Motorcyclist Crash Responsibility The Effect of Driver Age

Motorcyclist Crash Responsibility: The Effect of Driver Age and Motorcycle Displacement Dylan Antoniazzi, Sacha Dubois, Rupert Klein, Michel Bédard

Acknowledgments • A quick thank-you to the project co-authors for their collaborative efforts • Andrew Wheeler for his blog posts detailing the Graphics Processing Language in SPSS • The organizations below for their support

Introduction • In the USA, between 1980 to 2013: – Fatalities of riders under 29 have fallen from 73% of all fatalities to 27% – Fatalities of riders over 50 have risen from 3% to 34% (NHTSA, 2015) • This shift in fatality proportions is partly due to the aging population

Introduction • A motorcycle’s power can be measured by its displacement – Typically specified in cubic centimeters (CCs) – The higher the engine CCs the more powerful the motorcycle resulting in greater acceleration and speed Motorcycle Typical Displacement (CCs) Standard 250 Sport 500 -1000 Touring 1000+

Research Question • To examine the effect of displacement on fatal crash responsibility while considering motorcyclists’ age

Data Source Fatality Analysis Reporting System • Information on ALL fatal crashes in the USA since 1975 • Contains detailed information on environmental, vehicular and motorcyclistrelated factors

Design • Employed a case-control design – Cases had committed one or more Unsafe Motorcyclist Action (UMA), our proxy measure of crash responsibility – Examples of UMAs include: Speeding, Weaving – Controls did not commit an UMA

Inclusion Criteria • Not Impaired by alcohol or drugs: – Alcohol and drug data first captured in 1987 – To rule out alcohol and drugs, we used data from 1987 through 2009 • Sex: – Given ~97% of motorcyclists involved in fatal crashes were male, we excluded females

Analyses • Employed binary logistic regression to examine crash responsibility by motorcycle displacement and motorcyclist's age

Logistic Regression: Independent crash contributors • Displacement – Measured in CCs – Examined displacement in 250 CC increments up to 1500 CCs • Age – Measured in years – Examined age in 10 year increments up to age 70

Logistic Regression: Design • Dependent variable: – Responsibility – Either any UMA or one of the top three UMAs • Independent variable: – Both linear and quadratic terms for Age and Displacement (e. g. , Age and Age 2) – Interaction between Age and Displacement

RESULTS

CONSORT FLOW DIAGRAM MC riders involved in a fatal crash between 1987 -2009 (n=78, 006) Confirmed BAC of Zero (n=27, 777) Confirmed drug negative (n=13, 813) Male Riders (n=13, 293)

Top Unsafe Motorcycle Actions • 35% (4, 669) Speeding • 22% (2, 957) • 7% (910) Erratic Behavior Weaving • 61% (8, 064) • 395 (5, 229) Any UMA No UMAs

Top Unsafe Motorcycle Actions • 35% (4, 669) Speeding • 22% (2, 957) Erratic Behavior Weaving • 61% (8, 064) Any UMA • 7% (910) • 39% (5, 229) No UMAs

SPEEDING LOGISTIC REGRESSION

Top Unsafe Motorcycle Actions • 35% (4, 669) Speeding • 22% (2, 957) Erratic Behavior Weaving • 61% (8, 064) Any UMA • 7% (910) • 39% (5, 229) No UMAs

Speeding • 35% (4, 669) Speeding • 22% (2, 957) Erratic Behavior Weaving • 61% (8, 064) Any UMA • 7% (910) • 39% (5, 229) No UMAs

Speeding § For Speeding we see that displacement has an inverted JShape for ages 20 - 60 § That is the highest odds ratios of any UMA by age are typically seen at 750 -1000 CCs §And the lowest odds ratios are seen at the 1500 CC level Age 2 CC CC 2 Age*CC Age 2*CC Age*CC 2 Age 2*CC 2 0. 43 1. 10 1. 21 0. 99 1. 02 0. 99 1. 00 (0. 27 -0. 68) (0. 99 -1. 23) (1. 15 -1. 27) (0. 99– 0. 99) (0. 97 -1. 08) (0. 98 -1. 00) (1. 00 -1. 00)

Speeding §Riders aged 20 -60 had increased odds of committing a Speeding UMA for CCs 500 -1250 compared to equivalent aged riders of 250 CC motorcycles § For these riders, increased odds are not present at 1500 CCs Age 2 CC CC 2 Age*CC Age 2*CC Age*CC 2 Age 2*CC 2 0. 43 1. 10 1. 21 0. 99 1. 02 0. 99 1. 00 (0. 27 -0. 68) (0. 99 -1. 23) (1. 15 -1. 27) (0. 99– 0. 99) (0. 97 -1. 08) (0. 98 -1. 00) (1. 00 -1. 00)

Speeding § However, by age 70 we see a more linear shape §Riders aged 70 had increased odds of committing a Speeding UMA for 1500 CCs motorcycles compared to equivalent aged riders of 250 CC motorcycles §At lower CCs (≤ 1250), increased odds are not statistically significant Age 2 CC CC 2 Age*CC Age 2*CC Age*CC 2 Age 2*CC 2 0. 43 1. 10 1. 21 0. 99 1. 02 0. 99 1. 00 (0. 27 -0. 68) (0. 99 -1. 23) (1. 15 -1. 27) (0. 99– 0. 99) (0. 97 -1. 08) (0. 98 -1. 00) (1. 00 -1. 00)

Speeding Age 20 CCs Odds Ratio (95% CI) 250 1. 00 (1. 00; 1. 00) 500 1. 68 (1. 48; 1. 92) 750 2. 15 (1. 76; 2. 63) 1000 2. 08 (1. 65; 2. 62) 1250 1. 53 (1. 17; 2. 01) 1500 0. 85 (0. 57; 1. 27) Age 2 CC CC 2 Age*CC Age 2*CC Age*CC 2 Age 2*CC 2 0. 43 1. 10 1. 21 0. 99 1. 02 0. 99 1. 00 (0. 27 -0. 68) (0. 99 -1. 23) (1. 15 -1. 27) (0. 99– 0. 99) (0. 97 -1. 08) (0. 98 -1. 00) (1. 00 -1. 00)

Speeding Age 30 CCs Odds Ratio (95% CI) 250 1. 00 (1. 00; 1. 00) 500 1. 74 (1. 52; 1. 98) 750 2. 25 (1. 82; 2. 78) 1000 2. 17 (1. 70; 2. 76) 1250 1. 56 (1. 23; 1. 98) 1500 0. 84 (0. 65; 1. 07) Age 2 CC CC 2 Age*CC Age 2*CC Age*CC 2 Age 2*CC 2 0. 43 1. 10 1. 21 0. 99 1. 02 0. 99 1. 00 (0. 27 -0. 68) (0. 99 -1. 23) (1. 15 -1. 27) (0. 99– 0. 99) (0. 97 -1. 08) (0. 98 -1. 00) (1. 00 -1. 00)

Speeding Age 40 CCs Odds Ratio (95% CI) 250 1. 00 (1. 00; 1. 00) 500 1. 71 (1. 45; 2. 03) 750 2. 22 (1. 69; 2. 93) 1000 2. 18 (1. 58; 3. 01) 1250 1. 63 (1. 18; 2. 23) 1500 0. 92 (0. 68; 1. 22) Age 2 CC CC 2 Age*CC Age 2*CC Age*CC 2 Age 2*CC 2 0. 43 1. 10 1. 21 0. 99 1. 02 0. 99 1. 00 (0. 27 -0. 68) (0. 99 -1. 23) (1. 15 -1. 27) (0. 99– 0. 99) (0. 97 -1. 08) (0. 98 -1. 00) (1. 00 -1. 00)

Speeding Age 50 CCs Odds Ratio (95% CI) 250 1. 00 (1. 00; 1. 00) 500 1. 62 (1. 35; 1. 95) 750 2. 09 (1. 54; 2. 82) 1000 2. 13 (1. 49; 3. 05) 1250 1. 73 (1. 21; 2. 49) 1500 1. 12 (0. 80; 1. 57) Age 2 CC CC 2 Age*CC Age 2*CC Age*CC 2 Age 2*CC 2 0. 43 1. 10 1. 21 0. 99 1. 02 0. 99 1. 00 (0. 27 -0. 68) (0. 99 -1. 23) (1. 15 -1. 27) (0. 99– 0. 99) (0. 97 -1. 08) (0. 98 -1. 00) (1. 00 -1. 00)

Speeding Age 60 CCs Odds Ratio (95% CI) 250 1. 00 (1. 00; 1. 00) 500 1. 47 (1. 16; 1. 85) 750 1. 85 (1. 26; 2. 72) 1000 2. 01 (1. 27; 3. 21) 1250 1. 89 (1. 17; 3. 05) 1500 1. 53 (0. 96; 2. 41) Age 2 CC CC 2 Age*CC Age 2*CC Age*CC 2 Age 2*CC 2 0. 43 1. 10 1. 21 0. 99 1. 02 0. 99 1. 00 (0. 27 -0. 68) (0. 99 -1. 23) (1. 15 -1. 27) (0. 99– 0. 99) (0. 97 -1. 08) (0. 98 -1. 00) (1. 00 -1. 00)

Speeding Age 70 CCs Odds Ratio (95% CI) 250 1. 00 (1. 00; 1. 00) 500 1. 27 (0. 87; 1. 86) 750 1. 56 (0. 83; 2. 93) 1000 1. 84 (0. 86; 3. 95) 1250 2. 11 (0. 95; 4. 67) 1500 2. 32 (1. 06; 5. 08) Age 2 CC CC 2 Age*CC Age 2*CC Age*CC 2 Age 2*CC 2 0. 43 1. 10 1. 21 0. 99 1. 02 0. 99 1. 00 (0. 27 -0. 68) (0. 99 -1. 23) (1. 15 -1. 27) (0. 99– 0. 99) (0. 97 -1. 08) (0. 98 -1. 00) (1. 00 -1. 00)

WEAVING LOGISTIC REGRESSION

Top Unsafe Motorcycle Actions • 35% (4, 669) Speeding • 22% (2, 957) Erratic Behavior Weaving • 61% (8, 064) Any UMA • 7% (910) • 39% (5, 229) No UMAs

Weaving • 35% (4, 669) Speeding • 22% (2, 957) Erratic Behavior Weaving • 61% (8, 064) Any UMA • 7% (910) • 39% (5, 229) No UMAs

Weaving § For Weaving we see that displacement has an inverted UShape § However the curve tends to become linear as age increases Age 2 CC CC 2 Age*CC Age 2*CC Age*CC 2 Age 2*CC 2 0. 62 1. 07 1. 13 0. 99 0. 98 1. 00 (0. 40 -0. 96) (0. 97 -1. 18) (1. 07 -1. 19) (0. 99– 0. 99) (0. 93 -1. 04) (0. 99 -1. 01) (1. 00 -1. 00)

Weaving § Riders aged 20 -50 had increased odds of committing the Weaving UMA for motorcycles with 500 – 750 CCs compared to equivalent aged riders of 250 CC motorcycles Age 2 CC CC 2 Age*CC Age 2*CC Age*CC 2 Age 2*CC 2 0. 62 1. 07 1. 13 0. 99 0. 98 1. 00 (0. 40 -0. 96) (0. 97 -1. 18) (1. 07 -1. 19) (0. 99– 0. 99) (0. 93 -1. 04) (0. 99 -1. 01) (1. 00 -1. 00)

Weaving § Further, riders aged 20 -40 had reduced odds of the Weaving UMA with 1500 CC motorcycles compared to equivalent aged riders of 250 CC motorcycles Age 2 CC CC 2 Age*CC Age 2*CC Age*CC 2 Age 2*CC 2 0. 62 1. 07 1. 13 0. 99 0. 98 1. 00 (0. 40 -0. 96) (0. 97 -1. 18) (1. 07 -1. 19) (0. 99– 0. 99) (0. 93 -1. 04) (0. 99 -1. 01) (1. 00 -1. 00)

Weaving § By age 60, the displacement curve starts to take on a more linear shape §However odds of committing a Weaving UMA were not significantly increased at all CC levels compared to equivalent aged riders of 250 CC motorcycles Age 2 CC CC 2 Age*CC Age 2*CC Age*CC 2 Age 2*CC 2 0. 62 1. 07 1. 13 0. 99 0. 98 1. 00 (0. 40 -0. 96) (0. 97 -1. 18) (1. 07 -1. 19) (0. 99– 0. 99) (0. 93 -1. 04) (0. 99 -1. 01) (1. 00 -1. 00)

Weaving Age 20 CCs Odds Ratio (95% CI) 250 1. 00 (1. 00; 1. 00) 500 1. 32 (1. 14; 1. 53) 750 1. 41 (1. 13; 1. 75) 1000 1. 20 (0. 93; 1. 55) 1250 0. 83 (0. 61; 1. 13) 1500 0. 46 (0. 29; 0. 73) Age 2 CC CC 2 Age*CC Age 2*CC Age*CC 2 Age 2*CC 2 0. 62 1. 07 1. 13 0. 99 0. 98 1. 00 (0. 40 -0. 96) (0. 97 -1. 18) (1. 07 -1. 19) (0. 99– 0. 99) (0. 93 -1. 04) (0. 99 -1. 01) (1. 00 -1. 00)

Weaving Age 30 CCs Odds Ratio (95% CI) 250 1. 00 (1. 00; 1. 00) 500 1. 29 (1. 13; 1. 47) 750 1. 38 (1. 12; 1. 71) 1000 1. 25 (0. 98; 1. 58) 1250 0. 94 (0. 73; 1. 20) 1500 0. 59 (0. 45; 0. 78) Age 2 CC CC 2 Age*CC Age 2*CC Age*CC 2 Age 2*CC 2 0. 62 1. 07 1. 13 0. 99 0. 98 1. 00 (0. 40 -0. 96) (0. 97 -1. 18) (1. 07 -1. 19) (0. 99– 0. 99) (0. 93 -1. 04) (0. 99 -1. 01) (1. 00 -1. 00)

Weaving Age 40 CCs Odds Ratio (95% CI) 250 1. 00 (1. 00; 1. 00) 500 1. 25 (1. 07; 1. 47) 750 1. 36 (1. 05; 1. 76) 1000 1. 29 (0. 95; 1. 75) 1250 1. 06 (0. 78; 1. 44) 1500 0. 76 (0. 57; 1. 01) Age 2 CC CC 2 Age*CC Age 2*CC Age*CC 2 Age 2*CC 2 0. 62 1. 07 1. 13 0. 99 0. 98 1. 00 (0. 40 -0. 96) (0. 97 -1. 18) (1. 07 -1. 19) (0. 99– 0. 99) (0. 93 -1. 04) (0. 99 -1. 01) (1. 00 -1. 00)

Weaving Age 50 CCs Odds Ratio (95% CI) 250 1. 00 (1. 00; 1. 00) 500 1. 21 (1. 03; 1. 43) 750 1. 34 (1. 02; 1. 75) 1000 1. 33 (0. 96; 1. 83) 1250 1. 20 (0. 86; 1. 66) 1500 0. 98 (0. 72; 1. 34) Age 2 CC CC 2 Age*CC Age 2*CC Age*CC 2 Age 2*CC 2 0. 62 1. 07 1. 13 0. 99 0. 98 1. 00 (0. 40 -0. 96) (0. 97 -1. 18) (1. 07 -1. 19) (0. 99– 0. 99) (0. 93 -1. 04) (0. 99 -1. 01) (1. 00 -1. 00)

Weaving Age 60 CCs Odds Ratio (95% CI) 250 1. 00 (1. 00; 1. 00) 500 1. 18 (0. 99; 1. 41) 750 1. 31 (0. 98; 1. 76) 1000 1. 37 (0. 96; 1. 96) 1250 1. 35 (0. 94; 1. 95) 1500 1. 26 (0. 88; 1. 80) Age 2 CC CC 2 Age*CC Age 2*CC Age*CC 2 Age 2*CC 2 0. 62 1. 07 1. 13 0. 99 0. 98 1. 00 (0. 40 -0. 96) (0. 97 -1. 18) (1. 07 -1. 19) (0. 99– 0. 99) (0. 93 -1. 04) (0. 99 -1. 01) (1. 00 -1. 00)

Weaving Age 70 CCs Odds Ratio (95% CI) 250 1. 00 (1. 00; 1. 00) 500 1. 14 (0. 86; 1. 52) 750 1. 28 (0. 81; 2. 04) 1000 1. 41 (0. 82; 2. 45) 1250 1. 52 (0. 86; 2. 69) 1500 1. 61 (0. 90; 2. 88) Age 2 CC CC 2 Age*CC Age 2*CC Age*CC 2 Age 2*CC 2 0. 62 1. 07 1. 13 0. 99 0. 98 1. 00 (0. 40 -0. 96) (0. 97 -1. 18) (1. 07 -1. 19) (0. 99– 0. 99) (0. 93 -1. 04) (0. 99 -1. 01) (1. 00 -1. 00)

ERRACTIC OR RECKLESS RIDING LOGISTIC REGRESSION

Top Unsafe Motorcycle Actions • 35% (4, 669) Speeding • 22% (2, 957) Erratic Behavior Weaving • 61% (8, 064) Any UMA • 7% (910) • 39% (5, 229) No UMAs

Erratic Riding • 35% (4, 669) Speeding • 22% (2, 957) Erratic Behavior Weaving • 61% (8, 064) Any UMA • 7% (910) • 39% (5, 229) No UMAs

Erratic Riding § For Erratic Riding we see that displacement has a curvilinear shape Age 2 CC CC 2 Age*CC Age 2*CC Age*CC 2 Age 2*CC 2 0. 20 1. 34 1. 13 0. 99 1. 12 0. 97 0. 99 1. 00 (0. 10 -0. 41) (1. 15 -1. 55) (1. 05 -1. 22) (0. 99– 0. 99) (1. 03 -1. 22) (0. 95 -0. 99) (0. 99 -0. 99) (1. 00 -1. 00)

Erratic Riding § Riders aged 20 -40 had increased odds of committing the Weaving UMA for CCs 500 – 1250 compared to equivalent aged riders of 250 CC motorcycles Age 2 CC CC 2 Age*CC Age 2*CC Age*CC 2 Age 2*CC 2 0. 20 1. 34 1. 13 0. 99 1. 12 0. 97 0. 99 1. 00 (0. 10 -0. 41) (1. 15 -1. 55) (1. 05 -1. 22) (0. 99– 0. 99) (1. 03 -1. 22) (0. 95 -0. 99) (0. 99 -0. 99) (1. 00 -1. 00)

Erratic Riding § Riders aged 20 -40 had increased odds of committing the Weaving UMA for CCs 500 – 1250 compared to equivalent aged riders of 250 CC motorcycles §Riders age 50 have a similar pattern Age 2 CC CC 2 Age*CC Age 2*CC Age*CC 2 Age 2*CC 2 0. 20 1. 34 1. 13 0. 99 1. 12 0. 97 0. 99 1. 00 (0. 10 -0. 41) (1. 15 -1. 55) (1. 05 -1. 22) (0. 99– 0. 99) (1. 03 -1. 22) (0. 95 -0. 99) (0. 99 -0. 99) (1. 00 -1. 00)

Erratic Riding § By age 60 the effect of displacement is lost Age 2 CC CC 2 Age*CC Age 2*CC Age*CC 2 Age 2*CC 2 0. 20 1. 34 1. 13 0. 99 1. 12 0. 97 0. 99 1. 00 (0. 10 -0. 41) (1. 15 -1. 55) (1. 05 -1. 22) (0. 99– 0. 99) (1. 03 -1. 22) (0. 95 -0. 99) (0. 99 -0. 99) (1. 00 -1. 00)

Erratic Riding Age 20 CCs Odds Ratio (95% CI) 250 1. 00 (1. 00; 1. 00) 500 1. 45 (1. 19; 1. 78) 750 1. 82 (1. 34; 2. 47) 1000 1. 96 (1. 38; 2. 77) 1250 1. 81 (1. 18; 2. 77) 1500 1. 44 (0. 76; 2. 74) Age 2 CC CC 2 Age*CC Age 2*CC Age*CC 2 Age 2*CC 2 0. 20 1. 34 1. 13 0. 99 1. 12 0. 97 0. 99 1. 00 (0. 10 -0. 41) (1. 15 -1. 55) (1. 05 -1. 22) (0. 99– 0. 99) (1. 03 -1. 22) (0. 95 -0. 99) (0. 99 -0. 99) (1. 00 -1. 00)

Erratic Riding Age 30 CCs Odds Ratio (95% CI) 250 1. 00 (1. 00; 1. 00) 500 1. 82 (1. 43; 2. 31) 750 2. 51 (1. 71; 3. 69) 1000 2. 64 (1. 70; 4. 08) 1250 2. 10 (1. 37; 3. 23) 1500 1. 27 (0. 83; 1. 95) Age 2 CC CC 2 Age*CC Age 2*CC Age*CC 2 Age 2*CC 2 0. 20 1. 34 1. 13 0. 99 1. 12 0. 97 0. 99 1. 00 (0. 10 -0. 41) (1. 15 -1. 55) (1. 05 -1. 22) (0. 99– 0. 99) (1. 03 -1. 22) (0. 95 -0. 99) (0. 99 -0. 99) (1. 00 -1. 00)

Erratic Riding Age 40 CCs Odds Ratio (95% CI) 250 1. 00 (1. 00; 1. 00) 500 1. 92 (1. 40; 2. 63) 750 2. 69 (1. 61; 4. 50) 1000 2. 77 (1. 52; 5. 04) 1250 2. 08 (1. 15; 3. 77) 1500 1. 15 (0. 66; 1. 99) Age 2 CC CC 2 Age*CC Age 2*CC Age*CC 2 Age 2*CC 2 0. 20 1. 34 1. 13 0. 99 1. 12 0. 97 0. 99 1. 00 (0. 10 -0. 41) (1. 15 -1. 55) (1. 05 -1. 22) (0. 99– 0. 99) (1. 03 -1. 22) (0. 95 -0. 99) (0. 99 -0. 99) (1. 00 -1. 00)

Erratic Riding Age 50 CCs Odds Ratio (95% CI) 250 1. 00 (1. 00; 1. 00) 500 1. 71 (1. 21; 2. 41) 750 2. 24 (1. 28; 3. 93) 1000 2. 26 (1. 16; 4. 40) 1250 1. 76 (0. 90; 3. 44) 1500 1. 06 (0. 56; 1. 99) Age 2 CC CC 2 Age*CC Age 2*CC Age*CC 2 Age 2*CC 2 0. 20 1. 34 1. 13 0. 99 1. 12 0. 97 0. 99 1. 00 (0. 10 -0. 41) (1. 15 -1. 55) (1. 05 -1. 22) (0. 99– 0. 99) (1. 03 -1. 22) (0. 95 -0. 99) (0. 99 -0. 99) (1. 00 -1. 00)

Erratic Riding Age 60 CCs Odds Ratio (95% CI) 250 1. 00 (1. 00; 1. 00) 500 1. 28 (0. 88; 1. 86) 750 1. 45 (0. 79; 2. 66) 1000 1. 44 (0. 70; 2. 97) 1250 1. 27 (0. 61; 2. 65) 1500 0. 99 (0. 48; 2. 05) Age 2 CC CC 2 Age*CC Age 2*CC Age*CC 2 Age 2*CC 2 0. 20 1. 34 1. 13 0. 99 1. 12 0. 97 0. 99 1. 00 (0. 10 -0. 41) (1. 15 -1. 55) (1. 05 -1. 22) (0. 99– 0. 99) (1. 03 -1. 22) (0. 95 -0. 99) (0. 99 -0. 99) (1. 00 -1. 00)

Erratic Riding Age 70 CCs Odds Ratio (95% CI) 250 1. 00 (1. 00; 1. 00) 500 0. 81 (0. 49; 1. 36) 750 0. 73 (0. 32; 1. 66) 1000 0. 72 (0. 27; 1. 89) 1250 0. 78 (0. 28; 2. 15) 1500 0. 94 (0. 31; 2. 82) Age 2 CC CC 2 Age*CC Age 2*CC Age*CC 2 Age 2*CC 2 0. 20 1. 34 1. 13 0. 99 1. 12 0. 97 0. 99 1. 00 (0. 10 -0. 41) (1. 15 -1. 55) (1. 05 -1. 22) (0. 99– 0. 99) (1. 03 -1. 22) (0. 95 -0. 99) (0. 99 -0. 99) (1. 00 -1. 00)

ANY UMA LOGISTIC REGRESSION

Top Unsafe Motorcycle Actions • 35% (4, 669) Speeding • 22% (2, 957) Erratic Behavior Weaving • 61% (8, 064) Any UMA • 7% (910) • 39% (5, 229) No UMAs

Any UMA • 35% (4, 669) Speeding • 22% (2, 957) Erratic Behavior Weaving • 61% (8, 064) Any UMA • 7% (910) • 39% (5, 229) No UMAs

Any UMA § For Any UMA we see the now familiar curvilinear effect of displacement, especially for lower aged riders Age 2 CC CC 2 Age*CC Age 2*CC Age*CC 2 Age 2*CC 2 0. 48 1. 12 1. 07 0. 99 1. 02 0. 99 1. 00 (0. 35 -0. 65) (1. 05 -1. 19) (1. 03 -1. 12) (0. 99– 0. 99) (0. 98 -1. 06) (0. 98 -1. 00) (0. 99 -1. 00) (1. 00 -1. 00)

Any UMA § Riders aged 20 -40 had increased odds of committing any UMA for motorcycles with 500 – 1000 CCs compared to equivalent aged riders of 250 CC motorcycles § Further, riders age 30 -40 had reduced odds of committing any UMA for 1500 CC motorcycles compared to equivalent aged riders of 250 CC motorcycles Age 2 CC CC 2 Age*CC Age 2*CC Age*CC 2 Age 2*CC 2 0. 48 1. 12 1. 07 0. 99 1. 02 0. 99 1. 00 (0. 35 -0. 65) (1. 05 -1. 19) (1. 03 -1. 12) (0. 99– 0. 99) (0. 98 -1. 06) (0. 98 -1. 00) (0. 99 -1. 00) (1. 00 -1. 00)

Any UMA §Riders aged 50 had similar but weaker increased odds at 500750 CCs §For these riders, increased odds do not remain at 1000 CCs Age 2 CC CC 2 Age*CC Age 2*CC Age*CC 2 Age 2*CC 2 0. 48 1. 12 1. 07 0. 99 1. 02 0. 99 1. 00 (0. 35 -0. 65) (1. 05 -1. 19) (1. 03 -1. 12) (0. 99– 0. 99) (0. 98 -1. 06) (0. 98 -1. 00) (0. 99 -1. 00) (1. 00 -1. 00)

Any UMA §At age 70 displacement takes on a linear effect § While odds increase by displacement this is not statistically significant Age 2 CC CC 2 Age*CC Age 2*CC Age*CC 2 Age 2*CC 2 0. 48 1. 12 1. 07 0. 99 1. 02 0. 99 1. 00 (0. 35 -0. 65) (1. 05 -1. 19) (1. 03 -1. 12) (0. 99– 0. 99) (0. 98 -1. 06) (0. 98 -1. 00) (0. 99 -1. 00) (1. 00 -1. 00)

Any UMA Age 20 CCs Odds Ratio (95% CI) 250 1. 00 (1. 00; 1. 00) 500 1. 19 (1. 07; 1. 33) 750 1. 27 (1. 08; 1. 50) 1000 1. 21 (1. 00; 1. 46) 1250 1. 03 (0. 81; 1. 30) 1500 0. 78 (0. 55; 1. 10) Age 2 CC CC 2 Age*CC Age 2*CC Age*CC 2 Age 2*CC 2 0. 48 1. 12 1. 07 0. 99 1. 02 0. 99 1. 00 (0. 35 -0. 65) (1. 05 -1. 19) (1. 03 -1. 12) (0. 99– 0. 99) (0. 98 -1. 06) (0. 98 -1. 00) (0. 99 -1. 00) (1. 00 -1. 00)

Any UMA Age 30 CCs Odds Ratio (95% CI) 250 1. 00 (1. 00; 1. 00) 500 1. 23 (1. 12; 1. 35) 750 1. 32 (1. 14; 1. 54) 1000 1. 25 (1. 05; 1. 49) 1250 1. 04 (0. 87; 1. 24) 1500 0. 75 (0. 62; 0. 92) Age 2 CC CC 2 Age*CC Age 2*CC Age*CC 2 Age 2*CC 2 0. 48 1. 12 1. 07 0. 99 1. 02 0. 99 1. 00 (0. 35 -0. 65) (1. 05 -1. 19) (1. 03 -1. 12) (0. 99– 0. 99) (0. 98 -1. 06) (0. 98 -1. 00) (0. 99 -1. 00) (1. 00 -1. 00)

Any UMA Age 40 CCs Odds Ratio (95% CI) 250 1. 00 (1. 00; 1. 00) 500 1. 22 (1. 09; 1. 37) 750 1. 32 (1. 10; 1. 59) 1000 1. 26 (1. 01; 1. 56) 1250 1. 06 (0. 85; 1. 32) 1500 0. 79 (0. 64; 0. 97) Age 2 CC CC 2 Age*CC Age 2*CC Age*CC 2 Age 2*CC 2 0. 48 1. 12 1. 07 0. 99 1. 02 0. 99 1. 00 (0. 35 -0. 65) (1. 05 -1. 19) (1. 03 -1. 12) (0. 99– 0. 99) (0. 98 -1. 06) (0. 98 -1. 00) (0. 99 -1. 00) (1. 00 -1. 00)

Any UMA Age 50 CCs Odds Ratio (95% CI) 250 1. 00 (1. 00; 1. 00) 500 1. 18 (1. 05; 1. 33) 750 1. 27 (1. 05; 1. 54) 1000 1. 24 (0. 98; 1. 56) 1250 1. 10 (0. 87; 1. 39) 1500 0. 88 (0. 70; 1. 11) Age 2 CC CC 2 Age*CC Age 2*CC Age*CC 2 Age 2*CC 2 0. 48 1. 12 1. 07 0. 99 1. 02 0. 99 1. 00 (0. 35 -0. 65) (1. 05 -1. 19) (1. 03 -1. 12) (0. 99– 0. 99) (0. 98 -1. 06) (0. 98 -1. 00) (0. 99 -1. 00) (1. 00 -1. 00)

Any UMA Age 60 CCs Odds Ratio (95% CI) 250 1. 00 (1. 00; 1. 00) 500 1. 11 (0. 98; 1. 25) 750 1. 17 (0. 95; 1. 44) 1000 1. 19 (0. 92; 1. 52) 1250 1. 15 (0. 89; 1. 49) 1500 1. 07 (0. 83; 1. 38) Age 2 CC CC 2 Age*CC Age 2*CC Age*CC 2 Age 2*CC 2 0. 48 1. 12 1. 07 0. 99 1. 02 0. 99 1. 00 (0. 35 -0. 65) (1. 05 -1. 19) (1. 03 -1. 12) (0. 99– 0. 99) (0. 98 -1. 06) (0. 98 -1. 00) (0. 99 -1. 00) (1. 00 -1. 00)

Any UMA Age 70 CCs Odds Ratio (95% CI) 250 1. 00 (1. 00; 1. 00) 500 1. 01 (0. 83; 1. 22) 750 1. 04 (0. 76; 1. 43) 1000 1. 11 (0. 76; 1. 61) 1250 1. 22 (0. 83; 1. 80) 1500 1. 38 (0. 92; 2. 09) Age 2 CC CC 2 Age*CC Age 2*CC Age*CC 2 Age 2*CC 2 0. 48 1. 12 1. 07 0. 99 1. 02 0. 99 1. 00 (0. 35 -0. 65) (1. 05 -1. 19) (1. 03 -1. 12) (0. 99– 0. 99) (0. 98 -1. 06) (0. 98 -1. 00) (0. 99 -1. 00) (1. 00 -1. 00)

Implications • Given these results education and legislative measures should be considered • For example, develop training interventions focusing on control, stability, and breaking differences given the vehicle’s greater weight and power

Implications • Legislatively, licensing tiers could be employed based on displacement and educational requirements • Both education and legislative measures could curb the trend seen between higher levels of displacement and crash responsibility

Contact Info Mr Dylan Antoniazzi dantonia@lakeheadu. ca Mr Sacha Dubois duboiss@tbh. net Dr Rupert Klein rgklein@lakeheadu. ca Dr Michel Bédard mbedard@lakeheadu. ca