Spatial environmental factors predict cardiovascular and all-cause mortality: Results of the SPACE study

• Published in: PloS one Vol. 17; no. 6; p. e0269650
• Main Authors: Hadley, Michael B, Nalini, Mahdi, Adhikari, Samrachana, Szymonifka, Jackie, Etemadi, Arash, Kamangar, Farin, Khoshnia, Masoud, McChane, Tyler, Pourshams, Akram, Poustchi, Hossein, Sepanlou, Sadaf G, Abnet, Christian, Freedman, Neal D, Boffetta, Paolo, Malekzadeh, Reza, Vedanthan, Rajesh
• Format: Journal Article
• Language: English
• Published: San Francisco Public Library of Science 24-06-2022; Public Library of Science (PLoS)
• Subjects: Air pollution; Analysis; Biology and Life Sciences; Cancer; Cardiovascular disease; Cardiovascular diseases; Diabetes; Ecology and Environmental Sciences; Engineering and Technology; Enrollments; Environmental factors; Environmental risk; Ethnicity; Evaluation; Exposure; Frailty; Fuels; Geospatial data; Health aspects; Heart; Hypertension; Income; Land use; Medicine and Health Sciences; Mortality; Particulate matter; Patient outcomes; Physical Sciences; Population density; Risk analysis; Risk factors; Socioeconomic factors; Stroke; Survival; Traffic; Ventilation; Iran
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0269650

Environmental exposures account for a growing proportion of global mortality. Large cohort studies are needed to characterize the independent impact of environmental exposures on mortality in low-income settings. We collected data on individual and environmental risk factors for a multiethnic cohort of 50,045 individuals in a low-income region in Iran. Environmental risk factors included: ambient fine particular matter air pollution; household fuel use and ventilation; proximity to traffic; distance to percutaneous coronary intervention (PCI) center; socioeconomic environment; population density; local land use; and nighttime light exposure. We developed a spatial survival model to estimate the independent associations between these environmental exposures and all-cause and cardiovascular mortality. Several environmental factors demonstrated associations with mortality after adjusting for individual risk factors. Ambient fine particulate matter air pollution predicted all-cause mortality (per [mu]g/m.sup.3, HR 1.20, 95% CI 1.07, 1.36) and cardiovascular mortality (HR 1.17, 95% CI 0.98, 1.39). Biomass fuel use without chimney predicted all-cause mortality (reference = gas, HR 1.23, 95% CI 0.99, 1.53) and cardiovascular mortality (HR 1.36, 95% CI 0.99, 1.87). Kerosene fuel use without chimney predicted all-cause mortality (reference = gas, HR 1.09, 95% CI 0.97, 1.23) and cardiovascular mortality (HR 1.19, 95% CI 1.01, 1.41). Distance to PCI center predicted all-cause mortality (per 10km, HR 1.01, 95% CI 1.004, 1.022) and cardiovascular mortality (HR 1.02, 95% CI 1.004, 1.031). Additionally, proximity to traffic predicted all-cause mortality (HR 1.13, 95% CI 1.01, 1.27). In a separate validation cohort, the multivariable model effectively predicted both all-cause mortality (AUC 0.76) and cardiovascular mortality (AUC 0.81). Population attributable fractions demonstrated a high mortality burden attributable to environmental exposures.