Assessing the health and economic burden of sick leave associated with long-term fine particulate matter exposure: a 13-year analysis using German health claims data.

BACKGROUND: Ambient fine particulate matter (PM) is a major environmental health risk, yet its contribution to sick leave and related productivity losses remains insufficiently quantified. We therefore examined the association between PM exposure and all-cause sick leave days and estimated the corresponding model-based burden and productivity losses.

METHODS: Using routine health insurance data from AOK Baden-Württemberg for 2010-2022, we fitted generalized additive models with penalised splines to estimate the exposure-response curve between monthly PM exposure and all-cause sick leave days. Models were adjusted for long-term trends, seasonality, temperature, sex, the COVID-19 period, NO, vacation days, and lockdown days, and accounted for spatial heterogeneity using a postal-code-based Markov random field. Model-based exposure contrasts were derived from predicted sick leave days at selected PM concentrations. Productivity losses were estimated using the human capital approach.

RESULTS: PM showed a positive non-linear association with sick-leave days (p < 0.001). Compared with 5 µg/m, adjusted predicted sick-leave days were 9.56% higher at 10 µg/m (95% CI 9.09-10.00) and 15.00% higher at 20 µg/m (95% CI 14.20-15.80), while little change was observed between 10 and 15 µg/m (+0.04%, 95% CI - 0.30 to 0.38). The overall non-linear association was supported across additional analyses, although its magnitude and precise shape varied with temporal coverage and covariate adjustment. PM concentrations above the WHO guideline of 5 µg/m corresponded to 105 model-attributable excess sick-leave days per 1,000 working-age inhabitants per year, equivalent to approximately 5.31 million excess sick-leave days and €1.56 billion in annual productivity losses in Germany.

CONCLUSION: Higher PM exposure was associated with a relevant model-attributable burden of sickness absence and productivity losses. These findings suggest that ambient PM may be an important population-level correlate of work absence, although causal interpretation is limited by the ecological study design and residual confounding.

Copyright © 2026 The Authors. Published by Elsevier Ltd.. All rights reserved.

PMID: 43025282