Buta Bernardo Oliveira, Froner Matheus Britto, Tabak Benjamin Miranda
Fundação Getulio Vargas, School of Public Policy and Government, Brasília, 70830-051, Brazil.
Sci Rep. 2025 Apr 27;15(1):14703. doi: 10.1038/s41598-025-98435-9.
Environmental Health Literacy (EHL) focuses on significant impact of environmental factors on human health and emphasizes the importance of public awareness and engagement in identifying and mitigating environmental health risks. This paper presents a study in the Distrito Federal, Brazil, aimed at evaluating EHL and identify the main socioeconomic characteristics capable of predicting EHL levels. Using the EHL Scale, which assesses knowledge, attitudes, and behaviors toward environmental health, this research applies a questionnaire to 397 respondents. Through descriptive statistics and confirmatory and exploratory factor analyses, the study validates the scale for the Brazilian context and offers structural adjustments for the air scale. Using the socioeconomic data we implemented a predictive Random Forest algorithm to forecast EHL levels on each of the scales. By extracting the Shapley values from the model, we established the most relevant variables to predict EHL, offering valuable insights for policymakers, health and environmental professionals to enhance public engagement with environmental health issues. The results indicate that social vulnerability features are predictive of EHL, including education, income, age, ethnicity, presence of disability and use of continuous medication. This study identifies factors that bolster policy strategies to communicate environmental health risks and promote behavior change regarding the environment and self-care.
环境健康素养（EHL）关注环境因素对人类健康的重大影响，并强调公众意识以及参与识别和减轻环境健康风险的重要性。本文介绍了一项在巴西联邦区开展的研究，旨在评估环境健康素养并确定能够预测环境健康素养水平的主要社会经济特征。本研究使用环境健康素养量表来评估对环境健康的知识、态度和行为，对397名受访者进行了问卷调查。通过描述性统计以及验证性和探索性因素分析，该研究验证了该量表在巴西背景下的有效性，并对空气质量量表进行了结构调整。利用社会经济数据，我们实施了一种预测性随机森林算法来预测每个量表上的环境健康素养水平。通过从模型中提取夏普利值，我们确定了预测环境健康素养最相关的变量，为政策制定者、健康和环境专业人员提供了有价值的见解，以加强公众对环境健康问题的参与。结果表明，社会脆弱性特征可预测环境健康素养，包括教育程度、收入、年龄、种族、残疾状况以及持续用药情况。本研究确定了有助于制定政策策略的因素，以传达环境健康风险并促进在环境和自我护理方面的行为改变。
