Chapter 1.3 · The vanishing cradle

Where births are falling

Births in the counties that CDC WONDER identifies fell 4.6% from 2018 to 2024, by 5.6% in the least deprived quartile of counties and 7.3% in the most deprived, while births to mothers aged 15 to 29 fell and births to mothers aged 35 to 44 rose.

Author: Vishal Singh
Affiliation: NYU Stern
Published: 9 October 2026

Births in the 578 counties that CDC WONDER identifies fell from 3.02 million in 2018 to 2.88 million in 2024, a decline of 4.6%. These counties have 100,000 or more residents in the population vintage WONDER uses, and they record 79.4% of the births in the United States in 2024. In 380 of them births were lower in 2024 than in 2018, in 197 they were higher, and in one the count was the same. From the 5th to the 95th percentile of counties, changes run from a decline of 16.5% to a gain of 19.9%, and the extremes (Figure 3) are a decline of 23.9% in St. Louis city, Missouri, and a gain of 67.6% in Kaufman County, Texas.

Pooled over counties, births changed by 0.0% (95% CI −1.7% to 1.8%) in the South, −8.4% (95% CI −10.4% to −6.3%) in the Midwest, −7.9% (95% CI −10.7% to −5.0%) in the West and −5.0% (95% CI −7.3% to −2.5%) in the Northeast. Pooled births fell by 5.6% (95% CI 2.8% to 8.2%) in the least deprived quartile of these counties, by 2.6% and 3.1% in the second and third quartiles, and by 7.3% (95% CI 5.8% to 8.8%) in the most deprived. The losses do not rise in steps with deprivation, and region and deprivation overlap, so the chapter looks at them together. The ages of mothers shifted too. Between 2018 and 2024 births fell by 24.6% among mothers aged 15 to 19 and rose by 19.5% among mothers aged 40 to 44, and the counties that lost the most births lost them among mothers under 35.

Everything in this chapter is a count of births in a county or a share of those births. A birth rate divides births by the women who could have had them, and the files behind this book have no county counts of women by age, so the chapter reports counts and shares and no rates. The babies in these counties are the subject of Chapter 1.1, Birthweight and preterm birth, which asks how heavy they were at birth, and of Chapter 1.2, Infant mortality, which follows them through the first year.

Births have not returned to their 2018 level

Births in the named counties fell from 2018 to 2020, rose through 2022, fell again to a low in 2023, when they were 5.5% below 2018, and rose 0.9% in 2024 (Figure 1). In 2020 they were 4.8% below 2018, and by 2024 they were still 4.6% below. WONDER pools the births of every smaller county in a state into one row, 49 rows in all. Those rows record 0.77 million births in 2018 and 0.75 million in 2024, a decline of 3.0%, so the named counties lost a larger share of their births than the rest of the country combined. Across the whole country births fell from 3.79 million to 3.63 million, a decline of 4.3%. The count for 2024 is the one in the final report of the National Center for Health Statistics, and 2024 is final in these data.[1]

Birth rates in the United States have been falling since the Great Recession. Kearney, Levine and Pardue document that birth rates fell between 2007 and 2020 across many groups of women, and they find that the recession explains only part of the early decline.[2] This chapter starts in 2018 and describes where the recent loss fell.

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 counties

Live 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

Show data

Data for 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 counties
measure	n	series	value	year
index	3,020,813	Named counties	100	2018
births	3,020,813	Named counties	3020813	2018
index	2,985,056	Named counties	98.82	2019
births	2,985,056	Named counties	2985056	2019
index	2,875,172	Named counties	95.18	2020
births	2,875,172	Named counties	2875172	2020
index	2,912,953	Named counties	96.43	2021
births	2,912,953	Named counties	2912953	2021
index	2,920,239	Named counties	96.67	2022
births	2,920,239	Named counties	2920239	2022
index	2,855,036	Named counties	94.51	2023
births	2,855,036	Named counties	2855036	2023
index	2,881,385	Named counties	95.38	2024
births	2,881,385	Named counties	2881385	2024
index	770,899	Other counties	100	2018
births	770,899	Other counties	770899	2018
index	762,484	Other counties	98.91	2019
births	762,484	Other counties	762484	2019
index	738,475	Other counties	95.79	2020
births	738,475	Other counties	738475	2020
index	751,339	Other counties	97.46	2021
births	751,339	Other counties	751339	2021
index	747,519	Other counties	96.97	2022
births	747,519	Other counties	747519	2022
index	740,981	Other counties	96.12	2023
births	740,981	Other counties	740981	2023
index	747,549	Other counties	96.97	2024
births	747,549	Other counties	747549	2024

Births in the named counties drop to 2020, recover a little through 2022, reach a low in 2023 and rise in 2024. Births in the other counties are lowest in 2020 and end nearer their 2018 level. The index divides each year's births by the 2018 births of the same group of counties; the second view shows the counts.Note: The named counties are the 578 that CDC WONDER natality identifies in every year from 2018 to 2024: counties with 100,000 or more residents in the population vintage WONDER uses, which is earlier than the 2020 Census. WONDER pools the births of every other county in a state into one row, so those counties are not in the named counties.Note: Births are full counts from birth certificates, so no interval is drawn. A count of births is not a birth rate: the series blends births per woman with the number of women.Source: CDC WONDER natality, births in 2018-2024; full counts of births (no sampling error)

The 578 named counties are the counties that WONDER identifies in every year from 2018 to 2024 and that have births in every year. WONDER lists two more county identifiers in every year, Cape May County, New Jersey, and Portsmouth city, Virginia, but gives them no births because it folded them into their state's pooled row, so they are left out. Every named county appears in every year from 2018 to 2024, so no county drops out of the panel by entering or leaving WONDER's list. The selection is by size as WONDER measured it. WONDER applies its threshold of 100,000 residents to an earlier population estimate than the 2020 Census. By 2020 Census population, 27 counties outside Connecticut that have 100,000 or more residents are still in the pooled rows, among them Sumter County, Florida, Gallatin County, Montana, and Flagler County, Florida, and one named county, Ashtabula County, Ohio, is below the line. The staged atlas has no 2020 count for Connecticut, whose counties are all named. Counties that grew past the line after WONDER's estimate therefore sit in the pooled rows, so the comparison of the 3.0% decline there with the 4.6% decline in the named counties compares two groups defined by an earlier population estimate and not by size today. The named counties record 79.7% of births in 2018 and 79.4% in 2024, and the smallest of them recorded at least 613 births in every year. County results in this chapter describe these counties and not the country. The pooled rows lost fewer births, with the caveat that they include counties that now exceed the line.

Births held up in the South and fell elsewhere

The Census Bureau groups states into the Northeast, the Midwest, the South and the West. The South, which has 16 states and the District of Columbia, holds 232 of the named counties, or 40.1%. Pooled over its counties, the South's births changed by 0.0% (95% CI −1.7% to 1.8%) from 2018 to 2024, an interval that includes zero. Births in the Midwest changed by −8.4% (95% CI −10.4% to −6.3%), in the West by −7.9% (95% CI −10.7% to −5.0%) and in the Northeast by −5.0% (95% CI −7.3% to −2.5%), so the intervals for those three regions lie below zero. The South's change is higher than the Northeast's by 5.0 percentage points (95% CI 2.0 percentage points to 7.9 percentage points), than the Midwest's by 8.4 percentage points (95% CI 5.7 percentage points to 11.1 percentage points) and than the West's by 7.9 percentage points (95% CI 4.3 percentage points to 11.3 percentage points). The intervals come from a bootstrap that resamples whole counties, so they show how much a region's pooled change depends on which counties it holds.

Figure 2

Of the 58 counties with the largest gains in births, 43 are in the South, which holds 40.1% of the named counties

Percent 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)

Loading county values

Change in live births, 2018 to 2024 (%; the key ends at 20 either way)

Fewer birthsMore births

Values outside −20.0 to +20.0 take the end colors.

No data (3,143 counties)

Select a class to show only those places.

Find a county

Hover or tap a county for its value, or search by name. Zoom with the buttons on the map, then drag to move it.

Counties toward the high end of the key gained births and counties toward the low end lost them. Gray hatched counties are not named by WONDER, which pools their births by state, so they have no value; the tooltip says so. Texas and Florida each hold 12 of the 58 counties in the top tenth by change, and no other state holds more than 5. Counties in the Midwest, the Northeast and the West more often lost births than gained them. The key ends at 20 percent in each direction, and 34 counties changed by more and are drawn at its end color.Note: The named counties are the 578 that CDC WONDER natality identifies in every year from 2018 to 2024: counties with 100,000 or more residents in the population vintage WONDER uses, which is earlier than the 2020 Census. WONDER pools the births of every other county in a state into one row, so those counties are not in the named counties.Note: Births are full counts, so no interval is drawn for a county. A small county's count moves more from year to year by chance, so the shading of a county with few births is less stable than the shading of a large one.Note: The tooltip gives the value of a county whose change is beyond the end of the key.Note: Connecticut is shown as its eight legacy counties, the coding of the source. Alaska is drawn. Puerto Rico is not in these data and is not drawn.Source: CDC WONDER natality, births in 2018-2024; full counts of births (no sampling error); county changes are not weighted

The map (Figure 2) shows the same split county by county. The top tenth of counties by change, with gains of 10.2% or more, holds 58 counties, and 43 of them are in the South. The bottom tenth, with declines of 13.6% or more, holds 58 counties, and 13 are in the South. Counted one county at a time, 65.7% of the named counties lost births. The median county lost 3.8%, and from the 5th to the 95th percentile of counties, changes run from a decline of 16.5% to a gain of 19.9%. The pooled decline of 4.6% is larger than the median county's because the pooled figure weights each county by its births and the median counts each county once.

Figure 3

The ten largest gains in births are all in the South, and the ten largest declines are spread across every Census region

Percent 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

Largest gains
Largest declines

Show data

Data for The ten largest gains in births are all in the South, and the ten largest declines are spread across every Census region
births_2018	births_2024	change	county	group
1786	2993	67.58	Kaufman County, TX	Largest gains
1526	2203	44.36	Comal County, TX	Largest gains
2572	3670	42.69	Hays County, TX	Largest gains
6650	9325	40.23	Williamson County, TX	Largest gains
1537	2096	36.37	Parker County, TX	Largest gains
987	1320	33.74	Brunswick County, NC	Largest gains
2214	2914	31.62	Ellis County, TX	Largest gains
2299	2975	29.40	Johnston County, NC	Largest gains
1173	1501	27.96	Bartow County, GA	Largest gains
7355	9220	25.36	Montgomery County, TX	Largest gains
4127	3142	−23.87	St. Louis city, MO	Largest declines
3041	2361	−22.36	Hinds County, MS	Largest declines
1364	1062	−22.14	Humboldt County, CA	Largest declines
3109	2449	−21.23	St. Clair County, IL	Largest declines
1518	1204	−20.69	Monroe County, PA	Largest declines
1506	1195	−20.65	Terrebonne Parish, LA	Largest declines
8697	6930	−20.32	San Francisco County, CA	Largest declines
1326	1072	−19.16	Fayette County, PA	Largest declines
4656	3769	−19.05	Orleans Parish, LA	Largest declines
1246	1010	−18.94	Monroe County, IN	Largest declines

Dots right of the zero line gained births and dots left of it lost them. The lead gain, in Kaufman County, Texas, is 67.6%, and the lead decline, in St. Louis city, Missouri, is 23.9%. Every county listed had at least 987 births in 2018, and small counts move more from year to year, so the order within each group is less stable than the groups.Note: The named counties are the 578 that CDC WONDER natality identifies in every year from 2018 to 2024: counties with 100,000 or more residents in the population vintage WONDER uses, which is earlier than the 2020 Census. WONDER pools the births of every other county in a state into one row, so those counties are not in the named counties.Note: Births are full counts, so no interval is drawn. The data table lists each county's births in 2018 and 2024.Source: CDC WONDER natality, births in 2018-2024; full counts of births (no sampling error); county changes are not weighted

Figure 3 lists the ten counties with the largest gains and the ten with the largest declines. All of the gains are in the South, in Texas, North Carolina and Georgia. The declines are spread across every region and include St. Louis city, Missouri, Hinds County, Mississippi, Humboldt County, California, San Francisco County and Orleans Parish, Louisiana. Every county listed had at least 987 births in 2018. Small counts move more from year to year by chance, so the order within each group is less stable than the groups themselves.

A county's births change when women have fewer children, when the number of women of childbearing age changes, or both, and these data cannot separate them. WONDER places a birth in the mother's county of residence, so a county that adds young families counts their births, and a gain in a fast-growing county may reflect arrivals as much as larger families.

The most deprived counties lost more births than the middle quartiles

To place counties on a deprivation scale, each census tract carries its Area Deprivation Index national rank, which orders neighborhoods by income, education, employment and housing measures from the American Community Survey, with a higher rank meaning more deprived.[3] A tract's rank is the unweighted mean of the ranks of its block groups, and a county's rank is the average of its tracts' ranks, weighted by tract population, the measure used in Chapter 1.1, Birthweight and preterm birth. Quartiles hold equal numbers of the named counties, so the most deprived quartile is relative to large counties and not to the nation.

By 2024 pooled births in the most deprived quartile were 7.3% (95% CI 5.8% to 8.8%) below 2018 (Figure 4). All four quartiles fell to 2020. In 2021 births in the other three quartiles rose and births in the most deprived quartile did not: its pooled change was −0.3% (95% CI −0.8% to 0.1%), an interval that includes zero, and the other quartiles rose by more, by 1.9 percentage points (95% CI 1.0 percentage points to 3.0 percentage points) in the least deprived quartile, 2.5 percentage points (95% CI 1.4 percentage points to 3.6 percentage points) in the second and 1.3 percentage points (95% CI 0.5 percentage points to 2.2 percentage points) in the third. The second and third quartiles lost 2.6% (95% CI −0.6% to 5.3%) and 3.1% (95% CI 1.6% to 4.5%) from 2018 to 2024, and the middle quartiles together lost 2.8% (95% CI 1.1% to 4.5%), so the most deprived quartile lost 4.5 percentage points (95% CI 2.3 percentage points to 6.7 percentage points) more than the middle quartiles. The least deprived quartile lost 5.6% (95% CI 2.8% to 8.2%). It lost 2.7 percentage points (95% CI −0.5 percentage points to 5.9 percentage points) more than the middle quartiles and 1.7 percentage points (95% CI −1.2 percentage points to 5.0 percentage points) less than the most deprived quartile, and both intervals include zero, so the data do not place it with either. A single slope does not summarize the pattern. Regressing each county's change on its deprivation rank gives +0.5 percentage points (95% CI −0.2 percentage points to 1.2 percentage points) per ten ranks when counties are weighted by their births and −0.7 percentage points (95% CI −1.1 percentage points to −0.3 percentage points) when each county counts once, so the sign depends on the weights and only the unweighted interval excludes zero.

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 deprived

Pooled 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

Show data

Data for 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 deprived
conf_high	conf_low	index	n	quartile	year
n/a	n/a	100	1,224,834	Least deprived quartile	2018
99	98.12	98.51	1,206,641	Least deprived quartile	2019
95.57	93.10	94.28	1,154,721	Least deprived quartile	2020
97.84	93.85	95.77	1,173,023	Least deprived quartile	2021
97.77	93.60	95.59	1,170,851	Least deprived quartile	2022
95.57	90.73	93.09	1,140,185	Least deprived quartile	2023
97.19	91.77	94.43	1,156,626	Least deprived quartile	2024
n/a	n/a	100	710,664	Second quartile	2018
99.18	97.97	98.56	700,447	Second quartile	2019
96.58	94.40	95.43	678,194	Second quartile	2020
99.46	95.68	97.54	693,209	Second quartile	2021
100.9	95.90	98.47	699,762	Second quartile	2022
99.12	93.81	96.40	685,072	Second quartile	2023
100.6	94.70	97.44	692,445	Second quartile	2024
n/a	n/a	100	630,186	Third quartile	2018
99.75	98.96	99.31	625,862	Third quartile	2019
96.79	95.72	96.20	606,252	Third quartile	2020
98.35	96.20	97.14	612,146	Third quartile	2021
98.90	96.93	97.88	616,853	Third quartile	2022
97.59	95.05	96.34	607,127	Third quartile	2023
98.42	95.52	96.86	610,399	Third quartile	2024
n/a	n/a	100	455,129	Most deprived quartile	2018
99.76	98.90	99.34	452,106	Most deprived quartile	2019
96.26	95.35	95.80	436,005	Most deprived quartile	2020
96.17	94.80	95.48	434,575	Most deprived quartile	2021
96.14	93.99	95.09	432,773	Most deprived quartile	2022
94.09	91.59	92.86	422,652	Most deprived quartile	2023
94.20	91.23	92.70	421,915	Most deprived quartile	2024

Every line ends below the 2018 level. In 2021 the lines for the other three quartiles rise while the line for the most deprived quartile does not, and the differences between them and the most deprived quartile have intervals above zero. Each line is the pooled births of the counties in a quartile divided by the same counties' 2018 births. Bands show how much a quartile's pooled change depends on which counties it holds.Note: The named counties are the 578 that CDC WONDER natality identifies in every year from 2018 to 2024: counties with 100,000 or more residents in the population vintage WONDER uses, which is earlier than the 2020 Census. WONDER pools the births of every other county in a state into one row, so those counties are not in the named counties.Note: A tract's Area Deprivation Index national rank (1 is least deprived, 100 most) is the unweighted mean of the ranks of its block groups. A county's deprivation rank is the mean of its tracts' ranks weighted by 2019-2023 tract population. Quartiles hold equal numbers of the named counties, so the most deprived quartile is relative to large counties and not to the nation. The index is a measure of neighborhoods, averaged to counties.Note: Intervals are 95% intervals from a bootstrap over counties (replicates and seed in the methods note). Births are full counts, so an interval shows how much a pooled figure depends on which counties are in the group, not sampling error in the counts. The 2018 point is the base and has no interval.Source: CDC WONDER natality, births in 2018-2024; full counts of births; counties grouped by Area Deprivation Index 2023 with ACS 2019-2023 tract population (population-weighted); pooled over counties by births (births-weighted); intervals from a bootstrap over counties

Region and deprivation overlap. Of the counties in the most deprived quartile, 45% are in the South, against 24% of the counties in the least deprived quartile. Figure 5 splits the quartiles by region. The most deprived quartile lost births in every region: 9.3% (95% CI 6.6% to 11.8%) in the Northeast, 9.2% (95% CI 6.3% to 11.6%) in the Midwest, 5.0% (95% CI 2.9% to 7.0%) in the South and 9.3% in the West. The West's most deprived quartile holds only 5 counties, all of which lost births, and a bootstrap over so few counties is mechanical, so no interval is printed for it. In the South the other three quartiles together changed by +1.1% (95% CI −0.9% to 3.4%), which is higher than the change in the South's most deprived quartile by 6.1 percentage points (95% CI 3.2 percentage points to 9.0 percentage points). The South's flat total therefore combines a loss in its most deprived counties with no clear change elsewhere.

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 loss

Pooled 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

−12.0%0.0%+12.0%

Faded: the interval includes 0.0%

Heatmap of four Census regions by four deprivation quartiles, showing the pooled percent change in births from 2018 to 2024. Every cell in the most deprived column is negative. In the South row the three less deprived cells are near zero and faded, while cells for the West, Midwest and Northeast are mostly negative.
Region	Least deprived quartile	Second quartile	Third quartile	Most deprived quartile
Northeast	−4.4%, interval −7.7% to +0.1%, n = 39	−2.0%, interval −3.7% to −0.1%, n = 25	−7.7%, interval −9.9% to −4.4%, n = 24	−9.3%, interval −11.8% to −6.6%, n = 22
Midwest	−5.7%, n = 9	−10.6%, interval −14.1% to −4.3%, n = 26	−6.1%, interval −7.5% to −4.8%, n = 49	−9.2%, interval −11.6% to −6.3%, n = 53
South	+2.1%, interval −4.1% to +8.7%, n = 35	+1.3%, interval −1.6% to +4.6%, n = 69	+0.3%, interval −1.8% to +3.7%, n = 63	−5.0%, interval −7.0% to −2.9%, n = 65
West	−8.4%, interval −11.6% to −4.7%, n = 61	−4.5%, interval −8.0% to +1.8%, n = 25	−9.3%, n = 8	−9.3%, n = 5

Show data

Data for The most deprived quartile of counties lost births in every Census region, and in the South the other three quartiles show no clear loss
births_2018	change	conf_high	conf_low	n_lost_births	n_units	quartile	region
338526	−4.36	0.120	−7.66	24	39	Least deprived quartile	Northeast
76401	−1.99	−0.060	−3.67	16	25	Second quartile	Northeast
96145	−7.73	−4.41	−9.89	20	24	Third quartile	Northeast
48096	−9.26	−6.59	−11.84	21	22	Most deprived quartile	Northeast
52620	−5.68	n/a	n/a	6	9	Least deprived quartile	Midwest
158400	−10.63	−4.34	−14.08	19	26	Second quartile	Midwest
156974	−6.13	−4.79	−7.50	46	49	Third quartile	Midwest
189123	−9.20	−6.26	−11.60	44	53	Most deprived quartile	Midwest
183903	2.15	8.71	−4.06	17	35	Least deprived quartile	South
371925	1.30	4.59	−1.59	25	69	Second quartile	South
335404	0.340	3.71	−1.79	23	63	Third quartile	South
208110	−5.02	−2.92	−6.95	43	65	Most deprived quartile	South
649785	−8.37	−4.74	−11.55	46	61	Least deprived quartile	West
103938	−4.51	1.79	−7.96	17	25	Second quartile	West
41663	−9.28	n/a	n/a	8	8	Third quartile	West
9800	−9.27	n/a	n/a	5	5	Most deprived quartile	West

Cells toward the low end of the key lost births, and faded cells have an interval that includes zero. Cells with fewer than 10 counties show no interval. The cells in the most deprived column that show an interval lie below zero, and in the South row the three less deprived cells are faded. The tooltip gives the number of counties in each cell and the data table the number that lost births.Note: The named counties are the 578 that CDC WONDER natality identifies in every year from 2018 to 2024: counties with 100,000 or more residents in the population vintage WONDER uses, which is earlier than the 2020 Census. WONDER pools the births of every other county in a state into one row, so those counties are not in the named counties.Note: A tract's Area Deprivation Index national rank (1 is least deprived, 100 most) is the unweighted mean of the ranks of its block groups. A county's deprivation rank is the mean of its tracts' ranks weighted by 2019-2023 tract population. Quartiles hold equal numbers of the named counties, so the most deprived quartile is relative to large counties and not to the nation. The index is a measure of neighborhoods, averaged to counties.Note: Intervals are 95% intervals from a bootstrap over counties (replicates and seed in the methods note). Births are full counts, so an interval shows how much a pooled figure depends on which counties are in the group, not sampling error in the counts. A cell with fewer than 10 counties shows no interval; in the West, the most deprived and third quartiles hold few counties, and the least deprived quartile of the Midwest holds fewer than 10, so those cells are thin.Note: The Census South region is 16 states and DC; the Northeast, Midwest and West follow the Census Bureau's regions.Source: CDC WONDER natality, births in 2018-2024; full counts of births; counties grouped by Area Deprivation Index 2023 with ACS 2019-2023 tract population (population-weighted); pooled over counties by births (births-weighted); intervals from a bootstrap over counties

These are patterns across counties and describe groups of births, not the mothers in any one county. The index measures neighborhoods averaged to counties, and it understates deprivation in high-cost cities, so some counties in the least deprived quartile hold neighborhoods that are more deprived than their rank suggests.

WONDER splits each county's births by the mother's age in nine bands. Six of them, the bands from 15 to 19 through 40 to 44, are published for nearly every county and year. Of the 24,276 county-year cells for those bands, WONDER withholds 11. Each holds fewer than 10 births, so together they hold at most 99 births, against 20.4 million in published cells. The other three bands, mothers under 15 and mothers 45 and over, are mostly withheld, with 6,594 of 12,138 cells missing. The published cells hold 0.26% of births and the withheld ones at most 0.29%, so the chapter leaves all three bands out and compares mothers aged 15 to 44. A withheld cell is missing, never zero, and nothing is recovered from county totals.

From 2018 to 2024, births fell by 24.6% (95% CI 22.7% to 26.5%) among mothers aged 15 to 19, by 16.6% (95% CI 15.0% to 18.3%) among mothers aged 20 to 24 and by 11.2% (95% CI 9.6% to 12.9%) among mothers aged 25 to 29. Births to mothers aged 30 to 34 changed by +1.0% (95% CI −0.6% to 2.6%), an interval that includes zero. Births rose by 9.2% (95% CI 7.3% to 11.0%) among mothers aged 35 to 39 and by 19.5% (95% CI 17.0% to 22.3%) among mothers aged 40 to 44 (Figure 6). As shares of births to mothers aged 15 to 44, mothers aged 15 to 24 went from 21.8% (95% CI 21.0% to 22.7%) to 18.7% (95% CI 18.0% to 19.5%), a fall of 3.1 percentage points (95% CI 2.9 percentage points to 3.3 percentage points), and mothers aged 35 to 44 went from 19.7% (95% CI 18.9% to 20.5%) to 22.9% (95% CI 22.1% to 23.8%), a rise of 3.2 percentage points (95% CI 3.1 percentage points to 3.4 percentage points). The shift continues a rise in the mean age of mothers that the National Center for Health Statistics documented for every birth order from 2000 to 2014.[4]

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 2024

Pooled 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

Mother's age (years)

Show data

Data for 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 2024
age	births_2018	births_2024	change	conf_high	conf_low	n_units
15 to 19	129757	97772	−24.65	−22.72	−26.53	577
20 to 24	527582	439765	−16.65	−14.98	−18.31	578
25 to 29	848726	753795	−11.19	−9.57	−12.87	578
30 to 34	910977	920282	1.02	2.65	−0.620	578
35 to 39	490705	535630	9.16	11.05	7.32	578
40 to 44	103030	123085	19.47	22.34	17.02	578

Bars for the three youngest bands lie below zero and bars for the two oldest lie above it, so the bars climb with age. The bar for mothers aged 30 to 34 is near zero and its interval includes zero. Each bar compares a band's births in 2024 with its births in 2018, pooled over the counties that publish the band in both years.Note: The named counties are the 578 that CDC WONDER natality identifies in every year from 2018 to 2024: counties with 100,000 or more residents in the population vintage WONDER uses, which is earlier than the 2020 Census. WONDER pools the births of every other county in a state into one row, so those counties are not in the named counties.Note: Intervals are 95% intervals from a bootstrap over counties (replicates and seed in the methods note). Births are full counts, so an interval shows how much a pooled figure depends on which counties are in the group, not sampling error in the counts.Note: WONDER splits births into nine age bands. Mothers under 15 and mothers 45 and over are left out because WONDER withholds most of those cells; the methods note gives the counts. A withheld cell is missing, never zero, and a county that withholds a band in 2018 or 2024 is left out of that band's bar; the data table gives the number of counties in each bar.Source: CDC WONDER natality, births in 2018-2024; full counts of births by mother's age; changes pooled over counties; intervals from a bootstrap over counties

These are births and not birth rates. A fall in births to mothers aged 15 to 19 can mean fewer births per teenager or fewer teenagers in the county, and the files behind this book have no county counts of women by age. A different measure of teen births, for women who grew up in each census tract, is in Chapter 3.4, Teen births.

The age mix differs more across counties than it changed

In 2018 the share of births to mothers aged 15 to 24 was 17.0% (95% CI 15.6% to 18.3%) in the least deprived quartile of counties and 30.9% (95% CI 29.9% to 32.1%) in the most deprived, a gap of 14.0 percentage points (95% CI 12.3 percentage points to 15.8 percentage points). In 2024 the shares were 14.5% (95% CI 13.4% to 15.5%) and 26.9% (95% CI 25.8% to 28.0%), a gap of 12.4 percentage points (95% CI 11.0 percentage points to 14.0 percentage points). For mothers aged 35 to 44 the 2018 shares were 24.3% (95% CI 23.1% to 25.5%) in the least deprived quartile and 13.0% (95% CI 12.5% to 13.5%) in the most deprived, a gap of 11.3 percentage points (95% CI 10.0 percentage points to 12.5 percentage points), and in 2024 they were 27.8% (95% CI 26.4% to 29.2%) and 15.8% (95% CI 15.1% to 16.5%), a gap of 12.0 percentage points (95% CI 10.5 percentage points to 13.5 percentage points) (Figure 7).

Every quartile moved in the same direction. The share of births to mothers aged 15 to 24 fell by 2.5 percentage points (95% CI 1.9 percentage points to 3.0 percentage points) in the least deprived quartile and by 4.0 percentage points (95% CI 3.7 percentage points to 4.4 percentage points) in the most deprived, and the share to mothers aged 35 to 44 rose by 3.5 percentage points (95% CI 3.1 percentage points to 3.9 percentage points) and by 2.8 percentage points (95% CI 2.5 percentage points to 3.1 percentage points). The share of young mothers fell by 1.5 percentage points (95% CI 0.9 percentage points to 2.2 percentage points) more in the most deprived quartile, and the share of older mothers rose by 0.7 percentage points (95% CI 0.3 percentage points to 1.2 percentage points) more in the least deprived quartile, so the shifts differ in size. Each is much smaller than the gap between quartiles.

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 changes

Share 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

2018
2024

Show data

Data for 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 changes
group_label	hi1	hi2	lo1	lo2	measure	n_units	y2018	y2024
All named counties	22.67	19.48	20.99	17.98	Mothers aged 15 to 24	578	21.83	18.73
Least deprived quartile	18.27	15.51	15.57	13.42	Mothers aged 15 to 24	144	16.96	14.46
Second quartile	22.09	18.75	20.07	16.95	Mothers aged 15 to 24	145	21.01	17.80
Third quartile	26.55	23.11	24.72	21.20	Mothers aged 15 to 24	144	25.63	22.18
Most deprived quartile	32.08	28.03	29.93	25.83	Mothers aged 15 to 24	145	30.94	26.91
All named counties	20.51	23.80	18.92	22.08	Mothers aged 35 to 44	578	19.72	22.95
Least deprived quartile	25.46	29.18	23.05	26.40	Mothers aged 35 to 44	144	24.32	27.84
Second quartile	20.45	23.86	18.51	21.75	Mothers aged 35 to 44	145	19.53	22.86
Third quartile	16.41	19.40	15.17	18.01	Mothers aged 35 to 44	144	15.87	18.76
Most deprived quartile	13.50	16.52	12.50	15.07	Mothers aged 35 to 44	145	13.01	15.79

In the first block the 2024 dot lies left of the 2018 dot in every row, and in the second block it lies right. Rows move steadily with deprivation, and the distance between the top and bottom quartile rows is wider than the distance any dot moved. Shares are pooled over counties and use births in published age cells.Note: The named counties are the 578 that CDC WONDER natality identifies in every year from 2018 to 2024: counties with 100,000 or more residents in the population vintage WONDER uses, which is earlier than the 2020 Census. WONDER pools the births of every other county in a state into one row, so those counties are not in the named counties.Note: A tract's Area Deprivation Index national rank (1 is least deprived, 100 most) is the unweighted mean of the ranks of its block groups. A county's deprivation rank is the mean of its tracts' ranks weighted by 2019-2023 tract population. Quartiles hold equal numbers of the named counties, so the most deprived quartile is relative to large counties and not to the nation. The index is a measure of neighborhoods, averaged to counties.Note: Intervals are 95% intervals from a bootstrap over counties (replicates and seed in the methods note). Births are full counts, so an interval shows how much a pooled figure depends on which counties are in the group, not sampling error in the counts. Shares are of births to mothers aged 15 to 44; mothers under 15 and mothers 45 and over are left out, and withheld cells are missing.Source: CDC WONDER natality, births in 2018-2024; full counts of births by mother's age; counties grouped by Area Deprivation Index 2023 with ACS 2019-2023 tract population (population-weighted); pooled over counties by births (births-weighted); intervals from a bootstrap over counties

Counties that lost the most births lost them among younger mothers

Sorting counties by the change in their total births shows where in the age range the loss fell (Figure 8). The 144 counties in the quarter with the largest declines, falls of 8.8% or more, lost 13.5% of their births in all. Their births fell by 32.9% among mothers aged 15 to 19, by 25.1% among mothers aged 20 to 24, by 21.1% among mothers aged 25 to 29 and by 8.8% among mothers aged 30 to 34. Births to mothers aged 35 to 39 changed by −0.1%, and births to mothers aged 40 to 44 rose by 9.6%. The 145 counties in the quarter with the largest gains, gains of 2.6% or more, added 11.2% in all. Births in those counties fell by 13.0% among mothers aged 15 to 19 and by 4.0% among mothers aged 20 to 24, and rose in every older band, from 5.8% among mothers aged 25 to 29 to 39.3% among mothers aged 40 to 44.

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 25

Pooled 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

Show data

Data for 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 25
age	age_position	change	group	n_units
15 to 19	1	−32.87	Largest declines	144
20 to 24	2	−25.09	Largest declines	144
25 to 29	3	−21.11	Largest declines	144
30 to 34	4	−8.77	Largest declines	144
35 to 39	5	−0.060	Largest declines	144
40 to 44	6	9.55	Largest declines	144
15 to 19	1	−25.21	Smaller declines	145
20 to 24	2	−17.85	Smaller declines	145
25 to 29	3	−13.39	Smaller declines	145
30 to 34	4	−0.670	Smaller declines	145
35 to 39	5	9.07	Smaller declines	145
40 to 44	6	20.34	Smaller declines	145
15 to 19	1	−20.90	Little change	144
20 to 24	2	−12.76	Little change	144
25 to 29	3	−7.43	Little change	144
30 to 34	4	4.50	Little change	144
35 to 39	5	13.88	Little change	144
40 to 44	6	23.02	Little change	144
15 to 19	1	−12.97	Largest gains	144
20 to 24	2	−4.05	Largest gains	145
25 to 29	3	5.80	Largest gains	145
30 to 34	4	19.11	Largest gains	145
35 to 39	5	24.75	Largest gains	145
40 to 44	6	39.26	Largest gains	145

All four lines rise with mother's age. The line for the largest declines stays below zero until the oldest band, and the line for the largest gains is above zero from the third band. Groups are defined by the change in total births, so the figure splits each group's change by age and tests nothing.Note: The named counties are the 578 that CDC WONDER natality identifies in every year from 2018 to 2024: counties with 100,000 or more residents in the population vintage WONDER uses, which is earlier than the 2020 Census. WONDER pools the births of every other county in a state into one row, so those counties are not in the named counties.Note: Counties are sorted into four groups of equal size by their percent change in total births from 2018 to 2024: the largest-decline group has falls of 8.8% or more, and the largest-gain group has gains of 2.6% or more. Births are full counts, so no interval is drawn; the groups are formed on the outcome, so an interval would not describe a draw of counties.Note: A county that withholds a band in 2018 or 2024 is left out of that band's point.Source: CDC WONDER natality, births in 2018-2024; full counts of births by mother's age; changes pooled over counties in each group

The groups are formed on the change in total births, so the figure splits each group's change by age and does not test an explanation. A separate question is whether a county's age mix predicts its change. If every age band in a county changed at the all-county rate, the county's 2018 mix would imply a change in births to mothers aged 15 to 44 between a fall of 8.9% and a fall of 1.3% at the 5th and 95th percentiles of counties. The observed changes run over a much wider range, from a fall of 16.6% to a gain of 19.8%. The implied and observed changes have a correlation of −0.16 (95% CI −0.26 to −0.06) across 577 counties when counties are weighted by their births and −0.03 (95% CI −0.11 to 0.04) when each counts once. The one county that withholds an age cell is left out. A county's 2018 age mix therefore does not account for which counties lost births, and the weighted correlation is small and negative, so counties whose mix implied larger falls lost slightly less.

What these data cannot show

The chapter reports counts and shares of births and no rates. A birth rate needs the number of women of each age as its denominator, and the files staged for this book hold the total population of counties and tracts but not women by age. A fall in births to mothers aged 20 to 24 can mean fewer births per woman, fewer women in that age group, or both, and so can a gain. County population estimates by age and sex from the Census Bureau would supply the denominator for age-specific rates. Births are counted in the mother's county of residence, so the map is not a map of fertility.

County results describe the 578 counties that WONDER identifies, those with 100,000 or more residents in its population vintage. They hold 79.4% of births in 2024, and the pooled rows lost fewer births, although those rows include counties that now exceed the line, so the named counties are not a sample of the country. WONDER's county files used here have no cut by the mother's race or Hispanic origin, so the chapter cannot say whether the shift in mothers' ages differs by group.

The deprivation comparison is descriptive. The Area Deprivation Index describes neighborhoods in 2019 to 2023 and is averaged to counties, and region and deprivation overlap. The comparison of quartiles says nothing about why births fell in any county. It is an ecological pattern, and it need not hold for the people inside the counties. The comparison of 2018 with 2024 uses the endpoint years only, and a county with few births moves from year to year by chance, so a county's direction of change is better established than its rank among the named counties.

Data sources

CDC WONDER natalityCDC WONDER natality, county totals and county by mother's age, births in 2018 to 2024 (consolidated pulls); 2024 is finalYears: 2018-2024 · Weights: births in each county (pooled ratios of sums); changes and shares pooled over counties · License: Public domain (NCHS, CDC); WONDER data-use restrictions apply
Area Deprivation IndexNeighborhood Atlas Area Deprivation Index 2023 (v4.0.1), tract national rank, averaged to counties with 2019-2023 tract populationYears: 2023 release (version 4.0.1; built on ACS 2019-2023) · Weights: 2019-2023 tract population · License: Free for non-commercial use; cite the Neighborhood Atlas and Kind and Buckingham

All data sources

Methods

This chapter compares births from 2018 to 2024 across the 578 counties that CDC WONDER names individually in every year, a set chosen by population size in a vintage earlier than the 2020 Census and not by outcome, and across groups of those counties by deprivation quartile and region. The figures are counts and shares of births, not birth rates, because no file used here holds women by age for counties, and births by mother's age use six of nine bands because most cells of the youngest and oldest bands are withheld. Pooled changes weight each county by its births, and counties that WONDER pools into an Unidentified Counties row have no county value. Births are full counts, so the intervals show dependence on which counties are in a group and not sampling error.

Which births and counties are used

Births are counts from CDC WONDER natality for 2018 to 2024 (2024 is final), by county of the mother's residence. The 578 named counties are the counties that WONDER identifies in every year and that have births in every year: counties with 100,000 or more residents in the population vintage WONDER uses, which is earlier than the 2020 Census. By 2020 Census population 27 counties outside Connecticut that have 100,000 or more residents are still pooled, and one named county is below it.

WONDER pools every other county in a state into one Unidentified Counties row (49 rows), which is used only for the comparison of the named counties with the rest of the country. WONDER lists two further identifiers in every year with no births (Cape May County NJ, Portsmouth city VA), which are left out. The panel is defined by size, not by outcome, and every named county appears in all seven years. County totals have no withheld cell.

Figures explained here: Figure 1 and Figure 2

How births by mother's age and withheld cells are handled

Births by mother's age come in nine bands. WONDER withholds cells of 1 to 9 births. A withheld cell is missing: it leaves the numerator and the denominator, which is the births in the published cells, and nothing is derived from a county total minus the published cells.

The six bands from 15 to 19 through 40 to 44 have 11 withheld cells of 24,276, which could hold at most 99 births. The under-15 band and the 45-and-over bands are left out because most of their cells are withheld (6,594 of 12,138); the published tail cells hold 0.26% of births and the withheld ones at most 0.29%.

A share is the births to mothers in an age range over births in the published cells for mothers aged 15 to 44, pooled over counties. A change in a band compares the counties that publish the band in both 2018 and 2024. No rate is computed: no file used here holds women by age for counties.

The shift-share check applies the all-county change of each age band to each county's 2018 age mix and correlates the implied change with the observed change in births to mothers aged 15 to 44.

Figures explained here: Figure 6, Figure 7 and Figure 8

How counties are ranked, grouped and weighted

A tract's Area Deprivation Index national rank is the unweighted mean of the ranks of its block groups. A county's deprivation rank is the mean of its tracts' ranks weighted by 2019-2023 tract population, with Connecticut tracts assigned to the eight legacy counties; quartiles hold equal numbers of the named counties. Regions are the four Census Bureau regions (the South has 16 states and DC).

Pooled changes, shares and differences are ratios of sums over counties, so they weight each county by its births.

The map draws every county of the book's county map; counties that WONDER does not name have no value.

Figures explained here: Figure 4, Figure 5 and Figure 2

What the intervals do and do not show

Births are full counts, so these intervals show dependence on which counties are in a group and not sampling error. A region-by-quartile cell with fewer than 10 counties shows no interval, because a bootstrap over so few counties is mechanical. The groups of counties formed by the change in total births are defined on the outcome and carry no interval.

How the bootstrap intervals are computed

Pooled changes, shares and differences carry 95% percentile intervals from a bootstrap that resamples whole counties (2,000 replicates, seed 12345), with the same draws for every statistic so that a difference has its own interval. Correlations and slopes use a county-cluster bootstrap.

References

Osterman, Michelle J. K.; Hamilton, Brady E.; Martin, Joyce A.; Driscoll, Anne K.; Valenzuela, Claudia P. (2026). Births: Final Data for 2024. National Vital Statistics Reports 75(2). doi:10.15620/cdc/252440
Kearney, Melissa S.; Levine, Phillip B.; Pardue, Luke (2022). The Puzzle of Falling US Birth Rates since the Great Recession. Journal of Economic Perspectives 36(1): 151-176. doi:10.1257/jep.36.1.151
Kind, Amy J. H.; Buckingham, William R. (2018). Making Neighborhood-Disadvantage Metrics Accessible: The Neighborhood Atlas. New England Journal of Medicine 378(26): 2456-2458. doi:10.1056/NEJMp1802313
Mathews, T. J.; Hamilton, Brady E. (2016). Mean Age of Mothers is on the Rise: United States, 2000-2014. NCHS Data Brief No. 232. www.cdc.gov/nchs/products/databriefs/db232.htm

How to cite

@misc{singh2026wherebirthsarefalling,
  author = {Singh, Vishal},
  title = {Where births are falling},
  year = {2026},
  url = {https://vishalsingh.org/zipcode/where-births-are-falling},
  note = {In ZIP Code Destiny. Published 9 October 2026.}
}

Births have not returned to their 2018 level

Births held up in the South and fell elsewhere

The most deprived counties lost more births than the middle quartiles

A larger share of births were to older mothers in 2024

The age mix differs more across counties than it changed

Counties that lost the most births lost them among younger mothers

What these data cannot show

Data sources

Methods

Which births and counties are used

How births by mother's age and withheld cells are handled

How counties are ranked, grouped and weighted

What the intervals do and do not show

How the bootstrap intervals are computed

References

How to cite