Your Neighborhood's Health Profile

Public health statistics are usually reported at the national or state level, but they obscure enormous local variation. This post uses the CDC's PLACES program – 40+ health measures at ZIP code level across ~30,000 ZIPs – to show how health outcomes are hyperlocal, with two adjacent ZIP codes sometimes differing more than two states.

The CDC measures 40+ health indicators at ZIP code level — obesity, diabetes, depression, smoking, blood pressure, and more — for virtually every ZIP in the US. Enter your ZIP code below to see how your neighborhood compares to the national median on a radar chart. The headline finding: health outcomes are hyperlocal. Two adjacent ZIP codes can differ more than two states.

Public health statistics are usually reported at the national or state level. "30% of American adults have high blood pressure." "The obesity rate is rising." These aggregates are real, but they obscure enormous local variation. The neighborhood where you grew up, where you work, and where you live now shapes your health in ways that national averages can't capture.

The CDC's PLACES program changes that. Every year, CDC combines the Behavioral Risk Factor Surveillance System (BRFSS) survey with small-area estimation models to produce 40+ health measures at the ZIP code level. The 2023 release covers 29,983 US ZIP Code Tabulation Areas (ZCTAs) — essentially complete coverage of the country's populated ZIP codes.

The measures span the full spectrum: chronic disease outcomes (diabetes, heart disease, stroke), health behaviors (smoking, physical inactivity, binge drinking), preventive care use (mammograms, dental visits, checkups), mental health (depression, poor mental health days), disability status, and health-related social needs (food insecurity, housing insecurity, lack of transportation).

This post lets you explore that landscape. The interactive section below pulls your ZIP code's data directly from the CDC API.

Enter any US ZIP code to see its health profile compared to the national median across 12 key measures. Data comes directly from the CDC PLACES API in real time.

The radar shows absolute prevalence rates (percent of adults). A ZIP "inside" the orange national median line on a given measure has lower-than-typical rates for that condition — generally better for disease outcomes, though not always (lower physical inactivity is better; lower preventive care rates are not).

Before looking at your specific ZIP, it's worth understanding how much variation exists across US ZIP codes. For each of the 12 measures in the radar chart, this shows the spread from the 10th to 90th percentile across all ZIPs.

The variation is substantial. Obesity ranges from roughly 15% in the lowest-prevalence ZIPs to over 55% in the highest. Depression spans from around 10% to 37%. Even stroke — relatively rare — varies threefold.

These aren't just statistical artifacts. They reflect real differences in built environment (walkability, food access), socioeconomic stress, healthcare access, and local culture. The 10th-percentile ZIP for obesity is a fundamentally different place to live — in terms of food environment, activity infrastructure, and population health — than the 90th-percentile ZIP.

Of all the correlations in the dataset, obesity and diabetes are the tightest. This scatter plots every ZIP code on both axes.

The correlation coefficient is approximately 0.90 — among the strongest relationships in social epidemiology. Every point is a ZIP code. The spread around the regression line is real: ZIPs at the same obesity rate can have substantially different diabetes rates, reflecting differences in healthcare access (diagnosis rates), diet quality, and racial composition (some groups have higher diabetes risk at lower BMI).

The geographic color coding shows regional clustering. Southern ZIPs (red/orange) are concentrated in the upper-right — high obesity, high diabetes. Pacific and Northeast ZIPs (blue, green) tend toward the lower-left.

CDC PLACES covers far more than just the 12 measures in the radar chart. This chart shows the national average crude prevalence for all 40 measures, sorted by value and colored by category.

A few things stand out in the full picture:

• High blood pressure (37.5% median) and obesity (36.7%) are the highest-prevalence chronic conditions — more than one in three adults.
• Poor sleep (35.9%) is in the same tier, rarely discussed as a public health crisis despite its scale.
• Preventive care gaps are significant: meaningful shares of adults haven't had a dental visit, mammogram, or colorectal cancer screening in the recommended timeframe.
• Social determinants (the Health-Related Social Needs category) show that food insecurity, housing insecurity, and lack of transportation affect substantial fractions of ZIP code populations. These are not fringe conditions.

All data comes from the CDC PLACES 2024 release, using 2023 BRFSS-based estimates (a few measures use 2022 data):

• Dataset: CDC PLACES ZCTA-level data — 40+ measures, ~29,983 ZIP Code Tabulation Areas, all US states
• Measure type: "Crude prevalence" — percentage of adults estimated to have each condition or behavior, without age adjustment
• Method: CDC uses multilevel regression and poststratification (MRP) to produce small-area estimates from BRFSS survey responses. The model combines local survey data with demographic predictors to generate stable estimates for small geographies like ZIP codes.

ZCTA vs ZIP code: Technically, CDC reports data at the ZCTA (ZIP Code Tabulation Area) level. ZCTAs are Census constructs that approximate ZIP codes but aren't identical. The ZIP code you enter is matched to the closest ZCTA; most populated ZIPs have direct ZCTA matches.

Interactive lookup: The radar chart fetches live data from the CDC SODA API. No data is stored; your ZIP code is sent directly to data.cdc.gov.

National medians: Computed from the 29,983 ZCTAs with available data for each measure. For the radar chart normalization, the values are: Obesity 36.7%, Diabetes 12.7%, Depression 23.0%, Smoking 15.0%, High BP 37.5%, Physical Inactivity 26.4%, Poor Mental Health 16.9%, Poor Physical Health 14.5%, Poor Sleep 35.9%, Binge Drinking 15.8%, Asthma 10.7%, Stroke 3.9%.