Cause-effect chains in S-LCA based on DPSIR framework using Markov healthcare model: an application to “working hours” in Canada

Abstract

Purpose This study has two aims: first, propose the use of the driver-pressure-state-impact-response (DPSIR) framework to expand the normal focus of impact pathways in social life cycle assessment (S-LCA) on endpoint impacts to a systematic analysis to find links between the main sources of social issues and impacts; second, develop a new impact assessment method to quantify the lifetime health and economic outcomes associated with social subcategories, for the first time, using decision analytic models. Methods The DPSIR framework is mapped to the corresponding elements of the S-LCA context in relation to the social subcategories defined in the UNEP/SETAC methodological sheets. Next, a more robust approach is developed for cause-impact chains between social subcategories and impacts on human well-being based on decision-analytic models (decision trees and Markov models) using healthcare approaches and data. Finally, the health and economic consequences associated with social subcategories are quantified by using Quality Adjusted Life Years (QALYs) and costs based on medical literature and healthcare studies. Results and discussion The method was applied to the “working hours” social subcategory in Canada. The cause-effect chain is built using DPSIR framework in relation to the current social issue in Canada of working more than standard hours. Results of the decision analytic model show that working standard hours is more effective and cost-saving than working more than standard hours from the Canadian healthcare perspective. Working standard hours compared to more than standard hours led to an increase of 0.73 QALY and decrease in cost of $6702 per worker. Based on an estimated 2.4 million Canadian workers working more than standard hours, this resulted in a total gain of 1.7 million QALYs and saving of $16 billion overall. Using cost-effectiveness analysis, possible interventions at multiple entry points of the cause-effect chain within DPSIR framework are proposed to reduce the negative health impacts and associated costs of working more than standard hours in Canada. Conclusions Applying the method on other subcategories could help decision-makers establish the cause-effect aspects of the social performance of their product systems using a quantitative systematic analysis from a life cycle perspective. This approach supports corporate decision-makers to quantify social impacts associated with their product supply chains by calculating QALYs and healthcare costs of their socio-economic conditions enabling them to identify possible interventions to improve the social performance.

Establishing an index for monitoring occupational health and well‐being of coal mines: Consideration of individual characteristics

“…Additionally, they are more resistant to stress. The health risk rates were associated with individual characteristics, including exposure time, age, education, work experience, behavioral habits, psychological capital, etc (Hannouf et al., 2021). Workers prone to burnout were found to be mostly in their 30 and 40s.…”

“…2.1.2 | Structure and elements of the DPSIR model in a coal mining context DPSIR-based studies have demonstrated that it is an effective way to identify causal chains between human productive activities and health impacts. For example, research was carried out on health care models related to the design of working conditions (Hannouf et al, 2021). In addition, a health outcome-associated prospective study was conducted to explore the sustainability of community health (Yee et al, 2012).…”

“…Inspired by the research on the relationship between the environment and human health in conjunction with the driving force‐pressure‐state‐impact‐response (DPSIR) model, this study applies it to the context of occupational environment (Chen et al., 2020; Hannouf et al., 2021; Yee et al., 2012). For brief reasons, miners labor in and are an integral part of complex operating environments.…”

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“…On the other hand, LCA is retained as a powerful technique for calculating both input and output flow of materials and energy over the course of their life cycle. Moreover, it is gaining importance within business models and, more generally, as decision supporting tool for the transition towards Circular Economy (CE) at various levels (Le Téno and Mareschal 1998;Ghisellini and Ulgiati 2020;Vázquez-Rowe et al 2021;Hannouf et al 2021) and addressing the complexity of metabolic processes and systems (Peponi et al 2022).…”

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“…The DPSIR conceptual framework was developed by the European Environmental Agency (EEA) [28] and has been widely used to model environmental problems. As stated by [29], its application outside the environmental arena is limited. The approach consists of identifying the linkages between "drivers-D" through "pressures-P" on different "states-S," as well as their consequential "impacts-I" on the system, leading eventually to "responses-R" from the society.…”