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Increasing· Urban (RUCC 2)· Reported APS financial-abuse allegations
Data completeness
97.2%
of the 72 monthly values published as exact counts · 1 suppressed · 1 blank
FY2024–25 reported rate
90.6

Reported allegations per 10,000 residents age 65+

Estimated annual change
+10.9%

Modeled annual change in the reported allegation rate relative to the population age 65+

Trend classification
Increasing

Significant after FDR correction (q = <0.001)

Residents age 65+
76,271

American Community Survey 2024 5-year estimate

Interpretation

In FY2024–25, Stanislaus County recorded 90.6 reported financial-abuse allegations per 10,000 residents age 65+. Over the six-year window the modelled rate changed by about 10.9% per year upward, which was classified as increasing.

The classification describes the direction of reporting within this county over time. It does not rank this county against others and does not measure how much elder financial exploitation occurs here.

With about 76,271 residents age 65+, the denominator here is large enough that the rate is not driven by a handful of individual reports. Roughly 1.4% of this county's monthly values were withheld, which widens the plausible range around each annual rate.

SOC 242 records allegations reported to county Adult Protective Services agencies. It does not measure confirmed or substantiated abuse and should not be interpreted as the true prevalence of elder financial exploitation.

Data quality flags
  • · Low suppression
  • · No small-population flag
  • · Standard interpretation

Reported allegation rate by fiscal year

Midpoint scenario with the low–high range implied by suppressed monthly counts. Where a county publishes every month exactly, the band collapses onto the line.

02652781042019–202020–212021–222022–232023–242024–25Fiscal year
Midpoint scenarioLow–high suppression scenario rangeReported allegations per 10,000 residents age 65+
Stanislaus County reported allegations and rates by fiscal year
Fiscal yearMonths availableSuppressed monthsReported allegationsRate per 10,000 age 65+
FY2019–2012040958.7
FY2020–2112035349.6
FY2021–2211044467.9
FY2022–23121345–35446.9–48.1
FY2023–2412067890.5
FY2024–2512069190.6

What could explain this pattern?

  • · Awareness and outreach. Public campaigns and mandated-reporter training change how many concerns reach APS.
  • · Agency capacity. Intake staffing, hotline hours, and case-coding practices affect what gets recorded.
  • · Referral pathways. Bank, law-enforcement, and healthcare partnerships route reports differently by county.
  • · Population structure. With 76,271 residents age 65+, the denominator is large enough that the rate is not driven by a handful of individual reports.
  • · Suppression. 1.4% of this county's monthly values were published as “*” rather than as numbers, which widens the plausible descriptive range.

These are candidate explanations only. Nothing on this page establishes causation.

County demographics vs. California county average

Unweighted average across all 58 counties. Context only: these variables are not used to predict the reported rate.

Residents age 65+76,271
CA county average: 106,179
Senior share of population13.8%
CA county average: 19.4%
Median household income$81,468
CA county average: $89,387
Poverty rate13.5%
CA county average: 12.8%
Bachelor's degree or higher19.6%
CA county average: 30.5%
Broadband access92.1%
CA county average: 91.0%
Senior disability37.9%
CA county average: 34.3%
Seniors living alone (65+)22.4%
CA county average: 23.9%
Population density370.3/mi²
CA county average: 696.4/mi²
How to read this profile

Reported APS allegations are not confirmed cases and do not measure the true prevalence of elder financial exploitation.

Methodology for this page

Monthly SOC 242 financial-abuse allegation counts were assembled for a common six-year window (FY2019–20 through FY2024–25). Small monthly counts are published as “*” rather than as numbers, so each suppressed month is treated as an interval-censored count from 1 through 10 and propagated into low, midpoint and high scenarios. Across the six completed fiscal years, published SOC 242 files consistently showed numeric zeroes, no positive numeric values from 1 through 10, and a minimum published positive value of 11. The Observatory therefore treats “*” observations as interval-censored counts from 1 through 10. This interval is empirically inferred from the publication pattern and is not presented as an officially documented CDSS suppression rule.

Rates use year-specific population age 65+ as exposure. Trends come from interval-censored Negative Binomial models fitted per county, with significance corrected across all 58 counties using the Benjamini–Hochberg false discovery rate procedure.