ArticleInternational journal of biometeorology2013
A respiratory alert model for the Shenandoah Valley, Virginia, USA.
Article in International journal of biometeorology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 21 citations in OpenAlex.
- Climate and sino-nasal symptoms.International journal of biometeorology · 2026Article
- Analysis of indoor human thermal comfort in Pelotas municipality, extreme southern Brazil.International journal of biometeorology · 2021Article
- Examining the diurnal temperature range enigma: why is human health related to the daily change in temperature?International journal of biometeorology · 2020Article
- Excess of children's outpatient consultations due to asthma and bronchitis and the association between meteorological variables in Canoas City, Southern Brazil.International journal of biometeorology · 2019Article
- Latitude and daily-weather effects on gobbling activity of wild turkeys in Mississippi.International journal of biometeorology · 2019Article
- Past, present and future of the climate and human health commission.International journal of biometeorology · 2017Review
- A retrospective study of the impact of a telephone alert service (Healthy Outlook) on hospital admissions for patients with chronic obstructive pulmonary disease.NPJ primary care respiratory medicine · 2014Article
- Heat-related morbidity in brisbane, australia: spatial variation and area-level predictors.Environmental health perspectives · 2014Article
- The SSC: a decade of climate-health research and future directions.International journal of biometeorology · 2014Article
Corrections and comments
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Respiratory morbidity (particularly COPD and asthma) can be influenced by short-term weather fluctuations that affect air quality and lung function. We developed a model to evaluate meteorological conditions associated with respiratory hospital admissions in the Shenandoah Valley of Virginia, USA. We generated ensembles of classification trees based on six years of respiratory-related hospital admissions (64,620 cases) and a suite of 83 potential environmental predictor variables. As our goal was to identify short-term weather linkages to high admission periods, the dependent variable was formulated as a binary classification of five-day moving average respiratory admission departures from the seasonal mean value. Accounting for seasonality removed the long-term apparent inverse relationship between temperature and admissions. We generated eight total models specific to the northern and southern portions of the valley for each season. All eight models demonstrate predictive skill (mean odds ratio = 3.635) when evaluated using a randomization procedure. The predictor variables selected by the ensembling algorithm vary across models, and both meteorological and air quality variables are included. In general, the models indicate complex linkages between respiratory health and environmental conditions that may be difficult to identify using more traditional approaches.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.