Racial Misclassification Research Articles

Assessment of Racial Misclassification Among American Indian and Alaska Native Identity in Cancer Surveillance Data in the United States and Considerations for Oral Health: A Systematic Review.

Misclassification of American Indian and Alaska Native (AI/AN) peoples exists across various databases in research and clinical practice. Oral health is associated with cancer incidence and survival; however, misclassification adds another layer of complexity to understanding the impact of poor oral health. The objective of this literature review was to systematically evaluate and analyze publications focused on racial misclassification of AI/AN racial identities among cancer surveillance data. The PRISMA Statement and the CONSIDER Statement were used for this systematic literature review. Studies involving the racial misclassification of AI/AN identity among cancer surveillance data were screened for eligibility. Data were analyzed in terms of the discussion of racial misclassification, methods to reduce this error, and the reporting of research involving Indigenous peoples. A total of 66 articles were included with publication years ranging from 1972 to 2022. A total of 55 (83%) of the 66 articles discussed racial misclassification. The most common method of addressing racial misclassification among these articles was linkage with the Indian Health Service or tribal clinic records (45 articles or 82%). The average number of CONSIDER checklist domains was three, with a range of zero to eight domains included. The domain most often identified was Prioritization (60), followed by Governance (47), Methodologies (31), Dissemination (27), Relationships (22), Participation (9), Capacity (9), and Analysis and Findings (8). To ensure equitable representation of AI/AN communities, and thwart further oppression of minorities, specifically AI/AN peoples, is through accurate data collection and reporting processes.

Abstract 4872: Elevated colorectal cancer incidence among American Indian/Alaska Native persons in Alaska compared to other populations worldwide

Abstract Background: Colorectal cancer (CRC) is a leading cancer worldwide. Incidence varies greatly by country and racial group. We present recent CRC incidence and mortality rates among American Indian/Alaska Native (AI/AN) persons in Alaska and compare them to rates among other racial groups in Alaska and AI/AN persons in other regions of the United States, and to published CRC incidence rate estimates for other countries around the world. Methods: To calculate CRC incidence in the United States, we used U.S. Cancer Statistics data, which includes cancer registry data from the Centers for Disease Control and Prevention’s (CDC) National Program of Cancer Registries and the National Cancer Institute’s Surveillance, Epidemiology, and End Results Program. Cancer data for AI/AN persons in Alaska came from the Alaska Cancer Registry as well as the Alaska Native Tumor Registry. Death data came from the CDC’s National Death Index, which was linked with the Indian Health Service patient registry database to address race misclassification in AI/AN populations, to create the United States Cancer Statistics American Indian and Alaska Native Mortality Database. This database was used to calculate CRC mortality rates for AI/AN persons in this study. Rates were age-adjusted using the World Health Organization’s World Standard Population (2000-2025), so that rates for AI/AN persons in the United States could be more comparable to rates that have been estimated for countries around the world. Estimates of worldwide CRC incidence came from the International Agency for Research on Cancer Global Cancer Observatory GLOBOCAN 2020 database. Results: AI/AN persons in Alaska (males and females combined) had the highest CRC incidence rate (58.4 per 100,000 people) in the year 2020, when compared to AI/AN persons in every other region of the United States. Within Alaska, AI/AN persons had a higher CRC incidence rate than persons of any other racial group. When compared with published CRC incidence rates worldwide, the rate for AI/AN persons in Alaska was higher than the rates reported for any country in the world in 2020. The country with the highest recorded CRC incidence rate in 2020 was Hungary (45.3 per 100,000 people). AI/AN persons in Alaska also had the highest CRC mortality rate (27.1 per 100,000 people) in 2020. Worldwide, the country with the highest recorded CRC mortality rate in 2020 was Slovakia (21.0 per 100,000 people). Conclusions: This review of CRC incidence and mortality rates from populations in the US and worldwide showed that AI/AN persons in Alaska had the highest documented incidence and mortality rates of CRC in the world in 2020. Health systems serving AI/AN persons in Alaska could implement policies and interventions that support colorectal cancer screening, to reduce the burden of this preventable disease. Citation Format: Donald Haverkamp, Diana Redwood, Elena Roik, Stephen Vindigni. Elevated colorectal cancer incidence among American Indian/Alaska Native persons in Alaska compared to other populations worldwide [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4872.

Melanoma Incidence Rates Among Non-Hispanic American Indian/Alaska Native Individuals, 1999-2019

Non-Hispanic American Indian/Alaska Native people have the second highest incidence rate of invasive cutaneous melanoma in the US after non-Hispanic White people. To examine invasive cutaneous melanoma incidence rates and trends over time among non-Hispanic American Indian/Alaska Native people. This descriptive, observational cross-sectional study used population-based cancer registry data (US Cancer Statistics AI/AN Incidence Analytic Database) linked to the Indian Health Service administrative database to examine incidence rates by age, sex, region, histology, tumor site, stage, and other demographic and clinical characteristics. The study examined trends from 1999 to 2019 time period by age, sex, stage at diagnosis, and region. Non-Hispanic American Indian/Alaska Native people 15 years and older who received a diagnosis of invasive cutaneous melanoma from 1999 to 2019 who were members of federally recognized tribes and resided in Indian Health Service purchased/referred care delivery areas were included in this study to reduce racial misclassification and provide more accurate rates. The data were analyzed in 2022. Demographic and clinical characteristics, such as age, sex, geographic region, histology, stage, and tumor site. Invasive cutaneous melanoma incidence rates by age group, sex, region, resident county characteristics (poverty level, rurality, education level, and socioeconomic status), stage at diagnosis, tumor site, and histology. Trends over time by age, sex, region, and stage. From 1999 to 2019, 2151 non-Hispanic American Indian/Alaska Native people (1021 female individuals [47.5%]) received a diagnosis of incident cutaneous melanoma (rate, 10.7 per 100 000; 95% CI, 10.3-11.2). Rates were higher among male than female individuals (13.0 [95% CI, 12.2-13.8] vs 9.2 [95% CI, 8.6-9.8]) and for people 55 years and older (24.2; 95% CI, 22.8-25.7) compared with those aged 15 to 39 years (3.5; 95% CI, 3.2-3.9). Rates were highest for male individuals 55 years and older (34.5; 95% CI, 31.8-37.3) and people living in the Southern Plains (male individuals: 23.8; 95% CI, 21.5-26.2; female individuals: 15.5; 95% CI, 14.0-17.2) and Pacific Coast region (male individuals: 16.5; 95% CI, 14.5-18.7; female individuals: 12.3; 95% CI, 10.9-13.9). Rates increased among female individuals from 1999 to 2019 (average annual percent change [AAPC], 2.5; P < .001); among regional/distant stage tumors (AAPC, 2.5; P = .01) and people 55 years and older (AAPC, 2.8; P = .001). The results of this study suggest that additional studies could potentially identify risk factors among non-Hispanic American Indian/Alaska Native people.

Abstract B106: Assessing racial disparities in the receipt of quality care in the most prevalent cancers in American Indians

Abstract INTRODUCTION Previous SEER-Medicare analyses reported lower receipt of guideline concordant care for American Indian (AI) compared with White (WH) patients across several cancers. While large scale assessments are informative, there is a need to assess cancer outcomes and develop interventions at a level closer to communities. To address this gap, we assessed measures of quality care in AI and WH breast, prostate, and colorectal cancer patients. METHODS We assembled novel cohorts of AI and WH patients from the North Carolina (NC) cancer registry, the state with the largest AI population east of the Mississippi River. Eligible patients were diagnosed with breast, prostate, and colorectal cancers who linked to public and private insurance claims with continuous enrollment (2003-2019). Measures were assessed within 1 year of diagnosis unless stated otherwise. Breast cancer measures included receipt of: (1) HER2 testing within 3 months of diagnosis [NQF #1878]; (2) Tamoxifen/Aromatase Inhibitors for Stage I-III ER/PR+ [NQF #220]; (3) radiation among stage I-III breast conserving surgery or mastectomy patients [NQF #0219]. Stage II-III colorectal cancer measures included receipt of: (1) carcinoembryonic antigen (CEA) testing; (2) surveillance colonoscopy; and (3) computed tomography (CT) among resected patients [NCCN 2.2023 COL-8]. We assessed receipt of prostate-specific antigen (PSA) testing in the first 15 months after prostate cancer diagnosis to monitor disease recurrence. Poisson regression adjusting for sex, urbanicity, insurance type, and age at diagnosis was used to estimate risk ratios (RR) and 95% confidence intervals (CI) comparing the receipt of care between AI and WH patients. RESULTS The sample sizes of AI patients differed across measures, ranging from 104 colorectal to 554 prostate cancer patients. Evidence of disparity was mixed for the breast cancer measures. AI breast cancer patients less frequently received HER2 testing within 3 months of diagnosis (AI=61% vs WH=71%), although adjustment attenuated this association (RR=0.90; CI: 0.81-1.01). Among stage I-III breast cancer patients, AIs more frequently received radiation within 1 year of surgery (AI=75% vs WH=71%) compared with WH patients (RR=1.11; CI: 1.01-1.21). Across colorectal cancer measures, AI patients performed as well or better than WH patients. Notably, AI patients more frequently received CEA testing (AI=71% vs WH=59%), a difference that persisted after adjustment (RR=1.17; CI: 1.03-1.32). AI prostate cancer patients received PSAs less often in the 15 months following diagnosis (AI=82% vs WH=88%) than WH patients (RR=0.96; CI: 0.93-1.00). CONCLUSIONS The magnitude and direction of AI/WH disparities in receipt of quality cancer care differed across measures. Racial misclassification is a challenge in AI health outcomes research, which may misrepresent the experience of AIs. Nevertheless, our findings provide insight into specific areas of breast, prostate, and colorectal cancer care where local tailored interventions can be focused to improve care equity. Citation Format: Bradford E. Jackson, Marc E. Emerson, Lisa P. Spees, Chris D. Baggett, Hayley N. Morris, Ana I. Salas, Angelo Moore, Yadurshini Raveendran, Clare Meernik, Tomi Akinyemiju, Rachel Denlinger-Apte, Ronny A. Bell, Stephanie B. Wheeler. Assessing racial disparities in the receipt of quality care in the most prevalent cancers in American Indians [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr B106.

Disparities in Misclassification of Race and Ethnicity in Electronic Medical Records Among Patients with Traumatic Injury.

Systems-level barriers to self-reporting of race and ethnicity reduce the integrity of data entered into the medical record and trauma registry among patients with injuries, limiting research assessing the burden of racial disparities. We sought to characterize misclassification of self-identified versus hospital-recorded racial and ethnic identity data among 10,513 patients with traumatic injuries. American Indian/Alaska Native patients (59.9%) and Native Hawaiian/Pacific Islander patients (52.4%) were most likely to be misclassified. Most Hispanic/Latin(x) patients preferred to only be identified as Hispanic/Latin(x) (73.2%) rather than a separate race category (e.g., White). Incorrect identification of race/ethnicity also has substantial implications for the perceived demographics of patient population; according to the medical record, 82.3% of the population were White, although only 70.6% were self-identified as White. The frequency of misclassification of race and ethnicity for persons of color limits research validity on racial and ethnic injury disparities.

Effect of racial misclassification in police data on estimates of racial disparities

AbstractResearch on race and policing increasingly draws upon data collected by police officers to estimate racial disparities in police contact. Many of these data sets, however, rely on officer perception of a stopped person's race, which may be inconsistent with how those individuals self‐identify. Furthermore, researchers frequently benchmark contact data where race is perceived by police officers against census and survey data where race is self‐identified. We argue that discordance between how individuals self‐identify and how they are classified by officers can bias estimates of racial disparities. Using a unique data set, which allows us to compare officers’ racial classification of stopped persons with those same persons’ racial self‐identification, we characterize rates of racial misclassification in administrative police records. We find evidence of racial misclassification in police records, especially among Hispanic and Asians/Pacific Islanders. We find that officer classification of Hispanics as (non‐Hispanic) White is the most common form of racial misclassification in our sample and that its substantive consequences are significant. Specifically, we find that officer classification of Hispanics as White may lead analysts to incorrectly conclude that Hispanics are no more likely than Whites to be cited by police.

Racial Misclassification, Discrimination, Consciousness, and Self-Rated Health Among Native Hawaiian and Pacific Islander Adults in the USA.

Medical researchers have historically utilized the variable of race uncritically, rarely defining race, rarely acknowledging it as a social construct, and often omitting information about how it was measured. In this study, we use the following definition of race: "a system of structuring opportunity and assigning value based on the social interpretation of how one looks." We examine the influence of racial misclassification, racial discrimination, and racial consciousness on the self-rated health of Native Hawaiian and Pacific Islanders (NHPI) living in the United States of America (USA). Our analysis used online survey data from a subgroup of NHPI adults living in the USA (n = 252) who were oversampled as part of a larger study of US adults (N = 2022). Respondents were recruited between September 7, 2021 and October 3, 2021, from an online opt-in panel of individuals across the USA. Statistical analyses include weighted and unweighted descriptive statistics for the sample, as well as a weighted logistic regression for poor/fair self-rated health. Odds of poor/fair self-rated health were greater for women (OR = 2.72; 95% CI [1.19, 6.21]) and those who experienced racial misclassification (OR = 2.90; 95% CI [1.20, 7.05]). No other sociodemographic, healthcare, or race-related variables were significantly associated with self-rated health in the fully adjusted results. Findings suggest that racial misclassification may be an important correlate of self-rated health among NHPI adults in the US context.

Abstract C112: Understanding and addressing cancer disparities among American Indians in North Carolina: The Southeastern cancer health equity partnership

Abstract North Carolina (NC) is home to the largest American Indian population in the Eastern United States (approximately 300,000 residents, about 2.8% of the total NC population), represented by eight state and federally recognized tribes (Eastern Band of Cherokee Indians, Sappony, Occaneechi Band of Saponi Nation, Meherrin, Haliwa Saponi, Coharie, Lumbee, Waccamaw Siouan) and four urban Indian organizations (Metrolina Native American Association, Guilford Native American Association, Triangle Native American Society, Cumberland County Association for Indian People). This population experiences significant health disparities largely related to adverse social determinants of health and limited access to health care. With regards to cancer, disparities exist for incidence and mortality for certain cancer, although there are limited data available with regards to cancer screening stage at diagnosis, treatment and survivorship. Furthermore, evidence suggests that racial misclassification contributes to a significant underestimation of the true cancer incidence and mortality in this population. To address the cancer care needs of NC American Indians, a unique collaboration was established in 2021 among the leadership of the Community Outreach and Engagement programs at the three NCI-designated Comprehensive Cancer Centers in North Carolina (Duke Cancer Institute, University of North Carolina Lineberger Cancer Center, Wake Forest Baptist Comprehensive Cancer Center). The collaboration, entitled, The Southeastern American Indian Cancer Health Equity Partnership (SAICEP), has as its mission to "understand and address the cancer-related health needs of American Indian communities in our catchment areas and beyond." SAICEP includes: (1) a quarterly speakers' series, featuring nationally recognized experts in the area of American Indian cancer research and care; (2) educational outreach and engagement activities at tribal and state cultural events; and, (3) cutting-edge culturally respectful research to understand and address cancer disparities at the tribal and state level. Partnerships have been established with tribal leaders across the state as well as researchers at the University of North Carolina at Pembroke in the traditional homeland of the Lumbee tribe (the largest tribe in the state). Future endeavors will include partnerships with tribes in other states in our catchment areas (Virginia, South Carolina). Citation Format: Ronny A. Bell, Tomi Akinyemiju, Stephanie B. Wheeler. Understanding and addressing cancer disparities among American Indians in North Carolina: The Southeastern cancer health equity partnership [abstract]. In: Proceedings of the 15th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2022 Sep 16-19; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr C112.

Cancer statistics for American Indian and Alaska Native individuals, 2022: Including increasing disparities in early onset colorectal cancer.

American Indian and Alaska Native (AIAN) individuals are diverse culturally and geographically but share a high prevalence of chronic illness, largely because of obstacles to high-quality health care. The authors comprehensively examined cancer incidence and mortality among non-Hispanic AIAN individuals, compared with non-Hispanic White individuals for context, using population-based data from the National Cancer Institute, the Centers for Disease Control and Prevention, and the North American Association of Central Cancer Registries. Overall cancer rates among AIAN individuals were 2% higher than among White individuals for incidence (2014 through 2018, confined to Purchased/Referred Care Delivery Area counties to reduce racial misclassification) but 18% higher for mortality (2015 through 2019). However, disparities varied widely by cancer type and geographic region. For example, breast and prostate cancer mortality rates are 8% and 31% higher, respectively, in AIAN individuals than in White individuals despite lower incidence and the availability of early detection tests for these cancers. The burden among AIAN individuals is highest for infection-related cancers (liver, stomach, and cervix), for kidney cancer, and for colorectal cancer among indigenous Alaskans (91.3 vs. 35.5 cases per 100,000 for White Alaskans), who have the highest rates in the world. Steep increases for early onset colorectal cancer, from 18.8 cases per 100,000 Native Alaskans aged 20-49 years during 1998 through 2002 to 34.8 cases per 100,000 during 2014 through 2018, exacerbated this disparity. Death rates for infection-related cancers (liver, stomach, and cervix), as well as kidney cancer, were approximately two-fold higher among AIAN individuals compared with White individuals. These findings highlight the need for more effective strategies to reduce the prevalence of chronic oncogenic infections and improve access to high-quality cancer screening and treatment for AIAN individuals. Mitigating the disparate burden will require expanded financial support of tribal health care as well as increased collaboration and engagement with this marginalized population.

COVID-19, Medical Care, and Data Sovereignty

Abstract During the COVID-19 pandemic, Native American communities were not only heavily impacted by the virus but other socioeconomic factors as well. The Navajo Nation was at the forefront, setting an example for the United States and general public on establishing policies and ground efforts to minimize the spread of the virus through Navajo land. However, as the virus spread, it also revealed the interconnectedness surrounding Indigenous communities and Indigenous women. Through the Missing and Murdered Indigenous Women (MMIW) Movement, researchers found a lack of data as reports present unreliable and underreported information involving racial misclassification and data genocide. Data regarding Indigenous community COVID-19 statistics reflect historical trauma, especially in the exclusion of Indigenous communities from data sets and analyses used to make health policy decisions. I conclude this article by emphasizing the necessity of including Indigenous sovereign bodies in the dispersal of gathered data sets and establishing an amicable relationship promoting the well-being of Indigenous communities between social scientists and Native communities.

Just data representation for Native Hawaiians and Pacific Islanders: A critical review of systemic Indigenous erasure in census and recommendations for psychologists.

The decennial Census survey marks the emergence of federal classifications of race and ethnicity by which the U.S. government has historically conflated Native Hawaiians and Pacific Islanders (NHPI, hereafter) as "Asian or Pacific Islander." This conflation amplifies health injustices and inequities of NHPIs through multiple mechanisms because it masks the complex and heterogeneous experiences of NHPIs, whose positions and relations with the settler state are qualitatively and substantially distinct from Asian Americans. This critical review examines federal documents and research to examine how the panethnic categorizations are often sustained through scientific inquiry and methodologies. We found that self-determination and self-identification for NHPIs are impeded by settler-colonial relations between U.S. colonization of parts of Oceania (e.g., Hawai'i, Sāmoa, Fiji, and Guam) and the forcefully imposed categorization that continues to be in use to legitimize the domination of Indigenous Peoples through race misclassification. Specifically, Census data collection fails to capture accurate and reliable data due to serious methodological limitations. These implications for psychological research compel us to make several recommendations for psychologists: (1) engage with NHPI community partners in all research processes; (2) critically examine Census research design and consider oversampling NHPI households to ensure just data representation; (3) meaningfully engage when, whether and how to aggregate Asian Americans with NHPIs; and (4) use Indigeneity as a critical framework.

Sidebar: Impact of Racial Misclassification of Health Data on American Indians in North Carolina.

Mice deficient in hepatocyte nuclear factor 1α (HNF-1α) develop Laron dwarfism and non-insulin-dependent diabetes mellitus (Lee et al., 1998). Oxidative stress was present in the diabetic HNF-1α-null mice. To understand the mechanism underlying the oxidative stress in HNF-1α-null mice, we examined whether HNF-1α deficiency affects the integrity of the cellular defense system against oxidative stress. The glutathione level and activities of superoxide dismutase and glutathione reductase in liver and other tissues examined were not affected by HNF-1α deficiency. However, activities of cytosolic glutathione peroxidase and catalase, two enzymes responsible for detoxification of hydrogen peroxide within cells, were reduced specifically in liver of HNF-1α-null mice. The mRNA and protein levels of hepatic catalase in HNF-1α-null mice did not differ from those in normal mice. The loss of hepatic catalase activity in HNF-1α-null mice is probably caused by an insufficient heme pool in liver cells, because the mRNA level of ferrochelatase, the enzyme that catalyzes the last step of heme biosynthesis, was significantly reduced in liver, and the daily hemin treatment restored partial catalase activity in liver of HNF-1α-null mice. Furthermore, our results of cell transfection and luciferase reporter assay indicated that the mouse ferrochelatase promoter could be*trans-*activated directly by HNF-1α.

Inaccurate Ethnicity and Race Classification of Hispanics Following Trauma Admission

Race and ethnicity are associated with disparate trauma outcomes. This study seeks to characterize accuracy of trauma registry classification of patient race and ethnicity and to identify factors associated with misclassification. A prospective observational study of patients admitted to an urban Level 1 trauma center was conducted over a 6-mo period. Race and ethnicity data recorded in the trauma registry were compared to patients' self-identifying data obtained through in-person interviews. Logistic regression determined rates of discordant race and ethnicity between trauma registry and patient self-identification processes, and identified factors independently associated with misclassification. A total of 444 patients were recruited. 98 (22%) self-identified as Hispanic/Latino. 45 patients self-identifying as Hispanic (45.9%) had inaccurately recorded ethnicity in the trauma registry. There was an increased odds of ethnicity misclassification in younger patients (OR 0.97, P < 0.01) and Spanish-only speakers (OR 11.80, P < 0.001). A decreased odds was found in males (OR 0.43, P < 0.05). No factors increased odds of racial misclassification, while dual English/Spanish speakers (OR 0.05, P < 0.01) wereas found to have decreased odds. Neither ethnicity nor race misclassification was associated with clinical variables. New racial self-identification was observed with 75% of patients who self-identified ethnically as Hispanic also self-identifying racially as Hispanic. Hispanic trauma patients have racial and ethnic misclassifications regardless of clinical status. Racial and ethnic identification is not sufficiently captured by current standardized questionnaires. Accuracy of hospital level racial data is important for local and national policies to address trauma disparities.

Racial Misclassification and Disparities in Neonatal Abstinence Syndrome Among American Indians and Alaska Natives.

Maternal substance misuse can result in neonatal abstinence syndrome (NAS), a drug withdrawal process in newborns exposed in utero to drugs. This study aimed to examine the effect of racial misclassification of American Indians and Alaska Natives (AI/AN) on rates of NAS in two hospital discharge datasets in the Pacific Northwest. We conducted probabilistic record linkages between the Northwest Tribal Registry and Oregon and Washington hospital discharge datasets to correct racial misclassification of AI/AN people. We assessed outcomes using International Classification of Disease, Ninth Revision/Tenth Revision, Clinical Modification (ICD-9-CM or ICD-10-CM) diagnosis codes. Linkage increased ascertainment of NAS cases among AI/AN by 8.8% in Oregon and by 18.1% in Washington. AI/AN newborns were 1.5 and 3.9 times more likely to be diagnosed with NAS than NHW newborns in Oregon and Washington, respectively. The results showed that newborns residing in rural Washington were 1.4 times more likely to be diagnosed with NAS than those living in urban areas. Correct racial classification is an important factor in improving data quality for AI/AN populations and establishing accurate surveillance to help address the disproportionate burden of neonatal abstinence syndrome among AI/AN. The results highlight the need for programing efforts tailored by insurance status and rurality for pregnant women using substances.

Indigenous data sovereignty and COVID-19 data issues for American Indian and Alaska Native Tribes and populations.

Indigenous Peoples in the United States have been experiencing disproportionate impacts of COVID-19. American Indian and Alaska Native persons are more likely to be infected, experience complications, and die from coronavirus. Evidence suggests that Indigenous persons have 3.5 times the incidence rate of non-Hispanic/Latinx whites. Unfortunately, this is likely a gross underestimate because of a lack of reliable and accurate COVID-19 data for American Indian and Alaska Native populations. Multiple factors contribute to poor data quality including the lack of Indigenous representation in the data and rampant racial misclassification at both the individual and group levels. The current pandemic has shed light on multiple pre-existing issues related to Indigenous data sovereignty in data collection and management. We discuss the importance of centring Indigenous data sovereignty in the systemic efforts to increase COVID-19 data availability and quality. The federal and state governments must support and promote Tribes’ rights to access data. Federal and state governments should also focus on bolstering their data availability and quality for aggregated data on AIAN populations and for providing disaggregated Tribal data to Tribes. Given the pivotal moment in the United States with ongoing and parallel pandemics of coronavirus and racism, we urge demographers and population scientists to reflect on the role of structural racism in data, data collection and analysis.

Racial Misclassification Masks True Prevalence of Suicide in South Asian Americans

Racial Misclassification Masks True Prevalence of Suicide in South Asian Americans

Cancers Associated with Human Papillomavirus in American Indian and Alaska Native Populations - United States, 2013-2017.

Human papillomavirus (HPV) causes most cervical cancers and some cancers of the penis, vulva, vagina, oropharynx, and anus. Cervical precancers can be detected through screening. HPV vaccination with the 9-valent HPV vaccine (9vHPV) can prevent approximately 92% of HPV-attributable cancers (1).* Previous studies have shown lower incidence of HPV-associated cancers in non-Hispanic American Indian and Alaska Native (AI/AN) populations compared with other racial subgroups (2); however, these rates might have been underestimated as a result of racial misclassification. Previous studies have shown that cancer registry data corrected for racial misclassification resulted in more accurate cancer incidence estimates for AI/AN populations (3,4). In addition, regional variations in cancer incidence among AI/AN populations suggest that nationally aggregated data might not adequately describe cancer outcomes within these populations (5). These variations might, in part, result from geographic disparities in the use of health services, such as cancer screening or vaccination (6). CDC analyzed data for 2013-2017 from central cancer registries linked with the Indian Health Service (IHS) patient registration database to assess the incidence of HPV-associated cancers and to estimate the number of cancers caused by HPV among AI/AN populations overall and by region. During 2013-2017, an estimated 1,030 HPV-associated cancers were reported in AI/AN populations. Of these cancers, 740 (72%) were determined to be attributable to HPV types targeted by 9vHPV; the majority were cervical cancers in females and oropharyngeal cancers in males. These data can help identify regions where AI/AN populations have disproportionately high rates of HPV-associated cancers and inform targeted regional vaccination and screening programs in AI/AN communities.

Gastric Cancer Among American Indian and Alaska Native Populations in the United States, 2005-2016.

American Indian and Alaska Native (AI/AN) populations have higher gastric cancer rates than the general US population. This study provides a comprehensive overview of incidence rates among AI/AN persons during 2005-2016 compared with non-Hispanic whites (whites). Population-based cancer registry data for 2005-2016 were linked with the Indian Health Service patient registration databases to address racial misclassification. Age-adjusted gastric cancer incidence rates were expressed per 100,000 per year. Incidence and trend analyses were restricted to purchased/referred care delivery area counties in 6 geographic regions, comparing gastric cancer incidence rates for AI/AN vs white populations in the United States. Gastric cancer rates were higher in the AI/AN compared with white populations in nearly every US region. Incidence rates for central/distal portions of the stomach were higher in AI/AN individuals compared with whites. Rates of later stage gastric cancer were higher in AI/AN populations overall and in every region except the Pacific Coast and East. Incidence rates decreased significantly over time in both populations. Declining rates in the AI/AN populations were driven by changes in the Pacific Coast and Northern Plains regions. AI/AN populations have a disproportionately high incidence of gastric cancer, especially in Alaska. High incidence in the central/distal portions of the stomach among AI/AN populations likely reflects a high prevalence of Helicobacter pylori infection in these populations. These data can be used to develop interventions to reduce risk factors and improve access to health services among AI/AN people at high risk for gastric cancer.

Determinants of Racial Misclassification in COVID-19 Mortality Data: The Role of Funeral Directors and Social Context

Death certificates are a crucial tool in public health, yet American Indians and Alaska Natives have long been misclassified after death, most often as white. During the COVID-19 pandemic, rapid provisional death counts have used data from death certificates to identify outbreaks and allocate resources. This paper interrogates common practices of funeral directors—who complete the demographic portion of the death certificate—as well as the social context in which they operate. The paper then reviews how these determinants of American Indian and Alaska Native misclassification may have changed during the pandemic and discusses implications for the quality of COVID-19 mortality data and opportunities for improvement.

Blurred lines: racial misclassification in death certificates in Brazil.

To analyze the agreement between self-reported race and race reported on death certificates for older (≥ 60years) residents of São Paulo, Brazil (from 2000 to 2016) and to estimate weights to correct mortality data by race. We used data from the Health, Well-Being and Aging Study (SABE) and from Brazil's Mortality Information System. Misclassification was identified by comparing individual self-reported race with the corresponding race on the death certificate (n = 1012). Racial agreement was analyzed by performing sensitivity and Cohen's Kappa tests. Multinomial logistic regressions were adjusted to identify characteristics associated with misclassification. Correction weights were applied to race-specific mortality rates. Total racial misclassification was 17.3% (13.1% corresponded to whitening, and 4.2% to blackening). Racial misclassification was higher for self-reported pardos/mixed (63.5%), followed by blacks (42.6%). Official vital statistics suggest highest elderly mortality rates for whites, but after applying correction weights, black individuals had the highest rate (45.85/1000 population), followed by pardos/mixed (42.30/1000 population) and whites (37.91/1000 population). Official Brazilian data on race-specific mortality rates may be severely misclassified, resulting in biased estimates of racial inequalities.