The Intersection of Race, Immigration Status, and Environmental Justice

Diabetes quality of life, Chemical Intolerance, and generational status in a Latino sample: an RRNeT study

Objectives

The impact of diabetes on quality of life (QoL) includes deficits in physical functioning and emotional and mental health. Individuals with diabetes can experience significant distress related to diabetes management and burden. Comorbid conditions can contribute to QoL among individuals with diabetes. Chemical Intolerance (CI) has received minimal attention in the context of diabetes. CI is characterized by multi-systemic symptoms initiated by a one-time high dose or persistent low-dose exposure to environmental toxins. Latinos experience diabetes distress and are exposed to environmental factors at disproportionate rates. This study sought to investigate generational differences in diabetes QoL and CI in a Latino sample across generational status.

Methods

To assess the modifying effect of CI between QoL and generations, the analysis was stratified by those with and without CI.

Results

Compared to 2nd generation Latinos, Latino immigrants were more likely to indicate that without diabetes, their life would be better across several QoL domains. Latino immigrants had a lower A1C and BMI than2nd generation Latinos. Additionally, they were less likely to have scores indicative of CI than U.S.-born Latinos. QoL varied by generational status and suggested a greater emphasis on family and social relationships among immigrants than U.S.-born Latinos. There were no differences in health services measures across generations.

Conclusions

This study highlights generational differences in the impact of diabetes on QoL. It is one of the few studies to seek to understand the impact of CI on QoL in the context of a chronic condition such as type 2 diabetes.

Differential exposure to drinking water contaminants in North Carolina: Evidence from structural topic modeling and water quality data

To better understand water security of communities in North Carolina, this research uses structural topic modeling (STM) and geographic mapping to identify the main topics and pollutant categories being researched and the areas exposed to drinking water contaminants. The textual data derived from the journal article abstracts that examined water pollution in North Carolina is from 1964 to present. The STM analysis of textual data is paired with socio-demographic data from the 2015-2019 American Community Survey (ACS) 5-year estimates and water pollution data from North Carolina state agencies. The STM findings show that the most discussed topics relate to runoff management, wastewater from concentrated agricultural feeding operations, emerging contaminants, land development, and health impacts as a result of water contamination. The article discusses how the topics especially threaten groundwater resources used by community water systems and private wells. Those communities served by private wells are predominantly low-income and minority populations. As a result, threats to groundwater supplies exacerbate existing issues of environmental justice in North Carolina, especially in the Coastal Plains Region. The STM findings revealed that several key threats to safe drinking water are less covered by academic literature, such as poultry concentrated agricultural feeding operations and climate impacts, which may increase disparities in water access in North Carolina.

Multigenerational immigrant trajectories and children's unequal exposure to fine particulate matter in the US

Fine particulate matter is a serious health threat and exposures are particularly damaging for children. The environmental justice (EJ) literature shows that racial/ethnic minority communities experience disproportionate exposure to particulate pollution in the US. While important, those EJ studies tend to neglect people's complex identities, including their nativity and their families' generational histories of residence in the US. Yet there is growing interest in the intersection of immigrant populations and EJ. Our use of individual-level data enables examination of immigrant generational status by race/ethnicity, which provides insights on the intergenerational persistence of environmental injustice. We pair data on 12,570 US third graders (from 2013 to 2014) collected through the Early Childhood Longitudinal Survey with PM_2.5 concentrations for the census tracts of their home and school locations. We apply generalized estimating equations to test for intergenerational disparities in exposure and to examine how those disparities vary between racial/ethnic groups. Independent of race/ethnicity, first- and second-generation children have greater PM_2.5 exposure than 2.5- and third-generation children. However, generational status disparities in exposures vary based on race/ethnicity. First-generation White children face greater exposure than White children of later generational statuses, with inequalities attenuating by the second generation. In contrast, Hispanic/Latinx children experience no significant drop in exposure until the third generation. Among Asian and Black children, generational status was not a significant determinant of exposure. Results quantify the intergenerational persistence of environmental injustices for persons of color while showing the amelioration of inequalities for Whites after just one generation is born in the US, reflecting another facet of White privilege in the US.

An Environmental Justice Assessment of the Waste Treatment Facilities in Shanghai: Incorporating Counterfactual Decomposition into the Hedonic Price Model

Environmental justice (EJ) has become an increasingly significant issue for environmental management and has thus attracted increasing government and public attention. Although some studies have used techniques of proximity based on geographical information systems to assess EJ, their research is limited to individual or household data. Unlike the conventional hedonic price model (HPM) examining the effects of environmental features on housing rent, this article incorporates counterfactual decomposition into the HPM to estimate the environmental pressure on different groups by comparing the externality effects of municipal solid waste treatment facilities (MSWTFs) on two separate groups of people. To explore whether and, if so, the extent to which, vulnerable groups of people are restricted to disproportionate impacts of hazardous environmental facilities, this research uses Shanghai as the study area to highlight specific locations and exemplify the environmental injustice between the rich and the poor. The results, which represent the relationship between environmental quality and property prices, indicate that environmental quality is a robust predictor of housing rent. Simultaneously, the results suggest that some people conform better to environmental pressure than do others. Thus, the environmental impact of MSWTFs on different populations should be considered, and compensation policies should be implemented for disadvantaged groups.