Estimating the Causal Impact of Proximity to Gold and Copper Mines on Respiratory Diseases in Chilean Children: An Application of Targeted Maximum Likelihood Estimation

[Respiratory changes in children exposed to dust from mining waste in Brumadinho, Minas Gerais State, Brazil: Bruminha Project]

This study aimed to investigate the occurrence of respiratory diseases in children exposed to dust from mining waste after the Brumadinho dam disaster, Minas Gerais State, Brazil. The study population included children aged 0-6 years, living in three communities exposed to mining waste dust (Córrego do Feijão, Parque da Cachoeira, and Tejuco) and one unexposed community (Aranha). Data were collected from July 19 to 30, 2021, using questionnaires that addressed sociodemographic information and a recall survey on signs, symptoms, and respiratory diseases. A total of 217 children were evaluated, 119 living in the exposed communities and 98 in the non-exposed community. The residents in the exposed communities reported an increase in the frequency of home cleaning (p = 0.04) and in vehicular traffic (p = 0.03). Among children aged four, a higher frequency of upper (p = 0.01) and lower (p = 0.01) airway disorders, as well as respiratory allergy (p = 0.05) was observed. The exposed group had 1.5 times more reports of respiratory allergy (75%; p = 0.02) compared to the non-exposed group (50.5%). Children living in communities exposed to waste dust were three times more likely (adjusted OR = 3.63; 95%CI: 1.37; 9.57) to have respiratory allergies than those not exposed. Two years and six months after the environmental disaster occurred, children living in the communities affected by waste from mining and remediation activities remained exposed to dust with harmful effects on respiratory health.

Application of targeted maximum likelihood estimation in public health and epidemiological studies: a systematic review

PURPOSE

The targeted maximum likelihood estimation (TMLE) statistical data analysis framework integrates machine learning, statistical theory, and statistical inference to provide a least biased, efficient, and robust strategy for estimation and inference of a variety of statistical and causal parameters. We describe and evaluate the epidemiological applications that have benefited from recent methodological developments.

METHODS

We conducted a systematic literature review in PubMed for articles that applied any form of TMLE in observational studies. We summarized the epidemiological discipline, geographical location, expertize of the authors, and TMLE methods over time. We used the Roadmap of Targeted Learning and Causal Inference to extract key methodological aspects of the publications. We showcase the contributions to the literature of these TMLE results.

RESULTS

Of the 89 publications included, 33% originated from the University of California at Berkeley, where the framework was first developed by Professor Mark van der Laan. By 2022, 59% of the publications originated from outside the United States and explored up to seven different epidemiological disciplines in 2021-2022. Double-robustness, bias reduction, and model misspecification were the main motivations that drew researchers toward the TMLE framework. Through time, a wide variety of methodological, tutorial, and software-specific articles were cited, owing to the constant growth of methodological developments around TMLE.

CONCLUSIONS

There is a clear dissemination trend of the TMLE framework to various epidemiological disciplines and to increasing numbers of geographical areas. The availability of R packages, publication of tutorial papers, and involvement of methodological experts in applied publications have contributed to an exponential increase in the number of studies that understood the benefits and adoption of TMLE.

Allergic rhinitis aggravated by air pollutants in Latin America: A systematic review

The aim of this systematic review (SR) was to evaluate the most frequent pollutants and their effect on allergic rhinitis in Latin American countries. Observational studies up to December 2020 and comparing different indoor and outdoor pollutants that had allergic rhinitis (AR) as an outcome were included in the systematic review. Random-effect meta-analyses were conducted for the presence of allergic rhinitis. Estimates were presented as pooled odds ratios (ORs) and their respective 95% confidence intervals (CIs). Twenty-two publications comprised this review according to the inclusion and exclusion criteria and 12 had data that could be analyzed statistically. The most frequent pollutant was PM10, followed by NO2 /O3 and PM2.5 in studies conducted in Argentina, Brazil, Bolivia, Chile, Colombia, Costa Rica, and Peru. The OR of an exposed subject experiencing allergic rhinitis was 1.43 (95% CI 1.026; 1.980). The OR of children and adolescents experiencing of allergic rhinitis was 1.359 (95% CI 1.051; 1.759). Asymmetry and great variability in the effect estimated from the selected studies were observed. The publication bias was quantified by Kendall's correlation and Egger's test resulted in 0.152 (p-value = 0.493). Egger's test provided an intercept equal to 2.511 and a p-value = 0.398. The I2 statistic was 89.3% and reinforces the hypothesis of heterogeneity. This first systematic review conducted in Latin America confirmed the chance of a person exposed to pollutants and experiencing allergic rhinitis is 43% greater than that of a non-exposed person, reinforcing the importance of policies to reduce pollutant exposure and the use of protection systems for workforces exposed to occupational pollutants in work environments.

Housing Risk Factors Associated with Respiratory Disease: A Systematic Review

Cold, damp and mouldy housing arises from the degradation of the housing stock over time due to weathering and a lack of maintenance. Living in such houses is associated with many adverse impacts on human health, especially for those with existing health issues. This paper presents a systematic review, using the PRISMA protocol, consisting of an exploratory analysis of housing-related risk factors associated with respiratory disease. The review consisted of 360 studies investigating 19 risk factors associated with respiratory conditions. Each fall into one of four categories, namely, (1) outdoor environment-related factors; (2) indoor air pollution-related factors; (3) housing non-structure-related factors; or (4) housing structure-related factors. The results show that effects of poor housing conditions on occupants’ respiratory health is a growing research field, where poor indoor air quality, mainly due to a lack of adequate ventilation, was found to be the most influential risk factor. Usage of solid fuel and living in an urban area without a pollutant-free air filtration system are the main risk factors related to inadequate ventilation. Therefore, an adequate and reliable ventilation system with air-infiltration was considered to be the main mitigation solution to improve indoor air quality. It is suggested that government organisations and health practitioners could use the identified risk factors to measure the healthiness of existing dwellings and take measures to improve existing conditions and develop regulations for new housing construction to promote the healthy home concept. Further research is needed for risk mitigation strategies to reduce the respiratory health burden attributed to housing.

Machine Learning Within Studies of Early-Life Environmental Exposures and Child Health: Review of the Current Literature and Discussion of Next Steps

PURPOSE OF REVIEW

The goal of this article is to review the use of machine learning (ML) within studies of environmental exposures and children's health, identify common themes across studies, and provide recommendations to advance their use in research and practice.

RECENT FINDINGS

We identified 42 articles reporting upon the use of ML within studies of environmental exposures and children's health between 2017 and 2019. The common themes among the articles were analysis of mixture data, exposure prediction, disease prediction and forecasting, analysis of complex data, and causal inference. With the increasing complexity of environmental health data, we anticipate greater use of ML to address the challenges that cannot be handled by traditional analytics. In order for these methods to beneficially impact public health, the ML techniques we use need to be appropriate for our study questions, rigorously evaluated and reported in a way that can be critically assessed by the scientific community.

Air Quality in the Working Environment and Respiratory Health of Female Congolese Stone Quarry Workers

Background and Aim. Environmental and occupational exposure to high dust levels are known to be associated with lung function impairment. We assessed the ambient air quality in the working environment and the respiratory health of female stone quarry workers in Lubumbashi, Democratic Republic of Congo (DRC) in a context of severe economic, security, and health crises. Methods. This was a case-control study conducted in three stone quarry sites. Participants were 256 dust-exposed female stone quarry workers matched to 256 unexposed female office workers and market tax collectors (N = 512). They each answered a structured respiratory health questionnaire and underwent physical examination and a lung function test with the use of a spirometer and peak flow meter. Quality of ambient air in the working environment was assessed by means of a BRAMC air quality monitor (BR-AIR-329). Results. Results showed that exposed women did not use any personal protective equipment (PPE); in quarry sites, abnormally high levels of PM_2.5 (205 ± 13.2 μg/m³ vs. 31.3 ± 10.3 μg/m³ in control sites; p < 0.001) and volatile organic compounds (VOC, 2.2 ± 0.2 μg/m³ vs. 0.5 ± 0.3 μg/m³, respectively; p < 0.01) were found. Furthermore, respiratory complaints were more common among exposed women (32.4% vs. 3.5% in controls; p < 0.01), who had abnormal chest auscultation and reduced lung capacity than controls (mean PEFR: 344.8 ± 2.26 and 405 ± 67.7 L/s, respectively; p < 0.001 Conclusion. Findings from this study show that in the midst of severe crises in the DRC, women stone quarry workers are exposed to abnormally high levels of respiratory hazards, which contribute to impaired lung function. There is a need to regulate quarry work and improve the working conditions in quarry sites in the DRC.