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  • 标题:Racial Misclassification of American Indians and Alaska Natives by Indian Health Service Contract Health Service Delivery Area
  • 本地全文:下载
  • 作者:Melissa A. Jim ; Elizabeth Arias ; Dean S. Seneca
  • 期刊名称:American journal of public health
  • 印刷版ISSN:0090-0036
  • 出版年度:2014
  • 卷号:104
  • 期号:Suppl 3
  • 页码:S295-S302
  • DOI:10.2105/AJPH.2014.301933
  • 语种:English
  • 出版社:American Public Health Association
  • 摘要:Objectives. 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). Methods. 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. Results. 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). Conclusions. 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. Accurate determinations of disease and mortality are a critical first step toward addressing disease burden and health disparities. American Indian/Alaska Native (AI/AN) populations experience some of the greatest health disparities in the country compared with other racial and ethnic groups. 1–3 Health and mortality status assessments for AI/AN populations are often hindered by a lack of complete and accurate data on race and ethnicity in surveillance and vital statistics systems. AI/AN populations are more likely to be misclassified as another race than other racial groups in cancer registries, resulting in underestimates of cancer incidence. 4–10 Similarly, misclassification of AI/AN race is a common problem on death certificates, 11–18 on which ascertainment of race is usually provided by a funeral director. As a result, mortality estimates for the AI/AN population in the United States have been significantly underestimated. 13 A study of racial/ethnic misclassification on US death certificates, which compared self-identified race from the US Census Bureau’s Current Population Survey (CPS) to the race recorded on death certificates for a sample of decedents in the National Longitudinal Mortality Study (NLMS) database, found markedly higher race misclassification of AI/AN persons (30%) compared with persons of other races that varied substantially by degree of geographic co-ethnic concentration. 13 For example, AI/AN decedents who died in counties with high concentrations of AI/AN populations were significantly more likely to be classified correctly on death certificates than those who died outside of these counties. 13 Similarly, a study comparing the National Cancer Institute’s (NCI) Surveillance, Epidemiology, and End Results (SEER) Program with NLMS found that SEER data considerably underreported AI/AN persons. 19 A project matching Indian Health Service (IHS) patient registration records with the National Death Index (NDI) records of persons who died from 1986 to 1988 showed that the percentage of inconsistent classifications of AI/AN race varied from 1.2% in the Navajo IHS Area to 30.4% in the California IHS Area. 20 The IHS provides primary health care to approximately 2.2 million enrolled members of federally recognized tribes, a number equivalent to approximately 64% of the United States estimated 3.4 million AI/AN population. 21,22 Health care services for AI/AN individuals are provided in more than 670 IHS and tribal health care facilities, mostly in rural and isolated areas. 23 Eligible AI/AN persons can receive health care at any IHS facility, but complex rules govern and restrict the delivery of contract health services for specialty medical care that is not available at IHS facilities. 24 One eligibility requirement for contract health services is residence within the Contract Health Service Delivery Area (CHSDA) of the tribe in which the patient is enrolled. The geographic composition of the CHSDAs follows county boundaries and is established for each federally recognized tribe by the IHS. 25 Details of the IHS regions (Northern Plains, Alaska, Southern Plains, Pacific Coast, East, and Southwest) and CHSDA areas are provided elsewhere 26 and shown in Figure A (available as a supplement to the online version of this article at http://www.ajph.org ). Record linkages with IHS patient enrollment data are 1 method for addressing misclassification of AI/AN race in central cancer registries and in vital statistics mortality data; such linkages have been found to be both timely and cost effective. 8,26–29 An additional method to reduce the impact of race misclassification that has been used in cancer and mortality reporting is that of restricting analysis to CHSDA counties. 26,28,30–32 The proportion of AI/AN persons in the total population is higher in CHSDA counties than in non-CHSDA counties, and previous studies have shown lower levels of racial misclassification for AI/AN persons in CHSDA counties. 13,33 The rationale for this approach is that there is likely to be more awareness of AI/AN race in theses counties. 13 Our objective was to evaluate racial misclassification in both cancer registry incidence and all-cause mortality databases and to present evidence for using CHSDAs in future reports to address race misclassification of AI/AN individuals. To investigate this, we used data from the IHS linkages with mortality and cancer registries, with confirmation from an IHS-independent linkage in the form of the NLMS.
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