Racial Misclassification of American Indians in Oklahoma State Surveillance Data for Sexually Transmitted Diseases

Abstract

The burden of sexually transmitted diseases (STDs) is high in American Indian/Alaska Native (AI/AN) populations. In addition, race is often misclassified in surveillance data. This study examined potential racial misclassification of American Indians in STD surveillance data in Oklahoma. Oklahoma State STD surveillance data for 1995 were matched with the Oklahoma State Indian Health Service Patient Registry to determine the number of AI/AN women who had one of three STDs but were not listed in Oklahoma surveillance data as AI/AN. Accounting for racial misclassification increased the rate of chlamydia for AI/AN women in Oklahoma by 32% (342/100,000 vs. 452/100,000) in the overall population. For gonorrhea, the rate increased by 57% (94/100,000 vs. 148/100,000) and for syphilis by 27% (15/100,000 vs. 19/100,000). Misclassified AI/AN women most often were classified as "White," and the likelihood of misclassification increased with a lower percentage of AI/AN ancestry. These findings indicate that STD rates may be underestimated for AI/AN populations nationwide. Racial misclassification in state surveillance data causes inaccuracies in characterizing the burden of infectious diseases in minorities.

Sexually Transmitted Diseases among American Indians in Arizona: An Important Public Health Disparity

“…8,9 In Arizona, some AIs with syphilis who reside in tribal regions bordering Mexico have been misclassified as Hispanic, possibly as a result of surnames that are of Hispanic origin. Of those of known race diagnosed at an IHS center and not coded as AI, 60% were coded as Hispanic.…”

“…6,7 In addition, several studies have raised a concern about racial misclassification of AIs in multiple disease-surveillance databases, including those for STDs and HIV. 8,9 These studies suggest that rates in AI populations are frequently underestimated. An examination of the Oklahoma state STD surveillance system, for example, found that accounting for racial misclassification increased chlamydia rates by 32%, gonorrhea rates by 57%, and syphilis rates by 27%.…”

“…An examination of the Oklahoma state STD surveillance system, for example, found that accounting for racial misclassification increased chlamydia rates by 32%, gonorrhea rates by 57%, and syphilis rates by 27%. 8 A second study looking at HIV/ AIDS reporting systems in five states and one urban health center from 1984 to 2002 found that the percentages of AIs being misclassified as non-AI ranged from nearly 4% to 55%. 9 The southwestern region of the U.S. has the largest population of AIs by region and has experienced particularly high STD rates.…”

Trends in Clinical Diagnoses of Rocky Mountain Spotted Fever among American Indians, 2001–2008

“…Furthermore, race for American Indians is highly misclassified in national mortality and morbidity data, and studies have shown that rates for several public health outcomes have been underestimated in American Indian populations because of racial misclassification on medical records, in documents, and in data registering systems. [19][20][21][22] In the present study, the incidence and trend of RMSF among American Indians during 2001-2008 are analyzed and described.…”

Epidemiology of Ehrlichiosis and Anaplasmosis among American Indians in the United States, 2000–2007

“…55,56 Furthermore, studies have shown that misclassification of race and ethnicity in national surveillance data is a significant issue, particularly for minority groups such as AIs, whereas only members of federally recognized tribes are included in IHS data. [57][58][59][60] In particular, one study of race using NETSS data has shown that because of access to care issues and the requirement for cases classified as confirmed or probable ehrlichiosis and anaplasmosis to have accompanying laboratory evidence, cases among whites are more likely to be reported or confirmed than other race groups; thus cases for AIs are likely being underreported via NETSS and CRF systems because of racial misclassification and lack of confirmatory testing. 61 Other limitations of the IHS data include that the population denominator used to calculate the incidence is the number of AI/AN persons who are eligible to use and have recently used the IHS health care system and may not include all AI/AN persons who seek medical consultation.…”