Assessing environmental epidemiology questions in practice with a causal inference pipeline: An investigation of the air pollution‐multiple sclerosis relapses relationship

Sommer, Alice; Leray, Emmanuelle; Lee, Young; Bind, Marie‐Abèle

doi:10.1002/sim.8843

Cited by 10 publications

(8 citation statements)

References 61 publications

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“…We conceptualize plausible but hypothetical randomized experiments to estimate the short-term effects of an increase in vessel traffic on air pollutant concentrations in Marseille. We follow a "causal inference pipeline" (21,22,23,24) conceived to analyze observational data in a rigorous and transparent manner.…”

Section: Methodsmentioning

confidence: 99%

Estimating the Local Air Pollution Impacts of Maritime Traffic: A Principled Approach for Observational Data

Zabrocki¹,

Leroutier²,

Bind³

2021

Preprint

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Local environmental organizations and media have recently expressed concerns over air pollution induced by maritime traffic and its potential adverse health effects on the population of Mediterranean port cities. We explore this issue with unique high-frequency data from Marseille, France’s largest port for cruise ships, over the 2008- 2018 period. Using a new pair-matching algorithm designed for time series data, we create hypothetical randomized experiments and estimate the variation in air pollutant concentrations caused by a short-term increase in cruise vessel traffic. We carry out a randomization-based approach to compute 95% Fisherian intervals (FI) for constant treatment effects consistent with the matched data and the hypothetical intervention. At the hourly level, cruise vessels’ arrivals increase concentrations of nitrogen dioxide (NO2) by 4.7 μg/m³ (95% FI: [1.4, 8.0]), of sulfur dioxide (SO2) by 1.2 μg/m³ (95% FI: [-0.1, 2.5]), and of particulate matter (PM10) by 4.6 μg/m³ (95% FI: [0.9, 8.3]). At the daily level, cruise traffic increases concentrations of NO2 by 1.2 μg/m³ (95% FI: [-0.5, 3.0]) and of PM10 by 1.3 μg/m³ (95% FI: [-0.3, 3.0]). Our results suggest that well-designed hypothetical randomized experiments provide a principled approach to better understand the negative externalities of maritime traffic.

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Section: Methodsmentioning

confidence: 99%

Estimating the Local Air Pollution Impacts of Maritime Traffic: A Principled Approach for Observational Data

Zabrocki¹,

Leroutier²,

Bind³

2021

Preprint

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show abstract

“…We follow a "causal inference pipeline" (Sommer et al 2018, Rosenbaum et al 2010, Bind and Rubin 2019, Sommer et al 2021b conceived to analyze observational data in a rigorous and transparent manner.…”

Section: Methodsmentioning

confidence: 99%

Estimating the Local Air Pollution Impacts of Maritime Traffic: A Principled Approach for Observational Data

Zabrocki¹,

Leroutier²,

Bind³

2021

Preprint

View full text Add to dashboard Cite

Local environmental organizations and media have recently expressed concerns over air pollution induced by maritime traffic and its potential adverse health effects on the population of Mediterranean port cities. We explore this issue with unique highfrequency data from Marseille, France's largest port for cruise ships, over the 2008-2018 period. Using a new pair-matching algorithm designed for time series data, we create hypothetical randomized experiments and estimate the variation in air pollutant concentrations caused by a short-term increase in cruise vessel traffic. We carry out a randomization-based approach to compute 95% Fisherian intervals (FI) for constant treatment effects consistent with the matched data and the hypothetical intervention. At the hourly level, cruise vessels' arrivals increase concentrations of nitrogen dioxide (NO 2 ) by 4.7 µg/m 3 (95% FI: [1.4, 8.0]), of sulfur dioxide (SO 2 ) by 1.2 µg/m 3 (95% FI: [-0.1, 2.5]), and of particulate matter (PM 10 ) by 4.6 µg/m 3 (95% FI: [0.9, 8.3]). At the daily level, cruise traffic increases concentrations of NO 2 by 1.2 µg/m 3 (95% FI: [-0.5, 3.0]) and of PM 10 by 1.3 µg/m 3 (95% FI: [-0.3, 3.0]). Our results suggest that well-designed hypothetical randomized experiments provide a principled approach to better understand the negative externalities of maritime traffic.

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“…The causal inference framework illustrated in Figure 1 has been successfully implemented in recent observational studies examining whether air pollution exposure triggers multiple sclerosis relapses [10] or changes in human gut microbiome [11]. We now provide some additional examples.…”

Section: The Need Of a Conceptual Stage When Reporting The Statistical Analysis Of A Non-randomized Study That Estimates Causal Effectsmentioning

confidence: 99%

The importance of having a conceptual stage when reporting non-randomized studies

Bind

Rubin

2021

Biostatistics & Epidemiology

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Formal guidelines for statistical reporting of non-randomized studies are important for journals that publish results of such studies. Although it is gratifying to see some journals providing guidelines for statistical reporting, we feel that the current guidelines that we have seen are not entirely adequate when the study is used to draw causal conclusions. We therefore offer some comments on ways to improve these studies. In particular, we discuss and illustrate what we regard as the need for an essential initial stage of any such statistical analysis, the conceptual stage, which formally describes the embedding of a non-randomized study within a hypothetical randomized experiment.

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Assessing environmental epidemiology questions in practice with a causal inference pipeline: An investigation of the air pollution‐multiple sclerosis relapses relationship

Cited by 10 publications

References 61 publications

Estimating the Local Air Pollution Impacts of Maritime Traffic: A Principled Approach for Observational Data

Estimating the Local Air Pollution Impacts of Maritime Traffic: A Principled Approach for Observational Data

Estimating the Local Air Pollution Impacts of Maritime Traffic: A Principled Approach for Observational Data

The importance of having a conceptual stage when reporting non-randomized studies

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