Evidence map›Paper›PMID 33963898›Full record

ArticleInternational journal of biometeorology2021

Temperature-sensitive morbidity indicator: consequence from the increased ambulance dispatches associated with heat and cold exposure.

Qingchuan Wang, Yiling He, Shakoor Hajat, Jian Cheng, Zhiwei Xu, Wenbiao Hu, Wenjun Ma, Cunrui Huang

Abstract read
PubMed Publisher
In one paragraph

Article in International journal of biometeorology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Qingchuan Wang *Shenzhen Longhua District Central Hospital, 187 Guanlan Avenue, Longhua District, Shenzhen, 518110, China. 573664758@qq.com.
Yiling He *School of Public Health, Sun Yat-sen University, Zhongshan Road #2, Guangzhou, 510080, China.ORCID http://orcid.org/0000-0003-4243-191X
Shakoor HajatDepartment of Public Health, Environments and Society, School of Hygiene & Tropical Medicine, London, London, UK.
Jian ChengDepartment of Epidemiology and Biostatistics & Anhui Province Key Laboratory of Major Autoimmune Disease, School of Public Health, Anhui Medical University, Anhui, China.
Zhiwei XuSchool of Public Health, University of Queensland, Brisbane, Australia.
Wenbiao HuSchool of Public Health and Social Work, Queensland University of Technology, Brisbane, Australia.
Wenjun MaGuangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
Cunrui HuangSchool of Public Health, Sun Yat-sen University, Zhongshan Road #2, Guangzhou, 510080, China. huangcr@mail.sysu.edu.cn.

Funding

Asia-Pacific Network for Global Change Research (JP) CRRP2016-10MYSG02-HuangNational Key R&D Program of China 2018YFA0606200Natural Science Foundation of Guangdong Province 2016A030313216
6 · The paper itself

Abstract

Current development of temperature-related health early warning systems mainly arises from knowledge of temperature-related mortality or hospital-based morbidity. However, due to the delay in data reporting and limits in hospital capacity, these indicators cannot be used in health risk assessments timely. In this study, we examine temperature impacts on emergency ambulance and discuss the benefits of using this near real-time indicator for risk assessment and early warning. We collected ambulance dispatch data recording individual characteristics and preliminary diagnoses between 2015 and 2016 in Shenzhen, China. Distributed lag nonlinear model was used to examine the effects of high and low temperatures on ambulance dispatches during warm and cold seasons. Lag effects were also assessed to evaluate the sensitivity of ambulance dispatches in reflecting immediate health reactions. Stratified analyses by gender, age, and a wide range of diagnoses were performed to identify vulnerable subgroups. Disease-specific numbers of ambulance dispatches attributable to non-optimal temperature were calculated to determine the related medical burdens. Effects of temperature on ambulance dispatches appeared to be acute on the current day. Males, people aged 18-44 years, were more susceptible to non-optimal temperatures. Highest RR during heat exposure by far was for urinary disease, alcohol intoxication, and traumatic injury, while alcohol intoxication and cardiovascular disease were especially sensitive to cold exposure, causing the main part of health burden. The development of local health surveillance systems by utilizing ambulance dispatch data are important for temperature impact assessments and medical resource reallocation.

Indexed as

AmbulancesHot TemperatureCold TemperatureHumansMaleMorbidityTemperatureAmbient temperatureAmbulance dispatchClimate changeHealth effectSurveillance system

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.