Yearly Traffic Safety Analysis

312 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In 2023, Henry County recorded 312 total crashes, an 11.1% decrease from the 351 crashes reported in 2022. During this period, the number of people killed in crashes fell from 3 to 1, and total injuries decreased from 86 to 68. The most significant contributing factor in both years remained collisions with animals.

312

▼ -11.1%was 351

Total Crash Events

1

▼ -66.7%was 3

Persons Killed

68

▼ -20.9%was 86

Persons Injured

1

▼ -50.0%was 2

Fatal Crash Events

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) 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 crash volume in Henry County declined from 2022 to 2023. Total crashes fell by 11.1%, from 351 incidents to 312. This downward trend was also reflected in crash outcomes, with total fatalities decreasing from 3 to 1 and total injuries dropping from 86 to 68.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

1

Motorists Killed

Prior: 3↓-66.7%

2

Pedestrians Injured

Prior: 0→%

66

Motorists Injured

Prior: 86↓-23.3%

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 showed some shifts between the two periods. While Wednesday remained the peak day for crashes in both 2023 (53 crashes) and 2022 (62 crashes), the peak hour changed. In 2023, the most frequent time for crashes was the 5 p.m. hour with 27 incidents, a shift from 2022's peak at the 8 p.m. hour, which saw 29 crashes.

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

Crash severity outcomes improved from 2022 to 2023. The number of fatal crashes decreased from 2 to 1, and the total number of fatalities fell from 3 to 1. The proportion of crashes resulting in any level of injury (fatal, serious, minor, or possible) also decreased, accounting for 19.2% of all crashes in 2023 compared to 20.8% in 2022. Consequently, crashes resulting in no injury made up a larger share of the total, rising from 79.2% in 2022 to 80.8% in 2023.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.3%
↓-50.0%prior 2
Serious Injury11serious injury crashes3.5%
↓-8.3%prior 12
Minor Injury24minor injury crashes7.7%
↓-4.0%prior 25
Possible Injury24possible injury crashes7.7%
↓-29.4%prior 34
No Injury252no injury crashes80.8%
↓-9.4%prior 278

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 top contributing factor in both periods, though the count of such incidents decreased from 134 in 2022 to 114 in 2023. 'Lost Control' was the second-most cited factor in both years, with its count also falling from 31 to 23. A notable shift occurred with 'Ran off road - straight' crashes, which increased by 75% from a count of 12 incidents in 2022 to 21 in 2023. Conversely, crashes attributed to 'Driving too fast for conditions' saw their count drop from 19 in 2022 to 10 in 2023.

Officer-Reported Primary Contributing Cause

Animal114 (36.5%)↓-14.9%prior 134
Lost Control23 (7.4%)↓-25.8%prior 31
Ran off road - straight21 (6.7%)↑75.0%prior 12
FTYROW: From stop sign12 (3.8%)↓-14.3%prior 14
Operating vehicle in an reckless, erratic, careless, negligent manner12 (3.8%)→0.0%prior 12
Driver Distraction: Other interior distraction12 (3.8%)↑20.0%prior 10
Driving too fast for conditions10 (3.2%)↓-47.4%prior 19
Other (explain in narrative): Other10 (3.2%)→0.0%prior 10
Ran Stop Sign9 (2.9%)↓-10.0%prior 10
Ran off road - left9 (2.9%)→0.0%prior 9

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

Road & Environmental Conditions

Crashes in clear weather and on dry roads remained the most common scenarios in both years. In 2023, there were 154 crashes in clear weather and 162 on dry roads, compared to 162 and 160, respectively, in 2022. Crashes during snowfall increased, rising from a count of 5 in 2022 to 11 in 2023. Regarding lighting, the number of crashes occurring in daylight decreased from 160 to 131, while crashes on unlit dark roadways increased from 40 to 47.

Weather

Clear154 (74.8%)
↓-4.9%prior 162
Cloudy22 (10.7%)
↓-46.3%prior 41
Snow11 (5.3%)
↑120.0%prior 5
Rain9 (4.4%)
↓-40.0%prior 15
Fog, smoke, smog3 (1.5%)
Blowing sand, soil, dirt2 (1.0%)
Freezing rain/drizzle2 (1.0%)
Other (explain in narrative)2 (1.0%)
Blowing Snow1 (0.5%)
↓-80.0%prior 5

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

Lighting

Daylight131 (63.3%)
↓-18.1%prior 160
Dark - roadway not lighted47 (22.7%)
↑17.5%prior 40
Dark - roadway lighted16 (7.7%)
↓-20.0%prior 20
Dawn6 (2.9%)
→0.0%prior 6
Dusk6 (2.9%)
↓-14.3%prior 7
Dark - unknown roadway lighting1 (0.5%)

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

Road Surface

Dry162 (78.6%)
↑1.3%prior 160
Wet15 (7.3%)
↓-46.4%prior 28
Gravel10 (4.9%)
↓-60.0%prior 25
Snow9 (4.4%)
↓-35.7%prior 14
Ice/frost5 (2.4%)
Slush3 (1.5%)
Mud, dirt2 (1.0%)

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

Vehicles & Demographics

The most common vehicle makes involved in crashes remained consistent, with Chevrolet (60 vehicles) and Ford (53 vehicles) leading in 2023, though both saw a decrease in count from 70 and 64 respectively in 2022. Regarding the age of persons involved in crashes, the 35-44 age group was the largest cohort in 2023 with 107 individuals, overtaking the 26-34 age group which was the largest in 2022 with 122 individuals. The total number of persons involved in crashes decreased from 715 in 2022 to 619 in 2023.

Top Vehicle Makes (425 vehicles)

1
CHEV60 (14.1%)
↓-14.3%prior 70
2
FORD53 (12.5%)
↓-17.2%prior 64
3
TOYT27 (6.4%)
↓-12.9%prior 31
4
JEEP25 (5.9%)
↑25.0%prior 20
5
DODG21 (4.9%)
↓-32.3%prior 31
6
GMC19 (4.5%)
↓-13.6%prior 22
7
PONT16 (3.8%)
8
NISS16 (3.8%)
↑33.3%prior 12
9
CHEVROLET15 (3.5%)
↓-21.1%prior 19
10
HOND14 (3.3%)
↑7.7%prior 13

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

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

Sex Distribution (405 persons with recorded sex)

Male239 (59.0%)
↓-7.4%prior 258
Female166 (41.0%)
↓-17.4%prior 201

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: 312
  • Total persons involved: 619
  • Total vehicles involved: 425

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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