Olivier Jake, Radun Igor
a School of Mathematics and Statistics , University of New South Wales , Sydney , NSW , Australia.
b Human Factors and Safety Behavior Group, Department of Psychology and Logopedics, Faculty of Medicine , University of Helsinki , Helsinki , Finland.
Traffic Inj Prev. 2017 Oct 3;18(7):755-760. doi: 10.1080/15389588.2017.1298748. Epub 2017 Mar 1.
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.
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.
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).
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.
本研究的目的是探讨从受伤骑行者的病例对照研究中估计自行车头盔有效性所面临的挑战,并根据病例和可用的暴露数据估计头盔的有效性。
数据取自西雅图、澳大利亚维多利亚州和新南威尔士州以及荷兰的骑行者研究。将头盔使用估计值用作暴露因素,以计算西雅图和维多利亚州数据的相对风险。荷兰常规收集骑行距离数据;然而,这些数据无法按头盔使用情况进行分类,这使其不适用于估计头盔有效性。从更大的队列中为西雅图和新南威尔士州的病例确定了替代对照。
使用医院对照的比值比(OR)与使用头盔使用估计值的相对风险(RR)得出的头盔有效性估计值相似(西雅图:OR = 0.339,RR = 0.444;维多利亚:OR = 0.500,RR = 0.353)。此外,当从任何严重程度的头部损伤的更大队列中选取对照时,使用医院对照的比值比相似(西雅图:OR = 0.250,替代OR = 0.257;新南威尔士州:OR = 0.446,替代OR = 0.411)以及对于严重头部损伤(西雅图:OR = 0.135,替代OR = 0.139;新南威尔士州:OR = 0.335,替代OR = 0.308)。尽管荷兰没有相关的暴露数据,但使用竞赛、山地或混合动力自行车的人的头盔有效性比值比与其他估计值相似(OR = 0.371)。
尽管病例对照研究设计存在潜在弱点,但现有最佳证据表明,使用头盔是减少骑行时头部损伤的有效措施。