The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
Evaluating the impact of long-term exposure to fine particulate matter on mortality among the elderly
Open accessAbstract
Long-term exposure to fine particulate matter positively affects all-cause mortality among the elderly.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
XGBoost: A Scalable Tree Boosting System
Chen, T., & Guestrin, C. (2016) · Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining · doi:10.1145/2939672.2939785 · Cited by 54,569
An association between air pollution and mortality in six U.S. cities
Dockery, D. W., Pope, C. A., Xu, X., Spengler, J. D., Ware, J. H., Fay, M. E., Ferris, B. G., & Speizer, F. E. (1993) · New England Journal of Medicine · doi:10.1056/nejm199312093292401 · Cited by 8,018
The Environment and Disease: Association or Causation?
Hill, A. B. (1965) · Proceedings of the Royal Society of Medicine · doi:10.1177/003591576505800503 · Cited by 6,974
Austin, P. C. (2009) · Statistics in Medicine · doi:10.1002/sim.3697 · Cited by 6,758
Sensitivity analysis in observational research: Introducing the E-value
VanderWeele, T. J., & Ding, P. (2017) · Annals of Internal Medicine · doi:10.7326/m16-2607 · Cited by 6,350
Marginal Structural Models and Causal Inference in Epidemiology
Robins, J. M., Hernán, M. Á., & Brumback, B. (2000) · Epidemiology · doi:10.1097/00001648-200009000-00011 · Cited by 5,581
Cox’s regression model for counting processes: A large sample study
Andersen, P. K., & Gill, R. D. (1982) · The Annals of Statistics · doi:10.1214/aos/1176345976 · Cited by 4,419
Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction
Imbens, G. W., & Rubin, D. B. (2015) · doi:10.1017/cbo9781139025751 · Cited by 4,210
Causal Inference Using Potential Outcomes: Design, Modeling, Decisions
Rubin, D. B. (2005) · Journal of the American Statistical Association · doi:10.1198/016214504000001880 · Cited by 2,173
Air pollution and mortality in the Medicare population
Di, Q., Wang, Y., Zanobetti, A., Wang, Y., Koutrakis, P., Choirat, C., Dominici, F., & Schwartz, J. D. (2017) · New England Journal of Medicine · doi:10.1056/nejmoa1702747 · Cited by 1,510
Cited by
Strak, M., Weinmayr, G., Rodopoulou, S., Chen, J., de Hoogh, K., Andersen, Z. J., Atkinson, R., Bauwelinck, M., Bekkevold, T., Bellander, T., et al. (2021) · BMJ · doi:10.1136/bmj.n1904 · Cited by 284
Air Pollution and Mortality at the Intersection of Race and Social Class
Josey, K. P., Delaney, S. W., Wu, X., Nethery, R. C., DeSouza, P., Braun, D., & Dominici, F. (2023) · New England Journal of Medicine · doi:10.1056/nejmsa2300523 · Cited by 142
Self-citationYao, Y., Lv, X., Qiu, C., Li, J., Wu, X., Zhang, H., Yue, D., Liu, K., Eshak, E. S., Lorenz, T., et al. (2022) · The Lancet Healthy Longevity · doi:10.1016/s2666-7568(22)00004-6 · Cited by 96
Self-citationSchwartz, J. D., Di, Q., Requia, W. J., Dominici, F., & Zanobetti, A. (2021) · Epidemiology · doi:10.1097/ede.0000000000001354 · Cited by 17
Metadata
- Authors
- Wu, X., Braun, D., Schwartz, J., Kioumourtzoglou, M. A., & Dominici, F.
- Venue
- Science Advances
- Published
- 2020-07-17
- Volume
- 6
- Issue
- 29
- Pages
- eaba5692-eaba5692
- ISSN
- 2375-2548 (ISSN-L)
- OpenAlex
- W3037987006
- Cited by
- 226
- References
- 14
- FWCI
- 10.62
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Evaluating the impact of long-term exposure to fine particulate matter on mortality among the elderly. https://app.cochat.ai/papers/10.1126/sciadv.aba5692
- The paper
- Wu, X., Braun, D., Schwartz, J., Kioumourtzoglou, M. A., & Dominici, F. (2020). Evaluating the impact of long-term exposure to fine particulate matter on mortality among the elderly. Science Advances. https://doi.org/10.1126/sciadv.aba5692
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.