This Correspondence by Man Sun, Dan Zang and Jun Chen addresses interpretation and translational claims arising from a recent nationally representative case–control study by Alhattab et al. that associated long-term ambient PM2.5 exposure with lung cancer risk in a relatively low-pollution setting. The authors note the increasing prominence of lung cancer among never-smokers, and they frame the exchange as timely because environmental exposures are assuming a larger role in prevention frameworks.
The correspondence is a response to Alhattab et al., who used high-resolution geospatial modelling in a population-based case–control design to estimate the burden of lung cancer attributable to ambient particulate matter. Sun and colleagues acknowledge the value of a nationally representative dataset and detailed exposure modelling in contributing evidence on PM2.5 and lung cancer.
Sun et al. state that several methodological and interpretative issues in the original study "warrant clarification". While the correspondence does not present new empirical analyses, it raises concerns about how findings from observational exposure studies are characterised and communicated with respect to causation and practical translation.
The correspondence highlights the need to delineate clearly the scope of causal inference that can be drawn from observational designs, and to specify the limits of translating such associations into prevention recommendations or burden estimates. The authors call for clarification of these points to avoid overstating conclusions from the reported association between ambient PM2.5 and lung cancer in the analysed setting.
Sun and colleagues emphasise that, as lung cancer among never-smokers becomes more prominent, careful interpretation of environmental risk factor studies is essential. They argue that delimiting what can be inferred causally from observational data and what can reasonably be translated into public health action is necessary for valid prevention frameworks. The correspondence thus focuses attention on the intersection of methodological rigour in epidemiology and the responsible communication of findings relevant to policy and clinical prevention.
The correspondence references several items to contextualise its concerns and to point readers to methodological resources and relevant empirical literature. Citations include the original Alhattab et al. study and works on causal inference from observational studies, global PM2.5 exposures and inequalities, methods for estimating effects of time-varying exposures, exposure measurement error in PM2.5 and NO2 assessment, and reviews on particulate matter as a cause of lung cancer. Specific references listed in the correspondence are provided in the published article's reference list.
No new data were generated or analysed for this correspondence; all discussion is derived from the published study by Alhattab et al. The authors acknowledge the original investigators for their contribution. Funding for the correspondence was provided by the National Natural Science Foundation of China (Grant No. 82203056). The authors declare no competing interests.
Sun, Zang and Chen call for clarification on methodological and interpretative points to better define causal and translational inference in studies linking ambient PM2.5 and lung cancer. Their Correspondence underscores the importance of careful framing when reporting associations from observational environmental epidemiology, particularly given the rising relevance of environmental determinants in lung cancer among never-smokers. The correspondence—published 27 July 2026 in British Journal of Cancer—serves as a scholarly prompt for further methodological clarity and discussion of how best to translate observational evidence into prevention strategies.
This piece is a Correspondence published in British Journal of Cancer (received 20 December 2025; revised 10 June 2026; accepted 02 July 2026; published 27 July 2026). Authors: Man Sun, Dan Zang and Jun Chen (Department of Oncology, The Second Hospital of Dalian Medical University, Dalian City, China). Correspondence to Jun Chen. DOI: 10.1038/s41416-026-03555-2.
The authors thank the investigators of the original study for making their findings available for scholarly discussion. Springer Nature's publisher note indicates neutrality regarding jurisdictional claims in published maps and institutional affiliations.