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Cancer Mortality and Deprivation in the Proximity of Polluting Industrial Facilities in an Industrial Region of Spain

Author

Listed:
  • Vanessa Santos-Sánchez

    (Department of Economics and Business, University of Sassari, Via Muroni 25, 07100 Sassari, Italy)

  • Juan Antonio Córdoba-Doña

    (Department of Preventive Medicine and Public Health, Jerez University Hospital, Ronda de Circunvalación s/n, 11407 Jerez de la Frontera, Spain)

  • Javier García-Pérez

    (Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Avenida Monforte de Lemos 5, 28029 Madrid, Spain
    Center for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiología y Salud Pública-CIBERESP), 28029 Madrid, Spain)

  • Antonio Escolar-Pujolar

    (Consejería de Salud de la Junta de Andalucía, Cádiz, Avenida María Auxiliadora 2, 11009 Cádiz, Spain)

  • Lucia Pozzi

    (Department of Economics and Business, University of Sassari, Via Muroni 25, 07100 Sassari, Italy)

  • Rebeca Ramis

    (Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Avenida Monforte de Lemos 5, 28029 Madrid, Spain
    Center for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiología y Salud Pública-CIBERESP), 28029 Madrid, Spain)

Abstract

Residential proximity to industrial facilities that release pollutants is a source of exposure to a high number of toxics, many of them known or suspected carcinogens. The objective of the study was to analyze the association between lung, larynx, bladder, and kidney cancer mortality and deprivation in areas proximate to polluting industrial facilities in Cadiz, a highly industrialized province in Spain. An ecological study at census tract level was carried out to estimate the mortality rates associated with deprivation and proximity to polluting industrial facilities (1–5 km) using the Besag–York–Mollié model. The results show a negative social gradient for lung and larynx cancers in males and greater risk of lung cancer was observed in the least deprived areas in females. These associations were found regardless the distance to industrial facilities. Increasing excess risk (relative risk; 95% credibility interval) of lung cancer for males (1.09; 1.02–1.16 at 5 km vs 1.24; 1.08–1.41 at 1 km) and bladder cancer for males (1.11; 1.01–1.22 at 5 km vs 1.32; 1.08–1.60 at 1 km) and females (1.32; 1.04–1.69 at 4 km vs 1.91; 1.28–2.86 at 1 km) was found as proximity to polluting industrial facilities increased. For kidney cancer, high risks were observed near such facilities for both sexes. Knowing the possible influence of industrial pollution and social inequalities over cancer risk allows the definition of policies aimed at reducing the risk.

Suggested Citation

  • Vanessa Santos-Sánchez & Juan Antonio Córdoba-Doña & Javier García-Pérez & Antonio Escolar-Pujolar & Lucia Pozzi & Rebeca Ramis, 2020. "Cancer Mortality and Deprivation in the Proximity of Polluting Industrial Facilities in an Industrial Region of Spain," IJERPH, MDPI, vol. 17(6), pages 1-15, March.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:6:p:1860-:d:332036
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    References listed on IDEAS

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    1. Julian Besag & Jeremy York & Annie Mollié, 1991. "Bayesian image restoration, with two applications in spatial statistics," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 43(1), pages 1-20, March.
    2. Håvard Rue & Sara Martino & Nicolas Chopin, 2009. "Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(2), pages 319-392, April.
    3. Hong-Bae Kim & Jae-Yong Shim & Byoungjin Park & Yong-Jae Lee, 2018. "Long-Term Exposure to Air Pollutants and Cancer Mortality: A Meta-Analysis of Cohort Studies," IJERPH, MDPI, vol. 15(11), pages 1-15, November.
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