"We have to lie low that sort of poisons me more and more": A qualitative study of violent political rhetoric and health implications for Spanish and Chinese speaking immigrants.

BACKGROUND: In recent years, the historical legacy of anti-immigrant sentiment in the US has resurfaced, fueled by a new wave of anti-immigrant political rhetoric. Violent political rhetoric, defined as either explicit or metaphorically targeted language to dehumanize targeted groups, can incite discriminatory treatment of immigrants at both interpersonal and institutional levels, shaping their health and healthcare experiences. This qualitative study explores and compares how Spanish- and Chinese-speaking immigrant populations in Chicago make sense of violent political rhetoric against their racial and ethnic identities, utilize coping strategies to maintain their sense of belonging, and experience downstream health consequences. METHODS: In 2019, 14 semi-structured focus groups were conducted among immigrants to the U.S. (n = 79). Participants were recruited from four community sites in either Hispanic/Latino or Chinese neighborhoods in Chicago. Focus groups were conducted by racially- and linguistically concordant interviewers in Spanish, Mandarin, or Cantonese. The research team developed a codebook iteratively and analyzed transcripts using grounded theory and the constant comparison method. RESULTS: Participants included Chinese (61%) and Spanish-speaking immigrants (39%), with an average age of 61.4 years (sd = 13); the majority were female (62%), unemployed (68%), and attained less than a high school diploma (53%). Self-reported stress due to political rhetoric was more pronounced among Spanish-speaking participants (93%) than Chinese participants (39.6%). Immigrants responded to manifestations of violent political rhetoric in numerous ways including mobilizing the model minority myth with internalized racism, anticipatory stress, and "high effort" coping mechanisms (John Henryism), all with downstream health effects. CONCLUSION: Violent political rhetoric is one of the mechanisms by which racism and xenophobia exacerbate a toll on the health of racialized immigrant groups. These processes have implications for both interpersonal and institutional experiences, as well as health and healthcare interactions. We propose a conceptual model that outlines these mechanisms and points to potential areas of intervention to ameliorate immigrant health inequities.

The role of smoking history in longitudinal changes in C-reactive protein between Black and White older adults in the US.

Smoking cessation is associated with decreases in C-reactive protein (CRP), a biomarker of systemic inflammation and cancer risk; yet CRP levels remain higher long-term in individuals who quit vs. those who never smoked. While non-Hispanic, Black/African American (NHB) have higher levels of CRP vs. non-Hispanic, White/Caucasian (NHW) adults, the association between CRP and race has not been examined in individuals with smoking history. Utilizing longitudinal data from the Health and Retirement Study (HRS), the current study examined the effects of race and smoking history on CRP in older adults. NHB (n = 242) and NHW (n = 1529) participants completed HRS assessments in 2006, 2010, and 2014. Dried blood spots collected at each wave were assayed for CRP. Linear mixed models were used to examine the effect of race and smoking history on CRP across waves - controlling for sociodemographics, physical activity, body mass index (BMI), and current smoking. Overall, results showed no significant effects of race or current smoking on CRP; rather age, sex, education, BMI, physical activity, smoking history, and time × race predicted CRP (ps<.04). However, while age, sex, education, BMI, physical activity, and smoking history were also predictive of CRP in NHWs (ps<.04) in race-stratified models, only BMI was a significant predictor of CRP in NHBs (p=.012). BMI may be important in explaining inflammation-related disease risk in NHBs with a history of smoking. NHBs may not experience the same reductions in CRP with smoking cessation as NHWs - potentially contributing to tobacco-related health disparities.

Assessment of Structural Barriers and Racial Group Disparities of COVID-19 Mortality With Spatial Analysis.

IMPORTANCE: Although social determinants of health (SDOH) are important factors in health inequities, they have not been explicitly associated with COVID-19 mortality rates across racial and ethnic groups and rural, suburban, and urban contexts. OBJECTIVES: To explore the spatial and racial disparities in county-level COVID-19 mortality rates during the first year of the pandemic. DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study analyzed data for all US counties in 50 states and the District of Columbia for the first full year of the COVID-19 pandemic (January 22, 2020, to February 28, 2021). Counties with a high concentration of a single racial and ethnic population and a high level of COVID-19 mortality rate were identified as concentrated longitudinal-impact counties. The SDOH that may be associated with mortality rate across these counties and in urban, suburban, and rural contexts were examined. The 3 largest racial and ethnic groups in the US were selected: Black or African American, Hispanic or Latinx, and non-Hispanic White populations. EXPOSURES: County-level characteristics and community health factors (eg, income inequality, uninsured rate, primary care physicians, preventable hospital stays, severe housing problems rate, and access to broadband internet) associated with COVID-19 mortality. MAIN OUTCOMES AND MEASURES: Data on county-level COVID-19 mortality rates (deaths per 100 000 population) reported by the US Centers for Disease Control and Prevention were analyzed. Four indexes were used to measure multiple dimensions of SDOH: socioeconomic advantage index, limited mobility index, urban core opportunity index, and mixed immigrant cohesion and accessibility index. Spatial regression models were used to examine the associations between SDOH and county-level COVID-19 mortality rate. RESULTS: Of the 3142 counties included in the study, 531 were identified as concentrated longitudinal-impact counties. Of these counties, 347 (11.0%) had a large Black or African American population compared with other counties, 198 (6.3%) had a large Hispanic or Latinx population compared with other counties, and 33 (1.1%) had a large non-Hispanic White population compared with other counties. A total of 489 254 COVID-19-related deaths were reported. Most concentrated longitudinal-impact counties with a large Black or African American population compared with other counties were spread across urban, suburban, and rural areas and experienced numerous disadvantages, including higher income inequality (297 of 347 [85.6%]) and more preventable hospital stays (281 of 347 [81.0%]). Most concentrated longitudinal-impact counties with a large Hispanic or Latinx population compared with other counties were located in urban areas (114 of 198 [57.6%]), and 130 (65.7%) of these counties had a high percentage of people who lacked health insurance. Most concentrated longitudinal-impact counties with a large non-Hispanic White population compared with other counties were in rural areas (23 of 33 [69.7%]), included a large group of older adults (26 of 33 [78.8%]), and had limited access to quality health care (24 of 33 [72.7%]). In urban areas, the mixed immigrant cohesion and accessibility index was inversely associated with COVID-19 mortality (coefficient [SE], -23.38 [6.06]; P < .001), indicating that mortality rates in urban areas were associated with immigrant communities with traditional family structures, multiple accessibility stressors, and housing overcrowding. Higher COVID-19 mortality rates were also associated with preventable hospital stays in rural areas (coefficient [SE], 0.008 [0.002]; P < .001) and higher socioeconomic status vulnerability in suburban areas (coefficient [SE], -21.60 [3.55]; P < .001). Across all community types, places with limited internet access had higher mortality rates, especially in urban areas (coefficient [SE], 5.83 [0.81]; P < .001). CONCLUSIONS AND RELEVANCE: This cross-sectional study found an association between different SDOH measures and COVID-19 mortality that varied across racial and ethnic groups and community types. Future research is needed that explores the different dimensions and regional patterns of SDOH to address health inequity and guide policies and programs.

Coming up short: Comparing venous blood, dried blood spots & saliva samples for measuring telomere length in health equity research.

BACKGROUND: Telomere length (TL) in peripheral blood mononuclear cells (PBMC) from fresh venous blood is increasingly used to estimate molecular impacts of accumulated social adversity on population health. Sometimes, TL extracted from saliva or dried blood spots (DBS) are substituted as less invasive and more scalable specimen collection methods; yet, are they interchangeable with fresh blood? Studies find TL is correlated across tissues, but have not addressed the critical question for social epidemiological applications: Do different specimen types show the same association between TL and social constructs? METHODS: We integrate expertise in social epidemiology, molecular biology, and the statistical impact of measurement error on parameter estimates. Recruiting a diverse sample of 132 Metro-Detroit women, we measure TL for each woman from fresh blood PBMC, DBS, and saliva. Using regression methods, we estimate associations between social characteristics and TL, comparing estimates across specimen types for each woman. RESULTS: Associations between TL and social characteristics vary by specimen type collected from the same woman, sometimes qualitatively altering estimates of the magnitude or direction of a theorized relationship. Being Black is associated with shorter TL in PBMC, but longer TL in saliva or DBS. Education is positively associated with TL in fresh blood, but negatively associated with TL using DBS. CONCLUSION: Findings raise concerns about the use of TL measures derived from different tissues in social epidemiological research. Investigators need to consider the possibility that associations between social variables and TL may be systematically related to specimen type, rather than be valid indicators of socially-patterned biopsychosocial processes.

Redressing the limitations of the Affordable Care Act for Mexican immigrants through bi-national health insurance: a willingness to pay study in Los Angeles.

The 12.4 million Mexican migrants in the United States (US) face considerable barriers to access health care, with 45% of them being uninsured. The Affordable Care Act (ACA) does not address lack of insurance for some immigrants, and the excluded groups are a large proportion of the Mexican-American community. To redress this, innovative forms of health insurance coverage have to be explored. This study analyses factors associated with willingness to pay for cross-border, bi-national health insurance (BHI) among Mexican immigrants in the US. Surveys were administered to 1,335 Mexican migrants in the Mexican Consulate of Los Angeles to assess their health status, healthcare utilization, and willingness to purchase BHI. Logistic regression was used to identify predictors of willingness to pay for BHI. Having a job, not having health insurance in the US, and relatives in Mexico attending public health services were significant predictors of willingness to pay for BHI. In addition, individuals identified quality as the most important factor when considering BHI. In spite of the interest for BHI among 54% of the sampled population, our study concludes that this type of coverage is unlikely to solve access to care challenges due to ACA eligibility among different Mexican immigrant populations.