Selecting subpopulations for intervention |
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| Authors: | S Wacholder C R Weinberg |
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| Affiliation: | 1. McGill University, Department of Epidemiology and Biostatistics, 1020 Pine Avenue West, Montreal, Quebec, Canada H3A 1A2;2. National Institute of Environmental Health Sciences, Biometry and Risk Assessment Program, P.O.B. 12233, Research Triangle Park, NC 27709, U.S.A.;1. MScPH student, McGill University, Montreal, Canada;2. MScPH student intern, Connecting Organizations for Regional Disease Surveillance (CORDS), Lyon, France;3. Programme manager Strategy & Operations (Consultant), Connecting Organizations for Regional Disease Surveillance (CORDS), Lyon, France;4. Director Strategy & Operations (Consultant), Connecting Organizations for Regional Disease Surveillance (CORDS), Lyon, France;5. Managing Director, Dickmann Risk Communication DRC, London, UK;1. School of Materials Science and Engineering, South China University of Technology, Guangzhou 510641, China;2. School of Medicine, South China University of Technology, Guangzhou 510006, China;3. National Engineering Research Centre for Tissue Restoration and Reconstruction, Guangzhou 510006, China;4. School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, China;5. Key Laboratory of Biomedical Engineering of Guangdong Province, South China University of Technology, Guangzhou 510006, China;6. Key Laboratory of Biomedical Materials and Engineering of the Ministry of Education, South China University of Technology, Guangzhou 510006, China;7. Zhongshan Institute of Modern Industrial Technology of SCUT, Zhongshan, Guangdong 528437, China;1. Applied Chemistry, Department of Chemical and Biological Engineering, Chalmers University of Technology, 412 96 Göteborg, Sweden;2. SuMo BIOMATERIALS, VINN Excellence Center, Chalmers University of Technology, 412 96 Göteborg, Sweden;3. Department of Structure and Material Design, The Swedish Institute for Food and Biotechnology, SIK, Göteborg, Sweden;4. Singapore Institute of Technology, 10 Dover Drive, Singapore 138683, Singapore;1. INRA, UR1303 ALISS, F-94200 Ivry-sur-Seine, France;2. INRA, UMR1215 GAEL, F-38000 Grenoble, France;1. School of Chemistry and Chemical Engineering, Shanxi University, Taiyuan, 030006, PR China;2. Institute of Molecular Science, Chemical Biology and Molecular Engineering, Laboratory of Education Ministry, Shanxi University, Taiyuan 030006, PR China;3. College of Service, Naval University of Engineering, Tianjin, 300450, PR China |
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| Abstract: | The effectiveness of a program designed to eliminate exposure to a risk factor may be enhanced by selecting specific subpopulations for the intervention effort. A second factor is called an intervention effect modifier of the first factor if the effect of the intervention. If an intervention effect modifier exists, a program's effectiveness may be enhanced by choosing a subpopulation for intervention on the basis of the distribution of that factor. We discuss the conditions in which intervention effect modification can occur when there is a third factor which influences risk. Additivity of incidence rates, the criterion when only two factors are involved, is neither necessary nor sufficient to rule out intervention effect modification in this situation. We also discuss the cost effectiveness of intervention strategies when the cost per successful intervention varies. |
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