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Evaluation of Community-Based Injury Prevention Programs PhD course febr 2007 Leif Svanström. Evaluation of Community-Based Injury Prevention Programs First example Long-term evaluation of Vaeroy. Vaeroy, Norway. A lot of photos excluded!. The Role of the Health Sector !. VAEROY, NORWAY
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Evaluation of Community-Based Injury Prevention ProgramsPhD course febr 2007Leif Svanström
Evaluation of Community-Based Injury Prevention ProgramsFirst exampleLong-term evaluation of Vaeroy
VAEROY, NORWAY 1982-83 30% Reduction 1982-90 58% Reduction
PhD course jan- febr 2008VaeroyMultifactorial injury prevention programme started 1981 in a population of 1.000 population and lasted to 1987.Method:Registration 1970-2001Results: from 17.7% to 9.7% during 1981-7 and 96% by the year 2001Conclusion: Community program with defined aims will lead to a considerable and long-lasting reduction of injuries.
Evaluation of Community-Based Injury Prevention ProgramsSecond exampleLidköping Accid Prev Programme- children
PhD course jan- febr 2008Lidköping ChildrenMultifactorial injury prevention programme started 1984 in a population of about 30,000 population and evaluation lasted to 1991.Method:Surveillance hospital in-patient data 1983 to 1991Results: Annual decrease of 2.4% for boysand 2.1% for girls. Smaller decrease in control areas.Conclusion: Community program with defined aims will lead to a considerable reduction of injuries.
Evaluation of Community-Based Injury Prevention ProgramsThird exampleHelmet Wearing Programme- Sweden
Evaluation of Community-Based Injury Prevention Programs4th exampleIntra-Country Differences in Child Bicycle-related Injuries in Sweden?
PhD course jan- febr 2008Intra-Country DifferencesAnalyze differences in trend of childhood bicycle-related in Sweden.Method:Surveillance hospital in-patient data 1987 to 1996. Children 0-14 years.Statistical method with both linear and quadratic modelling.Results: No differences South-North, except for children 7-14 years. Substantial differences urban/rural areas.Conclusion: This method gives a better understanding of time trends than the traditional linear regression model only.