County profile
Worth County, Missouri 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
21
−29 vs U.S. mean
Disease
80
+30 vs U.S. mean
Provider
84
+34 vs U.S. mean
SDOH
63
+13 vs U.S. mean
Specific health risk patterns
Worth County, MO: 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 Worth 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.
0.24% customer-hours of outage exposure against 57 DME-dependent Medicare beneficiaries (93.8 per 1k).
Power outage risk × Electricity-dependent medical population
Defend this finding — full lineage to source data6 sources cited
Outage VulnerabilityWorth County: 78/100 (elevated above the 70th-percentile threshold)
Worth County: 78/100 (elevated above the 70th-percentile threshold)
Summer heat × DOE/ORNL outage burden × emPOWER electricity-dependent Medicare × CHD/COPD prevalence × pre-1980 housing AC proxy. The compound that no aggregator surfaces.
Methodology. Combines structural heat exposure with an outage-burden track record AND a population uniquely harmed by outages (electricity-dependent DME) AND comorbidities that amplify outage harm (CHD/COPD) AND a housing-stock proxy for AC penetration. The pre-1980 housing leg is currently null pending Census ACS B25034 derivation; the score still computes from 4 of 5 components.
Threshold. Elevated when score ≥ 70th national percentile across all US counties evaluated for this signal
Peer set. 3,050 of 3,222 US counties (DOE EAGLE-I coverage); Alaska + sparsely-served rural may have no signal
Evidence base
- · McBrien H, Casey JA. 'Power outages and respiratory hospitalization risk in the US.' PLOS Medicine 2026 (8+ hour county outages → respiratory hospitalization RR 1.05).
- · Stone B et al. 'Compound climate and infrastructure events.' Environmental Science & Technology 2023 (heat × blackout doubles all-cause mortality in modeling; Phoenix worst-case ~13,000 deaths).
- · Brelsford C et al. 'A dataset of recorded electricity outages by US county 2014–2022.' Scientific Data 2024 (validates DOE/ORNL EAGLE-I).
Components (5)
86.9 °F
Mean of the daily maximum temperature across the meteorological summer (June–August).
NOAA — Applied Climate Information System (ACIS) — RCC-ACIS
Vintage: Multi-year mean (2018–2023 typical) · Refresh: Monthly · Lag: Current year
How it's measured. NOAA ACIS aggregates GHCN-Daily station observations to county-level summer (JJA) daily-max means using inverse-distance weighting. Smooths year-to-year noise; captures the structural heat profile.
Coverage. All 3,222 US counties
8.6K customer-hours
Total customer-hours of electrical outage in the county for the year, summed from 15-minute interval data.
DOE / ORNL — EAGLE-I — Environment for Analysis of Geo-Located Energy Information
Vintage: Annual rollup of 15-minute interval data · Refresh: Annual · Lag: 1 year
Source page →DOI: 10.6084/m9.figshare.24237376
How it's measured. DOE/ORNL aggregates utility-reported 15-minute outage counts across ~93% of US electricity customers, stitched into a continuous county-level outage timeline. Validated against utility filings in Brelsford et al, Scientific Data 2024.
Caveat. Excludes some smaller cooperatives; the 7% missing customers are concentrated in rural Alaska and parts of the rural West.
Coverage. 3,050 of 3,222 US counties (AK + sparsely-served rural may have no block)
93.8 per 1,000 Medicare benes
Rate of Medicare beneficiaries using power-dependent durable medical equipment (oxygen concentrators, ventilators, IV pumps, hospital beds) per 1,000 county beneficiaries.
HHS / ASPR — emPOWER Map — Medicare DME claims
Vintage: Current month · Refresh: Monthly · Lag: Same month
How it's measured. HHS ASPR derives power-dependent DME counts from Medicare claims for HCPCS codes covering ventilators, suction pumps, oxygen concentrators, NPWT pumps, and infusion pumps. The population most directly harmed by sustained outages.
Caveat. Same 1–10 masking as the dialysis rate. Underestimates total power-dependent population by Medicaid + commercial-insured + uninsured exclusion.
Coverage. All 3,222 US counties
Coronary heart disease + COPD blend15%
60/40 dominant/secondary percentile blend of CHD and COPD prevalence.
Methodology. Outage-vulnerability cluster — the conditions most directly harmed when a sustained outage halts both CPAP/BiPAP and rescue-medication workflows.
Components (2)
9.9%
Percent of adults age 18+ self-reporting coronary heart 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. Self-reported CHD undercounts asymptomatic disease.
Coverage. All 3,222 US counties
11.7%
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
57.7%
Percent of housing units built before 1980 — a proxy for central air conditioning penetration (post-1980 codes typically include central AC).
Census Bureau — American Community Survey — Table B25034 (Year Structure Built)
Vintage: ACS 5-Year 2019–2023 · Refresh: Quarterly · Lag: 1 year
How it's measured. Sum of B25034 categories for housing units built 1979 and earlier, divided by total occupied units. Used as a proxy for the share of housing without central AC; the post-1978 lead-paint ban and the post-1980 construction-code uplift roughly coincide.
Caveat. Currently null in the production JSON pending pipeline derivation (methodology v1.8.0). Outage Vulnerability score still computes from 4 of 5 components.
Coverage. All 3,222 US counties (when populated)
PM2.5 averages 7.1 µg/m³ against an asthma + COPD prevalence of 10.6% + 11.7%.
Air pollution exposure × Respiratory-vulnerable population
Defend this finding — full lineage to source data5 sources cited
Respiratory BurdenWorth County: 75/100 (elevated above the 70th-percentile threshold)
Worth County: 75/100 (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)
7.1 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)
10.6%
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
11.7%
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)
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
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
3 signals near threshold: Heat Vulnerability (70) · Runoff Burden (69) · Smoke Burden (66)
7 signals evaluated. See all signal methodologies →
Where Worth County stands
2 of 4 major health-risk areas are worse than national averages
In Worth County, Missouri, two major health-risk areas stand out as worse than the national average: chronic disease rates (worse than 80% of U.S. counties) and doctor and specialist access (worse than 84% of U.S. counties). More residents have chronic conditions that need ongoing care, but the county has fewer doctors and specialists per capita than most of the U.S. This is one of the most direct mismatches between health need and healthcare supply — more demand, fewer providers — and it's typically a top priority in any community health needs assessment.
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
Worth County compared to Missouri 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 (80) and Provider Gap (84) are worse than at least 70% of U.S. counties, the largest contributors to community health risk here.
SDOH Stress (63) is moderately worse than the U.S. average of 50.
Environmental Risk (21) is at or better than the U.S. average.
- Worth County
- Missouri state mean
- U.S. mean (50)
- Signal threshold (70)
Current Conditions
Today's air quality, fires, and weather alerts
Live operational data for Worth 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 Worth County with state and national benchmarks. Full profile covers 40+ metrics on the platform.
| Indicator | Worth County | MO avg | US avg |
|---|---|---|---|
PM2.5 (annual mean) EPA AQS / EJSCREEN | 7.1 µg/m³ ▼ -4.9% vs MO | 7.5 | 7.4 |
Ozone EPA AQS / EJSCREEN | 54.4 ppb ▼ -3.5% vs MO | 56.4 | 57.1 |
Traffic Proximity EJSCREEN | 67 index ▼ -100% vs MO | 159,297 | 291,320 |
Days Above 95°F NOAA ACIS | 2 days/yr ▼ -81% vs MO | 11 | 25 |
Superfund Proximity EPA EJSCREEN | 0.00 score ▼ -100% vs MO | 0.66 | 0.16 |
Drinking Water Violations EPA EJSCREEN | 0.39 score ▼ -15% vs MO | 0.46 | 3.39 |
Wildfire-Attributable Air Quality
Smoke PM2.5 the EPA doesn't count
Stanford peer-reviewed wildfire-attributable PM2.5 for Worth 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 Worth 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 Worth 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 Worth 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 Worth 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.GLYPHOSATE18.0K kg
- 2.METOLACHLOR & METOLACHLOR-S8.5K kg
- 3.METOLACHLOR-S6.8K kg
- 4.ATRAZINE5.7K kg
- 5.2,4-D3.9K 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 Worth County. Full profile covers 15+ health outcomes plus mortality on the platform.
| Condition | Worth County | MO avg | US avg |
|---|---|---|---|
Current Asthma % of adults with current asthma | 10.6% -1.5% vs MO | 10.8% | 10.6% |
COPD % of adults with diagnosed COPD | 11.7% ▲ +15% vs MO | 10.2% | 8.6% |
Diabetes % of adults with diagnosed diabetes | 15.5% ▲ +14% vs MO | 13.6% | 13.7% |
Coronary Heart Disease % of adults with CHD | 9.9% ▲ +19% vs MO | 8.3% | 7.9% |
Depression % of adults ever diagnosed with depression | 24.5% ▼ -2.3% vs MO | 25.1% | 23.1% |
Frequent Mental Distress % of adults with 14+ poor mental health days/month | 17.5% ▼ -3.5% vs MO | 18.1% | 17.2% |
Vulnerable Medicare Population
Who needs the grid to stay alive
Medicare beneficiaries in Worth 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 | 608 | — |
Electricity-dependent (any DME) Ventilators, oxygen concentrators, IV pumps, motorized wheelchairs | 57 | 93.8 ▲ +37% vs MO |
Dialysis-dependent ESRD beneficiaries needing in-center or home dialysis | 0 | 0.00 ▼ -100% vs MO |
Oxygen-dependent Home oxygen concentrators (outage-vulnerable) | 33 | 54.3 ▲ +108% vs MO |
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 Worth 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 | Worth County | US avg |
|---|---|---|
Primary Care Family medicine, internal medicine, general practice, pediatrics. | 102.2 per 100k ▼ -22% vs US | 130.4 |
Source: CMS National Plan and Provider Enumeration System (NPPES). Counts reflect providers with a primary practice address in Worth 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 Worth 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 Worth 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 Worth 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 Worth County ranks for respiratory, oncology, cardiovascular, renal, endocrine, and behavioral health service line opportunity.
Multi-County Comparison
Compare Worth 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 Worth County with methodology citations. Drops straight into a CHNA or grant application.
Nearby Counties
Counties bordering Worth County
Adjacent county profiles with their own scores and environmental health data. Source: Census Bureau County Adjacency File.
Taylor County
Iowa
52
Moderate
Harrison County
Missouri
50
Moderate
Ringgold County
Iowa
47
Moderate
Gentry County
Missouri
47
Moderate
Nodaway County
Missouri
33
Below Avg
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