Yearly Traffic Safety Analysis

188 CRASHES IN
IOWA, IA
2016

All metrics benchmarked against2015

Total crashes in Adair County increased by 2.73% year-over-year, rising from 183 crashes in 2015 to 188 crashes in 2016. A significant shift was observed in fatalities, which increased from 0 in 2015 to 5 in 2016. Conversely, total injuries decreased from 56 to 50 during the same period.

188

▲ 2.7%was 183

Total Crash Events

5

Persons Killed

50

▼ -10.7%was 56

Persons Injured

4

Fatal Crash Events

Note: "Persons Killed" (5) counts individual fatalities across all crash events. "Fatal" in the severity table below (4) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the trend for crashes in Adair County shows a slight increase, with total crashes rising by 2.73% from 183 in 2015 to 188 in 2016. The most critical shift is the emergence of fatalities, which were zero in 2015 but rose to 5 in 2016.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

5

Motorists Killed

Prior: 0→%

3

Pedestrians Injured

Prior: 0→%

47

Motorists Injured

Prior: 56↓-16.1%

Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns for crashes in Adair County shifted year-over-year. The peak day for crashes moved from Friday with 41 crashes in 2015 to Thursday with 33 crashes in 2016. The peak hour also changed from 2 PM in 2015 to 6 AM in 2016, both recording 14 crashes.

Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity distribution of crashes saw notable changes, with fatal crashes increasing from 0 in 2015 to 4 in 2016, leading to a fatal crash rate of 2.1% in 2016. Serious injuries decreased from 7 to 4, while minor injuries increased from 18 to 25. Possible injuries also decreased, from 17 in 2015 to 12 in 2016.

Severity is per crash event (most severe injury). 4 fatal crash events resulted in 5 persons killed.

Outcome by Severity (Crash Events)

Fatal4fatal crashes2.1%
Serious Injury4serious injury crashes2.1%
↓-42.9%prior 7
Minor Injury25minor injury crashes13.3%
↑38.9%prior 18
Possible Injury12possible injury crashes6.4%
↓-29.4%prior 17
No Injury143no injury crashes76.1%
↑1.4%prior 141

Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · Most severe injury per crash record

Top Contributing Factors

Contributing factors showed shifts in crash counts year-over-year. Crashes involving 'Animal' increased by 5, from 40 in 2015 to 45 in 2016, maintaining its position as the top factor. 'Ran off road - straight' crashes increased by 11, from 23 to 34, while 'Lost Control' crashes decreased by 4, from 33 to 29. Additionally, 'Driver Distraction: Inattentive/lost in thought' crashes increased by 4, from 4 to 8.

Officer-Reported Primary Contributing Cause

Animal45 (23.9%)↑12.5%prior 40
Ran off road - straight34 (18.1%)↑47.8%prior 23
Lost Control29 (15.4%)↓-12.1%prior 33
Followed too close8 (4.3%)↓-42.9%prior 14
Ran off road - left8 (4.3%)↓-33.3%prior 12
Driver Distraction: Inattentive/lost in thought8 (4.3%)
Driving too fast for conditions8 (4.3%)↓-33.3%prior 12
Other (explain in narrative): Other5 (2.7%)
Exceeded authorized speed4 (2.1%)
FTYROW: Making left turn4 (2.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions increased by 9, from 90 in 2015 to 99 in 2016, while crashes in snowy conditions decreased by 12, from 21 to 9. Regarding road surface, dry conditions saw an increase of 16 crashes (91 to 107), and wet conditions decreased by 7 crashes (21 to 14). Crashes during daylight hours increased by 7, from 84 to 91, while those occurring at dusk decreased by 7, from 8 to 1.

Weather

Clear99 (64.3%)
↑10.0%prior 90
Cloudy29 (18.8%)
↑81.3%prior 16
Snow9 (5.8%)
↓-57.1%prior 21
Rain7 (4.5%)
↓-46.2%prior 13
Freezing rain/drizzle4 (2.6%)
Blowing Snow3 (1.9%)
↓-40.0%prior 5
Other (explain in narrative)1 (0.6%)
Severe Winds1 (0.6%)
Fog, smoke, smog1 (0.6%)
↓-85.7%prior 7

Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · Weather condition at time of crash

Lighting

Daylight91 (58.7%)
↑8.3%prior 84
Dark - roadway not lighted46 (29.7%)
↓-6.1%prior 49
Dawn8 (5.2%)
Dark - roadway lighted8 (5.2%)
↑14.3%prior 7
Dusk1 (0.6%)
↓-87.5%prior 8
Dark - unknown roadway lighting1 (0.6%)

Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · Lighting condition field

Road Surface

Dry107 (69.0%)
↑17.6%prior 91
Ice/frost19 (12.3%)
↑26.7%prior 15
Wet14 (9.0%)
↓-33.3%prior 21
Snow9 (5.8%)
↓-47.1%prior 17
Gravel5 (3.2%)
↓-37.5%prior 8
Oil1 (0.6%)

Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · Road surface condition field

Vehicles & Demographics

The top vehicle makes involved in crashes saw some shifts: Ford crashes decreased by 3 (42 to 39), while Chevrolet crashes increased by 4 (28 to 32). Toyota crashes notably increased by 11, from 2 in 2015 to 13 in 2016. In terms of persons involved, the 26-34 age group saw a decrease of 11 persons (61 to 50), while the 21-25 age group increased by 6 persons (30 to 36). The number of females involved in crashes decreased by 16, from 70 to 54.

Top Vehicle Makes (248 vehicles)

1
FORD39 (15.7%)
↓-7.1%prior 42
2
CHEVROLET32 (12.9%)
↑14.3%prior 28
3
CHEV19 (7.7%)
↓-13.6%prior 22
4
DODGE14 (5.6%)
↑27.3%prior 11
5
TOYOTA13 (5.2%)
6
DODG8 (3.2%)
↑60.0%prior 5
7
FREIGHTLINER8 (3.2%)
↓-52.9%prior 17
8
GMC6 (2.4%)
9
HONDA6 (2.4%)
10
PONT5 (2%)
→0.0%prior 5

Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · Vehicle unit records

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

Sex Distribution (192 persons with recorded sex)

Male138 (71.9%)
↑2.2%prior 135
Female54 (28.1%)
↓-22.9%prior 70

Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · 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: 2016-01-01 through 2016-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2016-01-01 through 2016-12-31 (366 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 188
  • Total persons involved: 284
  • Total vehicles involved: 248

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: 2016." Published September 9, 2026. Reporting period: 2016-01-01 to 2016-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2016-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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