The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Hospital Admissions for Heart Disease: The Effects of Temperature and Humidity
Abstract
BACKGROUND: We estimated the effects of temperature and humidity on hospital admissions for heart disease (International Classification of Diseases, 9th revision [ICD-9] codes 390-429) and myocardial infarction (ICD-9 code 410) of persons age 65 and older in 12 U.S. cities with a wide range of climates. To account for possible delayed effects and harvesting, we examined the impact of weather up to 20 days before each admission. METHODS: Poisson regression models were fitted in each city, with regression splines used to control for season and barometric pressure. We also controlled day of the week. We estimated the effect and the lag structure of both temperature and humidity based on a distributed lag model. FINDINGS: For cities in both hot and cold climates, we found that hospital admissions for all heart disease increased monotonically with average temperature on the same day as and the day before admission. The effect of very high temperatures had a temporal pattern consistent with harvesting: several days after an episode of high temperature, there were fewer admissions. In contrast, a protective effect of cold temperature persisted without rebound. The effects of either hot or cold temperature disappeared within 10 days of exposure. There was no evidence for a humidity effect. Similar but smaller effects of temperature were seen for admissions for myocardial infarction specifically. CONCLUSIONS: The effects of temperature on hospital admissions predominantly occur within a few days after exposure, and much of the effect of hot temperatures is short-term displacement of events.
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
Excess hospital admissions during the July 1995 heat wave in Chicago
Semenza, J. (1999) · American Journal of Preventive Medicine · doi:10.1016/s0749-3797(99)00025-2 · Cited by 619
Cited by
The Effects of Climate Change on Cardiac Health
De Blois, J., Kjellstrom, T., Agewall, S., Ezekowitz, J. A., Armstrong, P. W., & Atar, D. (2015) · Cardiology · doi:10.1159/000398787 · Cited by 1,697
Ambient Temperature and Morbidity: A Review of Epidemiological Evidence
Ye, X., Wolff, R., Yu, W., Vaneckova, P., Pan, X., & Tong, S. (2012) · Environmental Health Perspectives · doi:10.1289/ehp.1003198 · Cited by 660
Heat-related mortality: a review and exploration of heterogeneity
Hajat, S., & Kosatky, T. (2010) · Journal of Epidemiology and Community Health · doi:10.1136/jech.2009.087999 · Cited by 577
Uejio, C. K., Wilhelmi, O. V., Golden, J. S., Mills, D. M., Gulino, S. P., & Samenow, J. P. (2011) · Health & Place · doi:10.1016/j.healthplace.2010.12.005 · Cited by 504
Wong, C.-M., Vichit-Vadakan, N., Kan, H., & Qian, Z. (2008) · Environmental Health Perspectives · doi:10.1289/ehp.11257 · Cited by 476
Metadata
- Authors
- Schwartz, J., Samet, J. M., & Patz, J. A.
- Venue
- Epidemiology
- Published
- 2004-11
- Volume
- 15
- Issue
- 6
- Pages
- 755-761
- ISSN
- 1044-3983 (ISSN-L)
- OpenAlex
- W2073589335
- Cited by
- 349
- References
- 1
- FWCI
- 5.02
- Type
- journal article
- Language
- en
- Open access
- closed
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: Hospital Admissions for Heart Disease: The Effects of Temperature and Humidity. https://app.cochat.ai/papers/10.1097/01.ede.0000134875.15919.0f
- The paper
- Schwartz, J., Samet, J. M., & Patz, J. A. (2004). Hospital Admissions for Heart Disease: The Effects of Temperature and Humidity. Epidemiology. https://doi.org/10.1097/01.ede.0000134875.15919.0f
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.