Yearly Traffic Safety Analysis

540 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In 2023, Marion County recorded 540 total crashes, a 4.3% decrease from the 564 crashes documented in 2022. Despite the overall reduction in collisions, the number of injuries rose by 8.6%, from 140 to 152. The most significant year-over-year shift was a 60% increase in crashes attributed to reckless, erratic, careless, or negligent driving, which grew from 20 incidents in 2022 to 32 in 2023.

540

▼ -4.3%was 564

Total Crash Events

2

Persons Killed

152

▲ 8.6%was 140

Persons Injured

2

Fatal Crash Events

Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) 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 traffic collisions in Marion County showed a slight decline in 2023 compared to the previous year. The total number of crashes decreased by 4.3%, from 564 in 2022 to 540 in 2023. However, the outcomes of these crashes worsened, with total injuries increasing by 8.6% year-over-year, while fatalities held steady at two for both periods.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

1

Motorists Killed

Prior: 2↓-50.0%

1

Other Killed

Prior: 0→%

2

Pedestrians Injured

Prior: 3↓-33.3%

4

Cyclists Injured

Prior: 2↑100.0%

145

Motorists Injured

Prior: 135↑7.4%

1

Other Injured

Prior: 0→%

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 timing of crashes shifted slightly between the two periods. In 2023, the peak day for crashes was Wednesday with 91 incidents, a change from Thursday (101 incidents) in 2022. The peak hour also moved later, from the 5 p.m. hour in 2022 (48 crashes) to the 6 p.m. hour in 2023 (45 crashes), though both years show a concentration of crashes during the afternoon and evening commute hours.

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

The severity of crashes showed mixed results year-over-year. The number of fatal crashes remained unchanged at two in both 2023 and 2022, with the fatal crash rate holding nearly steady at 0.37% and 0.35% respectively. The proportion of crashes resulting in any form of injury increased slightly from 21.3% in 2022 to 22.2% in 2023, while the share of crashes with no reported injuries decreased from 78.4% to 77.4%.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.4%
→0.0%prior 2
Serious Injury16serious injury crashes3%
→0.0%prior 16
Minor Injury44minor injury crashes8.1%
↓-18.5%prior 54
Possible Injury60possible injury crashes11.1%
↑20.0%prior 50
No Injury418no injury crashes77.4%
↓-5.4%prior 442

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

Collisions involving an animal remained the leading contributing factor in both years, with counts increasing by 6% from 165 in 2022 to 175 in 2023. A notable shift occurred with crashes attributed to "Operating vehicle in a reckless, erratic, careless, negligent manner," which surged by 60% from 20 to 32 incidents, becoming the third-most common factor in 2023. Conversely, incidents involving "FTYROW: From stop sign" decreased by 25% from 40 to 30, and "Lost Control" crashes dropped by 32% from 31 to 21.

Officer-Reported Primary Contributing Cause

Animal175 (32.4%)↑6.1%prior 165
Followed too close42 (7.8%)↑16.7%prior 36
Operating vehicle in an reckless, erratic, careless, negligent manner32 (5.9%)↑60.0%prior 20
FTYROW: From stop sign30 (5.6%)↓-25.0%prior 40
Ran off road - straight21 (3.9%)↑31.3%prior 16
Improper Backing21 (3.9%)
Lost Control21 (3.9%)↓-32.3%prior 31
Driver Distraction: Other interior distraction20 (3.7%)↑42.9%prior 14
Driving too fast for conditions20 (3.7%)↑17.6%prior 17
Ran Stop Sign19 (3.5%)↑26.7%prior 15

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

Road & Environmental Conditions

The conditions under which crashes occurred saw some shifts year-over-year. Crashes in dark conditions (both lighted and unlighted roadways) accounted for a larger share of total incidents in 2023, rising to 21.5% from 17.1% in 2022. Conversely, the proportion of crashes happening on adverse road surfaces like wet, snow, or ice decreased from 14.0% in 2022 to 10.0% in 2023. Crashes during adverse weather conditions also saw a slight proportional decrease.

Weather

Clear309 (76.1%)
↓-5.8%prior 328
Cloudy61 (15.0%)
↑32.6%prior 46
Rain15 (3.7%)
↑7.1%prior 14
Snow15 (3.7%)
↓-16.7%prior 18
Fog, smoke, smog4 (1.0%)
Sleet, hail1 (0.2%)
Blowing Snow1 (0.2%)

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

Lighting

Daylight270 (65.5%)
↓-9.7%prior 299
Dark - roadway not lighted76 (18.4%)
↑11.8%prior 68
Dark - roadway lighted40 (9.7%)
↑42.9%prior 28
Dusk18 (4.4%)
↑28.6%prior 14
Dawn6 (1.5%)
↓-45.5%prior 11
Dark - unknown roadway lighting2 (0.5%)

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

Road Surface

Dry324 (79.4%)
↑6.6%prior 304
Wet33 (8.1%)
↓-5.7%prior 35
Gravel30 (7.4%)
↓-21.1%prior 38
Snow12 (2.9%)
↓-52.0%prior 25
Ice/frost5 (1.2%)
↓-58.3%prior 12
Slush3 (0.7%)
↓-40.0%prior 5
Mud, dirt1 (0.2%)

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

Vehicles & Demographics

The top three vehicle makes involved in crashes—Ford, Chevrolet, and Dodge—remained consistent in rank for both 2023 and 2022, though counts for each saw a slight decline. Analysis of persons involved in crashes reveals shifts in age demographics, with the representation of the 35-44 age group increasing from a 14.4% share in 2022 to 16.2% in 2023. Conversely, the share of individuals aged 65 and older decreased from 15.1% to 13.5% over the same period.

Top Vehicle Makes (813 vehicles)

1
FORD156 (19.2%)
↓-7.7%prior 169
2
CHEV130 (16%)
↓-2.3%prior 133
3
DODG46 (5.7%)
↓-4.2%prior 48
4
JEEP37 (4.6%)
↓-2.6%prior 38
5
GMC33 (4.1%)
↑6.5%prior 31
6
CHEVROLET30 (3.7%)
↓-9.1%prior 33
7
NISS27 (3.3%)
↓-20.6%prior 34
8
BUIC25 (3.1%)
↓-10.7%prior 28
9
CHRY25 (3.1%)
↑38.9%prior 18
10
TOYT24 (3%)
↓-31.4%prior 35

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

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

Sex Distribution (756 persons with recorded sex)

Male443 (58.6%)
↓-8.7%prior 485
Female313 (41.4%)
↓-1.3%prior 317

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: 540
  • Total persons involved: 1,141
  • Total vehicles involved: 813

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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