This paper examines the differential impacts of early childhood exposure to air pollution on children’s health care use across parental income groups and vulnerability factors using French administrative data. Our quasi-experimental study reveals significant impacts on emergency admissions and respiratory medication in young children, attributed to air pollution shocks from thermal inversions. Using causal machine learning, we identify these health impacts as predominantly affecting 10% of infants, characterized by poor health indicators at birth and lower parental income. Our results suggest that intervention strategies focusing on vulnerability metrics may be more effective than those based solely on exposure levels.

JEL Codes: I14, I18, Q53, Q58

The authors have declared no competing interest.

- Agence Nationale de la Recherche through the program Investissements d'Avenir ANR-17-EURE-0001 - Social Sciences and Humanities Research Council of Canada

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The data collection and transmissions for the EDP-Sante to the DREES (Statistical Body of the French Ministry of Solidarity and Health) were approved by the French Data Protection Authority (CNIL) for the project of evaluation of the French National Health Strategy (Strategie Nationale de Sante), which comprises answers to environmental hazards such as air pollution. The DREES is allowed to process personal health data in order to compute statistics, under article 65 of the law Data processing and Liberties (Informatique et Libertes) of January 6th, 1978. All data processing and storage comply with the General Data Protection Regulation (GDPR).

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↵34 Neither the European Commission nor the European Centre for Medium-Range Weather Forecasts (ECMWF) bears responsibility for the use of Copernicus data in this report.

↵35 For instance, the point estimate 0.007 for outcome 4 in column (2) in Table 3 when multiplied by 1/0.12 equals to 0.058, which is statistically close to 0.057, the corresponding estimate in the fifth row and first column of Table B3, and equates 0.029 when multiplied by 1/0.24 whereas the corresponding estimate in B3 is 0.024.

All data produced in the present work are contained in the manuscript.