Evidence map›Paper›PMID 38510362›Full record

ArticleFrontiers in public health2024

Temporal dynamic effects of meteorological factors and air quality on the physical health of the older adults in Shenzhen, China.

Shuai Jiang, Chuanliang Han, Yue Ma, Jiajia Ji, Guomin Chen, Yinsheng Guo

Abstract read
In one paragraph

Article in Frontiers in public health, 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

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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.

Shuai Jiang *Shenzhen Center for Disease Control and Prevention, Shenzhen, Guangdong, China.
Chuanliang Han *Department of Electrical Engineering, The City University of Hong Kong, Hong Kong, Hong Kong SAR, China.
Yue Ma *Department of Healthcare-Associated Infection Management, National Clinical Research Center for Infectious Diseases, Third People’s Hospital of Shenzhen and The Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen, Guangdong, China.
Jiajia JiShenzhen Center for Disease Control and Prevention, Shenzhen, Guangdong, China.
Guomin ChenShenzhen Center for Disease Control and Prevention, Shenzhen, Guangdong, China.
Yinsheng GuoShenzhen Center for Disease Control and Prevention, Shenzhen, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Meteorological and environmental factors can affect people's lives and health, which is crucial among the older adults. However, it is currently unclear how they specifically affect the physical condition of older adults people. Methods: We collected and analyzed the basic physical examination indicators of 41 older adults people for two consecutive years (2021 and 2022), and correlated them with meteorological and environmental factors. Partial correlation was also conducted to exclude unrelated factors as well. Results: We found that among the physical examination indicators of the older adults for two consecutive years, five indicators (HB, WBC, HbAlc, CB, LDL-C) showed significant differences across the population, and they had significantly different dynamic correlation patterns with six meteorological (air pressure, temperature, humidity, precipitation, wind speed, and sunshine duration) and seven air quality factors (NO2, SO2, PM10, O3-1h, O3-8h, CO, PM2.5). Discussion: Our study has discovered for the first time the dynamic correlation between indicators in normal basic physical examinations and meteorological factors and air quality indicators, which will provide guidance for the future development of policies that care for the healthy life of the older adults.

Indexed as

Air PollutantsAir PollutionAgedChinaHumansMeteorological ConceptsTemperatureAir Pollutantsclimatephysical examinationpollutionpublic healthShenzhen

Identifiers

PMID38510362
PMCPMC10951054

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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.