Data catalog

PLACES county health measures

Centers for Disease Control and Prevention

Publisher site
health
statistic

In a RepVector build, this dataset quantifies clinical need and utilisation across the population.

Sample of the actual data
2 rows captured for Houston, Harris County, Texas on 2026-08-20. Showing the first 2.
CountyMeasureCategoryCrude prevalenceEstimated adults affected
HarrisDepressionHealth Outcomes19.7%708,395
Fort BendDepressionHealth Outcomes17.5%118,109

What this dataset is

Model-based prevalence estimates for around 40 health outcomes, behaviours, preventive services and social factors in every U.S. county — things like chronic disease rates, insurance coverage, checkup rates and mobility limitation. The standard way to compare health need or health-driven demand between places. It is published by Centers for Disease Control and Prevention and can be queried at county and tract level, refreshed annual. Each row is an aggregate statistic for a geography, so results describe a market as a whole rather than a single account.

Why it is useful

  • Separates markets with real clinical demand from markets that only have supply.
  • Grounds a territory case in published prevalence and utilisation instead of assumption.
  • Highlights where need outruns available capacity — usually the fastest conversations.

Questions it helps answer

  • Where is the underlying clinical need highest relative to available capacity?
  • How does utilisation here compare with the state and national picture?
  • Which measures are suppressed or unreported for this geography?

How different verticals use it

RepVector is vertical-agnostic: this dataset is selected by what your question asks for, not by industry. These are common ways teams put it to work.

Healthcare & life sciences

Prioritises territories where clinical need outruns available capacity.

Behavioral health & social services

Quantifies prevalence and utilisation behind a programme or referral case.

Financial services

Informs risk and benefit design with published utilisation patterns.

Education & workforce

Shows community health pressures that shape support-service demand.

How RepVector uses it

  1. You describe a market in plain language. The geography resolver turns the place you named into the exact identifiers this dataset needs — city to county to state, plus DMA where relevant — so a query at county runs without you knowing any codes.
  2. The planner selects PLACES county health measures only when your question matches what it actually reports. It is never included to pad a result.
  3. Returned rows are normalised into the shared metric layer, so figures from Centers for Disease Control and Prevention line up with every other source in the same dashboard instead of sitting in an isolated table.
  4. Quality checks score coverage and recency. If Centers for Disease Control and Prevention suppresses or omits a value for your geography, the gap is reported as a gap — nothing is estimated or filled in.
  5. The result renders as charts, KPIs and, where the rows are entities, prioritised targets you can export to PDF, Excel, CSV or JSON.

What it does not tell you

  • Aggregated and often suppressed at small geographies to protect privacy; gaps are reported rather than filled in.
At a glance
How this dataset can be queried and how current it stays.
Publisher
Centers for Disease Control and Prevention
Geographic grain
county
tract
Refresh cadence
Annual
Row represents
statistic
Topics
health
disease
prevalence
chronic
diabetes
obesity
smoking
insurance
uninsured
preventive
screening
mental health
Available fields
The columns this dataset returns in a RepVector build.
FieldKeyType
Countycountystring
MeasureshortMeasurestring
Categorycategorystring
Crude prevalenceprevalencepercent
Estimated adults affectedestimatedPeoplenumber

How it fits with the rest of the catalog

Need data explains why a territory matters; provider and facility data explains who you visit once you get there. RepVector queries every selected dataset against the same resolved geography and time window, then normalises the results into one metric layer so they can be charted side by side. These datasets are the most common companions to PLACES county health measures:

Browse all datasets

Common questions

What does PLACES county health measures contain?

Model-based prevalence estimates for around 40 health outcomes, behaviours, preventive services and social factors in every U.S. county — things like chronic disease rates, insurance coverage, checkup rates and mobility limitation. The standard way to compare health need or health-driven demand between places. It is published by Centers for Disease Control and Prevention at county and census tract grain.

How often is it refreshed?

Centers for Disease Control and Prevention publishes on a annual cycle. RepVector re-reads the source on that cadence and keeps every prior capture, so you can see what changed.

Do I need an account to use it?

No. Browsing the catalog and the free lookup tools needs no account. Running a full market build across every county in a territory is the paid product.

Put PLACES county health measures to work in your market
Describe the market and the customer you want in plain language. RepVector resolves the geography, selects the datasets that actually answer it — including this one when it fits — and builds the dashboard, targets and exports.

Build the list for one county and see whether the names are right.

Ask in plain language. RepVector finds the universe, enriches each target from its own website, scores it 0–100, and hands you a ranked call list with phones, addresses and named contacts.

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