Characterizing Risk for Cumulative Risk Assessments

What occupational risk factors significantly affect miners' health: Findings from meta-analysis and association rule mining

INTRODUCTION

The workplace's health hazard remains a significant concern to workers in the mining industry, where miners are continually exposed to various kinds of exposure sources.

METHOD

First, the determinants of miners' health were systematically extracted from 259 publications, comprising chemical, physical, ergonomic, and psychosocial stressors, vulnerability factors, and common health outcomes. Then, 16 meta-analyses were performed to ascertain the epidemiological evidence for associations between four stressors and three health outcomes. The seven top contributing factors affecting miners' health were identified through 166 available prospective studies. Finally, based on the classic and domestic measurement scales, a cross-sectional survey of 559 Chinese miners was conducted to determine the core psychosocial predictors. In addition to the traditional mechanisms, complex interactive networks among the antecedents and consequences and the reversed effects of consequences were also obtained, where 379 strong association rules were yielded via the Apriori algorithm.

RESULTS

The results showed that occupational dust, NO2, heavy metals, heat, vibration, awkward posture, and job stress are significant risk factors associated with individuals' health conditions. Psychological capital, coping style, job demand, social support, organizational support, justice, and culture are core psychosocial predictors of miners.

CONCLUSIONS

This study presents a case for identifying the most significant occupational risk factors related to individuals' health, which could be extended and applied to other industries, as working populations around the world are suffering from various chemical, physical, ergonomic, and psychosocial stressors.

PRACTICAL APPLICATIONS

Identifying the significant occupational risk factors affecting workers' health conditions is essential for comprehensive occupational health risk assessment and management. Therefore, this study could be important for health management in mines and other industries.

Cumulative risk assessment for combinations of environmental and psychosocial stressors: A systematic review

With the growing awareness of stressors, cumulative risk assessment (CRA) has been proposed as a potential method to evaluate possible additive and synergistic effects of multiple stressors on human health, thus informing environmental regulation and protecting public health. However, CRA is still in its exploratory stage due to the lack of generally accepted quantitative approaches. It is an ideal time to summarize the existing progress to guide future research. To this end, a systematic review of the literature on CRA issues dealing with combinations of environmental and psychosocial stressors was conducted in this study. Using typology and bibliometric analysis, the body of knowledge, hot topics, and research gaps in this field were characterized. It was found that research topics and objectives mainly focus on qualitative analysis and community settings; more attention should be paid to the development of quantitative approaches and the inclusion of occupational settings. Further, the roles of air pollution and vulnerability factors in CRA have attracted the most attention. This study concludes with views on future prospects to promote theoretical and practical development in this field; specifically, CRA is a multifaceted topic that requires substantial collaborations with various stakeholders and substantial knowledge from multidisciplinary fields. This study presents an overall review as well as research directions worth investigating in this field, which provides a historical reference for future study. Integr Environ Assess Manag 2024;20:602-615. © 2023 SETAC.

Mixture predicted no-effect concentrations derived by independent action model vs concentration addition model based on different species sensitivity distribution models

In the hazard assessment of mixtures, the mixture predicted no-effect concentration (mPNEC) is always derived by the concentration addition (CA) model (mPNEC_CA) to assess the risk of mixtures combined with exposure assessment. However, the independent action (IA) model, which is also widely used as the CA model in the prediction and evaluation of mixture toxicity, is always used to calculate the population fraction showing a predefined effect, not mPNEC, and this limits the application of IA model in the mixture risk assessment. In this study, we explored the process of mPNEC derived by the IA method (mPNEC_IA) based on the species sensitivity distribution (SSD) and compared mPNEC_IA with mPNEC_CA. Taking two common pesticides, dimethoate (DIM) and dichlorvos (DIC), exposed in the actual water environment as an example, their SSD models were constructed separately using nine distribution functions after toxicity data screening and quality testing. For both DIC and DIM, all different nine models had passed the Kolmogorov-Smirnov test. Then, the PNECs of two pesticides were derived based on SSD models. Finally, mPNEC_IA with different concentration ratios was derived and compared to mPNEC_CA based on 81 combinations of nine SSD models. Most mPNEC values derived by IA model were more conservative than those by CA. It is worth noting that the mPNEC_IA is more conservative than mPNEC_CA for the commonly used log-logit distribution (function 7), log-normal distribution (8), and log-Weibull distribution (9). This study provides a new direction for the application of IA in the risk assessment and enriches the framework of mixture risk assessment.

Association of the Built Environment With Childhood Psychosocial Stress

IMPORTANCE

Emerging research suggests that factors associated with the built environment, including artificial light, air pollution, and noise, may adversely affect children's mental health, while living near green space may reduce stress. Little is known about the combined roles of these factors on children's stress.

OBJECTIVE

To investigate associations between components of the built environment with personal and home characteristics in a large cohort of children who were assessed for perceived stress.

DESIGN, SETTING, AND PARTICIPANTS

In this cohort study, a total of 2290 Southern California Children's Health Study participants residing in 8 densely populated urban communities responded to detailed questionnaires. Exposures of artificial light at night (ALAN) derived from satellite observations, near-roadway air pollution (NRP) determined from a dispersion model, noise estimated from the US Traffic Noise Model, and green space from satellite observations of the enhanced vegetation index were linked to each participant's geocoded residence.

MAIN OUTCOMES AND MEASURES

Children's stress was assessed at ages 13 to 14 years and 15 to 16 years using the 4-item Perceived Stress Scale (PSS-4), scaled from 0 to 16, with higher scores indicating greater perceived stress. Measurements were conducted in 2010 and 2012, and data were analyzed from February 6 to August 24, 2019. Multivariate mixed-effects models were used to examine multiple exposures; modification and mediation analyses were also conducted.

RESULTS

Among the 2290 children in this study, 1149 were girls (50%); mean (SD) age was 13.5 (0.6) years. Girls had significantly higher perceived stress measured by PSS-4 (mean [SD] score, 5.7 [3.4]) than boys (4.9 [3.2]). With increasing age (from 13.5 [0.6] to 15.3 [0.6] years), the mean PSS-4 score rose from 5.6 (3.3) to 6.0 (3.4) in girls but decreased for boys from 5.0 (3.2) to 4.7 (3.1). Multivariate mixed-effects models examining multiple exposures indicated that exposure to secondhand smoke in the home was associated with a 0.85 (95% CI, 0.46-1.24) increase in the PSS-4 score. Of the factors related to the physical environment, an interquartile range (IQR) increase in ALAN was associated with a 0.57 (95% CI, 0.05-1.09) unit increase in the PSS-4 score together with a 0.16 score increase per IQR increase of near-roadway air pollution (95% CI, 0.02-0.30) and a -0.24 score decrease per IQR increase of the enhanced vegetation index (95% CI, -0.45 to -0.04). Income modified the ALAN effect size estimate; participants in households earning less than $48 000 per year had significantly greater stress per IQR increase in ALAN. Sleep duration partially mediated the associations between stress and both enhanced vegetation index (17%) and ALAN (18%).

CONCLUSIONS AND RELEVANCE

In this cohort study, children's exposure to smoke at home in addition to residential exposure to ALAN and near-roadway air pollution were associated with increased perceived stress among young adolescent children. These associations appeared to be partially mitigated by more residential green space. The findings may support the promotion of increased residential green spaces to reduce pollution associated with the built environment, with possible mental health benefits for children.