Evidence map›Paper›PMID 38562664›Full record

ArticleGeoHealth2024

Short-Term Effects of Extreme Meteorological Factors on Hand, Foot, and Mouth Disease Infection During 2010-2017 in Jiangsu, China: A Distributed Lag Non-Linear Analysis.

Xu Yang, Junshu Wang, Guoming Zhang, Zhaoyuan Yu

Open access · goldAbstract read
In one paragraph

Article in GeoHealth, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
4.8field-weighted citation impact, top 4% of its field
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

13 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.

  1. Building the model: a review of input structures in extreme temperature-health.Environmental health : a global access science source · 2026
    Pooled it
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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

4 authors at 2 institutions in 1 country.

Xu YangKey Laboratory of Virtual Geographic Environment Nanjing Normal University Ministry of Education Nanjing China.
Junshu WangKey Laboratory of Virtual Geographic Environment Nanjing Normal University Ministry of Education Nanjing China.ORCID https://orcid.org/0000-0002-4725-4193
Guoming ZhangHealth Information Center of Jiangsu Province Nanjing China.
Zhaoyuan YuKey Laboratory of Virtual Geographic Environment Nanjing Normal University Ministry of Education Nanjing China.ORCID https://orcid.org/0000-0003-4225-9435
Nanjing Normal University · CNNanjing Health and Health Commission · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hand, Foot, and Mouth Disease (HFMD) is an infectious disease that primarily affects young children. In densely populated Jiangsu Province in China, the impact of extreme meteorological factors on HFMD is a concern. We aimed to examine the association between extreme meteorological variables and HFMD infection risk using daily HFMD infections and meteorological data from 2010 to 2017 in Jiangsu Province. We used distributed lag non-linear model (DLNM) to analyze the data, which can effectively capture the nuanced non-linear dynamics and lag effects in the relationship between HFMD and extreme meteorological factors. Comparing the 10th and 90th percentiles of meteorological variables with their respective median values, our results showed that extremely low temperatures and high humidity were significantly associated with increased HFMD infection risk. The greatest effect of extremely low temperatures was observed at a lag of 1-2 days, elevating the risk by 18 ∼ 33% (RR = 1.18 ∼ 1.33). Extremely high humidity was found to increase the risk of infection, starting at a lag of 4 days. In contrast, extremely high temperatures, low humidity, and high wind speed were associated with reduced risk of infection at lag of 0-12 days, with the range of RR values being 0.60-0.98 for extremely high temperatures, 0.69-0.89 for extremely low humidity, and 0.84-0.98 for extremely high wind speed respectively. Our findings suggest that extreme meteorological factors can significantly impact the incidence of HFMD in Jiangsu Province, and highlight the need for effective public health protection measures during the periods of extreme meteorological condition, particularly for vulnerable populations.

Indexed as

distributed lag non‐linear modelextreme weatherhand, foot, and mouth disease

Identifiers

PMID38562664
PMCPMC10982542
OpenAlexW4393365087

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.