Impact of large industrial emission sources on mortality and morbidity in Chile: A small-areas study. (July 2016)

• Record Type: Journal Article
• Authors: Ruiz-Rudolph, Pablo; Arias, Nelson; Pardo, Sandra; Meyer, Marianne; Mesías, Stephanie; Galleguillos, Claudio; Schiattino, Irene; Gutiérrez, Luis
• Is Part Of: Environment international. Volume 92/93(2016:Jul.)
• Page Start: 130
• Page End: 138
• Publication Date: 2016-07
• Subjects: BYM Besag, York, and Mollie -- CAR conditional autoregressive model -- ICD-10 International Classification of Diseases, version 10 -- km2 square kilometers -- NOX nitrogen oxides -- MW megawatts -- OECD Organization for Economic Co-operation and Development -- PM2.5 particulate matter smaller than 2.5 μm -- PM10 particulate matter smaller than 10 μm -- SO2 sulfur dioxide -- UNDP United Nations Development Programme -- HDI Human Development Index -- SES socioeconomic status -- SMR standardized mortality/morbidity ratios -- $USD US dollars -- US United States -- WinBUGS Windows Bayesian inference Using Gibbs Sampling; Cardiovascular -- Respiratory -- Cancer -- Power plants -- Copper smelter -- Mining facilities; Environmental protection -- Periodicals; Environmental health -- Periodicals; Environmental monitoring -- Periodicals; Environmental Monitoring -- Periodicals; Environnement -- Protection -- Périodiques; Hygiène du milieu -- Périodiques; Environnement -- Surveillance -- Périodiques; Environmental health; Environmental monitoring; Environmental protection; Periodicals; 333.705
• DOI: 10.1016/j.envint.2016.03.036
• Languages: English
• ISSNs: 0160-4120

Abstract

Abstract: Chile suffers significant pollution from large industrial emitters associated with the mining, metal processing, paper production, and energy industries. The aim of this research was to determine whether the presence of large industrial facilities ( i.e. coal- and oil-fired power plants, pulp and paper mills, mining facilities, and smelters) affects mortality and morbidity rates in Chile. For this, we conducted an ecological study that used Chilean communes as small-area observation units to assess mortality and morbidity. Public databases provided information on large pollution sources relevant to Chile. The large sources studied were oil- and coal-fired power plants, copper smelters, pulp and paper mills, and large mining facilities. Large sources were filtered by first year of production, type of process, and size. Mortality and morbidity data were acquired from public national databases, with morbidity being estimated from hospitalization records. Cause-specific rates were calculated for the main outcomes: cardiovascular, respiratory, cancer; and other more specific health outcomes. The impact of the large pollution sources was estimated using Bayesian models that included spatial correlation, overdispersion, and other covariates. Large and significant increases in health risks (around 20%–100%) were found for communes with power plants and smelters for total, cardiovascular, respiratory, all-cancer, and lung cancer mortality. Higher hospitalization rates for cardiovascular disease, respiratory disease, cancer, and pneumonia (20–100%) were also found for communes with power plants and smelters. The impacts were larger for men than women in terms of both mortality and hospitalizations. The impacts were also larger when the sources were analyzed as continuous (production volume) rather than dichotomous (presence/absence) variables. In conclusion, significantly higher rates of total cardiovascular, respiratory, all-cancer and lung cancer mortality and cardiovascular, respiratory, cancer and pneumonia hospitalizations were observed in communes with power plants and smelters. Graphical abstract: Highlights: First study in Chile or Latin America of small-areas health impacts of large industrial facilities Power plants and copper smelters were associated with higher morbidity/mortality. Increased outcomes included cardiovascular, respiratory and cancer. Results were consistent between mortality and morbidity outcomes. Results were more robust when quantitative predictors were used.