Frequency of Human Immunodeficiency Virus (HIV) Testing in Urban vs. Rural Areas of the United States

Results From a Nationally-representative Sample

Michael E Ohl; Eli Perencevich

Disclosures

BMC Public Health. 2011;11(681) 

In This Article

Discussion

In this nationally-representative, population-based study of HIV testing frequencies in the United States, we found that the frequency of self-reported HIV testing decreased substantially as the residential environment became progressively more rural. After adjusting for differences in demographics and self-reported HIV risk factors, the odds of HIV testing in the past year were 35% lower among persons living in the most remote rural areas compared to persons in the most urban areas. Rural persons with a prior HIV test were more likely than urban to report testing in a hospital, but less likely in the outpatient setting.

A prior study in the early years of the HIV epidemic in the US also found that rural persons were less likely than urban to report HIV testing.[6] Our results demonstrate that this gap in testing persists in the modern era of effective HIV therapy, when early diagnosis and linkage to care are even more essential. Moreover, recent efforts to increase testing have not impacted the rural-urban gap in testing. Although rural persons with HIV experience barriers to care, prior studies have described effective models for delivering high-quality HIV care in rural settings.[12–18] This accentuates the importance of early testing and diagnosis among rural persons with HIV.

The observation of lower HIV testing rates in rural areas is consistent with published evidence that rural persons are, on average, diagnosed with HIV at a later stage of infection than urban persons.[4] Persons diagnosed at a later stage of HIV infection experience worse outcomes than persons diagnosed early and may unknowingly transmit infection to others.[19,20] Thus, there is pressing need for efforts to promote increased HIV testing and earlier diagnosis in rural areas.

Lower rates of HIV testing in rural areas may result from decreased access to settings where testing occurs, including both healthcare delivery sites and community-based HIV counseling and testing programs. In addition, rural healthcare providers may have less experience in HIV medicine and be less likely to recommend testing.[12] Stigma surrounding HIV infection may make rural persons less likely to seek testing.[15] Such stigma is intensified in rural areas due to a perceived lack of anonymity and fear that privacy will be lost when seeking testing.[21,22]

What is the optimal frequency of HIV testing in rural populations in the US? Until recently, the US has pursued a risk-based approach to HIV testing. Prior to 2006, the CDC recommended HIV testing for persons with identified risk factors, including persons with history of intravenous drug use or sexually transmitted infections, men who have sex with men, persons who have exchanged sex for money or drugs, or their sex partners.[23] Under this approach, HIV testing rates would naturally be lower in rural areas, where fewer persons report HIV risk factors. However, using 2005 data when risk-based testing policies were in place, we found that even after adjusting for differences in self-reported HIV risk factors and demographics, rural persons were substantially less likely to report HIV testing than urban persons.

In 2006 the CDC revised its policies and recommended routine, voluntary HIV testing in the healthcare setting for all persons between ages 13 and 64.[24] This change in policy reflected growing recognition that risk-based HIV testing strategies were inadequate. Despite prior risk-based testing policies, nearly half of persons with newly-diagnosed HIV infection were recognized late in their course and met criteria for Acquired Immune Deficiency Syndrome (AIDS)-an advanced stage of immune compromise-within a year of HIV diagnosis.[25] Many had missed opportunities for HIV testing and earlier diagnosis during prior healthcare encounters, in part due to lack of perceived risk for HIV infection or reluctance to disclose HIV risk factors to providers.[5,25] Routine testing seeks to remove stigma associated with identifying persons with HIV risk factors for testing, which may particularly increase testing among persons who are at risk for infection but who do not report risk factors. The overall goal of routine testing in healthcare settings is to increase the frequency of HIV testing in the overall US population, thus increasing the likelihood that persons in early stages of HIV infection undergo testing and preventing late diagnosis.

The rate of HIV testing did not change substantively in either urban or rural areas between 2005 and 2009, when routine testing policies had been in place for several years. In fact, the frequency of past-year testing declined slightly in rural areas. This indicates that the routine testing recommendation did not meaningfully impact the tendency toward less HIV testing in rural areas. Regardless of whether one views our results from a risk-based or population-based testing perspective, there is a substantial gap in HIV testing rates between urban and rural areas.

The relevance of CDC's routine testing policy to rural areas is unclear. Although modeling indicates that routine testing is cost-effective, with estimates generally less than $70,000 per Quality-adjusted life year (QALY) gained compared to prior testing policies, cost-effectiveness worsens as the prevalence of undiagnosed HIV infection in the local population decreases.[26] Prevalence of undiagnosed HIV infection is generally unknown in rural areas of the US, but is probably often significantly less than 0.1%. This mitigates the public health impact of routine HIV-testing in rural healthcare settings.

On the other hand, cost-effectiveness of routine testing improves as the background rate of HIV testing in the community decreases, leading to HIV diagnosis at a later stage of infection for many persons.[26] It is important to note that cost-effectiveness of routine HIV testing may be favorable in rural areas with low background rates of HIV testing and correspondingly high rates of late HIV diagnosis, even when local prevalence of undiagnosed HIV infection is low. To address this possibility, future studies should use HIV surveillance data, which are now geocoded in many states, and published mathematical models to explore the cost-effectiveness of routine HIV testing across a range of rural healthcare settings.

This study has several limitations. BRFSS relied on self-report of HIV testing and risk factors. Respondents may have had inaccurate awareness or recall of prior HIV testing. Stigma related to HIV infection may have made respondents reluctant to disclose information regarding HIV risk factors in a telephone survey. Disclosure of HIV risk factors is also incomplete during healthcare encounters and revised testing guidelines now emphasize population-based instead of risk-based HIV testing.[5] We therefore believe that the population-based HIV testing frequencies reported here are relevant, even if adjustment for HIV risk-factors was imperfect.

CDC recommendations call for routine HIV testing in the healthcare setting for persons age 13–64, but BRFSS did not include persons under age 18. BRFSS also did not include persons who were homeless, incarcerated, in the military, or in long-term care facilities. These are important populations when considering HIV testing policies.

BRFSS employs random-digit-dialing of land-based telephones. An increasing segment of the US population uses cell phones only, and this population is younger and displays differing health behavior patterns than land-line users.[7] Future studies of HIV testing frequencies would benefit from strategies to sample younger populations at increased risk for HIV infection, such as use of cell-phone and internet-based survey techniques.[7] Finally, this was a cross-sectional analysis. A cohort study analyzing time to HIV testing among rural and urban persons (survival analysis) may provide better estimates of testing discrepancies and avoid biases due to migration and loss to follow up.

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