Causal Modeling in Environmental Health

Bind, Marie-Abèle

doi:10.1146/annurev-publhealth-040218-044048

Cited by 56 publications

(45 citation statements)

References 120 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The PSM approach, mimic to a randomized intervention (i.e., higher or lower air pollution exposure in this study), enabled us to obtain two comparable groups dwelling in more-and less-polluted areas. Although this approach weakens generalizability by selecting subgroups, it improves comparability and, in turn, the possibility of causal inference in observational studies (Bind 2019). In the present study, the propensity score was defined as the probability to be assigned to the higher or lower exposure group given a set of individual covariates.…”

Section: Discussionmentioning

confidence: 99%

Long-Term Ambient Air Pollution Exposures and Brain Imaging Markers in Korean Adults: The Environmental Pollution-Induced Neurological EFfects (EPINEF) Study

Cho

Noh

Kim

et al. 2020

Environ Health Perspect

View full text Add to dashboard Cite

BACKGROUND: Only a limited number of neuroimaging studies have explored the effects of ambient air pollution in adults. The prior studies have investigated only cortical volume, and they have reported mixed findings, particularly for gray matter. Furthermore, the association between nitrogen dioxide (NO 2) and neuroimaging markers has been little studied in adults. OBJECTIVES: We investigated the association between long-term exposure to air pollutants (NO 2 , particulate matter (PM) with aerodynamic diameters of ≤10 lm (PM10) and ≤2:5 lm (PM2.5), and neuroimaging markers. METHODS: The study included 427 men and 530 women dwelling in four cities in the Republic of Korea. Long-term concentrations of PM10, NO 2 , and PM2.5 at residential addresses were estimated. Neuroimaging markers (cortical thickness and subcortical volume) were obtained from brain magnetic resonance images. A generalized linear model was used, adjusting for potential confounders.

show abstract

Section: Discussionmentioning

confidence: 99%

Long-Term Ambient Air Pollution Exposures and Brain Imaging Markers in Korean Adults: The Environmental Pollution-Induced Neurological EFfects (EPINEF) Study

Cho

Noh

Kim

et al. 2020

Environ Health Perspect

View full text Add to dashboard Cite

show abstract

“…Additional limitations of these observational studies include the fact that most environmental health studies estimate conditional associations between non-randomised environmental exposures and health outcomes by directly regressing observed data without conceptual and design stages [40], an approach that is well documented to not guarantee valid causal inferences in general, especially in air pollution studies in which environmental exposures can be correlated with each other and effects are small [41,42]. Disentangling independent air pollutant effects has been a challenge for observational studies, but can be achieved if the latter is embedded into a hypothetical multi-pollutant randomised experiment [42]. Moreover, to assess the robustness of epidemiological conclusions, air pollution studies should systematically consider sensitivity analyses that either: 1) vary the magnitude of the relationships between the unmeasured background covariates and both the exposure assignment mechanism and the outcome; or 2) study deviations from the assumed exposure assignment mechanism.…”

Section: Air Pollution and Covid-19mentioning

confidence: 99%

The impact of outdoor air pollution on COVID-19: a review of evidence fromin vitro, animal, and human studies

et al. 2021

Self Cite

View full text Add to dashboard Cite

Studies have pointed out that air pollution may be a contributing factor to the coronavirus disease 2019 (COVID-19) pandemic. However, the specific links between air pollution and severe acute respiratory syndrome-coronavirus-2 infection remain unclear. Here we provide evidence from in vitro, animal and human studies from the existing literature. Epidemiological investigations have related various air pollutants to COVID-19 morbidity and mortality at the population level, however, those studies suffer from several limitations. Air pollution may be linked to an increase in COVID-19 severity and lethality through its impact on chronic diseases, such as cardiopulmonary diseases and diabetes. Experimental studies have shown that exposure to air pollution leads to a decreased immune response, thus facilitating viral penetration and replication. Viruses may persist in air through complex interactions with particles and gases depending on: 1) chemical composition; 2) electric charges of particles; and 3) meteorological conditions such as relative humidity, ultraviolet (UV) radiation and temperature. In addition, by reducing UV radiation, air pollutants may promote viral persistence in air and reduce vitamin D synthesis. Further epidemiological studies are needed to better estimate the impact of air pollution on COVID-19. In vitro and in vivo studies are also strongly needed, in particular to more precisely explore the particle–virus interaction in air.

show abstract

“…Practically, this refers to the absence of (measured or unmeasured) common causes of the exposure and outcome. Randomization is notably expected to achieve exchangeability but different identification strategies can be used for observational research including instrumental variables or difference-in-differences, for example, to achieve exchangeability [ 29 , 30 ]. Exchangeability can also be addressed by achieving covariate balance between exposure groups for measured confounders; different analytic or design strategies can be used in this regard, such as standardization and matching.…”

Section: Causal Interpretation(s) Of Race/ethnicity In Epidemiologymentioning

confidence: 99%

Inferential challenges when assessing racial/ethnic health disparities in environmental research

2021

View full text Add to dashboard Cite

Numerous epidemiologic studies have documented environmental health disparities according to race/ethnicity (R/E) to inform targeted interventions aimed at reducing these disparities. Yet, the use of R/E under the potential outcomes framework implies numerous underlying assumptions for epidemiologic studies that are often not carefully considered in environmental health research. In this commentary, we describe the current state of thinking about the interpretation of R/E variables in etiologic studies. We then discuss how such variables are commonly used in environmental epidemiology. We observed three main uses for R/E: i) as a confounder, ii) as an effect measure modifier and iii) as the main exposure of interest either through descriptive analysis or under a causal framework. We identified some common methodological concerns in each case and provided some practical solutions. The use of R/E in observational studies requires particular cautions in terms of formal interpretation and this commentary aims at providing a practical resource for future studies assessing racial/ethnic health disparities in environmental research.

show abstract

Causal Modeling in Environmental Health

Cited by 56 publications

References 120 publications

Long-Term Ambient Air Pollution Exposures and Brain Imaging Markers in Korean Adults: The Environmental Pollution-Induced Neurological EFfects (EPINEF) Study

Long-Term Ambient Air Pollution Exposures and Brain Imaging Markers in Korean Adults: The Environmental Pollution-Induced Neurological EFfects (EPINEF) Study

The impact of outdoor air pollution on COVID-19: a review of evidence fromin vitro, animal, and human studies

Inferential challenges when assessing racial/ethnic health disparities in environmental research

Contact Info

Product

Resources

About