The European Journal of Public Health Advance Access published online on November 7, 2008
The European Journal of Public Health, doi:10.1093/eurpub/ckn102
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Statistical modelling needed to find the effects from a community-based elderly safety promotion program
Pia M. Johansson1, Antonio Ponce de Leon1,2, Siv Sadigh1, Per E. Tillgren1,3 and Clas Rehnberg4
1 Karolinska Institute, Department of Public Health Sciences, Stockholm, Sweden.
2 Department of Epidemiology, Institute of Social Medicine, University of Rio de Janeiro, Brazil.
3 Mälardalen University, School of Health, Care and Social Welfare, Västerås, Sweden.
4 Karolinska Institute, Medical Management Centre, Stockholm, Sweden.
Pia M Johansson, Norrbacka floor 2, SE-171 76 Stockholm, Sweden. tel.: +46 8 737 35 23, e-mail: pia.johansson{at}ki.se
Received March 26, 2008 , accepted September 29, 2008
Background: Multiple control areas and time-series analyses have been recommended for effect evaluations of community-based health promotion. Large fluctuations, maybe due to chance, among the areas and over the years might obscure the intervention effect. Methods: A quasi-experimental time-series analysis with several control areas was performed as an effect evaluation of a community-based elderly safety promotion program. The program was implemented during 1995–99 in a community in the Stockholm Metropolitan area (population +65 years: 5500; number of first hip fractures in 1995: 60). Four control areas were selected based on similar hip fracture-related characteristics as the intervention community, complemented with two larger control areas. The time series covered 6 years pre-intervention (1990–95) and 6 years post-intervention (1996–2001). The study population was divided into two age groups and gender, resulting in 28 panels. The first hip fracture incidence was obtained from the Swedish national in-patient register. Results: The time series revealed no discernible pattern, and conventional analyses showed no conclusive results. A multivariate analysis, examining the time trends by employing the intra-annual and intra-panel variance, revealed the underlying trends in hip fracture rates. Comparisons between predicted numbers of hip fractures in the intervention and control areas was enabled, which resulted in 14 less hip fractures in the intervention community than expected from the control communities. If one extreme value was altered, the result changed considerably. Conclusion: Effect evaluations of community-based health promotion programs using time-series from small communities might give faulty results, if statistical modelling is not employed.
Keywords: community intervention, effect evaluation, elderly injuries, panel data, random effects