Racial Misclassification Research Articles

Racial Misclassification in Mortality Records Among American Indians/Alaska Natives in Oklahoma From 1991 to 2015.

The primary purpose of this study was to compare age-adjusted mortality rates before and after linkage with Indian Health Service records, adjusting for racial misclassification. We focused on differences in racial misclassification by gender, age, geographic differences, substate planning districts, and cause of death. Our secondary purpose was to evaluate time trends in misclassification from 1991 to 2015. Retrospective, descriptive study. Oklahoma. Persons contained in the Oklahoma State Health Department Vital Records. To evaluate the age-adjusted mortality ratio pre- and post-Indian Health Service record linkage (misclassification rate ratio) and to evaluate the overall trend of racial misclassification on mortality records measured through annual percent change (APC) and average annual percent change (AAPC). We identified 2 stable trends of racial misclassification upon death for American Indians/Alaska Natives (AI/ANs) from 1991 to 2001 (APC: -0.2%; 95% confidence interval: -1.4% to 1.0%) and from 2001 to 2005 (APC: -6.9%; 95% confidence interval: -13.7% to 0.4%). However, the trend identified from 2005 to 2015 decreased significantly (APC: -1.4%; 95% confidence interval: -2.5% to -0.2%). For the last 5 years available (2011-2015), the racial misclassification adjustment resulted in higher mortality rates for AI/ANs reflecting an increase from 1008 per 100 000 to 1305 per 100 000 with the linkage process. There were an estimated 3939 AI/ANs in Oklahoma who were misclassified as another race upon death in those 5 years, resulting in an underestimation of actual AI/AN deaths by nearly 29%. An important result of this study is that misclassification is improving; however, this effort needs to be maintained and further improved. Continued linkage efforts and public access to linked data are essential throughout the United States to better understand the burden of disease in the AI/AN population.

Identification of American Indians and Alaska Natives in Public Health Data Sets: A Comparison Using Linkage-Corrected Washington State Death Certificates.

Efforts to address disparities experienced by American Indians/Alaska Natives (AI/ANs) have been hampered by a lack of accurate and timely health data. One challenge to obtaining accurate data is determining who "counts" as AI/AN in health and administrative data sets. To compare the effects of definition and misclassification of AI/AN on estimates of all-cause and cause-specific mortality for AI/AN in Washington during 2015-2016. Secondary analysis of death certificate data from Washington State. Data were corrected for AI/AN racial misclassification through probabilistic linkage with the Northwest Tribal Registry. Counts and age-adjusted rates were calculated and compared for 6 definitions of AI/AN. Comparisons were made with the non-Hispanic white population to identify disparities. Washington State. AI/AN and non-Hispanic white residents of Washington State who died in 2015 and 2016. Counts and age-adjusted rates for all-cause mortality and mortality from cardiovascular diseases, cancer, and unintentional injuries. The most conservative single-race definition of AI/AN identified 1502 AI/AN deaths in Washington State during 2015-2016. The least conservative multiple-race definition of AI/AN identified 2473 AI/AN deaths, with an age-adjusted mortality rate that was 48% higher than the most conservative definition. Correcting misclassified AI/AN records through probabilistic linkage significantly increased mortality rate estimates by 11%. Regardless of definition used, AI/AN in Washington had significantly higher all-cause mortality rates than non-Hispanic whites in the state. Reporting single-race versus multiple-race AI/AN had the most consequential effect on mortality counts and rates. Correction of misclassified AI/AN records resulted in small but statistically significant increases in AI/AN mortality rates. Researchers and practitioners should consult with AI/AN communities on the complex issues surrounding AI/AN identity to obtain the best method for identifying AI/AN in health data sets.

A Forgotten Danger: Burden of Influenza Mortality Among American Indians and Alaska Natives, 1999-2016.

American Indians and Alaska Natives (AI/ANs) are the only racial group in the United States that is identified as having a higher risk for developing influenza-related complications. As such, influenza-related mortality has consistently been one of the leading causes of death among AI/ANs. In addition, estimating influenza-related mortality is hampered by significant degrees of racial misclassification and underreporting of both morbidity and mortality data in the AI/AN population. Using data available from the Centers for Disease Control and Prevention, we analyzed influenza mortality by geography, race, gender, and age group to improve our understanding of the influenza burden on AI/AN communities. We found that while mortality rates generally declined across the AI/AN population, significant disparities exist between AI/ANs and non-Hispanic whites (NHWs). The greatest disparities occurred at the earliest stages of life, with mortality rates for AI/AN children younger than 5 years being more than 2 times higher than for NHW children. Similarly, the burden of influenza-related mortality among AI/AN adults emerged much earlier in life compared with NHWs. Perhaps most important, though, we found significant disparities in the geographic distribution of influenza-related mortality among AI/ANs. Because these are largely vaccine-preventable deaths, these results identify an area for targeted intervention to reduce the overall deaths attributable to influenza.

Abstract C25: Series of breast cancer brochures for American Indian addressing breast cancer disparities

Abstract Breast cancer mortality disproportionately affects American Indians, with one-half of the newly diagnosed cases at regional or distant metastasis. Low screening rates are a primary reason for the disproportionate number of late-stage diagnoses in this under-served community. American Indians are also under-represented in clinical trials and other research, as well as in the health and research professions. The lack of American Indian researchers has a direct impact on the number of studies conducted with American Indians and the poor rates of mammography and other breast cancer screenings. The AIHREA/ Susan G. Komen Scholars in American Indian Breast Cancer Disparities seek to increase the number of American Indian researchers trained in breast cancer research to reduce disparities in their communities. Breast cancer is the second leading cause of cancer mortality among American Indian (AI) and Alaska Native (AN) women, who have the lowest 5-year survival rates of all racial/ethnic groups. AI/AN women are twice as likely to die from breast cancer than non-Hispanic white women. Incidence rates have risen steadily over the last 50 years. Although incidence rates among AI/AN women are lower than for other racial/ethnic groups (67.2/100,000 women versus 125.3/100,000 women for all ethnic groups),10 more AI/AN women are diagnosed with late-stage breast cancers than other racial/ethnic groups, with 44% of newly diagnosed cases staged at regional or distant metastasis, compared to 33% among non-Hispanic whites. Breast cancer incidence rates among AI/AN women differ by geographic region, with rates as high as 139.5/100,000 women in Alaska and as low as 50.4/100,000 women in the Southwest. Recent data show that breast cancer incidence may be significantly under-reported among AI/AN women due, in large part, to racial misclassification. To help reduced the disparities in breast cancer screening we created five culturally tailored brochures. Focus groups with American Indian community members were used to determine topics for the brochures titled BRCA Facts, BRCA Screening, BRCA Positive Screen, BRCA Someone You Love, and BRCA Men. After drafting the brochures they were edited focusing on access for scientific accuracy by using a panel of experts, then checking the readability level by using Suitability Assessment of Materials, followed by checking the cultural appropriateness by receiving feedback from community members at events such as powwows. Culturally appropriate imagery was added and adjustments were made according to the feedback we received. The finalized brochures are now available to the American Indian tribes, organizations and individuals. Citation Format: Jordyn Gunville, Charley Lewis, Kelly Berryhill, Crissandra Wilkie, Joseph Pacheco, Christine Daley. Series of breast cancer brochures for American Indian addressing breast cancer disparities. [abstract]. In: Proceedings of the Ninth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2016 Sep 25-28; Fort Lauderdale, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(2 Suppl):Abstract nr C25.

STRATEGIES FOR EQUITABLE PHARMACOGENOMIC-GUIDED WARFARIN DOSING AMONG EUROPEAN AND AFRICAN AMERICAN INDIVIDUALS IN A CLINICAL POPULATION.

The blood thinner warfarin has a narrow therapeutic range and high inter- and intra-patient variability in therapeutic doses. Several studies have shown that pharmacogenomic variants help predict stable warfarin dosing. However, retrospective and randomized controlled trials that employ dosing algorithms incorporating pharmacogenomic variants under perform in African Americans. This study sought to determine if: 1) including additional variants associated with warfarin dose in African Americans, 2) predicting within single ancestry groups rather than a combined population, or 3) using percentage African ancestry rather than observed race, would improve warfarin dosing algorithms in African Americans. Using BioVU, the Vanderbilt University Medical Center biobank linked to electronic medical records, we compared 25 modeling strategies to existing algorithms using a cohort of 2,181 warfarin users (1,928 whites, 253 blacks). We found that approaches incorporating additional variants increased model accuracy, but not in clinically significant ways. Race stratification increased model fidelity for African Americans, but the improvement was small and not likely to be clinically significant. Use of percent African ancestry improved model fit in the context of race misclassification.

Discrepancies in Race and Ethnicity Documentation: a Potential Barrier in Identifying Racial and Ethnic Disparities

BackgroundData collection on race and ethnicity is critical in the assessment of racial disparities related to health. Studies comparing clinical and administrative data show discrepancies in race documentation and attribution.MethodsSelf-reported data from two studies were compared to demographics in the electronic health record (EHR) extracted from the Biomedical Translational Research Information System (BTRIS) repository. McNemar and Bhapkar analyses were conducted to quantify the agreement of ethnicity and race between self-reported and EHR data. Pearson’s chi-square tests were used to explore the relationship between acculturation, length of time in the USA, country of residence, and how individuals self-reported their race.ResultsThe sample (n = 280) was predominantly female (52.1 %), with a mean age of 47 (SD ± 13.74), mean years in the USA were 12.8 (SD ± 11.67) and the majority were born outside of the USA. (55.6 %). Those who self-identified as Hispanic (n = 208) scored a mean of 5.5 (SD ± 3.07) on the short acculturation scale (SAS) that ranges 4 to 20; lower scores indicate less acculturation. A significant difference was found between the way race is reported in the electronic medical record and self-reported data among those people who identified as Hispanic, with significant differences in the white (p < 0.0001) and other (p < 0.0001) categories.ConclusionsThe misclassification of race is most frequent in those individuals who self-identified as Hispanic. As the Hispanic population in the USA continues to grow, understanding the factors that affect the way that individuals from this heterogeneous population self-report race may provide important guidance in tailoring care to address health disparities.

Hospitalizations at Nonfederal Facilities for Lower Respiratory Tract Infection in American Indian and Alaska Native Children Younger than 5 Years of Age, 1997-2012

To evaluate hospitalizations at nonfederal facilities for lower respiratory tract infection (LRTI) in American Indian/Alaska Native (AI/AN) children and to compare associated rates and risk factors in AI/AN children and white children. We used Kids' Inpatient Database samples from 1997-2012 to identify discharges in non-Hispanic AI/AN and white children ages <5years with a principal or secondary diagnosis code indicating LRTI. To address systematic underreporting and misclassification of race in administrative databases, population rates were estimated by deriving race- and year-specific denominators from hospital births. During the study period, LRTI-associated discharge rates (per 1000) declined for white children (from 14.8 to 10.9; P<.001 for trend). For AI/AN children, rates varied widely by census region and were highest in the West, where they ranged from 38.6 in 1997 to 26.7 in 2012 (P=.35 for trend). Discharges in AI/AN children were associated with low household income, Medicaid insurance, and rural residence. In a case-cohort analysis of infants hospitalized with LRTI in 2012, discharge rates were higher for AI/AN infants than for white infants only in the West (72.8 vs 22.2; aOR, 2.5; 95% CI, 1.8-3.4). Among young children who use nonfederal hospitals, LRTI-associated hospitalizations occur at substantially higher rates for AI/AN children than for white children. These hospitalizations occur at rates that are particularly high for AI/AN infants in the West, where rates are comparable with those reported for Indian Health Service enrollees.

Causes and Disparities in Death Rates Among Urban American Indian and Alaska Native Populations, 1999-2009.

To characterize the leading causes of death for the urban American Indian/Alaska Native (AI/AN) population and compare with urban White and rural AI/AN populations. We linked Indian Health Service patient registration records with the National Death Index to reduce racial misclassification in death certificate data. We calculated age-adjusted urban AI/AN death rates for the period 1999-2009 and compared those with corresponding urban White and rural AI/AN death rates. The top-5 leading causes of death among urban AI/AN persons were heart disease, cancer, unintentional injury, diabetes, and chronic liver disease and cirrhosis. Compared with urban White persons, urban AI/AN persons experienced significantly higher death rates for all top-5 leading causes. The largest disparities were for diabetes and chronic liver disease and cirrhosis. In general, urban and rural AI/AN persons had the same leading causes of death, although urban AI/AN persons had lower death rates for most conditions. Urban AI/AN persons experience significant disparities in death rates compared with their White counterparts. Public health and clinical interventions should target urban AI/AN persons to address behaviors and conditions contributing to health disparities.

Using Record Linkage to Improve Race Data Quality for American Indians and Alaska Natives in Two Pacific Northwest State Hospital Discharge Databases.

To evaluate and adjust for American Indian and Alaska Native (AI/AN) racial misclassification in two hospital discharge datasets in the Pacific Northwest. Oregon (2010-2011) and Washington (2011) hospital discharge datasets were linked with the Northwest Tribal Registry (NTR), a registry of AI/AN individuals who accessed services at Indian health facilities in the Northwest. Record linkage was used to match state hospital records to the NTR. A state record was considered misclassified if it matched the NTR and was coded as non-AI/AN or missing race data. Effect of misclassification was evaluated by comparing prelinkage and postlinkage, age-adjusted hospital discharge rates. Researchers used Link Plus 2.0 software (Atlanta, GA, USA) for linkages and SAS 9.4 (Cary, NC, USA) for statistical analyses. In Oregon, 55.4 percent of matching records were misclassified (66.5 percent miscoded white, and 22.1 percent were missing race information). In Washington, 44.9 percent of matching records were misclassified (61.8 percent miscoded white, and 32.7 percent were missing race information). Linkage increased ascertainment of AI/AN hospitalizations by 31.8 percent in Oregon and 33.9 percent in Washington. Linkage increased the rate ratio (RR) for AI/AN hospitalizations in comparison to non-Hispanic whites (NHW) from 0.81 to 1.07 in Oregon, and from 1.21 to 1.62 in Washington. Correction of race in hospital discharge datasets through linkage with a reference file of known AI/AN individuals is an important first step before analytic research on AI/AN health care in the Pacific Northwest can be accomplished with administrative datasets.

Stroke in American Indians and Alaska Natives: A Systematic Review.

We conducted a systematic review of published studies on stroke epidemiology in American Indians and Alaska Natives (AI/ANs). We used MeSH terms and strict inclusion criteria to search PubMed, identifying a relevant sample of 57 refereed publications. We report a consensus view in which prevalent stroke is more common, and estimates of cerebrovascular risk factors are higher, among AI/ANs than among other US populations. Like other minority groups, AI/ANs suffer stroke at younger ages than do non-Hispanic Whites. However, data on AI/AN stroke mortality are significantly compromised by racial misclassification and nonrepresentative sampling. Studies correcting for these problems have found that stroke mortality rates among AI/ANs are among the highest of all US racial and ethnic groups. As with Black and non-Hispanic White stroke mortality, AI/AN stroke mortality varies by geographic region, with the highest rates in Alaska and the Northwest and the lowest in the Southwest. Our results underscore the need for a concerted national effort to collect accurate cross-sectional and longitudinal data on stroke in AI/ANs.

Uncovering a missing demographic in trauma registries: epidemiology of trauma among American Indians and Alaska Natives in Washington State

BackgroundThe objectives of this study were to evaluate racial misclassification in a statewide trauma registry and to describe the epidemiology of trauma among the Washington American Indian and Alaska Native...

Disparities in life expectancy of pacific northwest American Indians and Alaska natives: analysis of linkage-corrected life tables.

American Indians and Alaska Natives (AI/ANs) experience a high burden of mortality and other disparities compared with the general population. Life tables are an important population health indicator; however, federal agencies have not produced life tables for AI/ANs, largely due to racial misclassification on death certificates. Our objective was to correct this misclassification and create life tables for AI/ANs who resided in the Pacific Northwest region of the U.S., making comparisons with the general population. To correct racial misclassification, we conducted probabilistic record linkages between death certificates from three Northwest states-Idaho, Oregon, and Washington State-issued during 2008-2010, and AI/AN patient registration records. We calculated mortality rates and generated period life tables for AI/ANs and non-Hispanic white (NHW) Americans. Overall life expectancy at birth for Northwest AI/ANs was 72.8 years, which was 6.9 years lower than that of NHW Americans. Male AI/ANs had a lower life expectancy (70.9 years) than female AI/ANs (74.6 years). The disparity in life expectancy between AI/ANs and their NHW counterparts was higher for females (with AI/ANs living 7.3 years fewer than NHW females) than for males (with AI/ANs living 6.7 years fewer than NHW males). The greatest disparity in mortality rates was seen among young adults. Data linkage with a registry of known AI/ANs allowed us to generate accurate life tables that had not previously been available for this population and revealed disparities in both life expectancy at birth and survival across the life span. These results represent an important tool to help AI/AN communities as they monitor their health and promote efforts to eliminate health disparities.

Abstract B55: Cervical cancer incidence and mortality disparities among American Indians and Alaska Natives, 1999-2009

Abstract Objectives. Previous studies have reported higher rates of cervical cancer incidence and mortality in American Indian and Alaska Native (AI/AN) women compared to women of other races. However, race misclassification hampers accurate determinations of rates among AI/AN women. Observed disparities in incidence rates of cervical cancer between AI/AN and white populations increased after efforts were made to ensure that members of AI/AN populations were properly identified, which increased the number of AI/AN cases and corresponding rates. The purpose of this analysis is to describe the incidence and mortality of cervical cancer among AI/AN women from 1999-2009, using techniques to minimize the effect of race misclassification in surveillance data, and to compare rates of cervical cancer among these women to rates among white women living in the same areas. Methods. Data on cervical cancer deaths and incidence were linked with Indian Health Service records in order to improve identification of AI/AN populations. Analyses focused on deaths of AI/AN residents in IHS Contract Health Service Delivery Area (CHSDA) counties in 35 states. Linked data were used to produce age-adjusted incidence and death rates for 1999 to 2009. Data for both white and AI/AN populations were limited to non-Hispanics only. Results: Mortality. AI/AN women had a cervical cancer death rate of 3.3 per 100,000, which was higher than the rate of 2.2 for white women (RR 1.54). For CHSDA areas only, the death rate from cervical cancer for AI/AN women was 4.2 per 100,000, which was nearly twice the corresponding rate among white women in CHSDA areas (rate 2.0 per 100,000; RR 2.11). Cervical cancer mortality among AI/AN women in CHSDA areas was highest in the Northern Plains region and correspondingly higher than white women in Northern Plains (RR 4.15), Southern Plains (RR 1.58), and the Southwest (RR 2.05). Cervical cancer mortality in CHSDA areas declined during 1990-2009 among both AI/AN women and white women. Major declines for AI/AN women occurred primarily during 1990-1993 (APC -25.8, p&amp;lt;0.05); but death rates remained relatively steady from 1993-2009 (APC -1.3). Declines among white women were more level, and statistically significant (APC -2.4 for 1990-2009) Results: Incidence. AI/AN women had an incidence rate of cervical cancer of 8.7 per 100,000, compared to a rate of 7.5 for white women. However, when limiting to CHSDA areas, the rate for AI/AN women was 11.0 per 100,000, which was higher than for white women in CHSDA areas (rate 7.1 per 100,000). Cervical cancer incidence among AI/AN women in CHSDA areas was highest in the Southern Plains region (rate 15.1 per 100,000) and was higher than incidence for White women in Northern Plains (RR 1.97), Alaska (RR 1.94), Southern Plains (RR 1.64), Southwest (RR 1.19), and Pacific Coast (RR 1.36). Conclusions. Our results demonstrate that AI/AN women suffer disproportionately from cervical cancer incidence and mortality, compared to white women in the same areas. However, both incidence and mortality have decreased over time, documenting improvements in identifying and treating cervical cancer and precancerous lesions. Most cervical cancers can be avoided or diagnosed early through screening and treatment. We noted steep declines in cervical cancer deaths among AI/AN women in the early 1990's. We believe that these are likely due to screening and treatment programs aimed specifically at AI/AN women. However, our data also underscore the need for further efforts as noted in CHSDA areas, where identification of AI/AN women is likely to be highest, because AI/AN women still die from cervical cancer at twice the rate of white women. Citation Format: Meg Watson, Vicki Benard, Cheryll Thomas, Annie Brayboy, Roberta Paisano, Thomas Becker. Cervical cancer incidence and mortality disparities among American Indians and Alaska Natives, 1999-2009. [abstract]. In: Proceedings of the Sixth AACR Conference: The Science of Cancer Health Disparities; Dec 6–9, 2013; Atlanta, GA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2014;23(11 Suppl):Abstract nr B55. doi:10.1158/1538-7755.DISP13-B55

American Indian and Alaska Native infant and pediatric mortality, United States, 1999-2009.

We described American Indian/Alaska Native (AI/AN) infant and pediatric death rates and leading causes of death. We adjusted National Vital Statistics System mortality data for AI/AN racial misclassification by linkage with Indian Health Service (IHS) registration records. We determined average annual death rates and leading causes of death for 1999 to 2009 for AI/AN versus White infants and children. We limited the analysis to IHS Contract Health Service Delivery Area counties. The AI/AN infant death rate was 914 (rate ratio [RR] = 1.61; 95% confidence interval [CI] = 1.55, 1.67). Sudden infant death syndrome, unintentional injuries, and influenza or pneumonia were more common in AI/AN versus White infants. The overall AI/AN pediatric death rates were 69.6 for ages 1 to 4 years (RR = 2.56; 95% CI = 2.38, 2.75), 28.9 for ages 5 to 9 years (RR = 2.12; 95% CI = 1.92, 2.34), 37.3 for ages 10 to 14 years (RR = 2.22; 95% CI = 2.04, 2.40), and 158.4 for ages 15 to 19 years (RR = 2.71; 95% CI = 2.60, 2.82). Unintentional injuries and suicide occurred at higher rates among AI/AN youths versus White youths. Death rates for AI/AN infants and children were higher than for Whites, with regional disparities. Several leading causes of death in the AI/AN pediatric population are potentially preventable.

Linkages to improve mortality data for American Indians and Alaska Natives: a new model for death reporting?

Racial misclassification is a well-documented weakness of mortality data taken from death certificates. As a result, mortality statistics for American Indians and Alaska Natives (AI/ANs) present, at best, an inaccurate and misleading assessment of mortality in this population. Studies evaluating the quality of race/ethnicity reporting on death certificates have linked data from death certificates to other data sources collected when the decedent was still alive (e.g., Census, Current Population Survey). Such studies have shown substantial misclassification of AI/AN decedents. Despite limitations, linking mortality data from death certificates with data from other sources collected when decedents were living provides opportunities to evaluate and correct misclassification of populations such as AI/AN persons and facilitates the calculation and presentation of more accurate mortality statistics.

Breast Cancer Mortality Among American Indian and Alaska Native Women, 1990–2009

We compared breast cancer death rates and mortality trends among American Indian/Alaska Native (AI/AN) and White women using data for which racial misclassification was minimized. We used breast cancer deaths and cases linked to Indian Health Service (IHS) data to calculate age-adjusted rates and 95% confidence intervals (CIs) by IHS-designated regions from 1990 to 2009 for AI/AN and White women; Hispanics were excluded. Mortality-to-incidence ratios (MIR) were calculated for 1999 to 2009 as a proxy for prognosis after diagnosis. Overall, the breast cancer death rate was lower in AI/AN women (21.6 per 100,000) than in White women (26.5). However, rates in AI/ANs were higher than rates in Whites for ages 40 to 49 years in the Alaska region, and ages 65 years and older in the Southern Plains region. White death rates significantly decreased (annual percent change [APC] = -2.1; 95% CI = -2.3, -2.0), but regional and overall AI/AN rates were unchanged (APC = 0.9; 95% CI = 0.1, 1.7). AI/AN women had higher MIRs than White women. There has been no improvement in death rates among AI/AN women. Targeted screening and timely, high-quality treatment are needed to reduce mortality from breast cancer in AI/AN women.

Racial misclassification of American Indians and Alaska Natives by Indian Health Service Contract Health Service Delivery Area.

We evaluated the racial misclassification of American Indians and Alaska Natives (AI/ANs) in cancer incidence and all-cause mortality data by Indian Health Service (IHS) Contract Health Service Delivery Area (CHSDA). We evaluated data from 3 sources: IHS-National Vital Statistics System (NVSS), IHS-National Program of Cancer Registries (NPCR)/Surveillance, Epidemiology and End Results (SEER) program, and National Longitudinal Mortality Study (NLMS). We calculated, within each data source, the sensitivity and classification ratios by sex, IHS region, and urban-rural classification by CHSDA county. Sensitivity was significantly greater in CHSDA counties (IHS-NVSS: 83.6%; IHS-NPCR/SEER: 77.6%; NLMS: 68.8%) than non-CHSDA counties (IHS-NVSS: 54.8%; IHS-NPCR/SEER: 39.0%; NLMS: 28.3%). Classification ratios indicated less misclassification in CHSDA counties (IHS-NVSS: 1.20%; IHS-NPCR/SEER: 1.29%; NLMS: 1.18%) than non-CHSDA counties (IHS-NVSS: 1.82%; IHS-NPCR/SEER: 2.56%; NLMS: 1.81%). Race misclassification was less in rural counties and in regions with the greatest concentrations of AI/AN persons (Alaska, Southwest, and Northern Plains). Limiting presentation and analysis to CHSDA counties helped mitigate the effects of race misclassification of AI/AN persons, although a portion of the population was excluded.

Lung Cancer Deaths Among American Indians and Alaska Natives, 1990–2009

We examined regional differences in lung cancer among American Indians/Alaska Natives (AI/ANs) using linked data sets to minimize racial misclassification. On the basis of federal lung cancer incidence data for 1999 to 2009 and deaths for 1990 to 2009 linked with Indian Health Service (IHS) registration records, we calculated age-adjusted incidence and death rates for non-Hispanic AI/AN and White persons by IHS region, focusing on Contract Health Service Delivery Area (CHSDA) counties. We correlated death rates with cigarette smoking prevalence and calculated mortality-to-incidence ratios. Lung cancer death rates among AI/AN persons in CHSDA counties varied across IHS regions, from 94.0 per 100,000 in the Northern Plains to 15.2 in the Southwest, reflecting the strong correlation between smoking and lung cancer. For every 100 lung cancers diagnosed, there were 6 more deaths among AI/AN persons than among White persons. Lung cancer death rates began to decline in 1997 among AI/AN men and are still increasing among AI/AN women. Comparison of regional lung cancer death rates between AI/AN and White populations indicates disparities in tobacco control and prevention interventions. Efforts should be made to ensure that AI/AN persons receive equal benefit from current and emerging lung cancer prevention and control interventions.

Methods for improving the quality and completeness of mortality data for American Indians and Alaska Natives.

We describe methods used to mitigate the effect of race misclassification in mortality records and the data sets used to improve mortality estimates for American Indians and Alaska Natives (AI/ANs). We linked US National Death Index (NDI) records with Indian Health Service (IHS) registration records to identify AI/AN deaths misclassified as non-AI/AN deaths. Analyses excluded decedents of Hispanic origin and focused on Contract Health Service Delivery Area (CHSDA) counties. We compared death rates for AI/AN persons and Whites across 6 US regions. IHS registration records merged to 176,137 NDI records. Misclassification of AI/AN race in mortality data ranged from 6.3% in the Southwest to 35.6% in the Southern Plains. From 1999 to 2009, the all-cause death rate in CHSDA counties for AI/AN persons varied by geographic region and was 46% greater than that for Whites. Analyses for CHSDA counties resulted in higher death rates for AI/AN persons than in all counties combined. Improving race classification among AI/AN decedents strengthens AI/AN mortality data, and analyzing deaths by geographic region can aid in planning, implementation, and evaluation of efforts to reduce health disparities in this population.

Leading causes of death and all-cause mortality in American Indians and Alaska Natives.

We present regional patterns and trends in all-cause mortality and leading causes of death in American Indians and Alaska Natives (AI/ANs). US National Death Index records were linked with Indian Health Service (IHS) registration records to identify AI/AN deaths misclassified as non-AI/AN. We analyzed temporal trends for 1990 to 2009 and comparisons between non-Hispanic AI/AN and non-Hispanic White persons by geographic region for 1999 to 2009. Results focus on IHS Contract Health Service Delivery Area counties in which less race misclassification occurs. From 1990 to 2009 AI/AN persons did not experience the significant decreases in all-cause mortality seen for Whites. For 1999 to 2009 the all-cause death rate in CHSDA counties for AI/AN persons was 46% more than that for Whites. Death rates for AI/AN persons varied as much as 50% among regions. Except for heart disease and cancer, subsequent ranking of specific causes of death differed considerably between AI/AN and White persons. AI/AN populations continue to experience much higher death rates than Whites. Patterns of mortality are strongly influenced by the high incidence of diabetes, smoking prevalence, problem drinking, and social determinants. Much of the observed excess mortality can be addressed through known public health interventions.