TY - JOUR
T1 - Modeled and perceived RF-EMF, noise and air pollution and symptoms in a population cohort. Is perception key in predicting symptoms?
AU - Martens, Astrid L.
AU - Reedijk, Marije
AU - Smid, Tjabe
AU - Huss, Anke
AU - Timmermans, Danielle
AU - Strak, Maciej
AU - Swart, Wim
AU - Lenters, Virissa
AU - Kromhout, Hans
AU - Verheij, Robert
AU - Slottje, Pauline
AU - Vermeulen, Roel C.H.
N1 - Funding Information:
This work was supported by The Netherlands Organisation for Health Research (ZonMw) within the programme Electromagnetic Fields and Health Research under grant number 85200001 . The ESCAPE model used for air pollutant modelling received funding from the European Community's Seventh Framework Program (FP7/2007-2011) under grant agreement number 211250. The authors declare they have no actual or potential competing financial interests. We would like to thank Inka Pieterson for data management and Johan Beekhuizen for the original RF-modelling. We would also like to thank all the participants for taking the time and effort to participate in our study.
Publisher Copyright:
© 2018 Elsevier B.V.
PY - 2018/10/15
Y1 - 2018/10/15
N2 - Background: Psychosocial research has shown that perceived exposure can influence symptom reporting, regardless of actual exposure. The impact of this phenomenon on the interpretation of results from epidemiological research on environmental determinants of symptoms is unclear. Objective: Our aim was to compare associations between modeled exposures, the perceived level of these exposures and reported symptoms (non-specific symptoms, sleep disturbances, and respiratory symptoms) for three different environmental exposures (radiofrequency electromagnetic fields (RF-EMF), noise, and air pollution). These environmental exposures vary in the degree to which they can be sensorially observed. Methods: Participant characteristics, perceived exposures, and self-reported health were assessed with a baseline (n = 14,829, 2011/2012) and follow-up (n = 7905, 2015) questionnaire in the Dutch population-based Occupational and Environmental Health Cohort (AMIGO). Environmental exposures were estimated at the home address using spatial models. Cross-sectional and longitudinal regression models were used to examine the associations between modeled and perceived exposures, and reported symptoms. Results: The extent to which exposure sources could be observed by participants likely influenced correlations between modeled and perceived exposure as correlations were moderate for air pollution (rSp = 0.34) and noise (rSp = 0.40), but less so for RF-EMF (rSp = 0.11). Perceived exposures were consistently associated with increased symptom scores (respiratory, sleep, non-specific). Modeled exposures, except RF-EMF, were associated with increased symptom scores, but these associations disappeared or strongly diminished when accounted for perceived exposure in the analyses. Discussion: Perceived exposure has an important role in symptom reporting. When environmental determinants of symptoms are studied without acknowledging the potential role of both modeled and perceived exposures, there is a risk of bias in health risk assessment. However, the etiological role of exposure perceptions in relation to symptom reporting requires further research.
AB - Background: Psychosocial research has shown that perceived exposure can influence symptom reporting, regardless of actual exposure. The impact of this phenomenon on the interpretation of results from epidemiological research on environmental determinants of symptoms is unclear. Objective: Our aim was to compare associations between modeled exposures, the perceived level of these exposures and reported symptoms (non-specific symptoms, sleep disturbances, and respiratory symptoms) for three different environmental exposures (radiofrequency electromagnetic fields (RF-EMF), noise, and air pollution). These environmental exposures vary in the degree to which they can be sensorially observed. Methods: Participant characteristics, perceived exposures, and self-reported health were assessed with a baseline (n = 14,829, 2011/2012) and follow-up (n = 7905, 2015) questionnaire in the Dutch population-based Occupational and Environmental Health Cohort (AMIGO). Environmental exposures were estimated at the home address using spatial models. Cross-sectional and longitudinal regression models were used to examine the associations between modeled and perceived exposures, and reported symptoms. Results: The extent to which exposure sources could be observed by participants likely influenced correlations between modeled and perceived exposure as correlations were moderate for air pollution (rSp = 0.34) and noise (rSp = 0.40), but less so for RF-EMF (rSp = 0.11). Perceived exposures were consistently associated with increased symptom scores (respiratory, sleep, non-specific). Modeled exposures, except RF-EMF, were associated with increased symptom scores, but these associations disappeared or strongly diminished when accounted for perceived exposure in the analyses. Discussion: Perceived exposure has an important role in symptom reporting. When environmental determinants of symptoms are studied without acknowledging the potential role of both modeled and perceived exposures, there is a risk of bias in health risk assessment. However, the etiological role of exposure perceptions in relation to symptom reporting requires further research.
KW - Air pollutants (traffic);perceived exposure
KW - Multidisciplinary longitudinal cohort study
KW - Noise (traffic)
KW - RF-EMF base stations
KW - Symptom reporting
UR - http://www.scopus.com/inward/record.url?scp=85047059649&partnerID=8YFLogxK
U2 - 10.1016/j.scitotenv.2018.05.007
DO - 10.1016/j.scitotenv.2018.05.007
M3 - Article
AN - SCOPUS:85047059649
SN - 0048-9697
VL - 639
SP - 75
EP - 83
JO - Science of the Total Environment
JF - Science of the Total Environment
ER -