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Analys av bortfall i en uppföljningsundersökning av hälsa / Analysis of attrition in a longitudinal health study

<p>The LSH-study started in 2003 at the department of Health and Society at the University of Linköping. The purpose of the study was to examine the relationship between life condition, stress and health. A total of 1007 people from ten different health centres in Östergötlands län participated. At the follow up, a couple of years later, 795 of the 1007 participated. 127 of the 212 in the attrition turned down the follow up, twelve people were not invited (for example in case of death) and the rest did not respond at all. The purpose of this paper is to find out in what degree the attrition in the follow up can be predicted using the information from the first survey and which variables are important. The differences between different types of attrition have also been examined. Simple and multiple bi- and multinomial logistic regression have been used in the analysis.</p><p>In total 34 variables were examined and in the final model six variables remained with a significant relation to the attrition. High BMI, regular smoking, high pulse and lack of daily exercise at the first survey were connected to a higher risk for an individual to not participate at the follow up. It is interesting that these factors are considered as risk factors for unhealthy living. Other factors related to a higher attrition were unemployment in the last year before the first survey and if the individual had parents born in another country than Sweden. The risk for attrition increased gradually when more risk factors were shown by the individual. The factors contributing an individual to turn down the follow up instead of not responding at all was if he or she were in the older age segments in the survey or if they were not active in any type of association.</p>
Date January 2008
CreatorsUdd, Mattias, Pettersson, Niklas
PublisherLinköping University, Department of Computer and Information Science, Linköping University, Department of Computer and Information Science, Institutionen för datavetenskap
Source SetsDiVA Archive at Upsalla University
Detected LanguageEnglish
TypeStudent thesis, text

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