.6% against 4.9%dumbbellFive measures of the residents of tracts in the least and the most deprived tenth by Area Deprivation Index rank, percent; the index is built partly from income, employment and vehicle access, so all five gradients are partly mechanical
Figure 8. In the most deprived fifth of tracts in metropolitan counties, 43.7% of jobs located there were in the top earnings band against 32.6% of jobs held by the tracts' residentslinePercent of jobs paying more than $3,333 a month, jobs held by residents of a tract against jobs located in it, by fifth of tracts by Area Deprivation Index rank within each county type, 2019

Renting, affordability and eviction

Chapter 4.4 in Part IV

Figure 1. 45.6% of renter households pay more than 30% of their income for housing, against 20.8% of owner householdstabsHousing cost burden by tenure as HUD defines it, and by income relative to HUD's area median family income, 50 states and DC, 2018 to 2022
Figure 2. Between the 5th and 95th percentiles of counties, the share of renter households paying more than 30% of income runs from 23.0% to 50.9%, with a median county at 37.9%county-mapPercent of renter households with housing costs above 30% of income, counties of the 50 states and DC, 2018 to 2022
Figure 3. Pooled across the nation, renter burden is 44.4% in the least deprived tenth of tracts and 47.6% in the most deprived, but within a county it rises by 2.3 points per 10 percentile points of the indextabsShare of households paying more than 30% of income by tenth of tracts on the Area Deprivation Index, for all households, for low-income households and relative to the county, 2018 to 2022
Figure 4. Renter burden is higher in areas where the two-bedroom Fair Market Rent takes a larger share of the median household income, a renter-weighted correlation of +0.70 across 2,139 areastabsRenter households paying more than 30% of income (CHAS 2018-2022) against a year of the two-bedroom Fair Market Rent (fiscal year 2025) as a percent of the area's median household income (ACS 2019-2023), HUD FMR areas
Figure 5. Eviction filings fell to 0.09 times their pre-pandemic level in April 2020, stayed below it until early 2022 and peaked at 1.37 times that level in March 2023lineMonthly eviction filings divided by the pre-pandemic baseline for the same calendar month, summed over tracts in cities and metro areas the Eviction Lab tracks, January 2020 to December 2025
Figure 6. Eviction filings in majority-Black tracts ran at 0.98 times their baseline in 2023 and in majority-white tracts at 1.28 times, from baseline rates per renter household that differed by a factor of 3.0tabsEviction filings against the pre-pandemic baseline by the racial majority of the tract, and filings per 100 renter households per year before the pandemic and in 2023
Figure 7. From 2023 to 2025 filings ran from 0.62 times the baseline in Philadelphia to 1.84 times in Portland, with a median site at 1.11 timesdotEviction filings divided by the pre-pandemic baseline, January 2023 to December 2025, by site in the balanced panel of the Eviction Tracking System

Health behaviors and the supply of care

Chapter 5.1 in Part V

Figure 1. 11 measures are at least 4.8 points more common in the most deprived tenth of tracts than in the least deprived, and the annual checkup is 3.6 points more commonlineAdults with each condition or behavior, percentage points above the least deprived tenth of tracts, by twentieth of tracts ranked on the Area Deprivation Index national percentile, 2022
Figure 2. Binge drinking is higher in higher-income tracts in 50 of 51 states, while the other measures are lower in higher-income tracts in all 51 statesbeeswarmPoints of prevalence per doubling of tract median household income, one dot per state and measure, adults, with controls for the age, Black and Hispanic shares of residents, 2022
Figure 3. From the least to the most deprived tenth of tracts, the dental visit rate falls from 70.3% to 45.8% while the annual checkup rate rises from 74.2% to 77.8%lineAdults who visited a dentist or had a routine checkup in the past year, percent, by Area Deprivation Index national percentile of the tract, 2022
Figure 4. In the most deprived tenth of tracts, the dental visit and screening tests are less common by 6.2 to 24.4 points and barriers to care are more common by 9.7 and 11.1 pointsdotDifference in the share of adults, most deprived tenth of tracts minus least deprived tenth, percentage points, eight measures of care, 2021 and 2022
Figure 5. The checkup slope is within 0.5 points of zero in all four specifications, and the dental slope is between −2.37 and −3.86 pointsdotSlope of tract prevalence on the Area Deprivation Index national percentile, points of prevalence per ten percentiles, adults, four specifications, 2022
Figure 6. The dental visit rate falls with deprivation in all 51 states, and the checkup slope is within 0.5 points of zero in 42dotSlope of tract prevalence on the Area Deprivation Index national percentile within each state, points of prevalence per ten percentiles, adults, 2022
Figure 7. Residents per primary care physician rise from 1,159 to 2,730 and per dentist from 1,131 to 3,055 between the least and most deprived tenths of countieslineResidents per provider, pooled over the counties in each tenth of counties ranked on the county Area Deprivation Index, providers counted in 2021 (physicians), 2022 (dentists) and 2023 (mental health providers)
Figure 8. Residents per mental health provider exceed 3,200 in 275 counties, and 91.6% of those counties have a mostly rural populationcounty-mapResidents per mental health provider by county, providers counted in 2023, on a scale that doubles at each step

Health behaviors, person by person

Chapter 5.2 in Part V

Figure 1. Binge drinking rose from 13.3% to 20.4% of adults across the five income bands while smoking, obesity and inactivity felllinePercent of adults in the states and DC with each behavior, by household income band, BRFSS 2015 to 2024 for binge drinking and 2014 to 2024 for the other three, with 95% confidence intervals
Figure 2. The rise in binge drinking with income holds within age groups and education levels and differs by race and ethnicitytabsPercent of adults who binged in the past month by household income band within age group, education level, and race and ethnicity, BRFSS 2015 to 2024
Figure 3. Binge drinking is higher in the highest income band than in the lowest in all 51 jurisdictions, and smoking is lower in all 51dotRate in the highest household income band minus the rate in the lowest, percentage points of adults, by state and the District of Columbia, BRFSS 2015 to 2024 for binge drinking and 2014 to 2024 for smoking
Figure 4. Men binge drink more than women in every income band, by 8.5 to 9.2 pointslinePercent of adults who binged in the past month by sex and household income band, BRFSS 2015 to 2024, with 95% confidence intervals
Figure 5. The obesity difference between the highest and the lowest income band is −14.4 points for women and −0.2 for mendotRate in the highest household income band minus the rate in the lowest, percentage points of adults, by measure and sex, BRFSS 2014 to 2024 (binge drinking 2015 to 2024)
Figure 6. Smoking is 28.0% among adults who did not finish high school in the lowest income band and 4.4% among college graduates in the highestheatmapPercent of adults who currently smoke by education level and household income band, BRFSS 2014 to 2024
Figure 7. Men smoke more than women by 1.7 points among non-Hispanic White adults and 8.1 among Hispanic adultsdumbbellPercent of adults who currently smoke by sex within five race and ethnicity groups, BRFSS 2014 to 2024, with 95% confidence intervals

Air pollution

Chapter 5.3 in Part V

Figure 1. Traffic pollution ranks at a mean national percentile of 75 in the least deprived tenth of tracts and 39 in the most deprivedlineMean national percentile of four EJScreen air indicators by decile of the Area Deprivation Index national rank, population-weighted, census tracts
Figure 2. The fall in traffic and diesel PM percentiles with deprivation persists among metropolitan tracts, and the sign reverses when tracts are compared within a countytabsThree views of the link between the Area Deprivation Index and national pollution percentiles: rural share, metropolitan tracts only, and correlations by comparison
Figure 3. Pollution percentiles rise with the Hispanic share of a tract, from 33 to 73 for NO₂ across deciles, and with its Black share up to the fifth decile and in the tenthlineMean national percentile of four EJScreen air indicators by decile of the tract's Hispanic or Latino share and of its Black alone share, population-weighted
Figure 4. Residents of tracts in the highest Black-share decile live with 1.7 stacked air hazards on average, against 0.8 in the lowest, and the score falls across deprivation decileslineMean number of five air hazards in the top quarter of tracts, by decile of tract Black alone share, Hispanic or Latino share and ADI national rank, population-weighted, up to 82,993 tracts
Figure 5. The first component weights diesel PM, traffic, hazardous-waste facilities and NO₂ most, and the second weights storage tanks, lead paint and drinking-water violations against PM₂.₅ and ozonescatterWeights of the 13 standardized EJScreen percentiles on the first two principal components, 80,754 tracts, each tract counted once
Figure 6. The urban-industrial component is highest in Cook County, Illinois, and in dense counties around New York, and below the tract average in most countiescounty-mapPopulation-weighted county mean of the tract score on the first principal component of 13 EJScreen percentiles, in standard deviations of the tract score
Figure 7. Pollution percentiles correlate negatively with deprivation for 4 of 6 air indicators and positively with Hispanic share for 5heatmapPopulation-weighted correlation of 13 EJScreen national percentiles with the ADI national rank, Hispanic or Latino share and Black alone share, across tracts
Figure 8. Modeled asthma prevalence is highest in the lowest twentieth of tracts on the urban-industrial component (11.2%) and rises with the lead-paint percentile and with deprivationlineModeled prevalence of current asthma among adults by twentieth of tracts on three measures, population-weighted, 80,754 tracts with all 13 percentiles
Figure 9. Within the same county, tracts graded D in the 1930s rank 3.9 points above grade A tracts on the traffic percentile and 9.7 points on NO₂, and the stacked-hazard score is 0.6 higherdotDifference from grade A in the same county in the mean national percentile of four air indicators and in the mean stacked-hazard score, by dominant HOLC grade of the tract, population-weighted

Multiple chronic conditions

Chapter 5.4 in Part V

Figure 1. Stroke, diabetes, COPD and heart disease are high in the same tracts, with correlations from +0.74 to +0.90, while cancer correlates −0.13 with asthmaheatmapPopulation-weighted Pearson correlations between the tract prevalence of nine chronic conditions among adults, 82,781 census tracts, 2022
Figure 2. Tracts high on stroke are also high on 4.9 of the other eight conditions on average, against 2.5 for tracts high on cancer and 2.0 if the conditions were independentdotMean number of the other eight conditions that are also high in a tract, for tracts in the highest 25% of tracts on each condition, 2022
Figure 3. 34.0% of tracts are high on none of the nine conditions and 892 tracts are high on all nine, where independent conditions would give 0.3 tractsbarTracts by the number of the nine conditions whose prevalence is in the highest 25% of tracts, observed and expected if the conditions were independent, 82,781 tracts, 2022
Figure 4. Tracts are high on all nine conditions more often than independent conditions would give under every cutoff, from 14 tracts against 0.0 at the strictest to 2,679 against 4.5 at the loosesttableCount of high conditions per tract when a tract is high on a condition if it is in the highest 10%, 20%, 25% or 33.3% of tracts, 82,781 tracts, 2022
Figure 5. Weighted by adults, a tract in the most deprived tenth is high on 5.7 of nine conditions on average, against 0.5 in the least deprived tenthlinePopulation-weighted mean number of the nine conditions that are high, by tenth of tracts on the ADI national percentile, 82,781 tracts, 2022
Figure 6. An approximation of the model's census inputs leaves the average correlation among the nine conditions at +0.47, against +0.49 in the raw datadotMean of the 36 pairwise population-weighted correlations among the nine conditions across 82,781 tracts, 2022, under seven comparisons
Figure 7. In 1,229 counties, 50% or more of adults live in tracts that are high on 5 or more conditions, and 25.8% of adults in the South do, against 7.0% in the Westcounty-mapShare of adults living in tracts that are high on 5 or more of the nine conditions, by county, population-weighted, 2022
Figure 8. Life expectancy at birth is 6.1 years shorter in tracts that are high on eight conditions than in tracts that are high on nonelinePopulation-weighted mean tract life expectancy at birth by number of high conditions, 77,934 tracts, deaths in 2010 to 2015, institutional tracts dropped

Place and the length of a life

Chapter 6.1 in Part VI

Figure 1. Life expectancy is lower in each higher tenth of tracts by deprivation, and smoking rises with it while the annual checkup rises littletabsTract life expectancy at birth by Area Deprivation Index percentile, and two modeled health measures by tenth of tracts
Figure 2. Within every New York City borough, the 5th to 95th percentile of tract life expectancy spans at least 9.3 years, while the borough means lie within 4.2 years of one anothertract-mapLife expectancy at birth of 2,074 census tracts in the five boroughs of New York City, deaths in 2010 to 2015, on 2020 tracts; 250 tracts are gray because they have no value
Figure 3. In 17 large counties, the pair of tracts within 5 kilometers with the widest ADI difference had higher life expectancy in the less deprived tract in 15, and a median gap over the pairs of 5.4 yearsdumbbellLife expectancy at birth in the two tracts of one pair per county, the pair with the widest ADI difference, in 17 of the 20 most populous counties, native 2010 tracts, deaths in 2010 to 2015, 95% intervals
Figure 4. 70.3 percent of the variance of tract life expectancy lies between tracts in the same county, 26.7 points of it estimation error, against 34% percent for the ADIbarShare of the population-weighted variance of tract life expectancy and of the ADI national percentile that lies between states, between counties in a state and between tracts in a county, percent
Figure 5. In the 30 most populous counties, tract life expectancy spans a median of 10.5 years between the 5th and 95th percentile, 7.7 net of estimation errordotPopulation-weighted mean life expectancy at birth of each county (dot) and the 5th to 95th percentile of its tracts (whisker), sorted by the width of the range, deaths in 2010 to 2015
Figure 6. Life expectancy is lower in more deprived tracts in all 267 metros with enough tracts, by a median of 1.20 years per ten-point steptabsOne regression of tract life expectancy on the ADI national percentile in each metro with enough tracts, shown by metro and as a distribution, deaths in 2010 to 2015

Gun homicide and the causes of early death

Chapter 6.2 in Part VI

Figure 1. The tract clusters with the highest firearm homicide rates hold 50% of implied deaths and 9.5% of residents outside New York CitylineCumulative share of implied firearm homicide deaths against cumulative share of residents, tract clusters ranked from the highest to the lowest mean annual rate, 2022 to 2024, outside New York City
Figure 2. In Cook County the clusters holding 50% of firearm homicide deaths hold 10.5% of residents, against 24.4% in the county with the largest sharelineCumulative share of implied firearm homicide deaths against cumulative share of residents, tract clusters ranked from the highest rate, the counties with the most implied deaths, 2022 to 2024
Figure 3. In Cook County, 24.2% of tracts with an estimate sit in clusters with no recorded firearm homicide, while the highest cluster rate reaches 89 per hundred thousand residentstract-mapMean firearm homicide rate per 100,000 residents, 2022 to 2024, of the tract cluster each Cook County tract belongs to
Figure 4. In Cook County, residents of the highest-rate tenth of clusters have a life expectancy of 71.7 years (deaths in 2010 to 2015), 9.5 fewer than residents of clusters with no recorded deathstabsCook County residents in tenths by the firearm homicide rate of their tract cluster, 2022 to 2024: the rate, life expectancy at birth for deaths in 2010 to 2015, and the Area Deprivation Index
Figure 5. Premature mortality rises from 307 to 701 per hundred thousand residents across deciles of county deprivationlinePopulation-weighted mean age-adjusted deaths before age 75 per 100,000 residents, by decile of the county Area Deprivation Index, counties, County Health Rankings 2024 release
Figure 6. Overdose is 51.0% of the four-cause toll in the least deprived fifth of residents and 43.6% in the most, while motor-vehicle crashes go from 16.0% to 21.4%barEach kind of death's share of the sum of four crude death rates (overdose, suicide, homicide, motor-vehicle crash), by fifth of residents ranked by county deprivation, counties with all four rates published
Figure 7. Homicide and other causes of early death are higher in more deprived counties, with a population-weighted correlation of +0.41 for homicidedotCorrelation across counties of each death measure with the county Area Deprivation Index and with the rural share of residents, weighted by county population or counting every county once, County Health Rankings 2024 release
Figure 8. Overdose has the highest rate of the four causes in 829 of 1,248 counties, and homicide in only 11county-mapKind of death with the highest crude death rate among overdose, suicide, homicide and motor-vehicle crash, counties with all four rates published, County Health Rankings 2024 release

Overdose, alcohol and suicide

Chapter 6.3 in Part VI

Figure 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 ratescounty-mapCDC modeled death rates per 100,000 residents, mean of annual rates for 2019 to 2023, by county: overdose, suicide and homicide in three views
Figure 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 steadilylineCDC 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
Figure 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 countiesdotCDC 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
Figure 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 Midwestcounty-mapCrude 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
Figure 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 rateslineCrude 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

Mortality trends, 2018 to 2024

Chapter 6.4 in Part VI

Figure 1. The national overdose death rate rose from 21.5 per hundred thousand residents in 2019 to 32.4 in 2022 and was 23.3 in 2024, while the suicide rate stayed within 3.6% of its 2019 levellineCrude death rates per 100,000 residents for drug poisoning of any intent (overdose), alcohol-induced deaths and suicide, United States, 2018 to 2024
Figure 2. From 2020 to 2024 the United States had 131,549 more overdose deaths than a flat 2019 rate giveslineObserved national crude death rate per 100,000 residents and the 2019 rate held constant, United States, 2018 to 2024
Figure 3. In CDC's modeled county panel the overdose rate peaked in 2022 at 54.7% above its 2019 level and the homicide rate in 2021 at 35.2%, while the suicide rate stayed within 4.0% of its 2019 levellineMean of county death rates weighted by county population, relative to 2019 (2019 = 100), for overdose, homicide and suicide, counties with a stable modeled rate that year, United States, 2019 to 2024 (2024 provisional)
Figure 4. WONDER's overdose rate rose 51.0% from 2019 to 2022 outside Connecticut and the panel's rose 54.7%, a difference that matches a roughly constant number of deaths the panel does not counttabsDrug overdose deaths and crude rates, CDC WONDER (poisoning of any intent) and the CDC county panel (unintentional or undetermined intent), 2019 to 2024
Figure 5. Among counties with published counts in every year, death rates in 2022 were higher in the most deprived third of counties than in the least deprived third, by 1.49 times for overdose, 1.22 for alcohol-induced deaths and 1.37 for suicidelinePooled crude death rates per 100,000 residents by third of counties ranked by Area Deprivation Index, counties whose count CDC WONDER publishes in every year 2018 to 2024, United States
Figure 6. Within the same counties, the overdose rate in 2022 was 11.2 deaths per hundred thousand residents above its 2019 level and the alcohol-induced rate in 2021 4.3 above, while suicide rates never moved by more than about 0.6 deaths per hundred thousand residentslineTwo-way fixed-effects event study: population-weighted average change in a county's crude death rate since 2019, deaths per 100,000 residents, counties whose count CDC WONDER publishes in every year, 2018 to 2024, errors clustered by state
Figure 7. From 2019 to 2022 the overdose rate rose 5.1 deaths per hundred thousand residents more in the most deprived third of counties with published counts than in the least deprived third, with no detectable gap in 2018lineDifference in the change in the crude death rate since 2019 between the most deprived and the least deprived third of counties, deaths per 100,000 residents, counties whose count CDC WONDER publishes in every year, 2018 to 2024, errors clustered by state
Figure 8. The modeled overdose death rate was lower in 2024 than in 2022 in 80.2% of counties with any overdose deaths in 2022 or 2024, from 62.7% in the West to 91.8% in the Northeastcounty-mapChange in the CDC panel's modeled overdose death rate per 100,000 residents from 2022 to 2024 (2024 provisional), counties with a stable rate in both years and at least one death

Violence and the life-expectancy gap

Chapter 6.5 in Part VI

Figure 1. Homicide deaths per hundred thousand residents a year rise from 1.8 in the least deprived tenth of tracts to 14.8 in the most deprivedlineMean annual homicide deaths per 100,000 residents, 2022 to 2024, by tenth of tracts on the Area Deprivation Index, tracts outside New York City with a published rate
Figure 2. Homicide accounts for 0.39 of the 8.3 years by which life expectancy is lower in the most deprived tenth of tracts than in the least deprivedlineYears of life expectancy at birth below the least deprived tenth, by tenth of tracts on the Area Deprivation Index: observed for deaths in 2010 to 2015, and the part attributed to homicide by a rough accounting with homicide rates for 2022 to 2024
Figure 3. Homicide accounts for 3.4% of the gap if each takes 30 years of life and 6.3% if each takes 55, and for at most 8.5% when one value applies to every tenthlineShare of the gap in life expectancy between the least and the most deprived tenths of tracts attributed to homicide, by the years of life assumed lost per homicide
Figure 4. Changing the rate window, the set of deaths counted or the conversion moves the share of the gap between 3.9% and 6.2%tablePart of the gap in life expectancy between the least and the most deprived tenths of tracts attributed to homicide, in the main setting and in each variation, at the published years of life lost per death
Figure 5. Life expectancy is 8.1 years lower in clusters with homicide rates over 40 per hundred thousand than in clusters with rates up to 2, and homicide accounts for 18.5% of the differencebarYears of life expectancy at birth below the lowest-rate group of tract clusters, by group of clusters ranked on the homicide rate for 2022 to 2024: the observed difference split into the part attributed to homicide and a remainder
Figure 6. Within each tenth of tracts on the deprivation index, life expectancy is lower in the group with the higher homicide rate, by 0.8 years in the least deprived tenth and 2.1 in the most depriveddumbbellPopulation-weighted mean life expectancy at birth for deaths in 2010 to 2015 in the lower-rate and higher-rate groups of each tenth of tracts on the Area Deprivation Index, split on the homicide rate for 2022 to 2024

Civic life, loneliness and partnership

Chapter 7.1 in Part VII

Figure 1. Voter turnout and census self-response fall with county deprivation, and across counties they correlate less with upward mobility than family structure and friendship across incomes dotabsCounty Health Rankings 2024 participation measures by decile of county deprivation, and county measures of civic life against the adult income rank of children born 1978 to 1983 to parents at the 25th percentile
Figure 2. Census self-response in 2020 was highest in Minnesota, Wisconsin and Michigan and lowest in Alaska, West Virginia and Mainecounty-mapPercent of households that answered the 2020 census online, by mail or by phone without a visit from a census taker, by county
Figure 3. Once income, race and poverty are in the model, voter turnout has a coefficient of 0.00 on county mobility, and economic connectedness has 0.63dotStandardized coefficients on the adult income rank of children from low-income families (born 1978 to 1983) in three county regressions, weighted by 2018 county population
Figure 4. The partner premium is 0.50 ladder points overall and 0.50 within counties, and runs from 0.15 in the youngest age band to 0.80 in its largest banddotDifference in mean Cantril ladder score between adults who are married or in a domestic partnership and all others, under successive adjustments and by age band, Gallup U.S. Daily 2009 to 2017
Figure 5. The partner premium does not shrink where county social capital is higher: 0.45 ladder points in the lowest decile and 0.49 in the highesttabsCantril ladder scores of partnered and other adults by decile of the JEC Social Capital Index of the respondent's county, and the change in the premium per standard deviation of seven county measures
Figure 6. Modeled loneliness is lower in ZCTAs with more married adults, a correlation of −0.65, and higher where poverty is higher, +0.59dotCorrelation of CDC PLACES modeled loneliness (percent of adults, BRFSS 2023) with seven ZCTA characteristics, ZCTAs with an estimate and at least 500 residents
Figure 7. Modeled loneliness is higher in ZCTAs with fewer married adults and a younger populationtabsCDC PLACES modeled loneliness (percent of adults, BRFSS 2023) by decile of ZCTA married share and of ZCTA median age, population-weighted
Figure 8. Modeled loneliness rises from 32.7% to 37.9% across density classes of ZCTAs while modeled depression falls from 23.5% to 19.6%dotPopulation-weighted mean of two CDC PLACES modeled measures (percent of adults, BRFSS 2023) by population density of the ZCTA, ZCTAs with both estimates and at least 500 residents

Life evaluation and daily feelings

Chapter 7.2 in Part VII

Figure 1. The ladder runs from 2009 to 2017 and the feelings from 2008, but happiness and sadness stop after 2016 and anger was not asked in 2014, 2015 or 2017tableGallup U.S. Daily items used in this chapter: the years each was asked, interviews with a county and an answer, and the share of the interviews in those years that carry the item
Figure 2. The ladder score is 0.24 points lower in the most deprived tenth of counties, 0.13 points higher at the same nominal household income and other characteristics, and −0.02 once county rent levels also entertabsMean Cantril ladder score by decile of the deprivation of the respondent's county and ZIP area, as interviewed and after comparing respondents within cells, with the gap at each step
Figure 3. Physical pain is 8.8 percentage points more common in the most deprived tenth of counties, the largest gap of the seven feelings, and 1.8 at the same characteristics and 1.2 with county rent also allowed fordotDifference in the share reporting each feeling a lot of the day yesterday, most deprived minus least deprived tenth of interviews by county deprivation, Gallup U.S. Daily 2008 to 2017
Figure 4. The richest income bracket scores 0.68 standard deviations above the poorest on the ladder and −0.51 on physical pain, but only −0.12 on stresslineUnweighted mean of each item in standard deviations of the item, by household income bracket, Gallup U.S. Daily interviews (ladder 2009 to 2017, feelings 2008 to 2017)
Figure 5. The income gradient of the ladder is nearly the same in all three bands of counties, 0.250 points per bracket across respondents and 0.251 within countiestabsMean ladder score and share reporting physical pain by household income bracket, in three bands of county deprivation, Gallup U.S. Daily interviews (ladder 2009 to 2017, pain 2008 to 2017)
Figure 6. Across respondents the ladder correlates −0.28 with worry and +0.26 with enjoyment, and across county means it moves together with most feelings more tightlytabsCantril ladder scores against feelings yesterday, by whether the respondent reported each feeling, and the correlation of the two across respondents and across county means
Figure 7. Physical pain is the feeling most closely tied to the county deaths-of-despair rate under every weighting and comparison, with a correlation of +0.65 across countiestabsFeelings and life ratings of Gallup U.S. Daily respondents against the deaths-of-despair rate of their county (ladder 2009 to 2017, feelings 2008 to 2017)

Mental distress in young adults

Chapter 7.3 in Part VII

Figure 1. Frequent mental distress among adults 18 to 24 rose from 12.3% in 2014 to 25.3% in 2022, while the rate for adults 50 to 64 moved from 12.5% to 13.8%lineAdults reporting 14 or more of the past 30 days with mental health not good, percent, by age group and survey year, 50 states and DC, 2014 to 2024
Figure 2. The difference in frequent distress between adults 18 to 24 and adults 50 to 64 went from −0.2 points in 2014 to +11.6 points in 2022lineRate for adults 18 to 24 minus rate for adults 50 to 64, percentage points, design-based difference by survey year, 50 states and DC, 2014 to 2024
Figure 3. Frequent distress was close to flat from the youngest band to the late fifties in 2014 to 2016 and falls with age in 2022 to 2024lineAdults reporting 14 or more of the past 30 days with mental health not good, percent, by five-year age band, three periods of three survey years, 50 states and DC
Figure 4. Women reported frequent distress more often than men in every age group, and the gap among adults 18 to 24 rose from 5.5 to 10.8 pointsdumbbellRate for women minus rate for men, percentage points, by age group, 2014 to 2016 and 2022 to 2024, 50 states and DC
Figure 5. Frequent distress among adults 18 to 24 rose from 13.3% to 23.4%, and rose in every group by sex, household income and educationdumbbellAdults 18 to 24 reporting 14 or more of the past 30 days with mental health not good, percent, 2014 to 2016 and 2022 to 2024, by group, 50 states and DC
Figure 6. Frequent distress among adults 18 to 24 was 25.7% in the lowest household income bracket and 21.1% in the top, against 31.7% and 8.0% among adults 50 to 64heatmapAdults reporting 14 or more of the past 30 days with mental health not good, percent, by age group and annual household income, 2022 to 2024, 50 states and DC
Figure 7. In 2022 to 2024 the share of adults 18 to 24 ever told of depression was 25.6%, close to the 23.4% with frequent distress nowlineAdults with frequent mental distress and adults ever told by a health professional of a depressive disorder, percent, by five-year age band, 50 states and DC

Disability, retirement and Medicare

Chapter 8.1 in Part VIII

Figure 1. Adult disability is 23.3% in the least deprived tenth of census tracts and 42.9% in the most deprived, and it differs by 1.8 points between tenths of tracts with few and many older residentstabsPercent of adults with any disability and percent of older adults who have lost all their teeth, by tenth of the Area Deprivation Index, and disability against the share of older residents, census tracts, 2024 PLACES release
Figure 2. Disabled workers are 16.8% of Social Security beneficiaries in the most deprived fifth of ZIP codes and 7.2% in the least deprived, and retired workers are 65.9% against 80.5%barShare of OASDI beneficiaries by type, percent, ZIP codes in fifths of the Area Deprivation Index national rank, December 2024
Figure 3. The average monthly retired-worker benefit rises with ZIP code income, from $1,554 in the lowest tenth of ZIP codes to $2,370 in the highest, a correlation of +0.84scatterAverage monthly OASDI retired-worker benefit in dollars against median household income in dollars (log scale), one dot per sampled ZIP code area, with means for tenths of ZIP codes by income
Figure 4. Price-standardized Medicare payments are $12,680 per fee-for-service beneficiary in the least deprived fifth of counties and $13,176 in the most deprived, a difference whose interval includes zerotabsMedicare Part A and Part B payments per Original Medicare beneficiary with local prices removed, by fifth of the county Area Deprivation Index, service lines, emergency department visits and county life expectancy, 2024
Figure 5. Expected age at death at 40 for the poorest income quartile runs from 77.5 in the county at the fifth percentile to 81.8 in the county at the ninety-fifthcounty-mapExpected age at death in years for people who reach age 40 in the lowest quartile of national household income, 2001 to 2014, counties in the Health Inequality Project file
Figure 6. Weighted by residents, county values of expected age at death at 40 span 4.3 years between the 5th and 95th percentiles for the poorest income quartile and 3.0 for the richestscatterExpected age at death in years for people who reach age 40 in the poorest quartile against the richest quartile of national household income, one dot per county, dot area is county residents, 2001 to 2014
Figure 7. Across counties weighted by residents, the poorest quartile's expected age at death correlates −0.67 with the county ADI, −0.64 with obesity and −0.58 with smoking, and −0.15 with the uninsured sharedotCorrelation across counties of expected age at death at age 40 in the poorest and the richest income quartile with 15 county measures, 2001 to 2014 deaths and 2018 to 2023 measures, with 95% intervals

Well-being across the life span

Chapter 8.2 in Part VIII

Figure 1. Mean life evaluation falls from 7.03 among adults 18 to 24 to 6.84 among adults 45 to 54 and is 7.38 among adults 75 to 94lineUnweighted mean Cantril ladder score by year of age, adults aged 18 to 94 interviewed by Gallup, 2009 to 2017
Figure 2. Stress, worry and anger are lower among older adults, enjoyment and happiness are lowest in midlife, and physical pain peaks near age 60tabsShare of adults who reported each feeling during a lot of the day yesterday, by year of age, and the age at which each profile turns, Gallup 2008 to 2017
Figure 3. The ladder falls into midlife and rises after it in every third of interviews by county deprivation, and the fall from ages 25 to 34 to ages 45 to 54 is −0.17 points in the most deprived third and −0.11 in the leasttabsCantril ladder score and feelings yesterday by year of age, for the least deprived, middle and most deprived third of interviews ranked by the Area Deprivation Index of the respondent's county, Gallup ladder 2009 to 2017 and feelings 2008 to 2017
Figure 4. The fall in life evaluation from ages 25 to 34 to ages 45 to 54 is −0.59 ladder points in households under $36,000 and −0.05 in households of $90,000 or more, where the fall from ages 35 to 44 is −0.07tabsCantril ladder score and feelings yesterday by year of age, for interviews in 2009 to 2014 in households with annual income under the lower cutoff, between the cutoffs and above the upper cutoff, Gallup
Figure 5. Adjusting for household income moves the lowest point of the ladder profile from age 54 to age 48 with overlapping intervals, and a quadratic fit puts it at age 44, so no single age is the turning pointtabsCantril ladder score by year of age, raw and adjusted, the age of its lowest point under different adjustments and for groups, and the fall and rise between age bands, Gallup 2009 to 2017
Figure 6. Relative to adults at the same ages, stress among people born in 1950 to 1959 changed by −9.6 points and their ladder score by +0.22 points between 2009 and 2017, against −10.6 and +0.28 across the same ages in 2009tabsBirth cohorts of a decade followed across Gallup interview years, for the ladder (2009 to 2017), stress and physical pain (2008 to 2017), with the profile by year of age from all interviews

Eight types of neighborhood

Chapter 9.1 in Part IX

Figure 1. The typology covers 77,745 of the 85,396 census tractstableCensus tracts at each step from the 2020 census to the tracts with every input, counted at the first step that removes them
Figure 2. Life expectancy, one of the 13 inputs, averages 82.3 years among high-income owners and 72.3 years in the high-poverty type, with the other six types betweentablePopulation-weighted mean of tract values by neighborhood type, types numbered from most to least advantaged on the first principal component
Figure 3. Low-density, lower-income owners are the most common type in 1,274 counties and low-density older owners in 970, most of the 3,087 counties with a typecounty-mapNeighborhood type that holds the most residents in each county, tracts typed by k-means on 13 measures, ACS 2019-2023 population
Figure 4. The high-poverty type has the least favorable mean on all eight measures, four that went into the types and four that did nottabsPopulation-weighted mean of tract values by neighborhood type with 95% intervals from a bootstrap over counties, each panel in its own units
Figure 5. Neighboring types overlap along the first component, and 10.2% of 20,000 sampled tracts sit nearer another type than their ownscatterA random sample of tracts on the first two principal components of the 13 standardized inputs, colored by type, with each type's centroid labeled

Places that beat the model

Chapter 9.4 in Part IX

Figure 1. Five census measures account for 44.0% of the variation in tract upward mobility, and the population-weighted standard deviation of the gap between actual and predicted rank is 5.0 percentile pointsscatterAdult household income rank (percentile) of children raised in low-income families against the rank predicted from poverty, college, single-parent share, income and Black share, one dot per tract (random sample)
Figure 2. Counties below the prediction cluster in the South, and the largest counties above it lie around New Yorkcounty-mapPopulation-weighted mean residual of tract upward mobility (actual minus predicted rank, percentile points) by county, counties with at least 8 tracts in the model
Figure 3. Counties in the top tenth by residual have more pre-1960 housing, a larger Hispanic share, less poverty and fewer smokers than the bottom tenth, and the differences in the Black share, ownership and college include zerodumbbellPopulation-weighted tract means in the bottom and top tenths of counties by mean residual (equal numbers of counties), with 95% intervals from a bootstrap over counties
Figure 4. Net adjusted gross income was positive in 1,719 counties and negative in 1,367, with the largest losses per resident in San Francisco and Boston's Suffolk County and the largest gains in Floridacounty-mapNet adjusted gross income (arriving minus leaving returns) in dollars per resident by county, returns filed in 2022 matched with returns filed in 2023
Figure 5. Net migration of tax filers is lower in counties with higher childhood mobility, a population-weighted correlation of −0.19, and the two highest tenths by mobility lost filers on nettabsNet migrating returns per 1,000 returns filed for tax year 2022, by county, against the Opportunity Atlas upward-mobility rank, returns filed in 2022 matched with returns filed in 2023
Figure 6. Net income per resident is lower in the counties with the highest home values, a population-weighted correlation of −0.37 that is +0.11 when each county counts oncescatterNet adjusted gross income per resident in dollars against county home value in dollars (log scale), one dot per county sized by population, with pooled means for tenths of counties
Figure 7. In pooled tenths of counties by deprivation, returns arriving report about the same income as returns leaving, though the median county's arriving returns report 2,514 dollars morelineAverage adjusted gross income per return of arriving and of leaving returns in dollars, by tenth of counties ranked on the Area Deprivation Index (1 = least deprived), returns filed in 2022 matched with 2023

Gradients, slopes and variance

Chapter 10.1 in Part X

Figure 1. Life expectancy is 1.12 years lower per ten-point step of the ADI within counties, against 0.84 years across all tractsdotSlope of tract life expectancy at birth on the Area Deprivation Index national percentile, years lower per ten-point step, three specifications, deaths in 2010 to 2015
Figure 2. Life expectancy is lower in more deprived tracts in all 267 metros, by a median of 1.20 years per ten-point steptabsOne regression of tract life expectancy on the ADI national percentile in each metro with enough tracts, shown by metro and as a distribution, deaths in 2010 to 2015
Figure 3. Metro slopes are not detectably related to metro median income, a correlation of +0.05 counting each metro oncescatterSlope of life expectancy on the ADI, years lower per ten-point step, against the population-weighted median of tract median household income, one dot per metro, dot area is residents, ACS 2019-2023
Figure 4. The same regression in every state gives coefficients below zero for five measures in all 51 states and above zero for binge drinking in 50beeswarmPoints of prevalence per doubling of tract median household income, one dot per state and measure, adults, with controls for the age, Black and Hispanic shares of residents, 2022
Figure 5. The first of nine components holds 51.3% of the variance in nine census measures and the second holds 16.0%tabsPrincipal components of poverty, cash assistance, unemployment, education, single-parent households, income, labor-force participation and homeownership across tracts, 2019-2023
Figure 6. Weighted by population, the same pair of measures has a different correlation at each grain, and homeownership and poverty go from −0.53 across tracts to −0.05 across statesslopeCorrelation of six pairs of tract measures across tracts, across counties and across states, weighted by population or counting each unit once, with 95% intervals from a bootstrap over counties or states, 2019-2023
Figure 7. 70.3 percent of the variance of tract life expectancy lies between tracts in the same county, 26.7 points of it estimation error, against 34% percent for the ADIbarShare of the population-weighted variance of three tract measures between states, between counties in a state and between tracts in a county, percent
Figure 8. In each of the 30 most populous counties, tracts at the 10th and 90th percentile of the ADI are between 9 and 69 percentile points apartdotPopulation-weighted mean ADI national percentile of each county (dot) and the 10th to 90th percentile range of its tracts' ADI (whisker), the most populous counties sorted by range, ACS 2019-2023 population
Figure 9. WONDER withholds 71.3% of county-year cells in the lightest birthweight class and 77.6% in the heaviest, against 0.0% in the five middle classesbarShare of county-year cells that are withheld, published as zero or published with at least 10 births, by birthweight class, 578 counties named in every year, 2018 to 2024, percent

The anatomy of a deprivation index

Chapter 10.2 in Part X

Figure 1. The Atlas score sums 17 measures with fixed coefficients, and 4 of them are dollar amountstableThe measures in Singh's deprivation index, the unit each enters the sum in, Singh's factor score coefficient, and whether this chapter rebuilds it
Figure 2. Home value correlates −0.31 with the poverty rate across tracts, a weaker link than family income has at −0.61heatmapPopulation-weighted Pearson correlations among the 15 rebuilt measures in their own units, 75,717 tracts, ACS 2019 to 2023
Figure 3. In raw units home value accounts for 74.3% of the variance of the score on its own and 85.4% with its covariance with income shared out, against 5.3% after standardizationtabsShare of the population-weighted variance of the replica score allocated to each measure, same coefficients, measures in raw units and in standard deviation units, 75,717 tracts
Figure 4. The published ADI correlates +0.991 with its raw-units replica and +0.72 with the standardized version of the same measuresheatmapPopulation-weighted rank correlations among six rankings of 2020 tracts, measures from ACS 2019 to 2023
Figure 5. The published ADI percentile minus the standardized percentile averages −16.5 in the highest-cost counties and +11.1 in the lowest-cost countiestabsTract percentile on the published ADI against the percentile of the standardized replica score, by the cost of the tract's county, and the tracts with the largest gaps
Figure 6. The measures sort into housing money, economic hardship, and crowding with little schooling, which together hold 58.1% of their variancetabsVarimax-rotated loadings of the 15 standardized measures on 3 maximum-likelihood factors, 75,717 tracts, ACS 2019 to 2023
Figure 7. The published ADI tracks life expectancy about as closely as the standardized score does but upward mobility less closely, by 0.100 in correlationdotAbsolute population-weighted rank correlation of eight rankings with tract life expectancy at birth and with the adult income rank of children from low-income families, 71,874 and 75,667 tracts

A deprivation index at two zooms

Chapter 10.3 in Part X

Figure 1. Homeownership has a weight of −0.18 in the tract index and 0.03 in the county index, and crowding goes from 0.14 to −0.05barWeights of the 14 standardized measures in the first principal component, tract box (76,496 tracts) and county box (3,205 counties), ACS 2019 to 2023
Figure 2. Counted among residents, 32.7% of people live in a tract more than 25 percentile points from their county's percentile, and 40.7% when tracts and counties are ranked as unitshistogramPopulation-weighted distribution of a resident's tract percentile minus the resident's county percentile, in bins of five percentile points, 309.9 million residents of 76,496 tracts, ACS 2019 to 2023
Figure 3. Los Angeles County has a county percentile of 29.1, and its residents' tracts run from 2.0 to 94.2dotPercentile among residents of the county index built from the county's own estimates, beside the average and the 5th to 95th percentile range of the percentiles of its tracts, the 30 most populous counties
Figure 4. The index correlates −0.62 with life expectancy across tracts and −0.76 across counties, and −0.43 with homeownership across tracts and +0.06 across countiesdotCorrelation of the index percentile among residents with four tract measures, across tracts and across counties, ACS 2019 to 2023, USALEEP 2010 to 2015 and Opportunity Atlas 1978 to 1983 cohorts

Families of places

Chapter 10.4 in Part X

Figure 1. The tract data beat a cloud with no clusters by 0.09 in silhouette at four families, more than at any other number of familiestabsMean silhouette of k-means fits to the 15 standardized deprivation measures, tract data and simulated data with no clusters, and agreement of refits on resamples of counties
Figure 2. Crowded renters average 2.2 standard deviations above the mean tract on crowding, and the high-poverty family 1.4 above on povertyheatmapPopulation-weighted mean z-score of each of the 15 measures by family, tracts, ACS 2019 to 2023; zero is the mean tract
Figure 3. Mean tract family income runs from 58 thousand dollars in the high-poverty family to 162 thousand dollars in the high-income familytablePopulation-weighted means of tract values by family, in the units of each column, tracts and residents of the frame, ACS 2019 to 2023
Figure 4. Life expectancy runs from 81.7 years in the high-income family to 74.7 years in the high-poverty family, and the crowded-renter and mid-range families do not differ detectablytabsPopulation-weighted mean of tract values by family with 95% intervals from a bootstrap over counties; none of these measures was used to form the families
Figure 5. In the most deprived decile of tracts, 79.2% of residents live in high-poverty tracts and 16.1% in mid-range tractsbarShare of residents in each decile of the ADI national rank by family of their tract, percent of residents, tracts of the frame, ACS 2019 to 2023
Figure 6. Crowded-renter tracts hold 50.7% of the residents of counties that resemble the crowded-renter family, and high-income tracts hold 34.6%barShare of residents by family of their tract, in counties labeled by the nearest family center, percent of residents, ACS 2019 to 2023

Suppressed counties in death data

Chapter 10.5 in Part X

Figure 1. In every year from 2018 to 2024 WONDER withheld between 44.6% and 59.9% of county-year death counts, in county-years that hold between 8.6% and 17.4% of residentslineShare of county-years whose death count CDC WONDER withholds, and share of residents living in a withheld county-year, by year, for drug overdose, alcohol-induced causes and suicide, all counties in the county files
Figure 2. WONDER withholds 82.3% of overdose county-years in counties of 10,000 to 25,000 residents and 45.2% in smaller counties, where 54.7% are published as zerobarShare of county-years withheld, published as zero and published with at least 10 deaths, by size of county (mean residents 2018 to 2023), drug overdose, alcohol-induced causes and suicide
Figure 3. WONDER withheld the overdose count in every year from 2018 to 2023 in 591 counties and in no year in 950county-mapNumber of years from 2018 to 2023 in which CDC WONDER withholds a county's death count, by county, for drug overdose, alcohol-induced causes and suicide
Figure 4. Counties whose overdose count WONDER publishes in every year hold 83.8% of residents, and counties withheld in every year hold 4.1% and are smaller, more rural and more depriveddotCounties by how many years from 2018 to 2023 WONDER withholds the death count: share of counties and residents, median size, nonmetro residents, Area Deprivation Index rank and race and ethnicity of residents, other than Connecticut's counties
Figure 5. Among counties of 25,000 to 50,000 residents, the panel's overdose rate is 52.3 where WONDER publishes every year and 22.3 where it withholds the count in at least one year, and the order reverses under 10,000 residentsdotCDC modeled death rate per 100,000 residents, mean of annual rates for 2019 to 2023, in counties whose WONDER count is published in each year 2019 to 2023 and in counties where it is withheld in at least one of those years, including counties never published, by size of county, population-weighted
Figure 6. A rate pooled over published county-years is 1.8 times the true rate at 5.4 expected deaths a year, below it under 4.2 and within 5% of it above 14.2lineExpected pooled rate over the county-years WONDER publishes (counts of zero and of at least 10) divided by the true rate, against the expected number of deaths in a county-year, Poisson counts and a constant rate
Figure 7. A suicide rate pooled over published county-years is 0.18 times the panel's rate in counties under 10,000 residents and 1.51 times in counties of 25,000 to 50,000 residentsdotDeath rate pooled over the county-years CDC WONDER publishes, 2019 to 2023, divided by the CDC panel's population-weighted modeled rate for 2019 to 2023 in all counties of each size with a stable panel rate, suicide and drug overdose
Figure 8. In every source the counties left without a value are a larger share of counties than of residents, from 55 counties without a premature death rate to 2,881 that WONDER linked birth and infant death does not nametableCounties with no value in each source and measure, with the share of counties and the share of residents in them, for WONDER mortality, County Health Rankings, the CDC panel and the counties WONDER names in its birth products