期刊
EPIDEMIOLOGY
卷 28, 期 1, 页码 72-76出版社
LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1097/EDE.0000000000000567
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资金
- Ministry of Education of the Spanish Government [PRX12/00515]
- National Institute for Health Research Health Protection Research Unit (NIHR HPRU) in Environmental Change and Health
- UK Medical Research Council [MR/M022625/1]
- Medical Research Council [MR/M022625/1, G0701030] Funding Source: researchfish
- MRC [G0701030, MR/M022625/1] Funding Source: UKRI
Background: The minimum mortality temperature from J-or U-shaped curves varies across cities with different climates. This variation conveys information on adaptation, but ability to characterize is limited by the absence of a method to describe uncertainty in estimated minimum mortality temperatures. Methods: We propose an approximate parametric bootstrap estimator of confidence interval (CI) and standard error (SE) for the minimum mortality temperature from a temperature-mortality shape estimated by splines. Results: The coverage of the estimated CIs was close to nominal value (95%) in the datasets simulated, although SEs were slightly high. Applying the method to 52 Spanish provincial capital cities showed larger minimum mortality temperatures in hotter cities, rising almost exactly at the same rate as annual mean temperature. Conclusions: The method proposed for computing CIs and SEs for minimums from spline curves allows comparing minimum mortality temperatures in different cities and investigating their associations with climate properly, allowing for estimation uncertainty.
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