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J Toxicol Environ Health A ; 84(23): 973-985, 2021 12 02.
Artigo em Inglês | MEDLINE | ID: mdl-34369284

RESUMO

The continuous drop out of participants in longitudinal studies is a trend that may be observed in nearly all fields of medical research. A reduced participation rate might compromise the power of statistical analysis as well as lead to an attrition bias of the study. The aim of this analysis was to identify influencing factors on participation frequency in the monitoring program Health Effects in High Level Exposure to polychlorinated biphenyls (HELPcB) study, a cohort investigation of occupationally polychlorinated biphenyls (PCB) exposed individuals. The HELPcB study was initiated in 2010 and consisted of 7 study visits. At the last cross-section in 2019, less than one third of the included patients still actively participated. As possible influencing factors on study participation frequency, demographic, social, and medical characteristics of the participants were examined. In addition, a logistic regression model to predict study participation behavior was calculated. An overall higher frequency of participation was observed, if participants joined the program together with relatives or friends and had a higher age. For PCB plasma levels, an exceedance of the biological reference value (BAR) and further factors, such as (1) professional qualification, (2) later inclusion, (3) type of participant and (4) occupational-related disease notification, significant differences in the participation frequency were observed in the univariate analysis. Only age and joined study participation remained significant in the multivariate logistic regression. In conclusion, it was possible to identify several social and occupational-related factors that influence the frequency of participation of study attendees.


Assuntos
Participação da Comunidade/estatística & dados numéricos , Poluentes Ambientais/toxicidade , Bifenilos Policlorados/toxicidade , Adulto , Estudos Transversais , Demografia , Feminino , Humanos , Modelos Logísticos , Estudos Longitudinais , Perda de Seguimento , Masculino , Pessoa de Meia-Idade , Exposição Ocupacional/efeitos adversos , Exposição Ocupacional/estatística & dados numéricos , Fatores Sociais
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