Literature DB >> 25965040

A score for measuring health risk perception in environmental surveys.

Alessandro Marcon1, Giang Nguyen2, Marta Rava3, Marco Braggion4, Mario Grassi5, Maria Elisabetta Zanolin6.   

Abstract

BACKGROUND: In environmental surveys, risk perception may be a source of bias when information on health outcomes is reported using questionnaires. Using the data from a survey carried out in the largest chipboard industrial district in Italy (Viadana, Mantova), we devised a score of health risk perception and described its determinants in an adult population.
METHODS: In 2006, 3697 parents of children were administered a questionnaire that included ratings on 7 environmental issues. Items dimensionality was studied by factor analysis. After testing equidistance across response options by homogeneity analysis, a risk perception score was devised by summing up item ratings.
RESULTS: Factor analysis identified one latent factor, which we interpreted as health risk perception, that explained 65.4% of the variance of five items retained after scaling. The scale (range 0-10, mean ± SD 9.3 ± 1.9) had a good internal consistency (Cronbach's alpha 0.87). Most subjects (80.6%) expressed maximum risk perception (score = 10). Italian mothers showed significantly higher risk perception than foreign fathers. Risk perception was higher for parents of young children, and for older parents with a higher education, than for their counterparts. Actual distance to major roads was not associated with the score, while self-reported intense traffic and frequent air refreshing at home predicted higher risk perception.
CONCLUSIONS: When investigating health effects of environmental hazards using questionnaires, care should be taken to reduce the possibility of awareness bias at the stage of study planning and data analysis. Including appropriate items in study questionnaires can be useful to derive a measure of health risk perception, which can help to identify confounding of association estimates by risk perception.
Copyright © 2015 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Air pollution; Awareness bias; Environment; Optimal scaling; Psychometrics; Risk perception

Mesh:

Year:  2015        PMID: 25965040     DOI: 10.1016/j.scitotenv.2015.04.110

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  8 in total

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