Data Study · 4 min read
Which Large US Metros Grew? Population and Income Change Between Two Census Surveys
Published October 10, 2026 by the Demografics team
Growth is one of the first things expansion teams ask about, and one of the easiest to get wrong. This study compares two non-overlapping American Community Survey 5-year samples, 2013–2017 and 2018–2022, for the largest US metropolitan areas, keeps each metro's boundaries fixed so that redrawn borders are not mistaken for growth, and adjusts income for inflation so that real gains are not confused with rising prices.
Population grew fastest in Austin–Round Rock, TX (+14.8%), Orlando–Kissimmee, FL (+12.1%) and Raleigh–Cary, NC (+11.5%). 2 metros lost population: Los Angeles–Long Beach, CA (-1.1%) and Milwaukee–Waukesha, WI (-0.4%). After adjusting for inflation, median household income grew most in San Jose–Sunnyvale, CA (+20.3%), San Francisco–Oakland, CA (+17.5%) and Seattle–Tacoma, WA (+16.2%).
How we measured
Each ACS 5-year release reports income in dollars of its final year, so the 2013–2017 medians are in 2017 dollars and the 2018–2022 medians in 2022 dollars. We converted the earlier figures to 2022 dollars with the Consumer Price Index (CPI-U, US city average), which rose 19.4% between the 2017 and 2022 annual averages. The Census Bureau redrew several metro boundaries between the two surveys (Birmingham, AL, for example, lost Walker County), so comparing the published metro totals would mix real change with boundary changes. Instead, we took each metro's counties as defined for 2018–2022 and added up the same counties in both surveys. Median household income for each period is the household-weighted average of those counties' medians, the same approximation used throughout Demografics. Hartford–East Hartford, CT is left out because Connecticut replaced its counties with planning regions in 2022, so the two surveys do not share geography there.
| Metro area | Population change | Income change (nominal) | Income change (inflation-adjusted) |
|---|---|---|---|
| Austin–Round Rock, TX | +14.8% | +33.6% | +11.9% |
| Orlando–Kissimmee, FL | +12.1% | +36.7% | +14.5% |
| Raleigh–Cary, NC | +11.5% | +32.5% | +11.0% |
| Jacksonville, FL | +11.4% | +30.6% | +9.4% |
| Nashville–Davidson, TN | +10.2% | +31.8% | +10.4% |
| Dallas–Fort Worth, TX | +9.0% | +30.4% | +9.2% |
| Charlotte–Concord, NC-SC | +8.8% | +32.1% | +10.7% |
| San Antonio–New Braunfels, TX | +8.1% | +25.9% | +5.4% |
| Houston–The Woodlands, TX | +7.6% | +23.6% | +3.5% |
| Las Vegas–Henderson, NV | +7.3% | +27.4% | +6.7% |
| Tampa–St. Petersburg, FL | +7.3% | +32.8% | +11.3% |
| Salt Lake City, UT | +7.2% | +33.1% | +11.5% |
| Seattle–Tacoma, WA | +7.1% | +38.7% | +16.2% |
| Atlanta–Sandy Springs, GA | +6.9% | +34.2% | +12.4% |
| Phoenix–Mesa, AZ | +6.6% | +37.8% | +15.4% |
| Indianapolis–Carmel, IN | +6.1% | +30.4% | +9.2% |
| Denver–Aurora, CO | +5.7% | +35.3% | +13.4% |
| Columbus, OH | +5.6% | +27.1% | +6.5% |
| Sacramento–Roseville, CA | +5.6% | +38.2% | +15.7% |
| Oklahoma City, OK | +5.6% | +23.2% | +3.2% |
| Richmond, VA | +5.5% | +27.1% | +6.5% |
| Portland–Vancouver, OR-WA | +5.2% | +35.6% | +13.6% |
| Kansas City, MO-KS | +4.9% | +28.1% | +7.3% |
| Minneapolis–St. Paul, MN-WI | +4.8% | +28.0% | +7.2% |
| Washington–Arlington, DC-VA-MD-WV | +4.0% | +25.1% | +4.8% |
| Providence–Warwick, RI-MA | +3.6% | +31.4% | +10.0% |
| Cincinnati, OH-KY-IN | +3.4% | +28.6% | +7.7% |
| Birmingham–Hoover, AL | +3.3% | +28.4% | +7.5% |
| Riverside–San Bernardino, CA | +3.0% | +37.4% | +15.1% |
| Louisville/Jefferson County, KY-IN | +3.0% | +27.6% | +6.9% |
| Boston–Cambridge, MA-NH | +2.9% | +30.6% | +9.4% |
| Philadelphia–Camden, PA-NJ-DE-MD | +2.8% | +28.0% | +7.2% |
| Virginia Beach–Norfolk, VA-NC | +2.5% | +25.6% | +5.2% |
| Buffalo–Cheektowaga, NY | +2.4% | +26.2% | +5.7% |
| New York–Newark, NY-NJ-PA | +2.0% | +29.5% | +8.5% |
| Miami–Fort Lauderdale, FL | +1.7% | +33.3% | +11.6% |
| Baltimore–Columbia, MD | +1.7% | +23.9% | +3.8% |
| Detroit–Warren, MI | +1.6% | +28.0% | +7.2% |
| San Francisco–Oakland, CA | +1.1% | +40.2% | +17.5% |
| Cleveland–Elyria, OH | +0.8% | +27.0% | +6.3% |
| Pittsburgh, PA | +0.7% | +27.2% | +6.5% |
| San Jose–Sunnyvale, CA | +0.6% | +43.6% | +20.3% |
| St. Louis, MO-IL | +0.3% | +28.2% | +7.4% |
| New Orleans–Metairie, LA | +0.3% | +24.8% | +4.5% |
| Chicago–Naperville, IL-IN-WI | +0.2% | +29.1% | +8.1% |
| San Diego–Chula Vista, CA | +0.2% | +37.4% | +15.1% |
| Memphis, TN-MS-AR | +0.0% | +25.5% | +5.1% |
| Milwaukee–Waukesha, WI | -0.4% | +25.8% | +5.4% |
| Los Angeles–Long Beach, CA | -1.1% | +35.9% | +13.9% |
Patterns in the numbers
The median metro in this group grew its population by +4.0% and its inflation-adjusted median household income by +8.5%. Real median income rose in all 49 metros. Metro size says little about growth: the correlation between (log) population and population growth is -0.14, essentially no relationship.
16 metros grew faster than the median on both measures, population and real income: Dallas–Fort Worth, TX, Atlanta–Sandy Springs, GA, Phoenix–Mesa, AZ, Seattle–Tacoma, WA, Tampa–St. Petersburg, FL, Denver–Aurora, CO, Orlando–Kissimmee, FL, Charlotte–Concord, NC-SC, Portland–Vancouver, OR-WA, Sacramento–Roseville, CA, Austin–Round Rock, TX, Indianapolis–Carmel, IN, Nashville–Davidson, TN, Jacksonville, FL, Raleigh–Cary, NC and Salt Lake City, UT.
Reading growth numbers carefully
- Five-year survey averages smooth out short-term swings; they show direction over several years, not last year's change.
- Check how a metro is defined before comparing published totals across years: boundary changes can turn growth into apparent decline, as they would have for New York and Birmingham here.
- Nominal income gains can look impressive while real incomes stand still. Always check the inflation-adjusted column.
- Metro-level growth can hide very different trends inside the metro: new suburbs can grow while older neighborhoods shrink. Check growth for the specific trade area too.
Sources
- U.S. Census Bureau, American Community Survey 5-year estimates, 2018–2022 (tables B01001, B01002, B01003, B11001, B19001, B19013, B25003, C24050).
- U.S. Census Bureau, TIGERweb 2020 census tract boundaries (used to find the tracts inside each trade radius).
- U.S. Bureau of Labor Statistics, Consumer Price Index for All Urban Consumers (CPI-U), US city average, annual averages 2017 and 2022.
More data studies
- Who Lives Within 3 Miles of Downtown? Census Profiles of 25 Major US Cities
- 1, 3 or 5 Miles? How a Trade Radius Changes the Picture in 25 US Downtowns
- Is Downtown Richer or Poorer Than the Metro? Income in 25 US Cities Compared
- Where Young Adults Live: The 18–34 Share in the 50 Largest US Metros and 25 Downtowns