Evidence map›Paper›PMID 30414026›Full record

ArticleEnvironmental science and pollution research international2019

Socio-geographic disparity in cardiorespiratory mortality burden attributable to ambient temperature in the United States.

Yunquan Zhang, Qianqian Xiang, Yong Yu, Zhiying Zhan, Kejia Hu, Zan Ding

Abstract read
PubMed Publisher
In one paragraph

Article in Environmental science and pollution research international, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 3 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

27 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Global Population Exposure to Extreme Temperatures and Disease Burden.International journal of environmental research and public health · 2022
    Article
  17. Article
  18. Review
  19. Article
  20. Extended two-stage designs for environmental research.Environmental health : a global access science source · 2022
    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

6 authors.

Yunquan ZhangDepartment of Preventive Medicine, School of Health Sciences, Wuhan University, 185 Donghu Road, Wuhan, 430071, China. Yun-quanZhang@whu.edu.cn.ORCID http://orcid.org/0000-0002-2618-5088
Qianqian XiangHubei Provincial Center for Disease Control and Prevention, Wuhan, 430079, China.
Yong YuSchool of Public Health and Management, Hubei University of Medicine, Shiyan, 442000, China.
Zhiying ZhanDepartment of Biostatistics, School of Public Health and Tropical Medicine, Southern Medical University, Guangzhou, 510515, China.
Kejia HuInstitute of Island and Coastal Ecosystems, Ocean College, Zhejiang University, Zhoushan, 316021, China.
Zan DingThe Institute of Metabolic Diseases, Baoan Central Hospital of Shenzhen, Shenzhen, 518102, China. dingzan_1990@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Compared with relative risk, attributable fraction (AF) is more informative when assessing the mortality burden due to some environmental exposures (e.g., ambient temperature). Up to date, however, available AF-based evidence linking temperature with mortality has been very sparse regionally and nationally, even for the leading mortality types such as cardiorespiratory deaths. This study aimed to quantify national and regional burden of cardiorespiratory mortality (CRM) attributable to ambient temperature in the USA, and to explore potential socioeconomic and demographic sources of spatial heterogeneity between communities. Daily CRM and weather data during 1987-2000 for 106 urban communities across the mainland of USA were acquired from the publicly available National Morbidity, Mortality and Air Pollution Study (NMMAPS). We did the data analysis using a three-stage analytic approach. We first applied quasi-Poisson regression incorporated with distributed lag nonlinear model to estimate community-specific temperature-CRM associations, then pooled these associations at the regional and national level through a multivariate meta-analysis, and finally estimated the temperature-AF of CRM and performed subgroup analyses stratified by community-level characteristics. Both low and high temperatures increased short-term CRM risk, while temperature-CRM associations varied by regions. Nationally, the fraction of cardiorespiratory deaths caused by the total non-optimum, low, and high temperatures was 7.58% (95% empirical confidence interval, 6.68-8.31%), 7.15% (6.31-7.85%), and 0.43% (0.37-0.46%), respectively. Greater temperature-AF was identified in two northern regions (i.e., Industrial Midwest and North East) and communities with lower temperature and longitude, higher latitude, and moderate humidity. Additionally, higher vulnerability appeared in locations with higher urbanization level, more aging population, less White race, and lower socioeconomic status. Ambient temperature may be responsible for a large fraction of cardiorespiratory deaths. Also, temperature-AF of CRM varied considerably by geographical and climatological factors, as well as community-level disparity in socioeconomic status.

Indexed as

TemperatureAir PollutionCardiovascular DiseasesCold TemperatureEnvironmental ExposureHot TemperatureHumansHumidityMeteorologyMortalityMultivariate AnalysisNonlinear DynamicsRespiratory Tract DiseasesSocial ClassUnited StatesUrbanizationAttributable fractionCardiorespiratory mortalityClimate changeTemperatureUnited States

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.