Evidence map›Paper›PMID 34465329›Full record

ArticleBMC public health2021

A national survey of ambient air pollution health literacy among adult residents of Taiwan.

Wen-Hsuan Hou, Yi-Chin Huang, Chien-Yeh Lu, I-Chen Chen, Pei-Chen Lee, Ming-Yeng Lin, Yu-Chen Wang, Lilis Sulistyorini, Chung-Yi Li

Abstract read
In one paragraph

Article in BMC public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. [Environmental risks and health literacy: a systematic review].Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz · 2024
    Pooled it
  2. Article
  3. Article
  4. Impact of Housing Conditions and Air Quality Awareness with Indoor PM2.5 Levels in Urban Jodhpur.Indian journal of community medicine : official publication of Indian Association of Preventive & Social Medicine · 2025
    Article
  5. Environmental Health Literacy of Brazilian Indigenous People.International journal of environmental research and public health · 2025
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Air Pollution Health Literacy among Active Commuters in Hamilton, Ontario.International journal of environmental research and public health · 2023
    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

9 authors.

Wen-Hsuan HouSchool of Gerontology Health Management & Master Program in Long-Term Care, College of Nursing, Taipei Medical University, Taipei, Taiwan.
Yi-Chin HuangDepartment of Public Health, College of Medicine, National Cheng Kung University, #1, University Rd, Tainan, Taiwan, 701.
Chien-Yeh LuDepartment of Public Health, College of Medicine, National Cheng Kung University, #1, University Rd, Tainan, Taiwan, 701.
I-Chen ChenDepartment of Public Health, College of Medicine, National Cheng Kung University, #1, University Rd, Tainan, Taiwan, 701.
Pei-Chen LeeDepartment of Health Care Management, National Taipei University of Nursing and Health Sciences, Taipei, Taiwan.
Ming-Yeng LinDepartment of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
Yu-Chen WangDepartment of Law, College of Social Science, National Cheng Kung University, Tainan, Taiwan.
Lilis SulistyoriniDepartment of Environmental Health, Faculty of Public Health, University of Airlangga, Surabaya, Indonesia.
Chung-Yi LiDepartment of Public Health, College of Medicine, National Cheng Kung University, #1, University Rd, Tainan, Taiwan, 701. cyli99@mail.ncku.edu.tw.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo investigate the level of and covariates associated with ambient air pollution health literacy (AAPHL) among adult residents of Taiwan.

methodsWith a cross-sectional study design, we conducted telephone interviews using a Chinese version AAPHL scale, which consisted of 24 items assessing 12 subdomains of AAPHL formed by 4 information processing competence matrices (i.e., access, understand, appraise, and apply) and 3 health contexts (i.e., healthcare, disease prevention, and health promotion). The AAPHL was with the lowest and highest score at 1 to 4, respectively. Between September and November 2020, a sample of 1017 and 280 adults was successfully interviewed via home phones and mobile phones, respectively. We employed multiple linear regression models to identify covariates significantly associated with overall and 4 matric-specific AAPHL scores.

resultsThe mean and standard deviation (±SD) of overall AAPHL score was considered as moderate at 2.90 (±0.56), with the highest and lowest metric-specific score for "apply" (3.07 ± 0.59) and "appraise" (2.75 ± 0.66). Lower education was significantly associated with a lower overall score; and living with children < 12 years and single were both significantly associated with higher overall scores. We also noted a significant geographic variation in overall score in which people living in the east/remote islands had highest scores.

conclusionsPeople in Taiwan had only moderate level of AAPHL; and covariates including education, living arrangement, marital status, and area of living were significantly associated with AAPHL. These covariates should be considered in future educational interventions aiming to improve the AAPHL in the community.

Indexed as

Air PollutionHealth LiteracyAdultChildCross-Sectional StudiesHealth PromotionHumansTaiwanAmbient air pollution, environmental health literacyCommunity healthCross-sectional studiesLinear regression model

Identifiers

PMID34465329
PMCPMC8406719

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LicenceCC BY
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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.