Injury Case-Control Studies Using “Other Injuries” as Controls

Estimating lives saved and serious injuries reduced by bicycle helmet use in Colorado, 2006-2014

Using the methodology developed by the National Highway Traffic Safety Administration (NHTSA) for motorcyclists, this paper estimates bicycle helmet effectiveness factors (HEFs), defined as the percentage greater chance that a helmeted bicyclist will avoid a fatality or serious injury relative to a non-wearer. We analyse reported motor vehicle-bicycle collisions in Colorado between 2006 and 2014. We conclude that NHTSA's motorcycle HEF methodology did not provide reasonable results given underreporting of low-severity collisions of helmeted bicyclists. The HEF methodology may be applied to bicycles in future research if more complete bicyclist collision reporting can be obtained. To account for underreporting, we calibrated our bicycle HEFs to past research and found that approximately one of every two bicyclists killed may have survived (HEF = 0.50) and one of every three seriously injured bicyclists may have been less seriously injured (HEF = 0.33) if wearing a helmet at the time of the collision.

Bicycle helmet effectiveness is not overstated

OBJECTIVE

The objective of this study was to discuss the challenges in estimating bicycle helmet effectiveness from case-control studies of injured cyclists and to estimate helmet effectiveness from cases and available exposure data.

METHODS

Data were extracted from studies of cyclists in Seattle; Victoria and New South Wales, Australia; and The Netherlands. Estimates of helmet use were used as exposure to compute relative risks for Seattle and Victorian data. Cycling distance data are routinely collected in The Netherlands; however, these data cannot be disaggregated by helmet use, which makes it unsuitable for estimating helmet effectiveness. Alternative controls were identified from larger cohorts for the Seattle and New South Wales cases.

RESULTS

Estimates of helmet effectiveness were similar from odds ratios (ORs) using hospital controls or from relative risks (RRs) using helmet use estimates (Seattle: OR = 0.339, RR = 0.444; Victoria: OR = 0.500, RR = 0.353). Additionally, the odds ratios using hospital controls were similar when controls were taken from a larger cohort for head injury of any severity (Seattle: OR = 0.250, alt OR = 0.257; NSW: OR = 0.446, alt OR = 0.411) and for serious head injury (Seattle: OR = 0.135, alt OR = 0.139; NSW: OR = 0.335, alt OR = 0.308). Although relevant exposure data were unavailable for The Netherlands, the odds ratio for helmet effectiveness of those using racing, mountain, or hybrid bikes was similar to other estimates (OR = 0.371).

CONCLUSIONS

Despite potential weaknesses with case-control study designs, the best available evidence suggests that helmet use is an effective measure of reducing cycling head injury.

Time at risk and intention-to-treat analyses: parallels and implications for inference

Although the standard recommendation is to exclude person-time not at risk (ie, time during which the outcome could not have occurred) from the denominators of disease rates, there are scenarios where person-time not at risk should be included. In particular, we draw an analogy between including person-time not at risk and intention-to-treat (ITT) analyses of randomized trials, and excluding person-time not at risk and compliance-corrected analysis of these same trials. Excluding person-time not at risk is appropriate when addressing questions of the biologic or mechanistic effects of an exposure, whereas the ITT-type approach typically addresses questions regarding the effect of an exposure under observed compliance patterns. The choice of approach directly affects the causal question being addressed and subsequent inference, with potential implications for public health. When interested in estimating treatment effects that allow and account for potential noncompliance, or where the exposure may be associated with the time at risk, we argue that person-time not at risk should be included. In the case of time to pregnancy, although the ITT-type analysis may underestimate the biological fecundity of the population, it may also yield an answer to a question that is of more interest to couples trying to become pregnant.

The relationship between visibility aid use and motor vehicle related injuries among bicyclists presenting to emergency departments

BACKGROUND

Little is known about the effectiveness of visibility aids (VAs; e.g., reflectors, lights, fluorescent clothing) in reducing the risk of a bicyclist-motor-vehicle (MV) collision.

PURPOSE

To determine if VAs reduce the risk of a bicyclist-MV collision.

METHODS

Cases were bicyclists struck by a MV and assessed at Calgary and Edmonton, Alberta, Canada, emergency departments (EDs) from May 2008 to October 2010. Controls were bicyclists with non-MV injuries. Participants were interviewed about their personal and injury characteristics, including use of VAs. Injury information was collected from charts. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated for VAs during daylight and dark conditions, and adjusted for confounders using logistic regression. Missing values were imputed using chained equations and adjusted OR estimates from the imputed data were calculated.

RESULTS

There were 2403 injured bicyclists including 278 cases. After adjusting for age, sex, type of bicycling (commuting vs. recreational) and bicyclist speed, white compared with black (OR 0.52; 95% CI 0.28, 0.95), and bicyclist self-reported light compared with dark coloured (OR 0.67; 95% CI 0.49, 0.92) upper body clothing reduced the odds of a MV collision during daylight. After imputing missing values, white compared with black (OR 0.57; 95% CI: 0.32, 0.99) and bicyclist self-reported light compared with dark coloured (OR 0.71; 95% CI 0.52, 0.97) upper body clothing remained protective against MV collision in daylight conditions. During dark conditions, crude estimates indicated that reflective clothing or other items, red/orange/yellow front upper body clothing compared with black, fluorescent clothing, headlights and tail lights were estimated to increase the odds of a MV collision. An imputed adjusted analysis revealed that red/orange/yellow front upper body clothing colour (OR 4.11; 95% CI 1.06, 15.99) and tail lights (OR 2.54; 95% CI: 1.06, 6.07) remained the only significant risk factors for MV collisions. One or more visibility aids reduced the odds of a bicyclist MV collision resulting in hospitalization.

CONCLUSIONS

Bicyclist clothing choice may be important in reducing the risk of MV collision. The protective effect of visibility aids varies based on light conditions, and non-bicyclist risk factors also need to be considered.

The effectiveness of helmets in bicycle collisions with motor vehicles: a case-control study

There has been an ongoing debate in Australia and internationally regarding the effectiveness of bicycle helmets in preventing head injury. This study aims to examine the effectiveness of bicycle helmets in preventing head injury amongst cyclists in crashes involving motor vehicles, and to assess the impact of 'risky cycling behaviour' among helmeted and unhelmeted cyclists. This analysis involved a retrospective, case-control study using linked police-reported road crash, hospital admission and mortality data in New South Wales (NSW), Australia during 2001-2009. The study population was cyclist casualties who were involved in a collision with a motor vehicle. Cases were those that sustained a head injury and were admitted to hospital. Controls were those admitted to hospital who did not sustain a head injury, or those not admitted to hospital. Standard multiple variable logistic regression modelling was conducted, with multinomial outcomes of injury severity. There were 6745 cyclist collisions with motor vehicles where helmet use was known. Helmet use was associated with reduced risk of head injury in bicycle collisions with motor vehicles of up to 74%, and the more severe the injury considered, the greater the reduction. This was also found to be true for particular head injuries such as skull fractures, intracranial injury and open head wounds. Around one half of children and adolescents less than 19 years were not wearing a helmet, an issue that needs to be addressed in light of the demonstrated effectiveness of helmets. Non-helmeted cyclists were more likely to display risky riding behaviour, however, were less likely to cycle in risky areas; the net result of which was that they were more likely to be involved in more severe crashes.

Factors associated with injuries occurred on slope intersections and in snow parks compared to on-slope injuries

In alpine winter sports, external risk factors as snow and weather conditions as well as slope characteristics (width, steepness, slope intersections, and snow parks) should be considered when investigating potential risk factors. Therefore, ski patrol injury reports were used to compare factors associated with injuries occurred on slope intersections and in snow parks compared to on-slope injuries. Multivariate regression analysis revealed that in comparison to injuries occurring on ski slopes, collisions with other persons (OR: 2.1, 95% CI: 1.3-3.4) and arm injuries (OR: 2.1, 95% CI: 1.3-3.5) were more likely associated with injuries occurring on slope intersections while male gender (OR: 3.5, 95% CI: 2.1-5.7), younger age (OR: 1.1, 95% CI: 1.0-1.1), slushy/soft snow conditions (OR: 1.9, 95% CI: 1.1-3.3), knee injuries (OR: 0.4, 95% CI: 0.2-0.8) and back injuries (OR: 5.5, 95% CI: 3.0-10.2) were more likely associated with injuries which occurred in snow parks. In conclusion, injuries on slope intersections and in snow parks differ in some factors from injuries sustained on ski slopes.