Gilbert Gee

This study assesses the relationship between substance use disorders (SUD) and intersectional discrimination, the intersection of racial/ethnic discrimination, and gender discrimination. Authors aim to determine if the relationship between SUD and discrimination varies by race/ethnicity and gender.

This cross-sectional study analyzes data from a diverse sample of American Indian, Asian, Black, Latinx, and white adult respondents from Wave 2 of the 2004-2005 National Epidemiologic Survey on Alcohol and Related Conditions. Multinomial logistic regression was used to test the association between intersectional discrimination and SUD. Intersectional discrimination was assessed using an interaction term between racial/ethnic discrimination and gender discrimination. Alcohol use disorders (AUD) only and alcohol plus drug use disorders (SUD) were assessed separately. Analyses were stratified by race/ethnicity and gender.

Findings: Overall, intersectional discrimination was associated with increased predicted probabilities of SUD relative to those with no discrimination and was more often associated with SUD than AUD. Intersectional discrimination was associated with increased predicted probabilities of AUD and SUD among women, Black, Latinx, and white adults. Intersectional discrimination was associated with increased predicted probabilities of SUD but not AUD among men, American Indian, and Asian adults.

Intersectional discrimination consistently elevated AUD and/or SUD across subgroups defined by gender or race/ethnicity; however, effects were variable across gender, race/ethnicity, and disorder. Findings demonstrate the negative health implications of intersectional discrimination for men and women and American Indian, Asian, Black, Latinx, and white adults. Study findings have implications for the development of policies and interventions that are centered around intersectionality.
 

Summary: Self-reported racial or ethnic discrimination in a health care setting has been linked to worse health outcomes and not having a usual source of care, but has been rarely examined among Asian ethnic subgroups. Authors examined the association between Asian ethnic subgroup and self-reported discrimination in a healthcare setting, and whether both factors were associated with not having a usual source of care.

Using the California Health Interview Survey (CHIS) 2015–2017, authors used logistic regression models to assess associations among Asian ethnic subgroup, self-reported discrimination, and not having a usual source of care. Interactions between race and self-reported discrimination, foreign-born status, poverty level, and limited English proficiency were also analyzed. Respondents represented adults ages 18 and older residing in California who identified as white, Black, Hispanic, American Indian/Alaska Native, Asian (including Chinese, Filipino, Japanese, Korean, Vietnamese, and Other Asian), and other. Researchers examined two main outcomes: self-reported discrimination in a health care setting and having a usual source of care. There were 62,965 respondents.

Findings: After survey weighting, Asians as an aggregate group were more likely to report discrimination than non-Hispanic whites. When Asians were disaggregated, Japanese and Koreans were more likely to report discrimination than non-Hispanic whites. Self-reported discrimination was marginally associated with not having a usual source of care. Koreans were the only group associated with not having a usual source of care. Foreign-born Chinese and foreign-born Japanese were more associated with self-reported discrimination than being independently foreign-born and Chinese or Japanese.

Differences in self-reported discrimination in a health care setting and not having a usual source of care were observed among Asian ethnic subgroups. Better understanding of these differences in their sociocultural contexts will guide interventions to ensure equitable access to health care.

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• Journal Article: Asian American Self-Reported Discrimination in Healthcare and Having a Usual Source of Care

​Summary: Understanding how perceived discrimination affects Asian Americans can help stakeholders target subgroups that are at highest risk of discrimination-related behaviors and design culturally appropriate interventions to ensure equitable access to healthcare. The COVID-19 pandemic has exposed longstanding anti-Asian racism in the U.S. Yet, effects of discrimination on Asian American health are unknown, partly because diverse Asian American populations are analyzed in aggregate.

Authors aim to understand how perceived discrimination affects health care utilization among different Asian American subgroups. They examine the association of perceived discrimination with health care utilization using the California Health Interview Survey (CHIS). In the CHIS, respondents reported whether they would’ve gotten better medical care if they belonged to a different race. Researchers examine the association between these responses and physician visits within the past year, in the survey years 2003, 2004 and 2016–2017. Subsequent modeling examines potential mediating and moderating factors such as limited English proficiency, immigration status, income, and survey year. Asian American subgroups analyzed include Asian Indian, Korean, Chinese, Filipino, Vietnamese, Japanese, and other Asian.

Findings: Results will highlight how perceived discrimination incentivizes or disincentivizes certain Asian subgroups to utilize health care. Asian American subgroups have differing and diverse experiences with discrimination due to their historical and cultural differences; results will elucidate how discrimination affects these subgroups. Results will be compared to non-Hispanic whites, who represent the racial group least likely to experience discrimination in the U.S. Mediation and moderation analysis will help understand how traditionally cited factors for health care utilization interact with perceived discrimination on Asian Americans.

Asian American subgroups are understudied, despite Asian Americans being one of the fastest growing racial groups in the U.S. Understanding how perceived discrimination affects Asian Americans can help stakeholders target subgroups that are at highest risk of discrimination-related behaviors and design culturally appropriate interventions.

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• Journal Article: The Impact of Asian American Perceived Discrimination on Health Utilization

​Although immigrants are healthier than non-immigrants on numerous outcomes, the reverse appears to be true with regards to food insecurity. Most studies ignore heterogeneity in the risk for food insecurity within immigration status and by ethnicity, even though significant variation likely exists. Authors consider how immigration status and ethnicity are related to trends in food insecurity among Latinos and Asians in California from 2001 through 2011. Data come from the 2001 to 2011 restricted California Health Interview Survey (n=245,679). Latinos and Asians were categorized as U.S.-born, naturalized/legal permanent residents (naturalized/LPR), and non-LPRs (students, temporary workers, refugees, and undocumented persons). Multivariable weighted logistic regression analyses assessed temporal trends over the 10-year period after adjustment for demographics, socioeconomic characteristics, and program participation.

Findings: Across this period, U.S.-born Asians reported similar levels of food insecurity as U.S.-born Whites. Conversely, Latinos, regardless of immigration status or nativity, and Asian immigrants (i.e., naturalized/LPR and non-LPR) reported greater food insecurity than U.S.-born Whites. Further, from 2001 through 2009, non-LPR Latinos reported higher risk of food insecurity than naturalized/LPR Latinos. Thus, food insecurity differs between ethnic groups, but also differs within ethnic group by immigration status. Efforts to reduce food insecurity should consider the additional barriers to access that are faced by immigrants, particularly those without legal permanent residency.

• Katrina M. Waselmann
• Annie Ro
• Gilbert Gee, PhD