Modification effects of long-term air pollution levels on the relationship between short-term exposure to meteorological factors and hand, foot, and mouth disease: A distributed lag non-linear model-based study in Shandong Province, China Article Swipe
Chao Zhang
,
Xianjun Wang
,
Dapeng Sun
,
Yan Li
,
Yiping Feng
,
Rongguo Zhang
,
Yongxiao Zheng
,
Zengqiang Kou
,
Yunxia Liu
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1016/j.ecoenv.2024.116060
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1016/j.ecoenv.2024.116060
The occurrence of hand, foot, and mouth disease (HFMD) is closely related to meteorological factors. However, location-specific characteristics, such as persistent air pollution, may increase the complexity of the impact of meteorological factors on HFMD, and studies across different areas and populations are largely lacking. In this study, a two-stage multisite time-series analysis was conducted using data from 16 cities in Shandong Province from 2015 to 2019. In the first stage, we obtained the cumulative exposure-response curves of meteorological factors and the number of HFMD cases for each city. In the second stage, we merged the estimations from the first stage and included city-specific air pollution variables to identify significant effect modifiers and how they modified the short-term relationship between HFMD and meteorological factors. High concentrations of air pollutants may reduce the risk effects of high average temperature on HFMD and lead to a distinct peak in the cumulative exposure-response curve, while lower concentrations may increase the risk effects of high relative humidity. Furthermore, the effects of average wind speed on HFMD were different at different levels of air pollution. The differences in modification effects between subgroups were mainly manifested in the diversity and quantity of significant modifiers. The modification effects of long-term air pollution levels on the relationship between sunshine hours and HFMD may vary significantly depending on geographical location. The people in age＜3 and male groups were more susceptible to long-term air pollution. These findings contribute to a deepening understanding of the relationship between meteorological factors and HFMD and provide evidence for relevant public health decision-making.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.ecoenv.2024.116060
- OA Status
- gold
- Cited By
- 9
- References
- 70
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4391507202
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4391507202Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1016/j.ecoenv.2024.116060Digital Object Identifier
- Title
-
Modification effects of long-term air pollution levels on the relationship between short-term exposure to meteorological factors and hand, foot, and mouth disease: A distributed lag non-linear model-based study in Shandong Province, ChinaWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
-
2024-02-03Full publication date if available
- Authors
-
Chao Zhang, Xianjun Wang, Dapeng Sun, Yan Li, Yiping Feng, Rongguo Zhang, Yongxiao Zheng, Zengqiang Kou, Yunxia LiuList of authors in order
- Landing page
-
https://doi.org/10.1016/j.ecoenv.2024.116060Publisher landing page
- Open access
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1016/j.ecoenv.2024.116060Direct OA link when available
- Concepts
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Distributed lag, Term (time), Lag, Environmental science, Air pollution, Pollution, Environmental health, Econometrics, Biology, Ecology, Medicine, Computer science, Mathematics, Computer network, Quantum mechanics, PhysicsTop concepts (fields/topics) attached by OpenAlex
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9Total citation count in OpenAlex
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2025: 7, 2024: 2Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.persistent | 20 |
| abstract_inverted_index.pollutants | 128 |
| abstract_inverted_index.pollution, | 22 |
| abstract_inverted_index.pollution. | 179, 234 |
| abstract_inverted_index.short-term | 117 |
| abstract_inverted_index.differences | 181 |
| abstract_inverted_index.estimations | 96 |
| abstract_inverted_index.populations | 41 |
| abstract_inverted_index.significant | 109, 196 |
| abstract_inverted_index.susceptible | 230 |
| abstract_inverted_index.temperature | 137 |
| abstract_inverted_index.time-series | 51 |
| abstract_inverted_index.Furthermore, | 163 |
| abstract_inverted_index.geographical | 219 |
| abstract_inverted_index.modification | 183, 199 |
| abstract_inverted_index.relationship | 118, 208, 244 |
| abstract_inverted_index.city-specific | 103 |
| abstract_inverted_index.significantly | 216 |
| abstract_inverted_index.understanding | 241 |
| abstract_inverted_index.concentrations | 125, 153 |
| abstract_inverted_index.meteorological | 13, 31, 78, 122, 246 |
| abstract_inverted_index.characteristics, | 17 |
| abstract_inverted_index.decision-making. | 257 |
| abstract_inverted_index.exposure-response | 75, 149 |
| abstract_inverted_index.location-specific | 16 |
| cited_by_percentile_year.max | 99 |
| cited_by_percentile_year.min | 94 |
| corresponding_author_ids | https://openalex.org/A5109440030, https://openalex.org/A5100684455 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 9 |
| corresponding_institution_ids | https://openalex.org/I154099455, https://openalex.org/I4210167212 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/13 |
| sustainable_development_goals[0].score | 0.5 |
| sustainable_development_goals[0].display_name | Climate action |
| citation_normalized_percentile.value | 0.95403571 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |