The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Cause-Specific Risk of Hospital Admission Related to Extreme Heat in Older Adults
Open accessAbstract
IMPORTANCE: Heat exposure is known to have a complex set of physiological effects on multiple organ systems, but current understanding of the health effects is mostly based on studies investigating a small number of prespecified health outcomes such as cardiovascular and respiratory diseases. OBJECTIVES: To identify possible causes of hospital admissions during extreme heat events and to estimate their risks using historical data. DESIGN, SETTING, AND POPULATION: Matched analysis of time series data describing daily hospital admissions of Medicare enrollees (23.7 million fee-for-service beneficiaries [aged ≥65 years] per year; 85% of all Medicare enrollees) for the period 1999 to 2010 in 1943 counties in the United States with at least 5 summers of near-complete (>95%) daily temperature data. EXPOSURES: Heat wave periods, defined as 2 or more consecutive days with temperatures exceeding the 99th percentile of county-specific daily temperatures, matched to non-heat wave periods by county and week. MAIN OUTCOMES AND MEASURES: Daily cause-specific hospitalization rates by principal discharge diagnosis codes, grouped into 283 disease categories using a validated approach. RESULTS: Risks of hospitalization for fluid and electrolyte disorders, renal failure, urinary tract infection, septicemia, and heat stroke were statistically significantly higher on heat wave days relative to matched non-heat wave days, but risk of hospitalization for congestive heart failure was lower (P < .05). Relative risks for these disease groups were 1.18 (95% CI, 1.12-1.25) for fluid and electrolyte disorders, 1.14 (95% CI, 1.06-1.23) for renal failure, 1.10 (95% CI, 1.04-1.16) for urinary tract infections, 1.06 (95% CI, 1.00-1.11) for septicemia, and 2.54 (95% CI, 2.14-3.01) for heat stroke. Absolute risk differences were 0.34 (95% CI, 0.22-0.46) excess admissions per 100,000 individuals at risk for fluid and electrolyte disorders, 0.25 (95% CI, 0.12-0.39) for renal failure, 0.24 (95% CI, 0.09-0.39) for urinary tract infections, 0.21 (95% CI, 0.01-0.41) for septicemia, and 0.16 (95% CI, 0.10-0.22) for heat stroke. For fluid and electrolyte disorders and heat stroke, the risk of hospitalization increased during more intense and longer-lasting heat wave periods (P < .05). Risks were generally highest on the heat wave day but remained elevated for up to 5 subsequent days. CONCLUSIONS AND RELEVANCE: Among older adults, periods of extreme heat were associated with increased risk of hospitalization for fluid and electrolyte disorders, renal failure, urinary tract infection, septicemia, and heat stroke. However, the absolute risk increase was small and of uncertain clinical importance.
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Cites
Matching Methods for Causal Inference: A Review and a Look Forward
Stuart, E. A. (2010) · Statistical Science · doi:10.1214/09-sts313 · Cited by 5,478
Climate change and human health: present and future risks
McMichael, A. J., Woodruff, R. E., & Hales, S. (2006) · The Lancet · doi:10.1016/s0140-6736(06)68079-3 · Cited by 2,585
Bouchama, A., & Knochel, J. P. (2002) · New England Journal of Medicine · doi:10.1056/nejmra011089 · Cited by 1,898
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
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Self-citationGu, J., Shi, Y., Zhu, Y., Chen, N., Wang, H., Zhang, Z., & Chen, T. (2020) · PLOS Medicine · doi:10.1371/journal.pmed.1003188 · Cited by 184
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Dai, L., Kloog, I., Coull, B. A., Sparrow, D., Spiro, A., Vokonas, P. S., & Schwartz, J. D. (2016) · Environmental Research · doi:10.1016/j.envres.2016.06.036 · Cited by 58
Heat and emergency room admissions in the Netherlands
van Loenhout, J. A. F., Delbiso, T. D., Kiriliouk, A., Rodriguez-Llanes, J. M., Segers, J., & Guha-Sapir, D. (2018) · BMC Public Health · doi:10.1186/s12889-017-5021-1 · Cited by 58
Razzak, J. A., Agrawal, P., Chand, Z., Quraishy, S., Ghaffar, A., & Hyder, A. A. (2022) · BMJ Global Health · doi:10.1136/bmjgh-2021-006845 · Cited by 34
Climate change and human health in Montana: a special report of the Montana Climate Assessment
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Metadata
- Authors
- Bobb, J. F., Obermeyer, Z., Wang, Y., & Dominici, F.
- Venue
- JAMA
- Publisher
- American Medical Association (AMA)
- Published
- 2014-12-24
- Volume
- 312
- Issue
- 24
- Pages
- 2659
- ISSN
- 0002-9955 (ISSN-L)
- 0098-7484
- OpenAlex
- W2074805800
- Cited by
- 367
- References
- 6
- FWCI
- 8.39
- Type
- journal article
- Language
- en
- Open access
- green
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