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Protein biomarkers are associated with mortality in cardiovascular disease, but their effect on predicting respiratory and all-cause mortality is not clear. We tested whether a protein risk score (protRS) can improve prediction of all-cause mortality over clinical risk factors in smokers. We utilized smoking-enriched (COPDGene, LSC, SPIROMICS) and general population-based (MESA) cohorts with SomaScan proteomic and mortality data. We split COPDGene into training and testing sets (50:50) and developed a protRS based on respiratory mortality effect size and parsimony. We tested multivariable associations of the protRS with all-cause, respiratory, and cardiovascular mortality, and performed meta-analysis, area-under-the-curve (AUC), and network analyses. We included 2232 participants. In COPDGene, a penalized regression-based protRS was most highly associated with respiratory mortality (OR 9.2) and parsimonious (15 proteins). This protRS was associated with all-cause mortality (random effects HR 1.79 [95% CI 1.31-2.43]). Adding the protRS to clinical covariates improved all-cause mortality prediction in COPDGene (AUC 0.87 vs 0.82) and SPIROMICS (0.74 vs 0.6), but not in LSC and MESA. Protein-protein interaction network analyses implicate cytokine signaling, innate immune responses, and extracellular matrix turnover. A blood-based protein risk score predicts all-cause and respiratory mortality, identifies potential drivers of mortality, and demonstrates heterogeneity in effects amongst cohorts.

BACKGROUND: The potential health benefits of exposure to vegetation, or greenness, are well documented, but there are few nationwide studies in Brazil, a country facing challenges related to land-use planning, deforestation, and environmental health risks. OBJECTIVES: In this study, we investigated the association between greenness and hospitalizations for cardiorespiratory diseases in Brazil. METHODS: We accessed hospital admissions data from 967,771 postal codes (a total of 26,724,624 admissions) covering Brazil for the period between 2008 and 2018. We used Normalized Difference Vegetation Index (NDVI) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) to measure greenness at the postal-code level. First, we applied a quasi-Poisson regression model to estimate the association between greenness and hospitalizations for circulatory and respiratory diseases, adjusted for air pollution, weather variables, and area-level socioeconomic status. We stratified the analyzes by sex, age group, health outcome, and Brazilian regions. In the second stage, we performed a meta-analysis to estimate pooled effects across the Brazilian regions. RESULTS: The national meta-analysis for the whole population, incorporating both urban and nonurban areas, showed that higher levels of greenness were associated with a lower risk of hospitalizations for circulatory diseases. An interquartile range (IQR=0.18) increase in average NDVI was associated with a 17% (95% confidence interval: 8%, 27%) lower risk of cardiovascular admissions. In contrast, there was no association found between greenness and respiratory admissions. When specifically examining urban areas, the results remained consistent with the overall findings. However, the analyses of nonurban areas revealed divergent results, suggesting that higher levels of greenness in rural regions are associated with a lower risk of hospital admissions for both circulatory and respiratory diseases. DISCUSSION: The findings emphasize the importance of prioritizing the preservation and creation of green spaces in urban areas as a means of promoting cardiovascular health in Brazil. https://doi.org/10.1289/EHP13442.