Climate change, health, and discrimination: action towards racial justice

Envisioning environmental equity: climate change, health, and racial justice

Climate change has a broad range of health impacts and tackling climate change could be the greatest opportunity for improving global health this century. Yet conversations on climate change and health are often incomplete, giving little attention to structural discrimination and the need for racial justice. Racism kills, and climate change kills. Together, racism and climate change interact and have disproportionate effects on the lives of minoritised people both within countries and between the Global North and the Global South. This paper has three main aims. First, to survey the literature on the unequal health impacts of climate change due to racism, xenophobia, and discrimination through a scoping review. We found that racially minoritised groups, migrants, and Indigenous communities face a disproportionate burden of illness and mortality due to climate change in different contexts. Second, this paper aims to highlight inequalities in responsibility for climate change and the effects thereof. A geographical visualisation of responsibility for climate change and projected mortality and disease risk attributable to climate change per 100 000 people in 2050 was conducted. These maps visualise the disproportionate burden of illness and mortality due to climate change faced by the Global South. Our third aim is to highlight the pathways through which climate change, discrimination, and health interact in most affected areas. Case studies, testimony, and policy analysis drawn from multidisciplinary perspectives are presented throughout the paper to elucidate these pathways. The health community must urgently examine and repair the structural discrimination that drives the unequal impacts of climate change to achieve rapid and equitable action.

Development of a screening tool for assessment of climate change-related heat illness in the clinical setting

ABSTRACT

Extreme heat contributes to heat-related illnesses resulting from heat intolerance, which is the inability to maintain a thermal balance to tolerate heat stress. In the United States, heat-related mortality for older persons has almost doubled in the past 20 years. Other populations at risk for heat-related illness (HRI) include children, pregnant people, those who work outside, young people participating in outdoor sports, and at-risk populations such as Black, indigenous, and populations of color. The classic heat tolerance test used for decades monitoring physiological responses to repetitive motions is impractical across large and potentially health challenged populations and does not identify environmental or social factors or specific vulnerable populations. To address this issue, we developed a heat-related illness screening tool (HIST) to identify individuals at risk for HRI morbidity and mortality based on their physical, environmental, and social vulnerabilities with an emphasis on populations of concern. The HIST has the potential to be used as routine clinical screening in the same way as other commonly used screening tools. Heat intolerance affects patient outcomes and quality of life; therefore, early screening with a simple, easy-to-administer screening tool such as the HIST can identify people at risk and refer them to services that address heat exposure and/or create safety nets to prevent heat-related illnesses.

Healthy Cities, A comprehensive dataset for environmental determinants of health in England cities

This paper presents a fine-grained and multi-sourced dataset for environmental determinants of health collected from England cities. We provide health outcomes of citizens covering physical health (COVID-19 cases, asthma medication expenditure, etc.), mental health (psychological medication expenditure), and life expectancy estimations. We present the corresponding environmental determinants from four perspectives, including basic statistics (population, area, etc.), behavioural environment (availability of tobacco, health-care services, etc.), built environment (road density, street view features, etc.), and natural environment (air quality, temperature, etc.). To reveal regional differences, we extract and integrate massive environment and health indicators from heterogeneous sources into two unified spatial scales, i.e., at the middle layer super output area (MSOA) and the city level, via big data processing and deep learning. Our data holds great promise for diverse audiences, such as public health researchers and urban designers, to further unveil the environmental determinants of health and design methodology for a healthy, sustainable city.