The CDC's survey numbers for states and metro areas don't go down to the city. For cities it publishes something different: PLACES, a set of estimates for local areas that its national health survey can't measure one by one. Two of its measures matter for a training week: the share of adults with no leisure-time physical activity, and the share who usually sleep less than seven hours in a 24-hour period.1
The table is the 27 cities that have a page on this site, with each estimate's 95% interval and the survey year behind it. It is not a ranking of U.S. cities and not a sample of them: it is simply the cities with a page here.
Estimates from a model, not counts
Read this before the table. PLACES figures are model-based, age-adjusted estimates, not direct survey counts. The CDC doesn't ask enough people in each city to measure a city directly, so PLACES fills the gap with a statistical model that estimates each city's share from the national survey's answers and the city's population. Age-adjusted means every city is put on the same age mix, so cities with older or younger populations can be read on one scale. The crude rate, the share as it actually stands, can differ.
That is also why this table must not be set next to the state table or the metro table. Those print the CDC's direct survey estimates for whole states and metro areas, by a different method and from different years (the metro one, SMART, also asks a differently worded question and is not age-adjusted). A city's estimate beside its state's or its metro's figure says nothing about whether the city moves more or less than the area around it.
The table
The range in brackets is the CDC's 95% confidence interval: two cities whose ranges overlap are not meaningfully different. The year is the survey year each estimate is built on, from the CDC's 2025 PLACES release. Each city links to its page on this site.
| City | No leisure-time physical activity, age-adjusted (95% CI) | Year | Short sleep, under 7 hours, age-adjusted (95% CI) | Year |
|---|---|---|---|---|
| Anaheim, CA | 29.2% (26.2–32.3) | 2023 | 37.2% (33.4–41.0) | 2022 |
| Aurora, CO | 21.9% (19.6–24.4) | 2023 | 34.6% (31.2–37.9) | 2022 |
| Boca Raton, FL | 18.4% (15.8–21.3) | 2023 | 34.1% (29.2–39.1) | 2022 |
| Cape Coral, FL | 23.5% (20.5–26.9) | 2023 | 35.9% (31.2–40.9) | 2022 |
| Centennial, CO | 13.0% (11.1–14.9) | 2023 | 29.4% (26.1–32.8) | 2022 |
| Chandler, AZ | 17.1% (15.4–19.0) | 2023 | 34.6% (31.3–38.1) | 2022 |
| Columbia, MD | 16.5% (14.3–18.9) | 2023 | 38.5% (34.4–42.8) | 2022 |
| Concord, NC | 21.9% (18.0–25.8) | 2023 | 35.0% (28.7–41.7) | 2022 |
| Elgin, IL | 26.5% (23.5–30.0) | 2023 | 37.0% (32.6–42.0) | 2022 |
| Fort Lauderdale, FL | 23.8% (20.6–27.0) | 2023 | 39.4% (34.8–44.3) | 2022 |
| Gainesville, FL | 24.0% (20.8–27.6) | 2023 | 38.6% (33.9–43.5) | 2022 |
| Hollywood, FL | 26.1% (22.7–29.6) | 2023 | 39.5% (34.9–44.5) | 2022 |
| Lakeland, FL | 27.0% (23.6–30.4) | 2023 | 43.6% (38.9–48.6) | 2022 |
| Long Beach, CA | 25.8% (23.6–28.0) | 2023 | 37.3% (34.4–40.1) | 2022 |
| Mesa, AZ | 20.3% (18.2–22.4) | 2023 | 36.1% (32.8–39.7) | 2022 |
| Miami, FL | 32.8% (29.2–36.4) | 2023 | 38.3% (34.0–42.9) | 2022 |
| Naperville, IL | 15.7% (13.7–17.8) | 2023 | 34.2% (30.2–38.1) | 2022 |
| New Braunfels, TX | 22.5% (19.8–25.4) | 2023 | 36.0% (31.7–40.6) | 2022 |
| Ontario, CA | 28.1% (24.9–31.4) | 2023 | 38.2% (34.1–42.8) | 2022 |
| Pasadena, TX | 32.8% (29.5–36.4) | 2023 | 39.9% (36.4–43.6) | 2022 |
| Round Rock, TX | 24.1% (20.6–27.6) | 2023 | 34.4% (30.2–38.8) | 2022 |
| San Bernardino, CA | 33.0% (29.5–36.5) | 2023 | 40.4% (36.2–45.1) | 2022 |
| Sandy Springs, GA | 15.6% (13.6–17.9) | 2023 | 35.8% (32.0–39.6) | 2022 |
| St. Paul, MN | 22.6% (20.4–25.0) | 2023 | 30.9% (28.1–33.5) | 2022 |
| Tallahassee, FL | 24.8% (21.7–28.2) | 2023 | 41.2% (36.3–46.1) | 2022 |
| The Woodlands, TX | 17.0% (14.4–19.7) | 2023 | 35.0% (31.3–38.7) | 2022 |
| West Palm Beach, FL | 26.5% (23.2–30.0) | 2023 | 39.6% (34.4–44.8) | 2022 |
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What stands out
- The ends are apart; the order in between isn't. Centennial, Colorado (13.0%, range 11.1 to 14.9) and San Bernardino, California (33.0%, 29.5 to 36.5) are far apart, so that gap is real. But each end overlaps its neighbors: Centennial's range overlaps Sandy Springs' (15.6%) and Naperville's (15.7%), and San Bernardino's overlaps Pasadena, Texas and Miami (both 32.8%). No single city is clearly the least or the most active.
- Cities in the same metro can differ a lot. The Woodlands (17.0%, 14.4 to 19.7) and Pasadena, Texas (32.8%, 29.5 to 36.4) are both in the Houston–Pasadena–The Woodlands metro area, and their ranges don't come close. The same holds for Centennial and Aurora (21.9%, 19.6 to 24.4) in the Denver metro, and for Naperville (15.7%, 13.7 to 17.8) and Elgin (26.5%, 23.5 to 30.0) in the Chicago metro.
- Short sleep is common in every city here. The estimates run from 29.4% (Centennial) to 43.6% (Lakeland, Florida): about three in ten adults at one end, more than four in ten at the other. The ranges are wide (Concord, North Carolina's runs from 28.7 to 41.7), but the two ends do clear each other: Centennial's range tops out at 32.8, Lakeland's starts at 38.9.
- Moving and sleeping don't line up neatly. St. Paul sits near the middle for no activity (22.6%) but near the low end for short sleep (30.9%); Columbia, Maryland is near the low end for no activity (16.5%) but past the middle for short sleep (38.5%).
How to read your own city's row
Find your row and read the range, not just the number. If your city's range overlaps another's, the two are the same as far as this model can tell. Then read it as a backdrop, not a verdict: it is an estimate about adults around you, and it says nothing about what you do or can do.
The activity figure counts adults who did no physical activity or exercise outside their job in the past month: no walks for exercise, no gym, no sport. At the middle of the table, Fort Lauderdale's 23.8%, that's about one adult in four. If you train two or three times a week, your week already looks different from a big part of your city's.
The sleep figure is the CDC's short-sleep measure: adults who say they usually get less than seven hours in a 24-hour period. It describes nights, not training. Where it matters for a training plan is the schedule: a week with short nights in it needs sessions that still happen on the mornings after them.
What it changes in a training week
- Have a short-night version of the session. If short nights are part of your week (an early shift, a late class, a long drive), decide in advance what the session looks like on the day after one, so the day doesn't decide for you: the main lifts, fewer extra sets, done in about half an hour. A 30-minute session is that version.
- Put the hardest session after your usual long night. If one night of your week is reliably short, don't put your biggest session the morning after it. Move it to the day after the night you usually get the most sleep.
- Don't trade the night for the session. If a 5 a.m. session is what cuts your night short, a lunchtime or after-work slot may be the one to keep. The best time is the one you can repeat.
- If you're starting from nothing, start small. Two or three sessions a week built around the big movements is the whole first step. How often to train covers the week; the beginner's guide to lifting covers the first month.
Related tables: rain by metro and commute times by metro for 40 metro areas, and, from different CDC products to read on their own, how active your state is and how active your metro is.
Where the numbers come from
Both columns come from the CDC's PLACES: Local Data for Better Health, Place Data, 2025 release (data.cdc.gov dataset eav7-hnsx), published by the CDC's Division of Population Health. The first column is the measure LPA (no leisure-time physical activity among adults), the second the measure SLEEP (short sleep, under seven hours, among adults), both as age-adjusted prevalence with the CDC's 95% confidence intervals, rounded to one decimal. The activity estimate is built on 2023 survey answers and the sleep estimate on 2022's. These are model-based estimates (multilevel regression and poststratification), not direct survey counts, and the crude rate can differ.1
Each city's figures were requested from the CDC's open-data interface in October 2026, one city at a time, and re-checked against the CDC by a second, independent fetch: every value and interval matched. The cities are Census places: most are incorporated cities, while The Woodlands, Texas and Columbia, Maryland are census-designated places, and PLACES publishes the same measures for both kinds.
If you reuse the table, cite the CDC, not this site; a link back here is appreciated, but the data are theirs. The CDC's notice, as its reuse terms ask: Source: CDC. Materials developed by CDC; the data are available on the agency website (data.cdc.gov) at no charge. Use of this material does not imply endorsement by CDC, ATSDR, HHS or the United States Government of Diogo Fitness or its services. Reference to specific commercial products, manufacturers, companies, or trademarks does not constitute its endorsement or recommendation by the U.S. Government, Department of Health and Human Services, or Centers for Disease Control and Prevention.
Whatever your city's row says, the plan starts from your week, not the average. If you want help building it, apply.
General education only, not medical advice. If you have a medical condition, are pregnant, or take medication, check with your doctor before changing how you train or eat.
Sources
- Centers for Disease Control and Prevention, Division of Population Health. PLACES: Local Data for Better Health, Place Data, 2025 release (dataset eav7-hnsx), measures LPA (no leisure-time physical activity, BRFSS 2023) and SLEEP (short sleep, BRFSS 2022), age-adjusted prevalence, model-based estimates, 27 places. CDC, data.cdc.gov, 2026. https://data.cdc.gov/resource/eav7-hnsx.json (accessed October 22, 2026).