County profile
Jefferson County, Indiana Community Health Profile
Environmental risk, disease burden, provider access, and SDOH scores for community health needs assessment and service line planning. Fused from EPA, CDC, CMS, and Census data into a single free view.
Opportunity Score
Env
23
−27 vs U.S. mean
Disease
59
+9 vs U.S. mean
Provider
67
+17 vs U.S. mean
SDOH
42
−8 vs U.S. mean
Specific health risk patterns
Jefferson County, IN: 2 specific risk patterns triggered
Each pattern below combines a specific environmental exposure with a population that is more vulnerable to that exposure. When both are present at meaningful levels in Jefferson County, the pattern triggers. These are the most concrete data points for documenting a significant health need in a Community Health Needs Assessment and for planning where services or community investment would land hardest.
Internally, we call these “Compound Signals.” Each is a versioned, weighted composite scored against the national distribution. The full formula and citations live on the methodology page.
95,178,347 lbs of TRI-reported industrial releases (3,084,908 lbs of carcinogens).
Industrial emissions exposure × Surrounding population
Defend this finding — full lineage to source data5 sources cited
Industrial BurdenJefferson County: 91/100 (elevated above the 70th-percentile threshold)
Jefferson County: 91/100 (elevated above the 70th-percentile threshold)
TRI facility density × PFAS contamination × pesticide use × total provider access deficit. Captures cumulative industrial environmental load on the surrounding population.
Methodology. Combines three distinct industrial exposure modes (point-source releases, drinking-water contamination, pesticide use) with a generalist provider-access leg since industrial pollution health effects span multiple specialties. Methodology v1.8.0.
Threshold. Elevated when score ≥ 70th national percentile across all US counties evaluated for this signal
Peer set. All US counties evaluated for the signal (~3,222, less coverage gaps)
Components (4)
Number of EPA Toxics Release Inventory (TRI) reporting facilities in the county.
EPA — Toxics Release Inventory (TRI) via Envirofacts
Vintage: TRI 2023 reporting year · Refresh: Annual · Lag: 18 months
How it's measured. Count of facilities reporting any TRI-listed chemical release in the most recent reporting year. TRI thresholds (10K-25K lb manufacturing; 500 lb persistent-bioaccumulative) mean smaller polluters are excluded from this count.
Caveat. TRI is industrial self-report. Underreporting is documented for some sectors and chemicals; the count is a floor, not a ceiling.
Coverage. All 3,222 US counties (zero-inflated; many rural counties = 0)
Composite 0–100 severity score for per- and polyfluoroalkyl substance (PFAS) contamination in the county's drinking water and environment.
EPA — UCMR5 (Unregulated Contaminant Monitoring Rule) + ECHO
Vintage: UCMR5 sampling 2023–2025 · Refresh: Quarterly · Lag: 3–6 months
How it's measured. Composite score combining detection frequency, peak concentration relative to EPA Health Advisory Levels, and number of PFAS species detected from UCMR5 public water system sampling and ECHO enforcement records.
Caveat. UCMR5 only samples public water systems serving 3,300+ people; private well users in small or rural communities are not represented.
Coverage. Counties with at least one UCMR5-eligible PWS
95.9K kg/year
Total estimated agricultural pesticide use in the county for the year, in kilograms (EPest_HIGH conservative estimate).
USGS — Pesticide National Synthesis Project (PNSP)
Vintage: PNSP 2019 (preliminary; 2018 unavailable; 2020+ unreleased) · Refresh: Annual when published · Lag: 2–3 years (and the program is on medium-low update reliability)
How it's measured. USGS PNSP estimates county-level pesticide application from USDA Census of Agriculture acreage by crop, multiplied by crop-specific application rates from proprietary surveys. EPest_HIGH is the regional-pool imputation that's conservative against undercounting.
Caveat. PNSP funding was nearly cut in 2023 and the program now publishes irregularly. 2018 has no data; 2020+ is unreleased as of methodology v1.8.0. Use with the data-quality note shown on the platform.
Coverage. 3,054 of 3,222 US counties
Total provider access deficit20%
Inverted national percentile rank of total healthcare specialists per 100K, with a 50/50 adjacency adjustment.
Methodology. Same shape as the specialty-specific deficits. Used by Industrial Burden where the relevant access dimension isn't a single specialty (industrial pollution health effects span pulmonary, cardiovascular, oncologic, and developmental medicine).
Components (2)
All active healthcare specialists in the county, normalized to population.
CMS — NPPES — National Plan and Provider Enumeration System
Vintage: Current month · Refresh: Monthly · Lag: Same month
How it's measured. NPPES registry — all specialty taxonomy codes — geocoded to practice address, summed per county, divided by Census population estimate.
Caveat. NPPES is registration-time data, not practice attestation.
Coverage. All 3,222 US counties
All active healthcare specialists in the county, normalized to population.
CMS — NPPES — National Plan and Provider Enumeration System
Vintage: Current month · Refresh: Monthly · Lag: Same month
How it's measured. NPPES registry — all specialty taxonomy codes — geocoded to practice address, summed per county, divided by Census population estimate.
Caveat. NPPES is registration-time data, not practice attestation.
Coverage. All 3,222 US counties
PM2.5 averages 8.4 µg/m³ against an asthma + COPD prevalence of 11.5% + 9.2%.
Air pollution exposure × Respiratory-vulnerable population
Defend this finding — full lineage to source data5 sources cited
Respiratory BurdenJefferson County: 77/100 (elevated above the 70th-percentile threshold)
Jefferson County: 77/100 (elevated above the 70th-percentile threshold)
PM2.5 exposure × respiratory disease prevalence × pulmonology access deficit. Surfaces counties where chronic air-quality exposure lands on a population with elevated asthma/COPD and inadequate specialty access.
Methodology. Each leg is converted to a national percentile rank before weighting. The composite is then itself rank-percentiled to produce the 0–100 published score. Methodology v1.8.0.
Threshold. Elevated when score ≥ 70th national percentile across all US counties evaluated for this signal
Peer set. All US counties evaluated for the signal (~3,222, less coverage gaps)
Evidence base
- · Pope CA et al. 'Lung cancer, cardiopulmonary mortality, and long-term exposure to fine particulate air pollution.' JAMA 2002.
- · Schraufnagel DE et al. 'Air pollution and noncommunicable diseases.' Chest 2019 (American Thoracic Society + ERS joint review).
Components (3)
8.4 µg/m³
Yearly average fine particulate matter (PM2.5) concentration at ground level, in micrograms per cubic meter.
EPA — Air Quality System (AQS) + EJSCREEN modeled fallback
Vintage: AQS 2016–2025; EJSCREEN modeled 2024 · Refresh: AQS monthly; EJSCREEN quarterly · Lag: AQS: 6–18 months. EJSCREEN: 1 year.
How it's measured. EPA AQS reports monitor-network annual means where a county hosts a regulatory monitor. For counties without a monitor, the platform falls back to EPA EJSCREEN modeled PM2.5 (a downscaled NAAQS-grade product) so every county has a value.
Caveat. AQS undercounts wildfire-attributable PM2.5 by 10–30% in fire-affected counties; the platform reports wildfire smoke separately via Stanford Childs/Burke.
Coverage. All 3,222 US counties (mix of monitored + modeled)
Asthma + COPD prevalence blend30%
60/40 dominant/secondary percentile blend of asthma and COPD prevalence — the higher-percentile condition gets 60%, the lower gets 40%.
Methodology. The dominant/secondary blend ensures counties with both conditions elevated score higher than those with only one — a cardiometabolic-style cluster signal that a max() or simple average would miss. Introduced in methodology v1.1.0 to replace the original max() rule across all multi-condition disease components.
Components (2)
11.5%
Percent of adults age 18+ self-reporting current asthma diagnosis.
CDC — PLACES — Local Data for Better Health
Vintage: PLACES 2022–2023 (BRFSS source year ≈ 2 years prior) · Refresh: Monthly (PLACES release cadence) · Lag: 1–2 years
How it's measured. PLACES applies multilevel small-area estimation to BRFSS adult survey responses, producing county-level prevalence estimates with model-based uncertainty intervals. Self-reported, not provider-confirmed.
Coverage. All 3,222 US counties
9.2%
Percent of adults age 18+ self-reporting chronic obstructive pulmonary disease diagnosis.
CDC — PLACES — Local Data for Better Health
Vintage: PLACES 2022–2023 · Refresh: Monthly · Lag: 1–2 years
How it's measured. PLACES small-area estimation from BRFSS self-report. Underestimates true prevalence by an unknown factor since many cases go undiagnosed in low-access areas.
Coverage. All 3,222 US counties
Pulmonology access deficit30%
Inverted national percentile rank of pulmonologists per 100K, with a 50/50 in-county/neighbor-county adjacency adjustment.
Methodology. Inversion turns 'fewer providers' into a higher deficit score (so the signal weights point the same direction as exposure). The 50/50 adjacency adjustment uses Census Bureau county-adjacency files to reduce false positives where a county borders a major medical center: a small county next to Houston shouldn't read as 'no pulmonology' just because the practice happens to sit across the county line.
Components (2)
6.0 providers / 100K
Active pulmonology specialists practicing in the county, normalized to population.
CMS — NPPES — National Plan and Provider Enumeration System
Vintage: Current month (NPPES is registration-time data) · Refresh: Monthly · Lag: Same month
How it's measured. NPPES registry filtered to active pulmonology taxonomy codes, geocoded to practice address, summed per county, divided by Census population estimate.
Caveat. NPPES is registration-time data, not practice attestation — providers may have moved or retired without updating their record. The 50/50 adjacency adjustment in the access deficit derivation reduces but does not eliminate this noise.
Coverage. All 3,222 US counties
6.0 providers / 100K
Active pulmonology specialists practicing in the county, normalized to population.
CMS — NPPES — National Plan and Provider Enumeration System
Vintage: Current month (NPPES is registration-time data) · Refresh: Monthly · Lag: Same month
How it's measured. NPPES registry filtered to active pulmonology taxonomy codes, geocoded to practice address, summed per county, divided by Census population estimate.
Caveat. NPPES is registration-time data, not practice attestation — providers may have moved or retired without updating their record. The 50/50 adjacency adjustment in the access deficit derivation reduces but does not eliminate this noise.
Coverage. All 3,222 US counties
4 signals near threshold: Runoff Burden (62) · Smoke Burden (56) · Outage Vulnerability (53) · Heat-Dialysis Vulnerability (51)
8 signals evaluated. See all signal methodologies →
Where Jefferson County stands
Health risks here sit near national averages
Jefferson County, Indiana has elevated doctor and specialist shortages — primary care and specialty access rank worse than 67% of U.S. counties. Pollution exposure, chronic disease rates, and social and economic conditions all sit closer to the middle of the national distribution. The issue here is healthcare infrastructure — not enough providers for the population — rather than vulnerability piling up across multiple dimensions. Counties in this profile are candidates for provider-recruitment and capacity-building investment.
Methodology: when three or more of the four major health-risk areas (pollution, chronic disease, doctor access, social and economic conditions) score above the 70th national percentile, we call the pattern “multi-pillar convergence.” The scoring approach and citations live on the methodology page.
Risk profile
Jefferson County compared to Indiana and the U.S. average
Four health-risk scores on a 0-100 scale, where 50 is the U.S. average. A higher score means that area is a stronger contributor to community health risk.
Disease Burden (59) and Provider Gap (67) are moderately worse than the U.S. average of 50.
Environmental Risk (23) and SDOH Stress (42) are at or better than the U.S. average.
- Jefferson County
- Indiana state mean
- U.S. mean (50)
- Signal threshold (70)
Current Conditions
Today's air quality, fires, and weather alerts
Live operational data for Jefferson County: real-time AQI from EPA AirNow, active fires from NIFC, and any National Weather Service advisories. Updated daily.
Environmental Factors
Air, water, and exposure indicators
Top environmental indicators for Jefferson County with state and national benchmarks. Full profile covers 40+ metrics on the platform.
| Indicator | Jefferson County | IN avg | US avg |
|---|---|---|---|
PM2.5 (annual mean) EPA AQS / EJSCREEN | 8.4 µg/m³ -0.2% vs IN | 8.4 | 7.4 |
Ozone EPA AQS / EJSCREEN | 61.6 ppb -1.2% vs IN | 62.3 | 57.1 |
Traffic Proximity EJSCREEN | 123,452 index ▼ -49% vs IN | 240,590 | 291,320 |
Superfund Proximity EPA EJSCREEN | 0.00 score ▼ -100% vs IN | 0.11 | 0.16 |
Drinking Water Violations EPA EJSCREEN | 0.67 score ▲ +12% vs IN | 0.60 | 3.39 |
Wildfire-Attributable Air Quality
Smoke PM2.5 the EPA doesn't count
Stanford peer-reviewed wildfire-attributable PM2.5 for Jefferson County. The EPA classifies wildfire smoke as "exceptional events" and excludes it from official AQS monitoring; Childs/Burke fills that gap with daily county-level data.
Source: Childs et al, Environmental Science & Technology 2022 (Harvard Dataverse 10.7910/DVN/DJVMTV). Latest year shipped: 2020. Burke et al, Nature 2023 estimate that the EPA AQS network undercounts wildfire-attributable PM2.5 by 10–30% in fire-affected counties. Coverage is CONUS only. Full methodology →
Outage Burden
When the grid goes dark
DOE/ORNL EAGLE-I customer-hours-out for Jefferson County in 2024. The fraction is population-normalized via the Maximum Customer Count denominator (Brelsford et al, Sci Data 2024) so it's directly comparable across counties of any size.
Source: DOE/ORNL EAGLE-I (figshare 10.6084/m9.figshare.24237376). Latest year shipped: 2024. Coverage: 3,050 of 3,222 US counties; AK and some sparsely-served rural counties may have no data. Full methodology →
Severe Weather History
Recorded storm events and damages
NOAA NCEI Storm Events Database for Jefferson County, 2010–2026. Cumulative + last 5 years of recorded weather events with deaths, injuries, and damages.
Source: NOAA NCEI Storm Events Database (full history rollup). NOAA buckets ~50 raw event_type strings into 8 health-relevant categories. Coverage: 3,107 of 3,222 US counties; the absent are typically Alaska boroughs and territories where NOAA codes events as forecast zones rather than counties. Full methodology →
Concentrated Animal Feeding Operations
Livestock density and federal-permit confidence
USDA Census of Agriculture (vintage 2022) animal-unit totals for Jefferson County, normalized to land area and ranked nationally. Animal Units (AU) follow the EPA federal definition under 40 CFR §122.23.
Source: USDA Census of Agriculture 2022 (head counts) + EPA 40 CFR §122.23 (animal-unit conversion). The CAFO composite deliberately omits NPDES facility counts because federal coverage averages ~32% nationally per EPA-IG and is heavily state-skewed — adding it as a numerator would systematically bias the index toward delegated states. Full methodology →
Pesticide Use
USGS Pesticide National Synthesis
Annual pesticide application rollup for Jefferson County from the USGS Pesticide National Synthesis Project. Most recent year on file: 2019. Mass figures use the EPest_HIGH estimate (the conservative-against-undercounting framing); EPest_LOW is also retained on the underlying data.
- 1.GLYPHOSATE43.9K kg
- 2.METOLACHLOR & METOLACHLOR-S11.3K kg
- 3.ATRAZINE11.0K kg
- 4.METOLACHLOR-S8.8K kg
- 5.ACETOCHLOR4.7K kg
Source: USGS Pesticide National Synthesis Project (2019). USGS PNSP nationally; year 2019 is preliminary; 2018 unavailable; 2020+ not released. Update reliability medium-low. Full methodology →
Health Outcomes
Chronic disease prevalence
CDC PLACES model-based prevalence estimates for adults in Jefferson County. Full profile covers 15+ health outcomes plus mortality on the platform.
| Condition | Jefferson County | IN avg | US avg |
|---|---|---|---|
Current Asthma % of adults with current asthma | 11.5% ▲ +2.1% vs IN | 11.3% | 10.6% |
COPD % of adults with diagnosed COPD | 9.2% +0.4% vs IN | 9.2% | 8.6% |
Diabetes % of adults with diagnosed diabetes | 13.5% -0.6% vs IN | 13.6% | 13.7% |
Coronary Heart Disease % of adults with CHD | 7.5% -1.1% vs IN | 7.6% | 7.9% |
Depression % of adults ever diagnosed with depression | 26.4% ▲ +3.0% vs IN | 25.6% | 23.1% |
Frequent Mental Distress % of adults with 14+ poor mental health days/month | 18.2% +1.8% vs IN | 17.9% | 17.2% |
Vulnerable Medicare Population
Who needs the grid to stay alive
Medicare beneficiaries in Jefferson County who depend on electricity for dialysis, oxygen, or other powered medical equipment. From the HHS emPOWER program, which CMS publishes monthly so emergency managers know who to find first when the power goes out.
| Population | Count | Per 1,000 Medicare |
|---|---|---|
Total Medicare beneficiaries Denominator | 7,730 | — |
Electricity-dependent (any DME) Ventilators, oxygen concentrators, IV pumps, motorized wheelchairs | 539 | 69.7 ▲ +22% vs IN |
Dialysis-dependent ESRD beneficiaries needing in-center or home dialysis | 33 | 4.27 ▲ +35% vs IN |
Oxygen-dependent Home oxygen concentrators (outage-vulnerable) | 204 | 26.4 ▲ +36% vs IN |
Source: HHS emPOWER Map (ArcGIS county layer), May 2026. Counts of 1–10 are masked as “≤10” per HHS privacy rules; per-1,000 rates are derived and still respect the privacy floor. Full methodology →
Provider Supply
Specialty physician density per 100,000 residents
Active providers in Jefferson County from the CMS National Plan and Provider Enumeration System (NPPES). Compared to the U.S. average for each specialty. Adjacency adjustment is applied separately in the Provider Gap pillar score.
| Specialty | Jefferson County | US avg |
|---|---|---|
Primary Care Family medicine, internal medicine, general practice, pediatrics. | 114.9 per 100k ▼ -12% vs US | 130.4 |
Cardiology Cardiovascular disease, electrophysiology, interventional cardiology. | 12.1 per 100k +0.2% vs US | 12.1 |
Pulmonology Respiratory disease specialists — relevant to PM2.5 and wildfire smoke exposure. | 6.0 per 100k +0.3% vs US | 6.0 |
Psychiatry Mental health prescribers; complements behavioral health access. | 12.1 per 100k ▼ -35% vs US | 18.7 |
Oncology / Hematology Cancer specialists. | 6.0 per 100k ▼ -5.6% vs US | 6.4 |
Neurology Neurological disease specialists. | 6.0 per 100k ▼ -23% vs US | 7.9 |
Source: CMS National Plan and Provider Enumeration System (NPPES). Counts reflect providers with a primary practice address in Jefferson County; specialty is taken from the provider's primary NUCC taxonomy code.
Pro analytical view
What drives this county's scores
The flagged signals and service-line opportunities for Jefferson County, plus the methodology decomposition behind each score. Visible to Pro, Consultant Studio, and Enterprise tiers.
Where to focus
Pro feature
Top flagged signals + service lines are a Pro feature
See how each signal's components blend into its final score, and which signals + service lines this county should prioritize. Available on Professional, Consultant Studio, and Enterprise.
Score decomposition
Each named signal's component breakdown with weights. The bar length is the component's percentile rank; the parenthetical is its weight in the final blend.
Pro feature
Score decomposition is a Pro feature
See how each signal's components blend into its final score, and which signals + service lines this county should prioritize. Available on Professional, Consultant Studio, and Enterprise.
Tract drill-down
Census tracts inside Jefferson County
Pro feature
Tract-level drill-down is a Pro feature
See how each signal's components blend into its final score, and which signals + service lines this county should prioritize. Available on Professional, Consultant Studio, and Enterprise.
On the full platform
What else is available for Jefferson County
The page above is a subset. The free Community account unlocks the full single-county profile: every indicator, every data source, demographics, historical trends, and mortality data. Professional unlocks multi-county comparison, compound signal analysis, service line rankings, and consultant-ready PDF reports.
Full Environmental Profile
All 40+ environmental metrics including toxic releases, hazardous site proximity, PFAS detection, pesticide exposure, and climate stress indicators.
Service Line Opportunities
See how Jefferson County ranks for respiratory, oncology, cardiovascular, renal, endocrine, and behavioral health service line opportunity.
Multi-County Comparison
Compare Jefferson County side-by-side with neighboring counties across every dimension.
Trend Analysis
5-year sparklines for health outcomes, SDOH measures, and mortality rates so you can see where the county is heading, not just where it is today.
PDF Report Export
Generate a consultant-ready environmental health briefing for Jefferson County with methodology citations. Drops straight into a CHNA or grant application.
Nearby Counties
Counties bordering Jefferson County
Adjacent county profiles with their own scores and environmental health data. Source: Census Bureau County Adjacency File.
Switzerland County
Indiana
64
Elevated
Jennings County
Indiana
58
Elevated
Trimble County
Kentucky
57
Elevated
Scott County
Indiana
57
Elevated
Carroll County
Kentucky
54
Moderate
Clark County
Indiana
51
Moderate
Data sources: EPA AQS, EPA EJSCREEN, EPA TRI, CDC PLACES, CDC WONDER, CMS NPPES, Census ACS, County Health Rankings, NOAA ACIS, NCI State Cancer Profiles. Every score on this page is derived from publicly available federal data, fused by the Banana Analytics pipeline.
Methodology: See the full scoring methodology (v1.2.0) for weights, sensitivity analysis, and validation against county-level mortality data.
Last refreshed: May 28, 2026