The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Weather-Related Mortality: How Heat, Cold, and Heat Waves Affect Mortality in the United States
Open accessAbstract
BACKGROUND: Many studies have linked weather to mortality; however, role of such critical factors as regional variation, susceptible populations, and acclimatization remain unresolved. METHODS: We applied time-series models to 107 US communities allowing a nonlinear relationship between temperature and mortality by using a 14-year dataset. Second-stage analysis was used to relate cold, heat, and heat wave effect estimates to community-specific variables. We considered exposure timeframe, susceptibility, age, cause of death, and confounding from pollutants. Heat waves were modeled with varying intensity and duration. RESULTS: Heat-related mortality was most associated with a shorter lag (average of same day and previous day), with an overall increase of 3.0% (95% posterior interval: 2.4%-3.6%) in mortality risk comparing the 99th and 90th percentile temperatures for the community. Cold-related mortality was most associated with a longer lag (average of current day up to 25 days previous), with a 4.2% (3.2%-5.3%) increase in risk comparing the first and 10th percentile temperatures for the community. Mortality risk increased with the intensity or duration of heat waves. Spatial heterogeneity in effects indicates that weather-mortality relationships from 1 community may not be applicable in another. Larger spatial heterogeneity for absolute temperature estimates (comparing risk at specific temperatures) than for relative temperature estimates (comparing risk at community-specific temperature percentiles) provides evidence for acclimatization. We identified susceptibility based on age, socioeconomic conditions, urbanicity, and central air conditioning. CONCLUSIONS: Acclimatization, individual susceptibility, and community characteristics all affect heat-related effects on mortality.
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
Inference for Multivariate Normal Hierarchical Models
Everson, P. J., & Morris, C. N. (2000) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/1467-9868.00239 · Cited by 107
Cited by
Mortality risk attributable to high and low ambient temperature: a multicountry observational study
Gasparrini, A., Guo, Y., Hashizume, M., Lavigne, E., Zanobetti, A., Schwartz, J., Tobias, A., Tong, S., Rocklöv, J., Forsberg, B., et al. (2015) · The Lancet · doi:10.1016/s0140-6736(14)62114-0 · Cited by 2,965
Self-citationDistributed lag non‐linear models
Gasparrini, A., Armstrong, B., & Kenward, M. G. (2010) · Statistics in Medicine · doi:10.1002/sim.3940 · Cited by 2,481
Estimating economic damage from climate change in the United States
Hsiang, S., Kopp, R., Jina, A., Rising, J., Delgado, M., Mohan, S., Rasmussen, D. J., Muir-Wood, R., Wilson, P., Oppenheimer, M., et al. (2017) · Science · doi:10.1126/science.aal4369 · Cited by 1,239
Anderson, G. B., & Bell, M. L. (2011) · Environmental Health Perspectives · doi:10.1289/ehp.1002313 · Cited by 1,191
Self-citationReducing and meta-analysing estimates from distributed lag non-linear models
Gasparrini, A., & Armstrong, B. (2013) · BMC Medical Research Methodology · doi:10.1186/1471-2288-13-1 · Cited by 1,081
Metadata
- Authors
- Anderson, B. G., & Bell, M. L.
- Venue
- Epidemiology
- Published
- 2009-03
- Volume
- 20
- Issue
- 2
- Pages
- 205-213
- ISSN
- 1044-3983 (ISSN-L)
- OpenAlex
- W1987925218
- Cited by
- 1,229
- References
- 1
- FWCI
- 25.27
- Type
- journal article
- Language
- en
- Open access
- green
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
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.