Validation of self-reported perception of proximity to industrial facilities: MCC-Spain study
Background: Self-reported data about environmental exposures can lead to measurement error. Objectives: To validate the self-reported perception of proximity to industrial facilities. Methods: MCC-Spain is a population-based multicase-control study of cancer in Spain that recruited incident cases of...
| Autores: | , , |
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| Formato: | artículo |
| Fecha de publicación: | 2020 |
| País: | España |
| Recursos: | Universidad de Alcalá (UAH) |
| Repositorio: | e_Buah Biblioteca Digital Universidad de Alcalá |
| Idioma: | inglés |
| OAI Identifier: | oai:ebuah.uah.es:10017/42311 |
| Acesso em linha: | http://hdl.handle.net/10017/42311 https://dx.doi.org/10.1016/j.envint.2019.105316 |
| Access Level: | acceso abierto |
| Palavra-chave: | Self-reported perception Residential proximity Case-control study Sensitivity Specificity AUC Industrial pollution MCC-Spain Medicina Medicine |
| Resumo: | Background: Self-reported data about environmental exposures can lead to measurement error. Objectives: To validate the self-reported perception of proximity to industrial facilities. Methods: MCC-Spain is a population-based multicase-control study of cancer in Spain that recruited incident cases of breast, colorectal, prostate, and stomach cancer. The participant’s current residence and the location of the industries were geocoded, and the linear distance between them was calculated (gold standard). The epidemiological questionnaire included a question to determine whether the participants perceived the presence of any industry at ≤1 km from their residences. Sensitivity and specificity of individuals' perception of proximity to industries were estimated as measures of classification accuracy, and the area under the curve (AUC) and adjusted odds ratios (aORs) of misclassification were calculated as measures of discrimination. Analyses were performed for all cases and controls, and by tumor location, educational level, sex, industrial sector, and length of residence. Finally, aORs of cancer associated with real and self-reported distances were calculated to explore differences in the estimation of risk between these measures. Results: Sensitivity of the questionnaire was limited (0.48) whereas specificity was excellent (0.89). AUC was sufficient (0.68). Participants with breast (aOR(95%CI) = 2.03 (1.67;2.46)), colorectal (aOR(95%CI) = 1.41 (1.20;1.64)) and stomach (aOR(95%CI) = 1.59 (1.20;2.10)) cancer showed higher risk of misclassification than controls. This risk was higher for lower educational levels (aOR<primary vs. university (95%CI) = 1.78 (1.44;2.20)), among younger participants (aOR22-54 years vs. 73-85 years (95%CI) = 1.32 (1.09;1.60)), and for some industrial sectors: pharmaceutical (aOR(95%CI) = 29.02 (19.52;43.14)), galvanization (aOR(95%CI) = 14.14 (6.78;29.47)), and ceramic (aOR(95%CI) = 12.73 (7.22;22.44)). Participants living ≤1 year in the study area showed a lower risk of misclassification ((aOR≤1 vs. >15 years (95%CI) = 0.56 (0.36;0.85)). The use of self-reported proximity vs. real distance to industrial facilities biased the effect on cancer risk towards the nullity. Conclusions: Self-reported distance to industrial facilities can be a useful tool for hypothesis generation, but hypothesis-testing studies should use real distance to report valid conclusions. The sensitivity of the question might be improved with a more specific formulation. |
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