ZIP 48756 Property Distress & Foreclosure Data

Ogemaw County, Michigan's ZIP 48756 registers 10/100 composite distress, which DLRadar reads as minimal. The most distinctive pressure shows up in construction/permit lag (50/100), structural risk (23/100), mortgage stress (9/100). On the quiet end sit mortgage stress (9/100) and institutional ownership (3/100). Structural exposure scores 23 and live distress 3 on the 0–100 scale.

The expansion-phase market in 48756 posted values that rose 6.4% over the year, and 44% higher over three years, at 37/100 phase confidence. Rising prices can mask pockets of distress, where per-parcel scoring earns its keep.

Population is roughly 3,939 with a median age of 51. DLRadar's demographic-stress index for the area reads 39/100. Owners hold 84% of homes, renters 16%. Vacancy runs 44.5%, above the national norm and a classic distress-and-opportunity signal. Home values center near $81,500, an affordability ratio of 2.2× — accessible. 24.5% of residents fall below the poverty threshold. Median household income is $39,435, below the U.S. median near $78,000. Rent burden reaches 80% of tenant households. There are about 3,126 housing units across 48756. Educational attainment sits at 7% bachelor's-or-above.

On the whole, 48756 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.

10/100
Composite stress
23/100
Structural risk
3/100
Distress activity

Distress signal breakdown — ZIP 48756

Foreclosure activity0
Mortgage stress9
Climate / FEMA risk32
+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 Ogemaw County

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Deterministic. Every signal traces to a public dataset · methodology