Evidence map›Paper›PMID 26024362›Full record

ArticleInternational journal of environmental research and public health2015

Cardiovascular mortality associated with low and high temperatures: determinants of inter-region vulnerability in China.

Xunfeng Yang, Lianfa Li, Jinfeng Wang, Jixia Huang, Shijun Lu

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–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

10 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Spatial patterns of health vulnerability to heatwaves in Vietnam.International journal of biometeorology · 2020
    Article
  7. Regional Temperature-Sensitive Diseases and Attributable Fractions in China.International journal of environmental research and public health · 2019
    Article
  8. A new method to estimate the temperature-CVD mortality relationship.Environmental science and pollution research international · 2019
    Article
  9. Effects of Extreme Temperatures on Mortality and Hospitalization in Ho Chi Minh City, Vietnam.International journal of environmental research and public health · 2019
    Article
  10. The Threshold Temperature and Lag Effects on Daily Excess Mortality in Harbin, China: A Time Series Analysis.The international journal of occupational and environmental medicine · 2017
    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

5 authors.

Xunfeng YangState Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Datun Road, Beijing 100101, China. yxffcq@163.com.
Lianfa LiState Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Datun Road, Beijing 100101, China. lilf@lreis.ac.cn.
Jinfeng WangState Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Datun Road, Beijing 100101, China. wangjf@lreis.ac.cn.
Jixia HuangPrecision Forestry Key Laboratory of Beijing, Beijing Forestry University, Beijing 100083, China. jxhuang701@gmail.com.
Shijun LuNational Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, 29 Nanwei Road, Xicheng District, Beijing 100050, China. lushijun666666@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The objectives of this study were to estimate the effects of temperature on cardiovascular mortality in 26 regions in the south and west of China from 2008 to 2011, and to identify socioeconomic and demographic factors contributing to such inter-region variation in the temperature effect. A separate Poisson generalized additive model (GAM) was fitted to estimate percent changes in cardiovascular mortality at low and high temperatures on a daily basis for each region. The model used the smooth functions to model the nonlinear effects of temperature and humidity and to control for the seasonal factor using the calendar time variable. Given variation in the magnitude of the temperature effect on cardiovascular mortality, we employed a Bayesian network (BN) to identify potential region-specific socioeconomic and demographic factors that may explain the variation. In most regions, an increasing trend in high or low temperature was associated with an increase in cardiovascular mortality, with variation in the magnitude of the temperature effects across regions. Three factors, including per capita years of education (as an indicator of economic status), percentage of the population over 65 years of age and percentage of women had direct impact on cold-related cardiovascular mortality. Number of hospital beds (as an indicator of the availability of medical resources), percentage of population engaged in industrial occupations, and percentage of women showed direct impact on heat-related cardiovascular mortality. Due to the socioeconomic and demographic inequalities between regions, the development of customized prevention and adaptation programs to address the low/high temperatures in vulnerable regions should be prioritized.

Indexed as

Health Status DisparitiesAdultAgedAged, 80 and overBayes TheoremCardiovascular DiseasesChinaCold TemperatureFemaleHot TemperatureHumansMaleMiddle AgedModels, StatisticalRisk FactorsSeasonsBayesian networkcardiovascular mortalityPoisson generalized additive modelsocioeconomic and demographic factorstemperature

Identifiers

PMID26024362
PMCPMC4483679

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Registered trials

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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.