Dataset
Short sleep in the United States by state and county
Share of US adults sleeping under 7 hours per 24 h, by state (BRFSS 2022, age-adjusted, 95% CI) and by county (CDC PLACES 2025 model-based).
- Source
- CDC BRFSS 2022 via U.S. Chronic Disease Indicators (SLP03)Centers for Disease Control and Prevention, Division of Population Health. U.S. Chronic Disease Indicators (CDI), indicator SLP03 "Short sleep duration among adults", Behavioral Risk Factor Surveillance System 2022. data.cdc.gov dataset hksd-2xuw, retrieved 2026-10-14.
- Sample
- BRFSS 2022 adult telephone survey respondents in 50 states, DC, Guam, Puerto Rico and the U.S. Virgin Islands (per-state sample sizes not published in this dataset)
- Coverage
- United States (50 states + DC), plus Guam, Puerto Rico and U.S. Virgin Islands; 3,144 counties; survey year 2022
- License
- U.S. federal government work (CDC), public domain per CDC's Use of Agency Materials policy (https://www.cdc.gov/other/agencymaterials.html). On data.cdc.gov the PLACES dataset is labelled Public Domain; the CDI dataset's portal license field reads Open Data Commons ODbL (http://opendatacommons.org/licenses/odbl/1.0/), so attribute CDC and share-alike to be safe.
- Retrieved
- October 14, 2026
- Download
- All tables (JSON)Short sleep by state, 2022 (CSV)Short sleep, United States, 2022 (CSV)Short sleep in U.S. territories, 2022 (CSV)Short sleep by county, 2022 (model-based) (CSV)
- See also
Caveats
- Sleep duration is self-reported in a telephone survey, not measured, and covers neither sleep quality nor weekday/weekend differences.
- The state ranking uses direct survey estimates; neighbouring states often have overlapping 95% confidence intervals, so small rank differences are not meaningful.
- County figures are model-based (multilevel regression and poststratification), not survey results for each county; CDC cautions against using them to evaluate local programs or policies.
- County and state estimates come from different methods and should not be compared directly.
- BRFSS asks the sleep question only in even years; 2022 is the latest year published by CDI and PLACES at retrieval.
- Connecticut counties are its 9 planning regions (FIPS 09110–09190), as used by PLACES 2025.
- Loving County, Texas has no published estimate (suppressed in PLACES; stored as null).
- The CDI dataset does not publish per-state sample sizes, so none are included.
Built from this dataset
Short sleep by state, 2022
Share of adults (18+) sleeping < 7 hours per 24 hours, 50 states and DC. Direct BRFSS 2022 survey estimates as published in CDC's U.S. Chronic Disease Indicators (indicator SLP03).
| State | Abbr. | FIPS | Short sleep (age-adjusted) (%) | 95% CI low (%) | 95% CI high (%) | Short sleep (crude) (%) | Crude 95% CI low (%) | Crude 95% CI high (%) | Survey year |
|---|---|---|---|---|---|---|---|---|---|
| Alabama | AL | 01 | 41.4 | 39.2 | 43.6 | 40.5 | 38.4 | 42.6 | 2,022 |
| Alaska | AK | 02 | 37.6 | 35.8 | 39.4 | 37.1 | 35.3 | 38.9 | 2,022 |
| Arizona | AZ | 04 | 36.1 | 34.4 | 37.8 | 34.8 | 33.3 | 36.4 | 2,022 |
| Arkansas | AR | 05 | 39.9 | 38 | 41.8 | 38.7 | 36.9 | 40.5 | 2,022 |
| California | CA | 06 | 35.2 | 33.8 | 36.5 | 34.8 | 33.5 | 36.2 | 2,022 |
| Colorado | CO | 08 | 30.6 | 29.4 | 31.8 | 30.3 | 29.1 | 31.5 | 2,022 |
| Connecticut | CT | 09 | 36.4 | 34.9 | 37.9 | 35.7 | 34.2 | 37.2 | 2,022 |
| Delaware | DE | 10 | 37.3 | 35 | 39.6 | 35.6 | 33.5 | 37.8 | 2,022 |
| District of Columbia | DC | 11 | 31.8 | 29.7 | 34 | 31.9 | 29.7 | 34.2 | 2,022 |
| Florida | FL | 12 | 38.8 | 37 | 40.8 | 37.4 | 35.7 | 39.2 | 2,022 |
| Georgia | GA | 13 | 38.8 | 37.2 | 40.4 | 38.1 | 36.6 | 39.7 | 2,022 |
| Hawaii | HI | 15 | 45.9 | 44.2 | 47.6 | 45.6 | 44 | 47.2 | 2,022 |
| Idaho | ID | 16 | 33.2 | 31.8 | 34.7 | 32.5 | 31.1 | 34 | 2,022 |
| Illinois | IL | 17 | 36.7 | 34.8 | 38.7 | 36 | 34.1 | 38 | 2,022 |
| Indiana | IN | 18 | 38.6 | 37.4 | 39.9 | 37.7 | 36.5 | 38.9 | 2,022 |
| Iowa | IA | 19 | 34.2 | 32.8 | 35.6 | 32.9 | 31.6 | 34.2 | 2,022 |
| Kansas | KS | 20 | 36.7 | 35.3 | 38 | 35.5 | 34.2 | 36.8 | 2,022 |
| Kentucky | KY | 21 | 39.6 | 37.5 | 41.9 | 39.3 | 37.2 | 41.5 | 2,022 |
| Louisiana | LA | 22 | 40.5 | 38.7 | 42.3 | 39.8 | 38 | 41.5 | 2,022 |
| Maine | ME | 23 | 33.4 | 31.9 | 34.9 | 32.7 | 31.3 | 34 | 2,022 |
| Maryland | MD | 24 | 38.7 | 37.5 | 40 | 38 | 36.8 | 39.2 | 2,022 |
| Massachusetts | MA | 25 | 33.2 | 31.9 | 34.5 | 32.7 | 31.5 | 34 | 2,022 |
| Michigan | MI | 26 | 36.4 | 35 | 37.7 | 35.2 | 33.9 | 36.4 | 2,022 |
| Minnesota | MN | 27 | 30.3 | 29.3 | 31.4 | 29.6 | 28.6 | 30.5 | 2,022 |
| Mississippi | MS | 28 | 38.6 | 36.7 | 40.6 | 37.8 | 35.9 | 39.8 | 2,022 |
| Missouri | MO | 29 | 37.7 | 36.1 | 39.3 | 36.8 | 35.2 | 38.3 | 2,022 |
| Montana | MT | 30 | 32.9 | 31.4 | 34.5 | 31.7 | 30.3 | 33.1 | 2,022 |
| Nebraska | NE | 31 | 31.5 | 29.9 | 33.1 | 30.6 | 29.2 | 32.1 | 2,022 |
| Nevada | NV | 32 | 39.3 | 36.8 | 42 | 38.9 | 36.5 | 41.5 | 2,022 |
| New Hampshire | NH | 33 | 33.8 | 31.8 | 35.8 | 33 | 31.3 | 34.7 | 2,022 |
| New Jersey | NJ | 34 | 37.9 | 36.4 | 39.5 | 37.4 | 36 | 38.9 | 2,022 |
| New Mexico | NM | 35 | 34.1 | 32.1 | 36.3 | 32.8 | 30.9 | 34.8 | 2,022 |
| New York | NY | 36 | 38.8 | 37.7 | 39.9 | 38.4 | 37.3 | 39.5 | 2,022 |
| North Carolina | NC | 37 | 35 | 33.1 | 37 | 34.1 | 32.2 | 36 | 2,022 |
| North Dakota | ND | 38 | 34 | 32.2 | 35.9 | 33.2 | 31.4 | 35 | 2,022 |
| Ohio | OH | 39 | 39.9 | 38.7 | 41.1 | 38.5 | 37.4 | 39.7 | 2,022 |
| Oklahoma | OK | 40 | 36.2 | 34.7 | 37.8 | 35.5 | 34 | 37 | 2,022 |
| Oregon | OR | 41 | 31.8 | 30.2 | 33.4 | 30.9 | 29.5 | 32.5 | 2,022 |
| Pennsylvania | PA | 42 | 38.1 | 36 | 40.2 | 37.1 | 35.1 | 39.2 | 2,022 |
| Rhode Island | RI | 44 | 36.2 | 34.4 | 38.2 | 35.6 | 33.8 | 37.4 | 2,022 |
| South Carolina | SC | 45 | 36.6 | 35.1 | 38 | 35.4 | 34.1 | 36.7 | 2,022 |
| South Dakota | SD | 46 | 32.9 | 29.4 | 36.5 | 31.2 | 27.9 | 34.8 | 2,022 |
| Tennessee | TN | 47 | 39.8 | 38 | 41.7 | 38.8 | 37 | 40.5 | 2,022 |
| Texas | TX | 48 | 37.1 | 35.6 | 38.7 | 36.9 | 35.4 | 38.4 | 2,022 |
| Utah | UT | 49 | 34.3 | 33 | 35.5 | 34.2 | 33 | 35.5 | 2,022 |
| Vermont | VT | 50 | 30 | 28.5 | 31.5 | 29.6 | 28.2 | 31 | 2,022 |
| Virginia | VA | 51 | 36.9 | 35.5 | 38.4 | 36.2 | 34.8 | 37.6 | 2,022 |
| Washington | WA | 53 | 32.8 | 32 | 33.6 | 32.4 | 31.6 | 33.1 | 2,022 |
| West Virginia | WV | 54 | 42.6 | 40.7 | 44.5 | 41.3 | 39.6 | 43.1 | 2,022 |
| Wisconsin | WI | 55 | 33.9 | 32.6 | 35.2 | 32.8 | 31.6 | 34 | 2,022 |
First 50 of 51 rows. Download all as CSV
Short sleep, United States, 2022
The 'United States' row of CDC's U.S. Chronic Disease Indicators, indicator SLP03, BRFSS 2022.
| Area | Short sleep (age-adjusted) (%) | 95% CI low (%) | 95% CI high (%) | Short sleep (crude) (%) | Crude 95% CI low (%) | Crude 95% CI high (%) | Survey year |
|---|---|---|---|---|---|---|---|
| United States | 36.8 | 36.5 | 37.1 | 36.1 | 35.8 | 36.4 | 2,022 |
1 rows. Download all as CSV
Short sleep in U.S. territories, 2022
Puerto Rico, Guam and the U.S. Virgin Islands, from the same CDI SLP03 BRFSS 2022 release.
| Territory | Abbr. | FIPS | Short sleep (age-adjusted) (%) | 95% CI low (%) | 95% CI high (%) | Short sleep (crude) (%) | Crude 95% CI low (%) | Crude 95% CI high (%) | Survey year |
|---|---|---|---|---|---|---|---|---|---|
| Guam | GU | 66 | 50.2 | 45.9 | 54.4 | 50.4 | 46.1 | 54.6 | 2,022 |
| Puerto Rico | PR | 72 | 38.9 | 37 | 40.7 | 37.6 | 35.8 | 39.4 | 2,022 |
| Virgin Islands | VI | 78 | 39.9 | 33.3 | 46.9 | 39 | 32.1 | 46.3 | 2,022 |
3 rows. Download all as CSV
Short sleep by county, 2022 (model-based)
CDC PLACES 2025 release, model-based (multilevel regression and poststratification) estimates from BRFSS 2022 (all rows are survey year 2022). Not direct survey estimates; Connecticut uses its 9 planning regions.
| FIPS | County | State | Abbr. | Short sleep (age-adjusted) (%) | 95% CI low (%) | 95% CI high (%) | Short sleep (crude) (%) | Crude 95% CI low (%) | Crude 95% CI high (%) | Population | Adults (18+) |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 01001 | Autauga | Alabama | AL | 37.7 | 31.5 | 44.4 | 37.3 | 31.1 | 44 | 60,342 | 46,253 |
| 01003 | Baldwin | Alabama | AL | 36.4 | 31.4 | 41.7 | 34.8 | 29.9 | 40.1 | 253,507 | 200,397 |
| 01005 | Barbour | Alabama | AL | 44.6 | 37.5 | 52.1 | 43 | 36 | 50.4 | 24,585 | 19,517 |
| 01007 | Bibb | Alabama | AL | 41.4 | 34.6 | 48.6 | 40.6 | 33.8 | 47.7 | 21,868 | 17,522 |
| 01009 | Blount | Alabama | AL | 37.6 | 30.8 | 44.5 | 36.5 | 29.8 | 43.3 | 59,816 | 46,099 |
| 01011 | Bullock | Alabama | AL | 50.5 | 42.8 | 58.2 | 49.8 | 42.1 | 57.5 | 9,897 | 7,878 |
| 01013 | Butler | Alabama | AL | 43.6 | 36.7 | 50.9 | 41.8 | 35 | 49 | 18,382 | 14,276 |
| 01015 | Calhoun | Alabama | AL | 42.8 | 36.4 | 49.2 | 41.6 | 35.3 | 48 | 116,429 | 91,555 |
| 01017 | Chambers | Alabama | AL | 42.6 | 35.5 | 49.7 | 41.4 | 34.4 | 48.5 | 34,079 | 26,970 |
| 01019 | Cherokee | Alabama | AL | 37.4 | 30.4 | 44.8 | 35.4 | 28.6 | 42.6 | 25,666 | 20,877 |
| 01021 | Chilton | Alabama | AL | 34.1 | 27.9 | 40.8 | 33.6 | 27.4 | 40.3 | 46,431 | 35,269 |
| 01023 | Choctaw | Alabama | AL | 43.1 | 35.6 | 50.3 | 41.5 | 34.2 | 48.7 | 12,252 | 9,839 |
| 01025 | Clarke | Alabama | AL | 44 | 36.6 | 51.3 | 42.4 | 35.2 | 49.7 | 22,337 | 17,444 |
| 01027 | Clay | Alabama | AL | 40.8 | 33.3 | 48.4 | 39.3 | 32 | 46.7 | 14,111 | 11,157 |
| 01029 | Cleburne | Alabama | AL | 38.4 | 31.3 | 46.2 | 37.4 | 30.3 | 45.1 | 15,639 | 12,016 |
| 01031 | Coffee | Alabama | AL | 41.3 | 35 | 47.5 | 40.5 | 34.4 | 46.7 | 55,643 | 42,235 |
| 01033 | Colbert | Alabama | AL | 41.6 | 34.3 | 49.1 | 40.2 | 33 | 47.6 | 58,361 | 45,890 |
| 01035 | Conecuh | Alabama | AL | 43.7 | 35.9 | 51.3 | 41.8 | 34.1 | 49.3 | 11,174 | 8,894 |
| 01037 | Coosa | Alabama | AL | 41.9 | 34.8 | 49.3 | 39.8 | 33 | 47.1 | 10,268 | 8,603 |
| 01039 | Covington | Alabama | AL | 36.6 | 30.2 | 43.3 | 34.5 | 28.3 | 41 | 37,952 | 29,514 |
| 01041 | Crenshaw | Alabama | AL | 40.4 | 33.2 | 47.8 | 39.1 | 32 | 46.3 | 13,101 | 10,066 |
| 01043 | Cullman | Alabama | AL | 37.4 | 30.8 | 44.5 | 36.7 | 30.1 | 43.7 | 92,016 | 71,431 |
| 01045 | Dale | Alabama | AL | 39.7 | 33.3 | 46.8 | 38.9 | 32.5 | 46 | 49,871 | 38,227 |
| 01047 | Dallas | Alabama | AL | 47.6 | 40.8 | 54.5 | 46 | 39.2 | 52.9 | 36,165 | 27,736 |
| 01049 | DeKalb | Alabama | AL | 41.1 | 34.3 | 48 | 40.3 | 33.6 | 47.2 | 72,569 | 55,297 |
| 01051 | Elmore | Alabama | AL | 42.2 | 35.7 | 49 | 41.5 | 35 | 48.3 | 90,441 | 71,010 |
| 01053 | Escambia | Alabama | AL | 46.1 | 39.3 | 53.3 | 45 | 38.2 | 52.1 | 36,558 | 28,282 |
| 01055 | Etowah | Alabama | AL | 46.2 | 39.4 | 52.9 | 45 | 38.3 | 51.7 | 103,241 | 80,652 |
| 01057 | Fayette | Alabama | AL | 40.5 | 33.4 | 48 | 39 | 32 | 46.4 | 15,967 | 12,532 |
| 01059 | Franklin | Alabama | AL | 39.3 | 32.1 | 46.9 | 38.3 | 31.2 | 45.9 | 31,802 | 23,799 |
| 01061 | Geneva | Alabama | AL | 41.2 | 34.2 | 48.3 | 40.2 | 33.2 | 47.2 | 26,988 | 21,061 |
| 01063 | Greene | Alabama | AL | 51 | 43.3 | 58.5 | 48.9 | 41.3 | 56.4 | 7,341 | 5,755 |
| 01065 | Hale | Alabama | AL | 44.9 | 37.6 | 52.3 | 43.9 | 36.6 | 51.2 | 14,888 | 11,246 |
| 01067 | Henry | Alabama | AL | 42.6 | 35.4 | 50.2 | 41 | 34 | 48.6 | 17,899 | 14,236 |
| 01069 | Houston | Alabama | AL | 40.4 | 34.4 | 46.4 | 39 | 33.1 | 45 | 108,462 | 83,709 |
| 01071 | Jackson | Alabama | AL | 42.1 | 34.7 | 49.8 | 41 | 33.7 | 48.7 | 53,467 | 42,355 |
| 01073 | Jefferson | Alabama | AL | 38.4 | 34.4 | 42.7 | 37.6 | 33.6 | 41.9 | 662,895 | 511,715 |
| 01075 | Lamar | Alabama | AL | 39.5 | 32.1 | 47.2 | 38.2 | 30.8 | 45.8 | 13,661 | 10,648 |
| 01077 | Lauderdale | Alabama | AL | 41.4 | 34.7 | 48.4 | 39.6 | 33.1 | 46.5 | 96,814 | 78,262 |
| 01079 | Lawrence | Alabama | AL | 39.9 | 32.9 | 47.3 | 39 | 32.1 | 46.3 | 33,502 | 26,186 |
| 01081 | Lee | Alabama | AL | 37.5 | 31.5 | 42.9 | 36.8 | 30.9 | 42.1 | 183,215 | 145,050 |
| 01083 | Limestone | Alabama | AL | 39.8 | 33.2 | 46.5 | 39.4 | 32.9 | 46.1 | 114,654 | 89,453 |
| 01085 | Lowndes | Alabama | AL | 49.5 | 41.7 | 57.2 | 48.1 | 40.3 | 55.6 | 9,717 | 7,570 |
| 01087 | Macon | Alabama | AL | 44.7 | 37.3 | 52.3 | 43.5 | 36.1 | 51.1 | 18,370 | 15,322 |
| 01089 | Madison | Alabama | AL | 38.4 | 33.4 | 43.6 | 37.5 | 32.6 | 42.6 | 412,600 | 324,132 |
| 01091 | Marengo | Alabama | AL | 43.9 | 36.7 | 51.5 | 42.8 | 35.7 | 50.3 | 18,684 | 14,502 |
| 01093 | Marion | Alabama | AL | 38.6 | 31.5 | 45.9 | 37.6 | 30.6 | 44.9 | 29,244 | 23,108 |
| 01095 | Marshall | Alabama | AL | 40.3 | 33.6 | 47.4 | 39.1 | 32.5 | 46.2 | 100,756 | 74,538 |
| 01097 | Mobile | Alabama | AL | 41.5 | 37.3 | 46 | 40.7 | 36.5 | 45.1 | 411,640 | 316,274 |
| 01099 | Monroe | Alabama | AL | 45.6 | 38.2 | 53.4 | 44 | 36.7 | 51.7 | 19,229 | 15,175 |
First 50 of 3,144 rows. Download all as CSV
Methodology
What was measured
The Behavioral Risk Factor Surveillance System (BRFSS) is CDC's state-based telephone survey of adults aged 18 and over. In even years its core questionnaire asks: "On average, how many hours of sleep do you get in a 24-hour period?" (wording as given on CDC's adult sleep facts page).
Short sleep is defined, following the American Academy of Sleep Medicine and Sleep Research Society joint consensus statement (Watson et al., Sleep 2015; adults should sleep 7 or more hours per night), as reporting less than 7 hours on average in a 24-hour period. Per the CDI indicator definition, the numerator is adults reporting < 7 hours and the denominator is adults reporting 1–24 hours.
States: direct survey estimates (states, national, territories)
Taken unchanged from CDC's U.S. Chronic Disease Indicators (CDI), indicator SLP03 "Short sleep
duration among adults", data source BRFSS, year 2022, stratification "Overall". CDI publishes for
every location a crude prevalence and an age-adjusted prevalence, each with a 95% confidence
interval. Age adjustment uses the 2000 U.S. standard population, so states with older or younger
populations can be compared. pct_short_sleep is the age-adjusted value; the crude value is kept in
pct_short_sleep_crude.
The national table is CDI's own "United States" row (age-adjusted 36.8%, 95% CI 36.5–37.1). This repo
does not compute any national or state figure itself. As a cross-check, the PLACES county file contains
a United States row from the same BRFSS 2022 data: age-adjusted 36.8% (36.5–37.2), crude 36.0%
(35.7–36.3); it is not used in the tables.
Counties: model-based estimates (counties)
From CDC PLACES, County Data, 2025 release, measure SLEEP. The 2025 release uses BRFSS 2022 for
short sleep (the sleep question is asked every other year), plus Census 2023 county population
estimates and American Community Survey 5-year data (2019–2023 or 2018–2022, per the dataset description). PLACES fits a multilevel logistic regression
to BRFSS respondents (individual age, sex, race/ethnicity and education, county poverty level, and
state and county random effects), then applies the predicted probabilities to each county's population
(poststratification). The 95% intervals are the 2.5th and 97.5th percentiles of 1,000 Monte Carlo
simulations. These are statistical predictions, not counts of survey respondents in each county. CDC notes the
model cannot detect effects of local interventions.
population and population_18plus are the population figures PLACES publishes alongside each
estimate.
Processing in this repo
ingest/us-short-sleep/fetch.ts downloads two CSV exports from the data.cdc.gov Socrata API using
pinned SoQL queries ($select, $where, $order, $limit; full URLs are in manifest.json) and
checks their size and sha256 against the manifest. Copies are committed in ingest/us-short-sleep/raw/.
build.ts re-checks the hashes, joins each location's crude and age-adjusted rows, splits states (50 +
DC), territories and the national row into separate tables, and fails if any value lies outside its own
confidence interval or if any row is missing or duplicated. Values are copied exactly as published
(one decimal place). No rounding, weighting or aggregation is done here.
Generated October 14, 2026 by apps/data/ingest/us-short-sleep/build.ts in the site's repository.