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Population preventable fraction of bicycle related head injuries

机译:人口可预防的与自行车相关的头部受伤比例

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摘要

Objective—This study analyzes the population attributable fraction (PAF) of bicycle head injuries due to non-helmet use. Methods—The concept of the PAF and Levin's formula for its calculation were used to develop mathematical models for estimation of: (i) attributable fraction of bicycle related head injuries in the population due to non-helmet use, (ii) expected proportion of helmeted cases among all head injuries, and (iii) estimate of the helmet use rate in the population based on patient case information. The PAF was calculated for a sample of injuries from Stavanger, Norway. Results—Levin's formula was used to calculate the PAF. Two additional mathematical models were developed for calculating the expected proportion of helmeted cases and the estimation of the helmet use rate in the population. The calculation examples for all models were shown. It was estimated that 133 out of 210 injuries could have been avoided in Stavanger between 1990 and 1996 if all children aged 0–14 had used helmets. Conclusions—If applied correctly, the PAF is a valid and useful indicator for the population effects of bicycle helmets. The models developed in this study may help to better interpret and predict the population effects of helmet promotion interventions.
机译:目的—本研究分析了非头盔使用导致自行车头部受伤的人群可归因分数(PAF)。方法-使用PAF的概念及其计算的Levin公式来开发数学模型,以估算:(i)非头盔使用引起的自行车相关头部损伤在人群中所占的比例,(ii)头盔的预期比例所有头部受伤病例中;(iii)根据患者病例信息估算人群中头盔使用率。 PAF是针对挪威斯塔万格的一个伤害样本计算得出的。结果-使用莱文公式计算PAF。还开发了两个附加的数学模型,用于计算头盔病例的预期比例和人群中头盔使用率的估计。显示了所有模型的计算示例。据估计,如果所有0至14岁的儿童都戴头盔,在斯塔万格,在210例受伤中可以避免133例中的133例。结论—如果正确应用,PAF将是一种有效且有用的指示剂,用于说明自行车头盔的人口效应。在这项研究中开发的模型可能有助于更好地解释和预测头盔促进干预措施对人群的影响。

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