Environmental Justice for All - A Call for Big Data Analysis to Promote Health Equity

Introduction: The primary mission of Environmental Justice policy and programs is to ensure that all individuals, regardless of their backgrounds, are treated fairly and included in decision-making processes that affect their health and the environment. It highlights the intersections of environmental policy, social equity, and human rights, advocating for fair treatment and meaningful involvement of all individuals in environmental decision-making processes. Historically, communities of color, low-income populations, and indigenous groups have borne the brunt of pollution, resource depletion, and climate change, often due to systemic inequalities and discriminatory practices. Core to the implementation and measurement of environmental justice is the identification, collection, and analysis of the drivers of health data that describe the causal relationships between environmental, social, and genomic factors and document the health impacts that result from these relationships. Methods: Very large volumes of publicly available location and time-specific Environmental, Social & Genomic Drivers of Health (ESDoH+G) data already exist for analysis. The World Health Organization (WHO) and national health agencies worldwide have amassed the location and time-specific health impact data (ICD codes) needed to statistically establish the causal relationships. Results: The total worldwide ESDoH+G data housed in public and private databases as of 2023 is estimated to exceed 300 exabytes (300 million terabytes). Despite interest and attention to ESDoH+G data from governments, researchers, healthcare, NGOs, and private industry, most of this data has never been systematically correlated or subjected to big data analysis and predictive analysis. Conclusion: An extensive big data analysis using the publicly accessible ESDoH+G data and health impact data would demonstrate correlations and causative relationships between ESDoH+G factors and health outcomes. By leveraging big data, further analyses would inform policies and decisions that can help reduce health inequities.