Association Between Particulate Matter Pollution and CKD Mortality by Social Deprivation

Understanding the Cardiovascular and Metabolic Health Effects of Air Pollution in the Context of Cumulative Exposomic Impacts

Poor air quality accounts for more than 9 million deaths a year globally according to recent estimates. A large portion of these deaths are attributable to cardiovascular causes, with evidence indicating that air pollution may also play an important role in the genesis of key cardiometabolic risk factors. Air pollution is not experienced in isolation but is part of a complex system, influenced by a host of other external environmental exposures, and interacting with intrinsic biologic factors and susceptibility to ultimately determine cardiovascular and metabolic outcomes. Given that the same fossil fuel emission sources that cause climate change also result in air pollution, there is a need for robust approaches that can not only limit climate change but also eliminate air pollution health effects, with an emphasis of protecting the most susceptible but also targeting interventions at the most vulnerable populations. In this review, we summarize the current state of epidemiologic and mechanistic evidence underpinning the association of air pollution with cardiometabolic disease and how complex interactions with other exposures and individual characteristics may modify these associations. We identify gaps in the current literature and suggest emerging approaches for policy makers to holistically approach cardiometabolic health risk and impact assessment.

Association of Environmental Injustice and Cardiovascular Diseases and Risk Factors in the United States

BACKGROUND

While the impacts of social and environmental exposure on cardiovascular risks are often reported individually, the combined effect is poorly understood.

METHODS AND RESULTS

Using the 2022 Environmental Justice Index, socio-environmental justice index and environmental burden module ranks of census tracts were divided into quartiles (quartile 1, the least vulnerable census tracts; quartile 4, the most vulnerable census tracts). Age-adjusted rate ratios (RRs) of coronary artery disease, strokes, and various health measures reported in the Prevention Population-Level Analysis and Community Estimates data were compared between quartiles using multivariable Poisson regression. The quartile 4 Environmental Justice Index was associated with a higher rate of coronary artery disease (RR, 1.684 [95% CI, 1.660-1.708]) and stroke (RR, 2.112 [95% CI, 2.078-2.147]) compared with the quartile 1 Environmental Justice Index. Similarly, coronary artery disease 1.057 [95% CI,1.043-1.0716] and stroke (RR, 1.118 [95% CI, 1.102-1.135]) were significantly higher in the quartile 4 than in the quartile 1 environmental burden module. Similar results were observed for chronic kidney disease, hypertension, diabetes, obesity, high cholesterol, lack of health insurance, sleep <7 hours per night, no leisure time physical activity, and impaired mental and physical health >14 days.

CONCLUSIONS

The prevalence of CVD and its risk factors is highly associated with increased social and environmental adversities, and environmental exposure plays an important role independent of social factors.

Air pollution exposure and cardiometabolic risk

The Global Burden of Disease assessment estimates that 20% of global type 2 diabetes cases are related to chronic exposure to particulate matter (PM) with a diameter of 2·5 μm or less (PM2·5). With 99% of the global population residing in areas where air pollution levels are above current WHO air quality guidelines, and increasing concern in regard to the common drivers of air pollution and climate change, there is a compelling need to understand the connection between air pollution and cardiometabolic disease, and pathways to address this preventable risk factor. This Review provides an up to date summary of the epidemiological evidence and mechanistic underpinnings linking air pollution with cardiometabolic risk. We also outline approaches to improve awareness, and discuss personal-level, community, governmental, and policy interventions to help mitigate the growing global public health risk of air pollution exposure.

Geographical Patterns and Risk Factor Association of Cardio-Oncology Mortality in the United States

Cardio-oncology mortality (COM) is a complex issue that is compounded by multiple factors that transcend a depth of socioeconomic, demographic, and environmental exposures. Although metrics and indexes of vulnerability have been associated with COM, advanced methods are required to account for the intricate intertwining of associations. This cross-sectional study utilized a novel approach that combined machine learning and epidemiology to identify high-risk sociodemographic and environmental factors linked to COM in United States counties. The study consisted of 987,009 decedents from 2,717 counties, and the Classification and Regression Trees model identified 9 county socio-environmental clusters that were closely associated with COM, with a 64.1% relative increase across the spectrum. The most important variables that emerged from this study were teen birth, pre-1960 housing (lead paint indicator), area deprivation index, median household income, number of hospitals, and exposure to particulate matter air pollution. In conclusion, this study provides novel insights into the socio-environmental drivers of COM and highlights the importance of utilizing machine learning approaches to identify high-risk populations and inform targeted interventions for reducing disparities in COM.