East is east … or is it? Racialization of Asian, Middle Eastern, and Pacific Islander persons

The conventional use of racial categories in health research naturalizes "race" in problematic ways that ignore how racial categories function in service of a White-dominated racial hierarchy. In many respects, racial labels are based on geographic designations. For instance, "Asians" are from Asia. Yet, this is not always a tenable proposition. For example, Afghanistan resides in South Asia, and shares a border with China and Pakistan. Yet, people from Afghanistan are not considered Asian, but Middle Eastern, by the US Census. Furthermore, people on the west side of the Island of New Guinea are considered Asian, whereas those on the eastern side are considered Pacific Islander. In this article, we discuss the complexity of the racial labels related to people originating from Oceania and Asia, and, more specifically, those groups commonly referred to as Pacific Islander, Middle Eastern, and Asian. We begin with considerations of the aggregation fallacy. Just as the ecological fallacy refers to erroneous inferences about individuals from group data, the aggregation fallacy refers to erroneous inferences about subgroups (eg, Hmong) from group data (ie, all Asian Americans), and how these inferences can contribute to stereotypes such as the "model minority." We also examine how group averages can be influenced merely by the composition of the subgroups, and how these, in turn, can be influenced by social policies. We provide a historical overview of some of the issues facing Pacific Islander, Middle Eastern, and Asian communities, and conclude with directions for future research.

No Equity without Data Equity: Data Reporting Gaps for Native Hawaiians and Pacific Islanders as Structural Racism

Data on the health and social determinants for Native Hawaiians and Pacific Islanders (NHPIs) in the United States are hidden, because data are often not collected or are reported in aggregate with other racial/ethnic groups despite decades of calls to disaggregate NHPI data. As a form of structural racism, data omissions contribute to systemic problems such as inability to advocate, lack of resources, and limitations on political power. The authors conducted a data audit to determine how US federal agencies are collecting and reporting disaggregated NHPI data. Using the COVID-19 pandemic as a case study, they reviewed how states are reporting NHPI cases and deaths. They then used California's neighborhood equity metric-the California Healthy Places Index (HPI)-to calculate the extent of NHPI underrepresentation in communities targeted for COVID-19 resources in that state. Their analysis shows that while collection and reporting of NHPI data nationally has improved, federal data gaps remain. States are vastly underreporting: more than half of states are not reporting NHPI COVID-19 case and death data. The HPI, used to inform political decisions about allocation of resources to combat COVID-19 in at-risk neighborhoods, underrepresents NHPIs. The authors make recommendations for improving NHPI data equity to achieve health equity and social justice.

Exploring the Paradoxical Relationship of a Creb 3 Regulatory Factor Missense Variant With Body Mass Index and Diabetes Among Samoans: Protocol for the Soifua Manuia (Good Health) Observational Cohort Study

BACKGROUND

The prevalence of obesity and diabetes in Samoa, like many other Pacific Island nations, has reached epidemic proportions. Although the etiology of these conditions can be largely attributed to the rapidly changing economic and nutritional environment, a recently identified genetic variant, rs373863828 (CREB 3 regulatory factor, CREBRF: c.1370G>A p.[R457Q]) is associated with increased odds of obesity, but paradoxically, decreased odds of diabetes.

OBJECTIVE

The overarching goal of the Soifua Manuia (Good Health) study was to precisely characterize the association of the CREBRF variant with metabolic (body composition and glucose homeostasis) and behavioral traits (dietary intake, physical activity, sleep, and weight control behaviors) that influence energy homeostasis in 500 adults.

METHODS

A cohort of adult Samoans who participated in a genome-wide association study of adiposity in Samoa in 2010 was followed up, based on the presence or absence of the CREBRF variant, between August 2017 and March 2019. Over a period of 7-10 days, each participant completed the main study protocol, which consisted of anthropometric measurements (weight, height, circumferences, and skinfolds), body composition assessment (bioelectrical impedance and dual-energy x-ray absorptiometry), point-of-care glycated hemoglobin measurement, a fasting blood draw and oral glucose tolerance test, urine collection, blood pressure measurement, hand grip strength measurement, objective physical activity and sleep apnea monitoring, and questionnaire measures (eg, health interview, cigarette and alcohol use, food frequency questionnaire, socioeconomic position, stress, social support, food and water insecurity, sleep, body image, and dietary preferences). In January 2019, a subsample of the study participants (n=118) completed a buttock fat biopsy procedure to collect subcutaneous adipose tissue samples.

RESULTS

Enrollment of 519 participants was completed in March 2019. Data analyses are ongoing, with results expected in 2020 and 2021.

CONCLUSIONS

While the genetic variant rs373863828, in CREBRF, has the largest known effect size of any identified common obesity gene, very little is currently understood about the mechanisms by which it confers increased odds of obesity but paradoxically lowered odds of type 2 diabetes. The results of this study will provide insights into how the gene functions on a whole-body level, which could provide novel targets to prevent or treat obesity, diabetes, and associated metabolic disorders. This study represents the human arm of a comprehensive and integrated approach involving humans as well as preclinical models that will provide novel insights into metabolic disease.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR1-10.2196/17329.