Yearly Traffic Safety Analysis

184 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In Adair County, total crashes decreased by 15.21%, from 217 crashes in 2022 to 184 crashes in 2023. A significant shift was observed in fatalities, which dropped from 5 in 2022 to 0 in 2023, representing a 100% decrease. Conversely, total injuries increased by 24.56%, rising from 57 in 2022 to 71 in 2023.

184

▼ -15.2%was 217

Total Crash Events

0

▼ -100.0%was 5

Persons Killed

71

▲ 24.6%was 57

Persons Injured

0

▼ -100.0%was 5

Fatal Crash Events

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash trends in Adair County show a decrease in total incidents, with a 15.21% reduction in crashes from 217 in 2022 to 184 in 2023. Fatalities saw a complete elimination, dropping from 5 in 2022 to 0 in 2023. However, total injuries rose by 24.56% year-over-year, from 57 to 71.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 5↓-100.0%

71

Motorists Injured

Prior: 56↑26.8%

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal distribution of crashes showed shifts in peak times between the two periods. In 2023, the peak day for crashes was Saturday with 34 incidents, while in 2022, Monday had the highest count with 42 crashes. The peak hour also changed, with 11 AM recording the most crashes (15) in 2023, compared to 5 PM (16 crashes) in 2022.

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes were eliminated in 2023, dropping from 5 (2.3% of crashes) in 2022 to 0 (0% of crashes). However, serious injuries (Severity A) increased from 7 in 2022 to 8 in 2023, and minor injuries (Severity B) rose from 14 to 22. Possible injuries (Severity C) remained relatively stable, decreasing slightly from 21 in 2022 to 20 in 2023.

Outcome by Severity (Crash Events)

Serious Injury8serious injury crashes4.3%
↑14.3%prior 7
Minor Injury22minor injury crashes12%
↑57.1%prior 14
Possible Injury20possible injury crashes10.9%
↓-4.8%prior 21
No Injury134no injury crashes72.8%
↓-21.2%prior 170

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record

Top Contributing Factors

Animal-related crashes, the top contributing factor in both years, decreased from 39 incidents in 2022 to 35 in 2023. Crashes attributed to 'Lost Control' decreased by 6, from 30 to 24, and 'Ran off road - straight' decreased by 8, from 31 to 23. Notably, 'Improper or erratic lane changing' crashes saw a substantial increase, rising from 2 incidents in 2022 to 10 in 2023.

Officer-Reported Primary Contributing Cause

Animal35 (19%)↓-10.3%prior 39
Lost Control24 (13%)↓-20.0%prior 30
Ran off road - straight23 (12.5%)↓-25.8%prior 31
Driving too fast for conditions19 (10.3%)↓-29.6%prior 27
Improper or erratic lane changing10 (5.4%)
Ran off road - left9 (4.9%)↓-30.8%prior 13
Driver Distraction: Other interior distraction6 (3.3%)↑20.0%prior 5
Operating vehicle in an reckless, erratic, careless, negligent manner6 (3.3%)
Followed too close4 (2.2%)↓-69.2%prior 13
FTYROW: From stop sign4 (2.2%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Regarding weather conditions, crashes in clear weather decreased from 120 in 2022 to 96 in 2023, while crashes during snowy conditions increased from 7 to 20. In terms of lighting, crashes in dark conditions with unlighted roadways decreased from 59 in 2022 to 37 in 2023. Road surface conditions saw a decrease in crashes on wet surfaces, from 33 in 2022 to 21 in 2023, and on icy/frosty surfaces, from 12 to 6.

Weather

Clear96 (60.8%)
↓-20.0%prior 120
Cloudy26 (16.5%)
→0.0%prior 26
Snow20 (12.7%)
↑185.7%prior 7
Rain11 (7.0%)
↓-31.3%prior 16
Fog, smoke, smog2 (1.3%)
Freezing rain/drizzle1 (0.6%)
Blowing Snow1 (0.6%)
↓-83.3%prior 6
Severe Winds1 (0.6%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash

Lighting

Daylight109 (69.4%)
↑2.8%prior 106
Dark - roadway not lighted37 (23.6%)
↓-37.3%prior 59
Dark - roadway lighted4 (2.5%)
↓-33.3%prior 6
Dusk4 (2.5%)
Dawn3 (1.9%)
↓-57.1%prior 7

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field

Road Surface

Dry105 (66.5%)
↓-7.9%prior 114
Wet21 (13.3%)
↓-36.4%prior 33
Snow12 (7.6%)
↓-14.3%prior 14
Ice/frost6 (3.8%)
↓-50.0%prior 12
Slush6 (3.8%)
Gravel6 (3.8%)
↓-25.0%prior 8
Oil1 (0.6%)
Other (explain in narrative)1 (0.6%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field

Vehicles & Demographics

The total number of persons involved in crashes decreased from 418 in 2022 to 354 in 2023. The 16-20 age group saw an increase in involved persons, rising from 22 in 2022 to 42 in 2023, while the 35-44 age group experienced a significant decrease, from 97 to 52. Ford and Chev remained the top vehicle makes involved in crashes, with Ford decreasing from 42 to 36 and Chev from 34 to 28 year-over-year.

Top Vehicle Makes (250 vehicles)

1
FORD36 (14.4%)
↓-14.3%prior 42
2
CHEV28 (11.2%)
↓-17.6%prior 34
3
CHEVROLET22 (8.8%)
↑10.0%prior 20
4
FREIGHTLINER14 (5.6%)
↓-48.1%prior 27
5
KENWORTH10 (4%)
↑100.0%prior 5
6
GMC9 (3.6%)
→0.0%prior 9
7
RAM8 (3.2%)
↑60.0%prior 5
8
JEEP8 (3.2%)
→0.0%prior 8
9
TOYOTA7 (2.8%)
↓-30.0%prior 10
10
TOYO6 (2.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records

16 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (239 persons with recorded sex)

Male162 (67.8%)
↓-15.6%prior 192
Female77 (32.2%)
↑4.1%prior 74

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events

Data Sources & Methodology

Primary Data Source

All crash data in this report is sourced from Iowa Crash Data, accessed programmatically via the ArcGIS Open Data API (SODA). This dataset contains official police-reported motor vehicle traffic crash records maintained by the reporting jurisdiction's law enforcement agency. Records are published to the open data portal by the municipality and are subject to the portal's terms of use.

Data Retrieval

  • Access method: ArcGIS Open Data API (SoQL queries)
  • Data format: Structured JSON via REST API
  • Record types queried: Crash events, person records, and vehicle unit records
  • Date filter applied: 2023-01-01 through 2023-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 184
  • Total persons involved: 354
  • Total vehicles involved: 250

Analytical Methodology

  • Severity classification: Uses the KABCO injury scale (K=Fatal, A=Incapacitating injury, B=Non-incapacitating injury, C=Possible injury, O=No injury/property damage only), the standard classification in U.S. Model Minimum Uniform Crash Criteria (MMUCC). Severity is assigned per crash event based on the most severe injury in that crash. A single fatal crash (K) may involve multiple fatalities; therefore the "Persons Killed" count in the headline KPIs may differ from the "Fatal" crash count in the severity breakdown.
  • Contributing factors: Reflect the officer-determined primary contributory cause recorded at the time of the crash report. These are preliminary determinations and may not reflect final investigation findings.
  • Hit-and-run classification: Based on the hit-and-run indicator field in the official crash report, as determined by the responding officer at the scene.
  • Temporal analysis: Day-of-week and hour-of-day distributions are computed from the crash date/time timestamp in each record.
  • Demographics: Age and sex distributions are drawn from person-level records linked to each crash event. A single crash may involve multiple persons.
  • Vehicle data: Make information is drawn from vehicle unit records linked to each crash event.
  • AI commentary: Narrative sections are generated by Google Gemini (large language model) based on the structured data. Commentary is descriptive, not predictive, and should not be interpreted as expert opinion.

Limitations & Disclaimers

  • Only crashes reported to and documented by law enforcement are included. Minor incidents, unreported crashes, and near-misses are not captured in this dataset.
  • Data reflects conditions at the time of the initial police report and may be subject to subsequent corrections, reclassifications, or supplements by the reporting agency.
  • Open data portal records may experience a publication lag - recently occurring crashes may not yet appear in the dataset at the time of report generation.
  • AI-generated commentary is produced by a large language model and is intended to highlight patterns in the data. It does not constitute legal, medical, or professional analysis.
  • Percentages are calculated from reported data and are subject to rounding.

Non-Affiliation Disclosure

This report is produced independently by ThatCarHitMe.com (Injuria.ai). It is not affiliated with, endorsed by, or produced in partnership with any law enforcement agency, municipal government, state department of transportation, or the National Highway Traffic Safety Administration (NHTSA). Data is sourced from publicly available government open data portals.

Data License

The underlying crash data is provided under the municipality's Open Data Terms of Use and is made available to the public for unrestricted use. This analysis and report is © 2026 Injuria.ai and may be cited with attribution using the suggested citation below.

Corrections & Feedback

If you believe any data in this report is inaccurate or have questions about our methodology, please contact: data@injuria.ai. We are committed to accuracy and will issue corrections promptly.

Suggested Citation

ThatCarHitMe.com (Injuria.ai). "iowa, IA Crash Intelligence Report: 2023." Published September 9, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2023-annual-report

About the Publisher

ThatCarHitMe.com is a crash data intelligence platform developed by Injuria.ai, a legal technology company specializing in traffic safety analytics. We aggregate and analyze publicly available government crash data to produce structured intelligence reports for communities, researchers, journalists, and legal professionals. Our reports combine programmatic data retrieval from official open data portals with AI-assisted narrative analysis.

Questions about this report's data or methodology: data@injuria.ai

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