B Kopjar1. 1. Department of Population Health Sciences, National Institute of Public Health, Oslo, Norway. branko.kopjar@samfunnsmed.uio.no
Abstract
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 P calculation examples for all models were is 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.
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 P calculation examples for all models were is 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.