Mandatory helmet legislation in New South Wales: A statistical perspective

Transcription

1 Mandatory helmet legislation in New South Wales: A statistical perspective Jake Olivier University of New South Wales 15 May 2012 J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 1 / 66

2 Outline 1 Enactment of Mandatory Helmet Laws 2 Voukelatos and Rissel JACRS Paper 3 Thorough Analysis of NSW Data 4 Helmet Wars 5 New Zealand MHL 6 The Way Forward J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 2 / 66

3 Mandatory Helmet Laws in New South Wales, Australia Intervention directed at lowering bicycle related head injuries Solid evidence for helmet wearing from biomechanical and epidemiological studies One important aspect of bicycle safety Not a panacea for all bicycle related injuries Applies to all age groups Went into effect in two stages Adults (>16): January 1, 1991 Children: July 1, 1991 Led to greater helmet wearing rates Associated with fewer bicycle related head injuries J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 3 / 66

4 Criticisms of MHL Very controversial (for some?) Leads to reductions in cycling? Fewer cyclists fewer bicycle related head injuries? Fewer cyclists more danger? Has a negative health economics impact? Quit cycling no exercise more obesity Morbidity/mortality from obesity outweighs safety benefit of helmets? Increases propensity for injury Risk compensation Motorist behaviour Loss of freedom "Debate" rages on after 20+ years J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 4 / 66

5 Voukelatos and Rissel JACRS Paper Ratio of head and arm hospitalizations over time 1 Previous analyses did not account for variations in cycling rates and the cycling environment (exposure) Assumes ratio is constant over time unless a factor affects one injury differentially than the other Cases identified from NSW Health hospitalization data (ICD-9-CM, ICD-10-AM) Aggregated by fiscal year (July 1 to June 30) 1 Voukelatos, A., Rissel, C., The effects of bicycle helmet legislation on cycling related injury: the ratio of head to arm injuries over time. J. Aust. Coll. Road Saf. 21 (3), J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 5 / 66

6 Voukelatos and Rissel Analysis 1.6 ICD9 ICD10 <16 years > 16 years 1.4 Ratio Head injuries vs Arm injuries / / / / / / / / / / / / / / / / / / / /08 J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 6 / 66

7 Voukelatos and Rissel Criticisms No statistical analysis, passes the eyeball test Obfuscates trend in head injuries First year of hospitalizations had only one diagnosis field (head injury more likely to be documented if patient has both) Age group totals do not add up to overall totals Corrected totals show the opposite, i.e., larger decline after MHL Incorrect ICD9 codes J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 7 / 66

8 Voukelatos and Rissel Criticisms No statistical analysis, passes the eyeball test Obfuscates trend in head injuries First year of hospitalizations had only one diagnosis field (head injury more likely to be documented if patient has both) Age group totals do not add up to overall totals Corrected totals show the opposite, i.e., larger decline after MHL Incorrect ICD9 codes Retracted from journal (Australasian College of Road Safety (ACRS), Retraction of the Voukelatos and Rissel paper on bicycle helmet legislation and injury. J. Aust. Coll. Road Saf. 22 (1), 39.) J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 7 / 66

9 Other Unexplained Issue J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 8 / 66

10 Thorough Analysis of NSW Data Ratio of two injuries over time seems like a good idea Correct problems with Voukelatos/Rissel paper and perform a proper statistical analysis 2 Sensitivity analyses Is the general pattern noticeable for other body parts and/or road users? Interrupted time series with a dependent, non-equivalent, no-intervention group 3 2 Walter, S.R., Olivier, J., Churches, T., Grzebieta, R The impact of compulsory cycle helmet legislation on cyclist head injuries in New South Wales, Australia. Accid. Anal. Prev. 43 (6), Shadish, W.R., Cook, T.D., Campbell, D.T Experimental and Quasi-experimental Designs for Generalized Causal Inference. Wadsworth Cengage Learning, Belmont, CA. J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 9 / 66

11 Interrupted Time Series Type of quasi-experimental design Participants are not randomised Estimates a time series before and after an intervention Comparing single pre- and post-intervention effects can hide history Multiple pre- and post-intervention observations avoids regression to the mean Important comparisons made between pre- and post-intervention time series Change in level (immediate impact) Change in slope (gradual impact) Sometimes called Segmented Regression J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 10 / 66

12 Our Model Remove first year of data due to one diagnosis field 18 months of usable data prior to adult MHL Translate adult and child data so MHL date is the same Compare 18 months pre- and post-mhl More data available post-mhl, but imbalance can induce bias 4 Median date is January 1 for adults and July 1 for children Approach is likely conservative as child helmet wearing rates were rising pre-mhl 4 French, B., Heagerty, P.J Analysis of longitudinal data to evaluate a policy change. Stat. Med. 27, J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 11 / 66

13 Our Model Negative binomial regression due to overdispersion Injury rates are stable when aggregated by year Highly variable from month to month X11 seasonal adjustment method Accounts for seasonal and irregular components Seasonal effects are diffi cult to estimate due to translation of MHL date Outcome is no longer count data J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 12 / 66

14 Interrupted Time Series for Head Injuries J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 13 / 66

15 Interrupted Time Series for Head Injuries J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 14 / 66

16 Dependent, non-equivalent, no-intervention group Previous research criticised for unmeasured confounding Changes in head injury rate due to... Decline in cyclists? Risk compensation? More dangerous cycling environment? Data on potential confounders does not exist Compare with injury mechanism affected by changes in cycling environment but not MHL Non head-related cycling injuries make a better comparison than head injuries to Pedestrians Motorists Motorcyclists J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 15 / 66

17 Support for limb injuries as a comparison "[cycling limb fractures] reflects both the amount of travel done by cyclists and changes to the cycling environment..." 5 "...if the numbers of cyclists has dropped over time, the relative injury rates (head versus arm) should remain unchanged unless some factor is differentially impacting on one type of injury..." 6 5 Povey, L.J., Frith, W.J., Graham, P.G., Cycle helmet effectiveness in New Zealand. Acc.. Anal. Prev. 31, Voukelatos, A., Rissel, C., The effects of bicycle helmet legislation on cycling related injury: the ratio of head to arm injuries over time. J. Aust. Coll. Road Saf. 21 (3), J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 16 / 66

18 Support for limb injuries as a comparison "[cycling limb fractures] reflects both the amount of travel done by cyclists and changes to the cycling environment..." 5 "...if the numbers of cyclists has dropped over time, the relative injury rates (head versus arm) should remain unchanged unless some factor is differentially impacting on one type of injury..." 6 "One does not simply... remove one s head or limb from one s body." Boromir, The Fellowship of the Ring 5 Povey, L.J., Frith, W.J., Graham, P.G., Cycle helmet effectiveness in New Zealand. Acc.. Anal. Prev. 31, Voukelatos, A., Rissel, C., The effects of bicycle helmet legislation on cycling related injury: the ratio of head to arm injuries over time. J. Aust. Coll. Road Saf. 21 (3), J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 16 / 66

19 Our Model Time, mid-month with MHL date TIME = 0 Injury type TIME = 17.5,..., 1.5, 0.5, 0.5, 1.5,..., 17.5 INJURY = Pre- and post-mhl periods LAW = { 1 head injury 0 arm injury { 1 post-mhl 0 pre-mhl J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 17 / 66

20 Our Model E [log (count)] = β 0 + β 1 TIME + β 2 INJURY + β 3 LAW + β 4 TIME INJURY + β 5 TIME LAW + β 6 INJURY LAW + β 7 TIME INJURY LAW + log(exposure) NSW population size used for exposure Hypothesis driven, most parsimonious model not appropriate Certain interaction terms answer research questions J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 18 / 66

21 Change in level INJURY LAW Is there a noticeable increase/decrease in head injuries from pre- to post-mhl (relative to arm injuries)? J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 19 / 66

22 Change in slope TIME INJURY LAW Is the rate of change in head injuries different pre- and post-mhl (relative to arm injuries)? J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 20 / 66

23 Results Untransformed negative binomial regression estimates Variable Estimate 95% CI p-value TIME , INJURY , LAW , TIME LAW , INJURY LAW , TIME INJURY , TIME INJURY LAW , J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 21 / 66

24 Head and Arm Injuries for Cyclists J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 22 / 66

25 Sensitivity Analyses Was the drop in the head/arm ratio for cyclists an aberration? Is the drop there for other ratios? Head to leg ratio for cyclists? Since MHL was aimed at cyclists, is there a noticeable drop for other road users? Head to arm ratio for pedestrians? Head to leg ratio for pedestrians? J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 23 / 66

26 Sensitivity Analyses Head/arm/leg injuries for cyclists Head: 35% decrease Arm: 11% decrease (p=0.03) Leg: 6% decrease (p=0.03) Head/arm/leg injuries for pedestrians Head: 14% decrease Arm: 22% decrease (p=0.41) Leg: 4% decrease (p=0.38) J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 24 / 66

27 Sensitivity Analyses Head/arm/leg injuries for cyclists Head: 35% decrease Arm: 11% decrease (p=0.03) Leg: 6% decrease (p=0.03) Adjusted Head: 27.5% (arm) and 31% (leg) decrease Head/arm/leg injuries for pedestrians Head: 14% decrease Arm: 22% decrease (p=0.41) Leg: 4% decrease (p=0.38) J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 25 / 66

28 Summary of Analysis Statistically significant drop in bicycle related head injuries after MHL 29% drop beyond changes in limb injuries Decrease did not happen gradually Decrease noticeable for cyclists and not pedestrians Conclusion: No evidence to repeal MHL in NSW J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 26 / 66

29 Helmet Wars "Given the above your categoric conclusion is unfortunately without any merit whatsoever, you have proved nothing. Or, allowing politics/religion to enter (and sadly this debate is dominated by this and not science), you have re-enforced the anti-mhl argument by being so categoric without basis." Nigel Perry "I think it s downright dishonest and deceitful to claim that the helmet law was a success unless you can *prove* that head injuries declined by *substantially more* than the decline in cycling." Dorothy Robinson J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 27 / 66

30 Common Criticisms Anti-MHL is a small but very vocal group 7 MHL is a barrier to cycling Helmet wearing increases risky behaviour Motorists are more aggressive to helmeted cyclists Head injuries increase after MHL Searching for significant p-values 7 Olivier J. (2011) Putting a lid on the debate: mandatory helmet laws reduce head injuries, The Conversation. J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 28 / 66

31 Helmet Laws are a Barrier to Cycling "[MHL] led to a 30% 40% reduction in [cyclists]" 8 In reality, reports of cycling rates around MHL are mixed 9 Slight decline in primary school students Drastic drop in high school students Increase in adult cycling Our model estimated nonsignificant drops of 10.6% (arm injuries) and 6.2% (leg injuries) Adequate physical exertion pre- and post-mhl is never addressed 8 Rissel, C., Wrong-headed laws. MJA InSight. 9 J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 29 / 66

32 CPF Survey 20+ years later, is MHL a barrier to cycling? Riding a Bike for Transport: 2011 Survey Findings 10 Cycling Promotion Fund and National Heart Foundation Random sample of 1000 Australian adults Road traffi c conditions and safety noted as main reasons for not cycling more Multiple response questions, results do not necessarily represent a person s "main" barrier to cycling "...one in five adults (20% of both non-regular and regular cyclists) said they would cycle more if they didn t have to wear a helmet." Rissel, C., Wrong-headed laws. MJA InSight. J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 30 / 66

33 Which of the following, if any, discourage you from riding a bicycle for transport more often? Response 12 Percent Unsafe Road Conditions 67.1 Speed/volume of traffi c 52.5 Lack of bicycle lanes/trails 48.1 Weather conditions 44.3 Destinations too far away 36.7 No place to park/store bicycle 26.0 Don t feel safe riding 25.3 Too hilly 23.4 No place to change/shower 17.7 Don t like wearing a helmet Respondents who have ridden a bike for transport in the past month (n=158) J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 31 / 66

34 What are the main reasons you do not ride a bicycle for transport? Response 13 Percent Unsafe Road Conditions 46.4 Speed/volume of traffi c 41.8 Don t feel safe riding 41.4 Lack of bicycle lanes/trails 34.6 Destinations too far away 29.9 No place to park/store bicycle 23.5 Do not own a bicycle 22.5 Weather conditions 22.1 Not fit enough 21.8 Too hilly Respondents who would like to be able to ride for transport or short trips (n=515) J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 32 / 66

35 Rissel and Wen Questionnaire Four helmet-related questions added to a routinely collected survey responders aged 16+ years living in Sydney Participants asked about future behaviour without MHL Rissel, C., Wen, L.M., The possible effect on frequency of cycling if mandatory bicycle helmet legislation was repealed in Sydney, Australia: a cross sectional survey. Health Promot. J. Austr. 22, J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 33 / 66

36 Logistic regression results Would you cycle more often if you didn t have to wear a helmet? Age Prop. OR (p<0.01) AOR (p=0.09) "Those who were aged years...and years...were significantly more likely to ride more if they did not have to wear a helmet." Only true when compared to those 55 years or older Olivier, J., Churches, T., Walter, S., McIntosh, A., Grzebieta, R., Response to Rissel and Wen: The possible effect on frequency of cycling if mandatory bicycle helmet legislation was repealed in Sydney, Australia: a cross sectional survey. Health Promot. J. Austr. 23, 76. J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 34 / 66

37 Most responders would not cycle more J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 35 / 66

38 Rissel and Wen s response Claims 22.6% promising to cycle more is a "significant" response What would be a minimally important difference? "Olivier et al. are unashamedly pro-helmet advocates..." Rissel, C., Wen, L.M., Response to Rissel and Wen: Author reply. Health Promot. J. Austr. 23, 77. J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 36 / 66

39 Additional Surveys Sydney Cycleways Newsletter (cycling counts, March 2010 to March 2012) % increase at the intersection of Anzac Parade, Flinders Street and Moore Park Road 237% increase at Bourke Street and Phelps Street, Surry Hills 190% increase at Miller Street and Saunders Street, Prymont 187% increase at Macquarie Street and Bent Street, CBD 180% increase at the intersection of Liverpool Street, College Street, Wentworth Street and Oxford Street 158% increase at King Street and Kent Street, CBD 82% increase overall Essential Report, 30 April % approve of MHL 65% strongly approve, 1% strongly disapprove J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 37 / 66

40 Helmet wearing increases risky behaviour Risk compensation 20 A cyclist exhibits riskier behaviour when wearing a helmet Regular helmet wearers are more cautious when not wearing a helmet 21 Wrong temporal order for MHL? Mostly theoretical, not much solid evidence 20 Lardelli-Claret, P., Luna-del-Castillo, J.D., Jimenez-Moleon, J.J., Garcia-Martin, M., Bueno-Cavanillas, A., Galvez-Vargas, R., Risk compensation theory and voluntary helmet use by cyclists in Spain. Inj. Prev. 9 (2), Phillips, R.O., Fyhri, A., Sagberg, F., Risk compensation and bicycle helmets. Risk Anal. 31 (8), J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 38 / 66

41 Police reported casualties in NSW ( ) 6,745 cyclist collisions with known helmet use Helmet wearing associated with being less likely to have 22 Disobeyed a traffi c control (OR=0.33) BAC over 0.05 (OR=0.22) Associated with cycling in higher speed limit area Speed limit OR 95% CI Bambach, M.R., Mitchell, R.J., Grzebieta, R.H., Olivier, J. Analysis of NSW police reported bicycle casualties. J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 39 / 66

42 Motorists are more aggressive to helmeted cyclists Ian Walker, University of Bath 23 Two sensors: one for overtaking distance and the other the distance to the kerb Alternated between wearing and not wearing a helmet (also wore a blonde wig) Vehicles overtook, on average, at a closer distance when helmeted Data available online 24 Large sample (n=2355) Significant (but small) effects 23 Walker, I., Drivers overtaking bicyclists: Objective data on the effects of riding position, helmet use, vehicle type and apparent gender. Acc. Anal. Prev. 39, J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 40 / 66

43 Ian Walker Data J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 41 / 66

44 Motorists regularly give more than 1m J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 42 / 66

45 Scatterplot J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 43 / 66

46 Close Overtaking (<1m) Most overtaking is at least 1 metre (95.4%) 94.8% helmeted 95.9% unhelmeted OR = 1.3, 95% CI: , p = 0.18 After adjusting for kerb distance AOR 95% CI Helmet Kerb distance 0.25m m m m m 1.00 J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 44 / 66

47 Close Overtaking (<1m) J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 45 / 66

48 25 J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 46 / 66 Head injuries increase after MHL "...any downward effects (such as they are) are not even persistent. The ratios of head-to-arm and head-to-leg injuries are both actually higher at the end of the 36-month period than they were at the start." 25

49 Head injuries increase after MHL "...any downward effects (such as they are) are not even persistent. The ratios of head-to-arm and head-to-leg injuries are both actually higher at the end of the 36-month period than they were at the start." 25 "The tendency towards stability in post-law trends with the inclusion of additional years of data suggests that either 18 months is not suffi cient follow up time to accurately detect trends or that the trends shown represent temporally localised changes that did not persist beyond the analysis period. Based on the original analysis there is some evidence that the initial improvement in head injury rates diminished over the 18 months following legislation as shown by the increasing post-law head to limb injury ratios in Fig. 4. Alternatively, the longer term post-law trends being closer to parallel for head and limb injury rates (equivalent to a post-law horizontal line in Fig. 4A and C) supports the idea that the legislation attributable improvement was maintained." p J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 46 / 66

50 Head and arm injuries diverge after MHL J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 47 / 66

51 "Searching" for significant p-values After removing insignificant interaction terms Variable Estimate 95% CI p-value TIME , INJURY , LAW , TIME LAW , INJURY LAW , < J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 48 / 66

52 New Zealand MHL Enacted 1 January 1994 for all ages Helmet wearing increased from 20-40% to over 90% Head fractures compared with limb fractures pre- and post-mhl ( ) 26 Motor vehicle crash vs. non-motor vehicle crash Primary and secondary school children, and adults Associated declines in head fractures of 24-32% (non-mvc) 20% (MVC) 26 Povey, L.J., Frith, W.J., Graham, P.G., Cycle helmet effectiveness in New Zealand. Acc. Anal. Prev. 31, J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 49 / 66

53 Criticism of Povey et al. Diminishing returns for head injury reduction with increased helmet wearing 27 Reanalysis of adults in non-mvcs only Head injuries per 100 limb injuries (HI/100L) declined by -45 HI/100L (1990 vs. 1993) -11 HI/100L (1993 vs. 1995) Povey et al. did not include trend terms in analysis 27 Robinson, D.L., Changes in head injury with the New Zealand bicycle helmet law. Acc. Anal. Prev. 33, Olivier, J., Walter, S.R., Grzebieta, R. The effectiveness of mandatory bicycle helmet legislation in New Zealand: A reanalysis of Robinson, In preparation. J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 50 / 66

54 Criticism of Povey et al. Diminishing returns for head injury reduction with increased helmet wearing 27 Reanalysis of adults in non-mvcs only Head injuries per 100 limb injuries (HI/100L) declined by -45 HI/100L (1990 vs. 1993) -11 HI/100L (1993 vs. 1995) Povey et al. did not include trend terms in analysis Neither did Robinson Robinson, D.L., Changes in head injury with the New Zealand bicycle helmet law. Acc. Anal. Prev. 33, Olivier, J., Walter, S.R., Grzebieta, R. The effectiveness of mandatory bicycle helmet legislation in New Zealand: A reanalysis of Robinson, In preparation. J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 50 / 66

55 Criticism of Povey et al. Diminishing returns for head injury reduction with increased helmet wearing 27 Reanalysis of adults in non-mvcs only Head injuries per 100 limb injuries (HI/100L) declined by -45 HI/100L (1990 vs. 1993) -11 HI/100L (1993 vs. 1995) Povey et al. did not include trend terms in analysis Neither did Robinson 28 Large decline overall HI/100L (1990) vs. 77 HI/100L (1996) 27 Robinson, D.L., Changes in head injury with the New Zealand bicycle helmet law. Acc. Anal. Prev. 33, Olivier, J., Walter, S.R., Grzebieta, R. The effectiveness of mandatory bicycle helmet legislation in New Zealand: A reanalysis of Robinson, In preparation. J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 50 / 66

56 Reanalysis of Povey/Robinson J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 51 / 66

57 Reanalysis of Povey/Robinson J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 52 / 66

58 NZ vs. NSW aggregated by year J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 53 / 66

59 Clarke Analysis of NZ Cycling Injuries Descriptive reanalysis of existing data 29,30 Contrasted bicycle injuries with survey data NZ MHL "has failed" due to Cycling reduction of 51% "53 premature deaths" Increased injury risk of 20-32% Heavily cites anti-helmet websites 29 Clarke, C.F., Evaluation of New Zealand s bicycle helmet law. N.Z. Med. J. 125, Tin Tin, S., Woodward, A., Ameratunga, S., Injuries to pedal cyclists on New Zealand roads, BMC Public Health 10, 655. J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 54 / 66

60 Clarke Analysis of NZ Cycling Injuries Descriptive reanalysis of existing data 29,30 Contrasted bicycle injuries with survey data NZ MHL "has failed" due to Cycling reduction of 51% "53 premature deaths" Increased injury risk of 20-32% Heavily cites anti-helmet websites Overly simplistic analysis, ignores crucial points 29 Clarke, C.F., Evaluation of New Zealand s bicycle helmet law. N.Z. Med. J. 125, Tin Tin, S., Woodward, A., Ameratunga, S., Injuries to pedal cyclists on New Zealand roads, BMC Public Health 10, 655. J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 54 / 66

61 Clarke Analysis of NZ Cycling Injuries Descriptive reanalysis of existing data 29,30 Contrasted bicycle injuries with survey data NZ MHL "has failed" due to Cycling reduction of 51% "53 premature deaths" Increased injury risk of 20-32% Heavily cites anti-helmet websites Overly simplistic analysis, ignores crucial points THERE ARE NO LIMITATIONS!!! 29 Clarke, C.F., Evaluation of New Zealand s bicycle helmet law. N.Z. Med. J. 125, Tin Tin, S., Woodward, A., Ameratunga, S., Injuries to pedal cyclists on New Zealand roads, BMC Public Health 10, 655. J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 54 / 66

62 Clarke Analysis of NZ Data J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 55 / 66

63 MHL Date J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 56 / 66

64 Data J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 57 / 66

65 Helmet Wearing Data J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 58 / 66

66 Serious Cycling Injuries (AIS>2) J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 59 / 66

67 Tin Tin et al. Results J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 60 / 66

68 The Way Forward MHL is a Red Herring Every discussion about cycling safety deteriorates to MHL Important research topics never get addressed Addressing cycling safety is clearly the way forward Increased cycling infrastructure associated with More cyclists 31 Less injury (especially head injuries) 31 Buehler, R., Pucher, J., Cycling to work in 90 large American cities: new evidence on the role of bike paths and lanes. Transportation 39, J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 61 / 66

69 More cyclists ( ) J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 62 / 66

70 Less Injury ( ) J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 63 / 66

71 Important Research Topics in Helmets/MHL 1 Does wearing a helmet increase the risk of cyclist being involved in a crash? (through risk homeostasis and/or drivers driving closer to cyclists, etc.) 32 2 Does a MHL discourage cycling (short-term and long-term are relevant)? 3 Would repealing a MHL encourage more cycling (including with voluntary wearing)? 4 Would the increased cycling in itself reduce the crash risk per unit of cycling? 5 Would there be health benefits from more cycling by those previously discouraged? 6 Would the value of these health benefits be greater than the value of the health costs of the additional head injuries? 32 Professor Max Cameron, personal communication. J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 64 / 66

72 Acknowledgements Scott Walter, Tim Churches, Raphael Grzebieta, Andrew McIntosh, Mike Bambach, Rebecca Mitchell NSW Department of Health NSW Roads and Maritime Services Anti-helmet/MHL Advocates J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 65 / 66

73 Thank You! Questions? J Olivier (UNSW) Bicycle Helmet Laws 15/05/12 66 / 66