Yearly Traffic Safety Analysis

10,675 CRASHES IN
IOWA, IA
2016

All metrics benchmarked against2015

In 2016, Polk County experienced 10,675 crashes, an increase of 7.17% compared to the 9,961 crashes reported in 2015. The most significant year-over-year shift was a 40% increase in total fatalities, rising from 20 in 2015 to 28 in 2016.

10,675

▲ 7.2%was 9,961

Total Crash Events

28

▲ 40.0%was 20

Persons Killed

3,660

▲ 2.4%was 3,575

Persons Injured

27

▲ 42.1%was 19

Fatal Crash Events

Note: "Persons Killed" (28) counts individual fatalities across all crash events. "Fatal" in the severity table below (27) 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, crash data for Polk County shows an upward trend year-over-year. Total crashes increased by 7.17%, from 9,961 in 2015 to 10,675 in 2016. This was accompanied by a significant 40% rise in total fatalities, from 20 to 28, and a 2.38% increase in total injuries, from 3,575 to 3,660.

Vulnerable Road User Casualties

5

Pedestrians Killed

Prior: 4↑25.0%

0

Cyclists Killed

Prior: 1↓-100.0%

23

Motorists Killed

Prior: 15↑53.3%

0

Other Killed

Prior: 0→0.0%

110

Pedestrians Injured

Prior: 110→0.0%

74

Cyclists Injured

Prior: 67↑10.4%

3,469

Motorists Injured

Prior: 3,394↑2.2%

7

Other Injured

Prior: 4↑75.0%

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 of crashes remained consistent year-over-year, with Friday continuing to be the peak day and 5 PM the peak hour for crashes. Crashes on Fridays increased by 7.45% from 1,717 in 2015 to 1,845 in 2016, while crashes at 5 PM saw a 15.23% increase, rising from 985 to 1,135.

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

Fatal crashes increased by 42.11%, rising from 19 in 2015 to 27 in 2016, and the fatal crash rate increased from 0.19% to 0.25%. Serious injury crashes decreased by 13%, from 154 to 134. Minor injury crashes increased by 6.36% (from 802 to 853), and possible injury crashes increased by 8.04% (from 2,202 to 2,379).

Severity is per crash event (most severe injury). 27 fatal crash events resulted in 28 persons killed.

Outcome by Severity (Crash Events)

Fatal27fatal crashes0.3%
↑42.1%prior 19
Serious Injury134serious injury crashes1.3%
↓-13.0%prior 154
Minor Injury853minor injury crashes8%
↑6.4%prior 802
Possible Injury2,379possible injury crashes22.3%
↑8.0%prior 2,202
No Injury7,282no injury crashes68.2%
↑7.3%prior 6,784

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

The leading contributing factor, 'Followed too close', increased by 154 crashes (8.86%), from 1,739 in 2015 to 1,893 in 2016. 'FTYROW: Making left turn' crashes decreased by 19 (2.76%), dropping from 688 to 669, while 'Other (explain in narrative): Other' increased by 30 crashes (4.44%), rising from 675 to 705. 'Driving too fast for conditions' also saw an increase of 23 crashes (3.90%), from 589 to 612.

Officer-Reported Primary Contributing Cause

Followed too close1,893 (17.7%)↑8.9%prior 1,739
Other (explain in narrative): Other705 (6.6%)↑4.4%prior 675
FTYROW: Making left turn669 (6.3%)↓-2.8%prior 688
Ran off road - left633 (5.9%)↑20.3%prior 526
Driving too fast for conditions612 (5.7%)↑3.9%prior 589
Ran Traffic Signal586 (5.5%)↓-0.5%prior 589
FTYROW: From stop sign481 (4.5%)↑6.2%prior 453
Operating vehicle in an reckless, erratic, careless, negligent manner411 (3.9%)↑19.5%prior 344
Lost Control347 (3.3%)↑10.9%prior 313
Improper or erratic lane changing303 (2.8%)↑21.2%prior 250

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 increased by 9.01% (from 5,762 to 6,281), while those in rainy conditions decreased by 31.41% (from 1,006 to 690). On road surfaces, crashes on dry roads increased by 12.27% (from 7,132 to 8,007), and crashes on icy/frosty roads increased by 22.29% (from 314 to 384). Crashes during dusk saw a 29.05% increase, rising from 210 to 271.

Weather

Clear6,281 (60.3%)
↑9.0%prior 5,762
Cloudy2,798 (26.9%)
↑17.0%prior 2,391
Rain690 (6.6%)
↓-31.4%prior 1,006
Snow404 (3.9%)
↑4.4%prior 387
Freezing rain/drizzle139 (1.3%)
↑98.6%prior 70
Fog, smoke, smog45 (0.4%)
→0.0%prior 45
Blowing Snow38 (0.4%)
↓-26.9%prior 52
Severe Winds11 (0.1%)
↑83.3%prior 6
Sleet, hail7 (0.1%)
↑40.0%prior 5
Other (explain in narrative)3 (0.0%)

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

Lighting

Daylight7,486 (71.5%)
↑6.5%prior 7,030
Dark - roadway lighted2,087 (19.9%)
↑5.8%prior 1,973
Dark - roadway not lighted400 (3.8%)
↑19.0%prior 336
Dusk271 (2.6%)
↑29.0%prior 210
Dawn195 (1.9%)
↑4.3%prior 187
Dark - unknown roadway lighting25 (0.2%)
↓-13.8%prior 29

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

Road Surface

Dry8,007 (76.7%)
↑12.3%prior 7,132
Wet1,499 (14.4%)
↓-7.4%prior 1,619
Snow434 (4.2%)
↓-19.0%prior 536
Ice/frost384 (3.7%)
↑22.3%prior 314
Slush83 (0.8%)
↓-1.2%prior 84
Gravel11 (0.1%)
↓-21.4%prior 14
Other (explain in narrative)9 (0.1%)
→0.0%prior 9
Mud, dirt5 (0.0%)
Sand4 (0.0%)
Water (standing or moving)3 (0.0%)

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

Vehicles & Demographics

Ford remained the most frequently involved vehicle make, increasing by 6.12% from 2,924 in 2015 to 3,103 in 2016. Chevrolet (CHEV) involvement decreased by 12.36% from 2,467 to 2,162, while Chevrolet (CHEVROLET) saw a 54.34% increase from 1,082 to 1,670. All top five age groups involved in crashes showed decreases, with the 35-44 age group experiencing the largest decline of 8.11%.

Top Vehicle Makes (20,688 vehicles)

1
FORD3,103 (15%)
↑6.1%prior 2,924
2
CHEV2,162 (10.5%)
↓-12.4%prior 2,467
3
CHEVROLET1,670 (8.1%)
↑54.3%prior 1,082
4
TOYT1,013 (4.9%)
↓-16.1%prior 1,207
5
NR777 (3.8%)
↑21.6%prior 639
6
TOYOTA728 (3.5%)
↑55.9%prior 467
7
DODG724 (3.5%)
↓-21.6%prior 923
8
JEEP716 (3.5%)
↑15.3%prior 621
9
HOND680 (3.3%)
↓-15.2%prior 802
10
DODGE607 (2.9%)
↑29.4%prior 469

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

2,848 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (16,158 persons with recorded sex)

Male8,807 (54.5%)
↓-7.4%prior 9,508
Female7,351 (45.5%)
↓-5.0%prior 7,737

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: 10,675
  • Total persons involved: 23,063
  • Total vehicles involved: 20,688

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

ThatCarHitMe.com · An Injuria.ai Company