ZIP 15429 Property Distress & Foreclosure Data

ZIP code 15429 in Washington County, Pennsylvania carries a composite property-distress score of 26/100 — a low reading on DLRadar's deterministic public-record index. What sets it apart are the readings on construction/permit lag (63/100), structural risk (59/100), institutional ownership (21/100). On the quiet end sit institutional ownership (21/100) and mortgage stress (9/100). Environmental exposure also runs high (flood (NFIP) exposure (94/100), climate & FEMA risk (84/100)). The latent-versus-live split is 59/100 structural and 3/100 already moving.

The peak-phase market in 15429 posted values that rose 4.7% over the year (phase confidence 31/100). Near a top, distress surfaces unevenly, so parcel screening beats headline strength.

The demographic-stress sub-score lands at 17/100. The poverty rate is 9.7%. At $53,056, median income runs below typical U.S. levels. Around 20% of adults hold a bachelor's degree or higher. The vacancy rate is 23.0% — elevated. Population is roughly 464 with a median age of 37. Around 0% of renters are cost-burdened. 97% of housing is owner-occupied. The ZIP holds roughly 234 housing units. The typical home is worth about $75,000 (1.2× income, relatively affordable).

On the whole, 15429 leans distressed, with opportunity clustered in specific stressed parcels. Every signal above traces to a verifiable public dataset, refreshed continuously and scored the same way in every ZIP nationwide.

26/100
Composite stress
59/100
Structural risk
3/100
Distress activity

Distress signal breakdown — ZIP 15429

Foreclosure activity0
Mortgage stress9
Climate / FEMA risk84
+9 more distress dimensions scored for this ZIP

Tax delinquency, institutional ownership, insurance pressure, NFIP/flood, construction lag, price dislocation and auction velocity — plus the 0 individual distressed properties (owner, address, APN, per-property score and exit read) are in the full DLRadar report.

Nearby ZIPs in Washington County

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Deterministic. Every signal traces to a public dataset · methodology