Evidence map›Paper›PMID 39758783›Full record

ArticleFrontiers in neurology2024

Exploring the effect of a sweltering environment on the risk of death from cardiovascular diseases.

Zhaocong Chen, Wangchao Li, Zhengjie Zhu, Xueliang Miao, Shuai Jiang, Caiming Li

Abstract read
In one paragraph

Article in Frontiers in neurology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Zhaocong Chen *The Second Clinical Medical College of Guangdong Medical University, Dongguan, Guangdong, China.
Wangchao Li *The Second Clinical Medical College of Guangdong Medical University, Dongguan, Guangdong, China.
Zhengjie ZhuThe Second Clinical Medical College of Guangdong Medical University, Dongguan, Guangdong, China.
Xueliang MiaoThe Second Clinical Medical College of Guangdong Medical University, Dongguan, Guangdong, China.
Shuai JiangHuizhou Meteorological Bureau, Huizhou, Guangdong, China.
Caiming LiDepartment of Neurology, Huizhou First Hospital, Huizhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: A substantial body of research has demonstrated a notable impact of hot temperatures on mortality from cardiovascular diseases (CVDs). However, a paucity of studies has addressed the influence of sweltering conditions on CVD mortality. Objective: To investigate the effect of sweltering conditions on mortality from CVD among permanent residents of Huizhou City, using the temperature-humidity index (THI) as an indicator. Methods: This study employs descriptive statistics, distributed lag non-linear model (DLNM) and general algebraic modeling system (GAMs) with the THI as an indicator in order to examine the impact of sweltering conditions on the mortality of CVD among permanent residents of Huizhou City. Results: Sweltering conditions increase the risk of death from CVDs and have a cumulative lag effect. The greater the THI, the more pronounced the increase in mortality, and after a certain range, the mortality rate from CVDs increases significantly, and the effect is gender-specific. The lag effect generally peaks in 2-3 days, and the lag effect of stroke mortality is longer and deeper than that of coronary heart disease (CAD) mortality. Conclusion: Sweltering increased the mortality of cardiovascular diseases in Huizhou city, so we should pay attention to public health intervention strategies under sweltering.

Indexed as

cardiovascular diseasescumulative lagstrokesweltering conditionstemperature-humidity index

Identifiers

PMID39758783
PMCPMC11697591

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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.