Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2020 Oct 13.
Published in final edited form as: J Psychiatr Res. 2018 Aug 3;105:1–8. doi: 10.1016/j.jpsychires.2018.08.007

Prevalence and correlates of HIV testing and HIV-positive status in the US: Results from the National Epidemiological Survey on Alcohol and Related Conditions III (NESARC-III)

Carlos Blanco 1, Melanie M Wall 2, Wilson M Compton 1, Shoshana Kahana 1, Tianshu Feng 2, Tulshi Saha 3, Jennifer C Elliott 2,4, H Irene Hall 5, Bridget F Grant 3
PMCID: PMC7551804  NIHMSID: NIHMS1634360  PMID: 30118996

Abstract

We used the 2012–2013 National Epidemiologic Survey on Alcohol and Related Conditions III (NESARC-III), a nationally representative sample of US adults (n=34,653), to estimate the prevalence and correlates of HIV testing and HIV status. The diagnostic interview used was the Alcohol Use Disorder and Associated Disabilities Interview Schedule-DSM-5 Version. We found that in 2012–2013, the prevalence of a history of HIV testing was 53.0% among females and 47.0% among males. Among individuals tested, the prevalence of HIV was 1.06%, resulting in a known estimated prevalence of 0.54% in the full sample. In adjusted results, being non-white, aged 30–44, having college, being non-heterosexual, having history of unprotected sex or history of childhood sexual abuse and lower mental health-related quality of life increased the odds of having been tested, whereas being foreign-born, 45 years or older, family income ≥$20,000, being unemployed or a student, living in a rural setting and older age at first sex lowered those odds. Among those tested, being 30–64, being non-heterosexual, having history of unprotected sex or having a sexually transmitted disease in the last year was associated with greater odds of being HIV+. Having some college decreased those odds. In the adjusted results all psychiatric disorders were associated with increased rates of HIV testing, but only a lifetime history of drug use disorder and antisocial personality disorders were associated with HIV status among those tested. Despite CDC recommendations, only about half of US adults have ever been tested for HIV, interfering with efforts to eradicate HIV infection.

Keywords: HIV, NESARC-III, psychiatric disorders, comorbidity, CDC recommendations

National goals for the United States (Office of National AIDS Policy, 2015) and the new NIH HIV research priorities (National Institutes of Health, 2015) call for renewed efforts to reduce incidence of HIV infections, increase access to HIV testing and timely entry, linkage and retention in care, and decrease HIV-related disparities and health inequities. The 90-90-90 target outlined by the United Nations proposes that by 2020, 90% of all people living with HIV will know their HIV status, 90% of all people with diagnosed HIV infection will receive sustained antiretroviral therapy, and that 90% of all people receiving antiretroviral therapy will have viral suppression (UNAIDS, 2014). HIV testing is the entry point for many preventive and treatment services, including pre-exposure prophylaxis (PrEP) and ART (antiretroviral therapy) treatment, and a substantial body of literature has shown different “seek and test” strategies may be needed for various populations (McNulty and Schneider, 2018). Data has shown that though the percentage of persons with a late HIV diagnosis in the US decreased, even in areas with intensified HIV testing interventions, about 1 in 5 persons had advanced disease at the time of HIV diagnosis (Hall et al., 2016). In addition, given the current opioid epidemic and the increased number of individuals who are injecting substances, and thus at risk for acquiring and transmitting HIV, active and continued efforts toward promoting HIV testing and prevention efforts is paramount (Burnett et al., 2018; Peters et al., 2016).

The Centers for Disease Control and Prevention (CDC) recommends that individuals aged 13–64 years in the general population get tested at least once in their lifetimes, with more frequent testing for high-risk groups (Branson et al., 2006). However, little is known about the extent to which these guidelines are implemented on a national basis in the US. HIV testing behavior is often studied in special populations, rather than general population samples. For example, some studies that collect national HIV testing data are drawn from populations of particular age and status, such as school-based sample in the case of the National Youth Risk Behavior Survey (Van Handel et al., 2016), or are drawn from samples at elevated HIV risk, such as gay and bisexual men, individuals who inject drugs, or heterosexuals at increased risk for HIV, as done by the CDC’s National HIV Behavioral Surveillance (Centers for Disease Control and Prevention, 2017a). Other sources of national data, such as the National Health Interview Survey (Murray and Oraka, 2014) lack diagnostic information on important correlates of HIV risk, such as substance use disorders and other psychiatric disorders. To date, only one national study has examined the association between HIV serostatus and psychiatric disorders (Lopes et al., 2012), but that study did not examine sociodemographic or psychiatric correlates of HIV testing. Previous national studies have estimated that the prevalence of having ever been tested for HIV is approximately 42%, whereas the prevalence of HIV positive status is around 0.3% (Centers for Disease Control and Prevention, 2017a; Lopes et al., 2012; National Center for Health Statistics, 2016).

The current study was designed to address these gaps in knowledge by analyzing data from a recent large, nationally representative sample of US adults. Specifically, we sought to estimate the prevalence and sociodemographic and psychiatric correlates of HIV testing, and the prevalence and correlates of HIV status among those tested.

Methods

Sample

The National Epidemiological Survey on Alcohol and Related Conditions III (NESARC-III) is a nationally representative in-person interview study of 36,309 adults age 18 and older residing in households and selected group quarters. Data collection occurred in 2012–2013. As detailed elsewhere (Grant et al., 2014), probability sampling was used to select respondents. Primary sampling units were counties or groups of contiguous counties, secondary sampling units (SSU) comprised groups of Census-defined blocks, and tertiary sampling units were households within SSUs. Eligible adults within sampled households were randomly selected. Hispanic, Black, and Asian individuals were oversampled. The screener- and person-level response rates were 72.0% and 84.0%, yielding a total response rate of 60.1% (N=36,309), comparable to most current U.S. national surveys (Centers for Disease Control and Prevention, 2013; Substance Abuse and Mental Health Services Administration, 2014). Data were adjusted for oversampling and nonresponse, then weighted to represent the US civilian population based on the 2012 American Community Survey (Census, 2013). Weighting adjustments compensated adequately for nonresponse as detailed elsewhere (Grant et al., 2015a). The investigation was carried out in accordance with the latest version of the Declaration of Helsinki. Oral informed consent was recorded and respondents received $90.00 for participation. The interview lasted one hour on average. Protocols were approved by National Institutes of Health and Westat Institutional Review Boards.

Measures

The National Institute on Alcohol Abuse and Alcoholism (NIAAA) Alcohol Use Disorder and Associated Disabilities Interview Schedule-5 (AUDADIS-5) (Grant et al., 2011) was the assessment instrument used for NESARC-III. The AUDADIS-5 is a computer-assisted interview that assesses substance use and psychiatric disorders, psychosocial functioning, and selected medical conditions.

The primary outcomes for this study were whether participants had ever been tested for HIV, and whether they had received a diagnosis of HIV infection. Participants responded yes or no to the question: “Have you ever been tested for HIV, the virus that causes AIDS, or tested for AIDS?” Participants who answered positively to this question were asked, “Did you ever test positive for HIV or AIDS?”

Psychiatric disorders were assessed as defined by DSM-5 (American Psychiatric Association, 2013). Participants were assessed for alcohol use disorder, any drug use disorder, and tobacco use disorder; major depressive disorder, persistent depressive disorder (dysthymia), bipolar I disorder, and bipolar II disorder; panic disorder, agoraphobia, social anxiety disorder, specific phobia, and generalized anxiety disorder; posttraumatic stress disorder; and schizotypal, borderline, and antisocial personality disorders. Test-retest reliability of these binary AUDADIS-5 diagnoses ranges from fair to good (i.e., from kappa=0.39 for dysthymic disorder to kappa=0.87 for tobacco use disorder) (Grant et al., 2015), as does validity when compared to semi-structured clinical assessments (i.e., from kappa=0.22 for generalized anxiety disorder to kappa=0.68 for tobacco use disorder) (Hasin et al., 2015a; Hasin et al., 2015b); reliability and validity are generally higher when corresponding dimensional representations of the disorders are considered. Reliability of intra-class correlations [ICC] ranged from 0.59 to 0.85 (Grant et al., 2015). ICC for validity ranged from 0.19 for generalized anxiety disorder to 0.85 for alcohol use disorder (Hasin et al., 2015a; Hasin et al., 2015b).

Participants also reported on sociodemographic information, including sex, race/ethnicity, nativity, age, education, family income, employment status, marital status, urbanicity, and US region. They provided, by self-report, information on health insurance status, sexual orientation and same-sex sexual behavior, history of unprotected sex with someone outside a spouse or committed relationship, history of childhood sexual abuse, past 12-month condom use, history of sex with a man who had sex with male partners (for women), history of sexually transmitted disease, and age at first sexual encounter. Physical and mental health-related quality of life were measured using the Short Form 12, version 2 (SF-12v2), a reliable and valid measure of impairment commonly used in population-based surveys (Rubio et al., 2014; Rubio et al., 2013). Scores range from 0–100 (M=50; SD=10), with lower scores indicating poorer health-related quality of life.

Data Analysis

We conducted our analysis in two steps. In the first step, we computed weighted means and percentages for continuous and categorical sociodemographic and psychiatric correlates, stratified by whether the person had been tested for HIV or not. Odds ratios (ORs) and 95% confidence intervals were estimated for the association of each predictor with HIV testing using separate logistic regressions. In the second step, we followed similar procedures to estimate the sociodemographic and psychiatric correlates of HIV status among those tested. For all analyses, we present unadjusted ORs as well as ORs adjusted for sociodemographic characteristics. To account for the NESARC-III complex sample design, all analyses utilized strata, clusters, and weights in SAS 9.4 SurveyFreq and Surveylogistic.

Results

Sociodemographic and psychiatric correlates of HIV testing status

In 2012–2013, the prevalence of reporting a history of HIV testing was 50.4% across the whole population, 53.0% of females and 47.0% of males. In the unadjusted analyses, individuals were more likely to be tested if they were female and non-white, and less likely to be tested if they were foreign-born. Compared with individuals aged 18–29, those aged 30–44 were more likely to be tested, and those aged 45–64 and greater than 65 were less likely to be tested. Compared with those who completed less than high school, testing was higher among those who had completed at least some college. Individuals were less likely to be tested if their family income was at least $20,000, or if they were unemployed. When compared with those married or cohabitating, those who were widowed, separated, or divorced and who were never married were more likely to be tested. Those living in rural areas were less likely to be tested than those in urban areas, and those in the Midwest and West were less likely to be tested than those living in the Northeastern United States. Individuals without health insurance were more likely to have been tested (Table 1).

Table 1.

Associations of Sociodemographic and Health Characteristics with HIV Testing Status in the NESARC-III

Sociodemographic Characteristics HIV-Tested (N=20,098) % (SE) HIV- Not tested or Unknown (N=16,211) % (SE) Unadjusted OR (95% CI)/P valuea Adjusted ORa (95% CI)/P value
Total 50.4 (0.6) 49.6 (0.6) - -
Sex
 Male 47.0 (0.4) 49.2 (0.5) 1.0 (Reference) 1.0 (Reference)
 Female 53.0 (0.4) 50.8 (0.5) 1.1 (1.0–1.1) 0.8 (0.6–1.1)
Race-ethnicity
 White 61.2 (0.9) 71.3 (0.8) 1.0(Reference) 1.0(Reference)
 Non-White 38.8 (0.9) 28.7 (0.8) 1.6 (1.5–1.7) 1.6 (1.5–1.7)
Nativity
 US-born 85.1 (0.5) 83.0 (0.6) 1.0(Reference) 1.0(Reference)
 Foreign-born 14.9 (0.5) 17.0 (0.6) 0.9 (0.8–0.9) 0.7 (0.6–0.8)
Age, y
 18–29 23.1 (0.4) 20.3 (0.5) 1.0(Reference) 1.0(Reference)
 30–44 35.1 (0.5) 16.2 (0.4) 1.9 (1.8–2.0) 1.7 (1.6–1.9)
 45–64 34.2 (0.5) 35.9 (0.5) 0.8 (0.8–0.9) 0.8 (0.7–0.8)
 ≥65 7.7 (0.3) 27.6 (0.6) 0.2 (0.2–0.3) 0.3 (0.25–0.3)
Education
 Less than high school 12.3 (0.4) 13.7 (0.5) 1.0 (Reference) 1.0 (Reference)
 High school 24.1 (0.6) 27.5 (0.7) 1.0 (0.9–1.1) 1.0 (0.9–1.1)
 Some college or higher 63.7 (0.8) 58.7 (0.9) 1.2 (1.1–1.3) 1.3 (1.1–1.4)
Family income
 $0–19,999 23.8 (0.5) 21.8 (0.6) 1.0 (Reference) 1.0 (Reference)
 ≥$20,000 76.2 (0.5) 78.2 (0.6) 0.9 (0.8–1.0) 0.9 (0.8–1.0)
Employment status
 Employed 76.1 (0.6) 63.9 (0.7) 1.0 (Reference) 1.0 (Reference)
 Unemployed or student 23.9 (0.6) 36.1(0.7) 0.6 (0.5–0.6) 0.9 (0.8–1.0)
Marital status
 Married/cohabiting 55.3 (0.7) 60.4 (0.5) 1.0 (Reference) 1.0 (Reference)
 Widowed/separated/divorced 20.4 (0.4) 18.9 (0.4) 1.2 (1.1–1.3) 1.7 (1.6–1.8)
 Never married 24.3 (0.6) 20.7 (0.5) 1.3 (1.2–1.4) 1.1 (1.0–1.3)
Urbanicity
 Urban 81.3 (1.3) 76.2 (1.9) 1.0 (Reference) 1.0 (Reference)
 Rural 18.7 (1.3) 23.8 (1.9) 0.7 (0.7–0.8) 0.8 (0.8–0.9)
Region
 Northeast 19.1 (0.6) 17.4 (0.7) 1.0 (Reference) 1.0 (Reference)
 Midwest 19.1 (0.5) 23.9 (0.9) 0.7 (0.6–0.8) 0.7 (0.6–0.8)
 South 39.2 (1.1) 34.9 (1.0) 1.0 (0.9–1.1) 1.0 (0.8–1.1)
 West 22.6 (1.0) 23.8 (1.0) 0.9 (0.8–1.0) 0.8 (0.7–0.9)
Health insurance
 Health insurance 80.7 (0.5) 84.5 (0.5) 1.0 (Reference) 1.0 (Reference)
 No health insurance 19.3 (0.5) 15.5 (0.5) 1.3 (1.2–1.4) 0.9 (0.9–1.0)
Sexual orientation
 Heterosexual 95.3 (0.2) 98.1 (0.1) 1.0(Reference) 1.0(Reference)
 Non-heterosexual 4.7 (0.2) 1.9 (0.1) 2.5 (2.2–3.0) 2.1 (1.7–2.5)
Sexual orientation or same-sex behaviorb
 Heterosexual and never had same-sex behavior 91.4 (0.3) 95.8 (0.2) 1.0(Reference)
 Non-heterosexual or had same-sex behavior 8.6 (0.3) 4.2 (0.2) 2.1 (1.9–2.4)
History of unprotected sex
 Yes 27.7 (0.6) 14.2 (0.4) 2.3 (2.2–2.5) 1.7 (1.5–1.8)
 No 72.3 (0.6) 85.8 (0.4) 1.0 (Reference) 1.0 (Reference)
History of childhood sexual abuse
 Yes 7.7 (0.2) 3.8 (0.2) 2.1 (1.9–2.3) 1.3 (1.2–1.5)
 No 92.3 (0.2) 96.2 (0.2) 1.0 (Reference) 1.0 (Reference)
Condom use in last 12-month
 Fairly/Very often 18.6 (0.4) 11.0 (0.4) 1.0 (Reference) 1.0 (Reference)
 Never-sometimes 63.7 (0.6) 52.1 (0.6) 0.7 (0.7–0.8) 1.0 (0.9–1.1)
 Did not have sex 17.8 (0.4) 37.0 (0.6) 0.3 (0.3–0.3) 0.8 (0.7–0.9)
Sex with male that had sex with male partner*
 Yes 0.8 (0.1) 0.5 (0.1) 1.2(0.7–2.1) 0.9(0.5–1.5)
 Unknown/missing 20.5 (0.6) 44.6 (0.7) 0.3(0.3–0.3) 0.9(0.4–2.1)
 No sex 2.3 (0.2) 1.7 (0.2) 1.0(0.8–1.3) 0.7(0.5–1.0)
 No 76.3 (0.6) 53.3 (0.7) 1.0 (Reference) 1.0 (Reference)
Sexually transmitted disease in past year
 Yes 1.2 (0.1) 0.3(0.0) 4.1(3.0–5.8) 2.0(1.4–3.0)
 No 98.8(0.1) 99.7(0.0) 1.0 (Reference) 1.0 (Reference)
Age at first sex
 5–14 15.4 (0.4) 6.0 (0.3) 1.0(Reference) 1.0 (Reference)
 15–24 77.7 (0.4) 75.4 (0.5) 0.4 (0.4–0.4) 0.6 (0.5–0.6)
 25–34 2.4 (0.1) 5.8 (0.2) 0.2 (0.1–0.2) 0.3 (0.2–0.3)
 ≥35 0.2 (0.0) 0.4 (0.1) 0.2 (0.1–0.3) 0.3 (0.2–0.5)
 Never had sex 0.6 (0.1) 5.1(0.2) 0.0 (0.0–0.1) 0.1 (0.06–0.1)
 Unknown 3.8 (0.2) 7.4 (0.4) 0.2 (0.2–0.2) 0.4 (0.3–0.4)
Mean SF-12 physical 49.9 49.2 <.0001 <.0001
Mean SF-12 mental 49.8 51.9 <.0001 <.0001
Open in a new tab
a.

Mutually adjusted for sex, race-ethnicity, nativity, age, education, family income, employment status, marital status, urbanicity, region, sexual orientation, history of unprotected sex and history of childhood sexual abuse. b. AOR cannot reliably estimated for this variable due to high collinearity with the sexual orientation variable.

Non-heterosexual individuals, those with same-sex behavior, history of unprotected sex, or history of sexually transmitted disease or history of childhood sexual abuse reported greater likelihood of testing. Those who reported that they never or sometimes used condoms were less likely to be tested than those who used condoms fairly or very often. HIV testing was higher among individuals who first had sex at a younger age, and with higher scores on the physical summary score of the SF-12, lower scores on its mental summary scores. Women who reported having had sex with a man who had male partners were no more likely to have had an HIV test, though those who were unsure were less likely to be tested (Table 1). All psychiatric disorders were associated with increased HIV testing. The strongest associations were with antisocial personality disorder and drug use disorders, whereas the weakest were with specific phobia, generalized anxiety disorder and social anxiety disorder (Table 2). After mutually adjusting for all other sociodemographic characteristics, all results remained significant, except being female, having used a condom never/sometimes, being a woman who was unsure whether she had had sex with a male that had sex with a male, which were no longer significant, and not having health insurance, which decreased the odds of being tested.

Table 2.

Association of Psychiatric Disorders with HIV Testing Status in the NESARC-III

Psychiatric Disorder HIV-Tested (N=20,098) % (SE) HIV- Not tested or Uknown (N=16,211) % (SE) OR (95% CI)/P valuea Adjusted ORa (95% CI)/P value
Any substance use disorder 51.3(0.8) 34.8(0.6) 2.0(1.8–2.1) 1.9(1.7–2.0)
 Alcohol use disorder 35.8(0.7) 22.3(0.5) 1.9(1.8–2.1) 1.7(1.6–1.9)
 Any drug use disorder 13.9(0.4) 5.9(0.2) 2.6(2.4–2.8) 2.1(1.9–2.3)
 Tobacco use disorder 33.9(0.7) 21.7(0.5) 1.9(1.7–2.0) 1.9(1.8–2.1)
Any mood disorder 28.1(0.6) 19.6(0.4) 1.6(1.5–1.7) 1.4(1.3–1.5)
 Major depressive disorder 23.8(0.5) 17.3(0.4) 1.5(1.4–1.6) 1.3(1.2–1.4)
 Persistent depressive disorder (dysthymia) 6.6(0.3) 4.5(0.2) 1.5(1.3–1.6) 1.4(1.2–1.5)
 Bipolar I 2.9(0.2) 1.2(0.1) 2.4(2.0–3.0) 2.1(1.7–2.7)
 Bipolar II 0.5(0.1) 0.2(0.0) 2.1(1.3–3.1) 1.7(1.0–2.8)
Any anxiety disorder 19.2(0.5) 14.6(0.3) 1.4(1.3–1.5) 1.3(1.2–1.4)
 Panic 6.8(0.3) 3.6(0.2) 1.9(1.7–2.2) 1.6(1.4–1.9)
 Agoraphobia 2.4(0.2) 1.4(0.1) 1.8(1.4–2.2) 1.5(1.2–1.9)
 Social phobia 4.3(0.2) 3.1(0.2) 1.4(1.2–1.6) 1.3(1.1–1.5)
 Specific phobia 6.9(0.2) 5.9(0.2) 1.2(1.1–1.3) 1.2(1.0–1.3)
 Generalized anxiety disorder 8.9(0.3) 6.5(0.2) 1.4(1.3–1.6) 1.3(1.2–1.5)
Posttraumatic stress disorder 8.5(0.3) 3.7(0.2) 2.4(2.2–2.7) 2.1(1.8–2.3)
Any personality disorder 20.1(0.6) 10.4(0.4) 2.2(2.0–2.4) 1.9(1.8–2.1)
 Schizotypal 8.3(0.3) 4.3(0.2) 2.0(1.8–2.2) 1.7(1.5–1.9)
 Borderline 15.2(0.5) 7.5(0.3) 2.2(2.0–2.5) 1.9(1.7–2.2)
 Antisocial 6.3(0.3) 2.4(0.2) 2.8(2.4–3.2) 2.4(2.0–2.9)
Open in a new tab
a.

Mutually adjusted for sex, race-ethnicity, nativity, age, education, family income, employment status, marital status, urbanicity, region, sexual orientation, history of unprotected sex and history of childhood sexual abuse.

Sociodemographic and psychiatric correlates of HIV status

Among individuals tested, the prevalence of HIV+ status was 1.06%, resulting in a prevalence of known HIV diagnosis of 0.54% in the full sample (where those not tested cannot be diagnosed), equivalent to 1,251,134 HIV+ individuals in the US population. Among those tested, in the unadjusted analyses, HIV+ status was directly associated with being 45–64 years old compared to 18–29, being unemployed, having never been married or being widowed, separated or divorced, being non-heterosexual or having had same-sex behavior, having a history of unprotected sex, history of childhood sexual abuse, having had a sexually transmitted disease in the past year, and having lower scores on the physical and mental health component summaries of the SF-12 (i.e., indicating lower physical and mental health-related quality of life). Women reporting having sex with a male partner who had sex with male partners and those unsure were much more likely to have HIV than those saying they never did. Only 2.6% of HIV-positive women report knowing they had had sex with a man who had sex with men, and 44.1% were unsure. Being HIV-positive was inversely associated with high school or higher education, income of at least $20,000, never/sometimes using a condom in the last 12 months compared to using one more frequently, and being older than 14 years at first sex. In the adjusted analyses, age 30–44 was associated with HIV+ status, whereas having a high school education, a family income of ≥$20,000, being unemployed or a student, having never been married or being widowed, separated or divorced, having a history of childhood sexual abuse, being a woman who had sex with a male that had sex with male partner or being unsure about it, age at first sex, or a having a lower score on the SF-12 physical and mental component summaries were no longer associated with HIV status (Table 3).

Table 3.

Associations of Sociodemographic and Health Characteristics by HIV Diagnostic Status among Tested in the NESARC-III

Sociodemographic Characteristics HIV-Positive (N=235) % (SE) HIV- Not Positive (N=19,842) % (SE) OR (95% CI)/P valuea Adjusted ORa (95% CI)/P value
Total 1.1(0.1) 98.9(0.1) - -
Sex
 Male 51.9(4.6) 47.0(0.4) 1.0(Reference) 1.0(Reference)
 Female 48.1(4.6) 53.0(0.4) 0.8(0.6–1.2) 0.5(0.2–1.6)
Race-ethnicity
 White 58.5(4.5) 61.2(0.9) 1.0(Reference) 1.0(Reference)
 Non-White 41.5(4.5) 38.8(0.9) 1.1(0.8–1.6) 1.1(0.8–1.5)
Nativity
 US-born 87.2(2.5) 85.0(0.5) 1.0(Reference) 1.0(Reference)
 Foreign-born 12.8(2.5) 15.0(0.5) 0.8(0.5–1.3) 0.9(0.5–1.4)
Age, y
 18–29 15.3(3.1) 23.1(0.4) 1.0(Reference) 1.0(Reference)
 30–44 31.3(4.0) 35.1(0.5) 1.4(0.8–2.3) 2.0(1.1–3.6)
 45–64 45.5(4.1) 34.1(0.5) 2.0(1.2–3.3) 2.4(1.3–4.6)
 ≥65 7.9(1.9) 7.6(0.3) 1.6(0.8–3.2) 1.5(0.6–4.0)
Education
 Less than high school 20.5(3.4) 12.2(0.4) 1.0(Reference) 1.0(Reference)
 High school 24.5(3.8) 24.1(0.6) 0.6(0.4–1.0) 0.7(0.4–1.1)
 Some college or higher 55.0(4.8) 63.7(0.8) 0.5(0.3–0.8) 0.5(0.3–0.8)
Family income
 $0–19,999 32.5(4.0) 23.7(0.5) 1.0(Reference) 1.0(Reference)
 ≥20,000 67.5(4.0) 76.3(0.5) 0.6(0.5–0.9) 1.1(0.7–1.6)
Employment status
 Employed 65.3(3.4) 76.2(0.6) 1.0(Reference) 1.0(Reference)
 Unemployed or student 34.7(3.4) 23.8(0.6) 1.7(1.3–2.3) 1.2(0.8–1.8)
Marital status
 Married/cohabiting 43.3(4.5) 55.4(0.7) 1.0(Reference) 1.0(Reference)
 Widowed/separated/divorced 26.3(3.6) 20.4(0.4) 1.7(1.1–2.5) 0.9(0.5–1.6)
 Never married 30.4(3.4) 24.3(0.6) 1.6(1.1–2.3) 0.8(0.5–1.4)
Urbanicity
 Urban 85.7(4.5) 81.2(1.3) 1.0(Reference) 1.0(Reference)
 Rural 14.3(4.5) 18.8(1.3) 0.7(0.4–1.5) 0.8(0.4–1.6)
Region
 Northeast 18.3(3.8) 19.1(0.6) 1.0(Reference) 1.0(Reference)
 Midwest 18.3(4.6) 19.1(0.5) 1.0(0.5–2.1) 1.0(0.5–2.1)
 South 41.9(4.9) 39.2(1.1) 1.1(0.7–1.9) 1.1(0.6–1.9)
 West 21.6(4.0) 22.6(1.0) 1.0(0.5–1.8) 1.0(0.5–1.8)
Health insurance
 Health insurance 81.2(3.4) 80.7(0.5) 1.0(Reference) 1.0(Reference)
 No health insurance 18.8(3.4) 19.3(0.5) 1.0(0.6–1.5) 0.9(0.6–1.4)
Sexual orientation
 Heterosexual1 74.5(4.1) 95.5(0.2) 1.0(Reference) 1.0(Reference)
 Non-heterosexual 25.5(4.1) 4.5(0.2) 7.3(4.8–11.1) 6.9(4.2–11.5)
Sexual orientation or same-sex behaviorb
 Heterosexual and never had same-sex behavior 65.8(4.7) 91.7(0.2) 1.0(Reference)
 Non-heterosexual or had same-sex behavior 34.2(4.7) 8.3(0.2) 5.7(3.8–8.7)
History of unprotected sex
 Yes 40.9(4.8) 27.5(0.6) 1.8(1.2–2.7) 1.5(1.0–2.3)
 No 59.1(4.8) 72.5(0.6) 1.0(Reference) 1.0(Reference)
History of childhood sexual abuse
 Yes 13.0(2.4) 7.6(0.2) 1.8(1.2–2.8) 1.0(0.6–1.8)
 No 87.0(2.4) 92.4(0.2) 1.0(Reference) 1.0(Reference)
Condom use in last 12-month
 Fairly/Very often 24.8(3.0) 18.5(0.4) 1.0(Reference) 1.0(Reference)
 Never-sometimes 43.5(4.5) 63.9(0.6) 0.5(0.3–0.8) 0.5(0.3–0.8)
 Did not have sex 31.7(3.9) 17.6(0.4) 1.4(0.9–1.9) 0.7(0.3–1.5)
Sex with male that had sex with male partner
 Yes 2.6(1.6) 0.8(0.1) 5.0(1.5–17.3) 3.3(0.9–13.1)
 Unknown/missing 44.1(6.4) 20.3(0.6) 3.4(2.1–5.7) 2.2(0.7–7.1)
 No sex 4.8(2.0) 2.3(0.2) 3.3(1.3–8.1) 8.1(1.1–58.8)
 No 48.6(6.2) 76.6(0.6) 1.0(Reference) 1.0(Reference)
Sexually transmitted disease in past year
 Yes 4.3(1.6) 1.1(0.1) 3.9(1.8–8.4) 2.9(1.2–7.0)
 No 95.7(1.6) 98.9(0.1) 1.0(Reference) 1.0(Reference)
Age at first sex
 5–14 25.1(3.9) 15.3(0.4) 1.0(Reference) 1.0(Reference)
 15–24 65.7(4.0) 77.8(0.4) 0.5(0.3–0.8) 0.7(0.4–1.1)
 25–34 0.8(0.6) 2.4(0.1) 0.2(0.0–1.0) 0.2(0.0–1.2)
 ≥35 - 0.2(0.0) -
 Never had sex 3.4(1.7) 0.5(0.1) 3.8(1.2–11.9) 5.2(1.4–19.2)
 Unknown 5.0(1.7) 3.8(0.2) 0.8(0.4–1.7) 1.0(0.5–2.3)
Mean SF-12 physical 47.2 49.9 0.0112 0.7967
Mean SF-12 mental 46.5 49.9 0.0004 0.1035
Open in a new tab
a.

Mutually adjusted for sex, race-ethnicity, nativity, age, education, family income, employment status, marital status, urbanicity, region, sexual orientation, history of unprotected sex and history of childhood sexual abuse. b. AOR cannot reliably estimated for this variable due to high collinearity with the sexual orientation variable.

HIV positive status among those tested was directly associated with having a lifetime history of drug use disorder, tobacco use disorder, major depressive disorder, and borderline and antisocial personality disorders. After adjusting for sociodemographic characteristics, only having a drug use disorder or antisocial personality disorder remained associated with HIV status (Table 4).

Table 4.

Association of Psychiatric Disorders with HIV Status among tested in the NESARC-III

Psychiatric Disorder HIV-Positive (N=235) % (SE) HIV- Not Positive (N=19,842) % (SE) OR (95% CI)/P valuea Adjusted ORa (95% CI)/P value
Any substance use disorder 60.1(4.3) 51.2(0.8) 1.4(1.0–2.0) 1.2(0.9–1.7)
 Alcohol use disorder 35.9(4.2) 35.8(0.7) 1.0(0.7–1.4) 0.9(0.6–1.3)
 Any drug use disorder 23.9(4.1) 13.8(0.4) 2.0(1.2–3.1) 1.6(1.0–2.5)
 Tobacco use disorder 44.2(4.2) 33.8(0.7) 1.6(1.1–2.2) 1.3(0.9–1.8)
Any mood disorder 37.4(3.7) 28.0(0.6) 1.5(1.1–2.1) 1.3(0.9–1.8)
 Major depressive disorder 31.6(3.6) 23.8(0.5) 1.5(1.1–2.1) 1.3(0.9–1.8)
 Persistent depressive disorder (dysthymia) 10.1(3.1) 6.5(0.3) 1.6(0.8–3.1) 1.2(0.6–2.4)
 Bipolar I 2.4(1.0) 2.9(0.2) 0.8(0.3–1.9) 0.7(0.3–1.6)
 Bipolar II 0.1(0.1) 0.5(0.1) 0.2(0.0–1.3) 0.1(0.0–1.1)
Any anxiety disorder 24.9(3.6) 19.2(0.5) 1.4(1.0–2.0) 1.2(0.8–1.7)
 Panic 11.6(3.3) 6.7(0.3) 1.8(1.0–3.4) 1.4(0.7–2.7)
 Agoraphobia 3.2(1.3) 2.4(0.2) 1.3(0.6–3.1) 1.0(0.4–2.5)
 Social phobia 4.4(1.5) 4.3(0.2) 1.0(0.5–2.1) 0.8(0.4–1.7)
 Specific phobia 7.0(1.8) 6.9(0.2) 1.0(0.6–1.8) 0.9(0.5–1.5)
 Generalized anxiety disorder 10.2(2.4) 8.9(0.3) 1.2(0.7–1.9) 1.0(0.6–1.6)
Posttraumatic stress disorder 11.4(2.6) 8.5(0.3) 1.4(0.8–2.3) 1.1(0.6–1.9)
Any personality disorder 30.0(3.8) 20.0(0.6) 1.7(1.2–2.5) 1.3(0.9–2.0)
 Schizotypal 11.9(2.7) 8.3(0.3) 1.5(0.9–2.5) 1.1(0.6–1.8)
 Borderline 24.9(3.8) 15.2(0.5) 1.9(1.2–2.8) 1.4(0.9–2.3)
 Antisocial 13.2(3.5) 6.2(0.3) 2.3(1.3–4.2) 2.0(1.0–3.8)
Open in a new tab
a.

Mutually adjusted for sex, race-ethnicity, nativity, age, education, family income, employment status, marital status, urbanicity, region, sexual orientation, history of unprotected sex and history of childhood sexual abuse.

Discussion

This is the first national study to examine the association between psychiatric disorders and probability of lifetime HIV testing, and only the second to examine the association of psychiatric disorders and HIV status. We found that, despite current CDC recommendations that all adults have at least one HIV test in their lifetime, only about half of the US general population had ever been HIV tested. Our results confirm findings from prior studies in more selected populations (Centers for Disease Control and Prevention, 2013; Paz-Bailey et al., 2014) and are similar to those from previous national estimates (National Center for Health Statistics, 2016). The reasons for these low rates of testing across different samples and surveys are not fully understood and may be related to stigma about being tested or HIV infected, fear of receiving an HIV diagnosis, belief that one is not at risk, lack of awareness of CDC recommendations, or lack of means to carry out these recommendations (Evangeli et al., 2016; Thornton et al., 2012). They also may reflect provider behavior or systemic failures in implementing HIV testing among the general population (Burke et al., 2007; Zheng et al., 2014). Regardless of the reasons, our study suggests that new strategies may be needed to achieve the CDC goal of 100% testing and the national goal of eliminating HIV. By identifying groups with lower rates of testing, such as those with lower educational attainment or those who are unemployed, our study may allow for more targeted approaches to HIV testing. Because individuals unaware of their HIV status are estimated to contribute to a large proportion of infections, these targeted approaches appear crucial to end HIV transmission. Once identified, evidence-based interventions can be used to link them to and retain them in care (Centers for Disease Control and Prevention, 2015; Risher et al., 2017).

Our second finding was that 0.54% of respondents in the full sample were HIV-positive. This estimate is consistent with the prevalence (0.36%, 95% CI=0.27–0.48) estimated in the full sample of a previous national study using a similar design conducted by our group (Lopes et al., 2012). However, most prior national studies, including our previous study have not estimated the prevalence of HIV testing and thus were not able to delineate predictors of HIV testing from HIV diagnosis. Our results suggest that individuals at greater risk for HIV are also more likely to be tested, hence the prevalence among those untested is likely to be lower than among those tested, consistent with the models developed by CDC based on HIV reporting data (Hall et al., 2015). Future studies should consider testing all respondents, to provide more reliable estimates of HIV prevalence in the general population and to assess trends.

Consistent with previous reports (Sionean et al., 2014) HIV testing was associated with correlates of lower likelihood of stable romantic relationships and greater likelihood of higher risk sexual behavior, such as history of unprotected sex or having had a sexually transmitted disease in the year preceding the survey. Higher likelihood of HIV testing among women may be related to greater attention to their sexual health through their primary or gynecological care including prenatal testing (Green et al., 2012). Lower likelihood of testing among those without insurance highlight of the importance of expanding insurance as well as the role of free-of-charge testing facilities in addressing HIV. In line with prior reports of greater rates of testing among African Americans and Hispanics (Duran et al., 2008; Foundation, 2017), non-White had increased odds of having been tested. By contrast, individuals living in rural areas were less likely to have been tested, possibly reflecting more difficulty accessing testing facilities or concerns about stigma associated with HIV testing or diagnosis (Pellowski, 2013; Schafer et al., 2017). Existing disparities in health system infrastructure and funding highlight the need to adapt HIV treatment and preventive strategies to meet the challenges of each locality (Panagiotoglou et al., 2018). Increased testing among individuals with all psychiatric disorders may reflect greater access to services through utilization of mental or other healthcare services. Higher physical health-related quality of life and lower mental health-related quality of life were associated with greater likelihood of testing. However, the magnitude of those differences were small. Thus, they require replication to minimize the risk of prematurely overinterpreting them.

Also in line with previous studies (Beyrer and Abdool Karim, 2013; Fettig et al., 2014; Sullivan et al., 2014), being HIV-positive was associated with lower socioeconomic status, being non-married, being non-heterosexual, history of childhood sexual abuse and engaging in higher risk sexual behavior. By contrast with HIV testing, not all psychiatric disorders were associated with being HIV-positive. Rather, HIV was mostly associated with disorders characterized by impulsivity, consistent with the role that high-risk behaviors play in the acquisition of the virus (Shuper et al., 2014). Needle sharing and sexual behaviors often associated with drug use further contribute to the association with drug use disorders (Gilchrist et al., 2017). The stress associated with seroconversion, neurological effects of the HIV virus or HIV treatment also may trigger the onset of mental disorders, including MDD (Lopes et al., 2012). Identification of groups at increased risk for HIV can inform efforts to protect them against infection through the use of effective strategies, such as consistent use of pre-exposure prophylaxis (Riddell et al., 2018).

Although our findings confirm the need for integrated care for HIV and psychiatric disorders, recent reviews indicate that the model of integration may need to vary depending on the availability of resources (Chuah et al., 2017; Panagiotoglou et al., 2018; Risher et al., 2017). Provision of HIV and mental health services (including treatment for substance use disorders) in the same location helps decrease barriers to care, but require substantial financial and personnel resources. Integration of care using multiple facilities (e.g., in a larger healthcare system) or use of case managers may be more cost-effective, but present greater challenges regarding appropriate coordination to avoid fragmentation of care. Use of financial incentives and structural and pharmacy-based interventions can also help improve entry and retention in care (Risher et al., 2017).

This study has several limitations. First, information on HIV testing and status was based on self-report and was not independently verified by a physician or laboratory testing. Independent verification is not feasible for a large, nationally representative epidemiological study. Furthermore, respondents were queried about lifetime testing, rather than last year. However, rates of testing were similar to those reported in the National Health Interview Survey (Murray and Oraka, 2014). Second, the number of HIV-positive subjects in this sample is relatively small, due to the relatively low prevalence of HIV in the general population and the low rates of testing. To our knowledge, there are no larger epidemiological studies with information on psychiatric diagnoses and HIV status. Third, although the NESARC includes information on age of onset of psychiatric disorders, it does not include information regarding the time or location of HIV testing or of onset of HIV-positive status, preventing temporal sequencing of psychiatric disorder and HIV outcomes. Fourth, some individuals may have not revealed that they were tested or may have forgotten. Fifth, we did not attempt to model the prevalence of HIV among individuals who were not tested. However, the estimated number of HIV+ is close to the CDC estimates. This suggests that the percentage of HIV+ individuals among those untested is likely to be low, also consistent with CDC estimates. Sixth, estimates from the NESARC-III did not include some groups such as persons in prisons, hospitals, and those without stable housing who may be at high risk for HIV infection and psychiatric disorders. Seventh, the NESARC-III data were collected in 2012–2013. It is possible that the prevalence of HIV testing or HIV positive status may have changed since the time of the study.

In summary, despite CDC recommendations, only about half of US adults have ever been tested for HIV as of 2012–2013, making it difficult to accurately estimate the prevalence of HIV at the population level and interfering with efforts to eradicate HIV infection. Rates of testing are particularly low among heterosexual men, those with lower educational attainment and those in rural areas. Rates of HIV testing were elevated across all psychiatric disorders. However, among tested, HIV infection was mostly associated with disorders with high impulsivity. We hope that these findings can help in better targeting populations at risk for not being tested for HIV and to develop preventive interventions for individuals with psychiatric disorders associated with high risk behaviors.

Footnotes

Publisher's Disclaimer: Disclaimer: The views and opinions expressed in this report are those of the authors and should not be construed to represent the views of any of the sponsoring organizations or agencies or the US government.

References

  1. American Psychiatric Association, 2013. Diagnostic and statistical manual of mental disorders (Fifth ed). American Psychiatric Publishing, Arlington, VA. [Google Scholar]
  2. Beyrer C, Abdool Karim Q, 2013. The changing epidemiology of HIV in 2013. Curr Opin HIV AIDS 8(4), 306–310. [DOI] [PubMed] [Google Scholar]
  3. Branson BM, Handsfield HH, Lampe MA, Janssen RS, Taylor AW, Lyss SB, Clark JE, Centers for Disease, C., Prevention, 2006. Revised recommendations for HIV testing of adults, adolescents, and pregnant women in health-care settings. MMWR Recomm Rep 55(RR-14), 1–17; quiz CE11–14. [PubMed] [Google Scholar]
  4. Burke RC, Sepkowitz KA, Bernstein KT, Karpati AM, Myers JE, Tsoi BW, Begier EM, 2007. Why don’t physicians test for HIV? A review of the US literature. AIDS 21(12), 1617–1624. [DOI] [PubMed] [Google Scholar]
  5. Burnett JC, Broz D, Spiller MW, Wejnert C, Paz-Bailey G, 2018. HIV Infection and HIV-Associated Behaviors Among Persons Who Inject Drugs-20 Cities, United States, 2015. Mmwr-Morbid Mortal W 67(1), 23–28. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Census, B.o.t., 2013. American Community Survey, 2012. Suitland, MD. [Google Scholar]
  7. Centers for Disease Control and Prevention, 2013. Unweighted Response Rates for the NHANES 2011–2012. Centers for Disease Control and Prevention, Atlanta, GA. [Google Scholar]
  8. Centers for Disease Control and Prevention, 2015. Prevention Research Synthesis; Atlanta, GA. [Google Scholar]
  9. Centers for Disease Control and Prevention, 2017a. National HIV Behavioral Surveillance. Centers for Disease Control and Prevention, Atlanta, GA. [Google Scholar]
  10. Chuah FLH, Haldane VE, Cervero-Liceras F, Ong SE, Sigfrid LA, Murphy G, Watt N, Balabanova D, Hogarth S, Maimaris W, Otero L, Buse K, McKee M, Piot P, Perel P, Legido-Quigley H, 2017. Interventions and approaches to integrating HIV and mental health services: a systematic review. Health Policy Plan 32(suppl_4), iv27–iv47. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Duran D, Beltrami J, Stein R, Voetsch A, Branson B, 2008. Persons Tested for HIV-United States, 2006 (Reprinted from MMWR, vol 57, pg 845–849, 2008). Jama-J Am Med Assoc 300(17), 1990−+. [Google Scholar]
  12. Evangeli M, Pady K, Wroe AL, 2016. Which Psychological Factors are Related to HIV Testing? A Quantitative Systematic Review of Global Studies. Aids and Behavior 20(4), 880–918. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Fettig J, Swaminathan M, Murrill CS, Kaplan JE, 2014. Global Epidemiology of HIV. Infect Dis Clin N Am 28(3), 323−+. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Foundation, H.J.K.F., 2017. HIV testing in the United States. San Francisco, CA. [Google Scholar]
  15. Gilchrist G, Swan D, Widyaratna K, Marquez-Arrico JE, Hughes E, Mdege ND, Martyn-St James M, Tirado-Munoz J, 2017. A Systematic Review and Meta-analysis of Psychosocial Interventions to Reduce Drug and Sexual Blood Borne Virus Risk Behaviours Among People Who Inject Drugs. Aids and Behavior 21(7), 1791–1811. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Grant BF, Chu A, Sigman R, Ambary M, Kali J, Sugawara Y, Jiao R, Ren W, Goldstein R, 2014. Source and Accuracy Statement, in: (NESARC-III), N.E.S.o.A.a.R.C.-I. (Ed.). National Institute on Alcohol Abuse and Alcoholism, Rockville, MD. [Google Scholar]
  17. Grant BF, Goldstein RB, Chou SP, 2011. The Alcohol Use Disorder and Associated Disabilities Interview Schedule – Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition Version (AUDADIS-5). National Institute on Alcohol Abuse and Alcoholism, Rockville, MD. [Google Scholar]
  18. Grant BF, Goldstein RB, Saha TD, Chou SP, Jung J, Zhang HT, Pickering RP, Ruan WJ, Smith SM, Huang BJ, Hasin DS, 2015a. Epidemiology of DSM-5 Alcohol Use Disorder Results From the National Epidemiologic Survey on Alcohol and Related Conditions III. Jama Psychiat 72(8), 757–766. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Grant BF, Goldstein RB, Smith SM, Jung J, Zhang H, Chou SP, Pickering RP, Ruan WJ, Huang B, Saha TD, Aivadyan C, Greenstein E, Hasin DS, 2015. The Alcohol Use Disorder and Associated Disabilities Interview Schedule-5 (AUDADIS-5): reliability of substance use and psychiatric disorder modules in a general population sample. Drug Alcohol Depend 148, 27–33. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Green DR, Anderson BL, Burke MF, Griffith J, Schulkin J, 2012. Obstetric Providers’ Knowledge, Awareness, and Use of CDC’s HIV Testing Recommendations and One Test. Two Lives.(TM). Matern Child Hlth J 16(5), 1113–1119. [DOI] [PubMed] [Google Scholar]
  21. Hall HI, An Q, Tang T, Song RG, Chen M, Green T, Kang J, 2015. Prevalence of Diagnosed and Undiagnosed HIV Infection - United States, 2008–2012. Mmwr-Morbid Mortal W 64(24), 657–662. [PMC free article] [PubMed] [Google Scholar]
  22. Hall HI, Tang T, Espinoza L, 2016. Late Diagnosis of HIV Infection in Metropolitan Areas of the United States and Puerto Rico. Aids and Behavior 20(5), 967–972. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Hasin DS, Greenstein E, Aivadyan C, Stohl M, Aharonovich E, Saha T, Goldstein R, Nunes EV, Jung J, Zhang H, Grant BF, 2015a. The Alcohol Use Disorder and Associated Disabilities Interview Schedule-5 (AUDADIS-5): procedural validity of substance use disorders modules through clinical re-appraisal in a general population sample. Drug Alcohol Depend 148, 40–46. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Hasin DS, Shmulewitz D, Stohl M, Greenstein E, Aivadyan C, Morita K, Saha T, Aharonovich E, Jung J, Zhang H, Nunes EV, Grant BF, 2015b. Procedural validity of the AUDADIS-5 depression, anxiety and post-traumatic stress disorder modules: Substance abusers and others in the general population. Drug Alcohol Depend 152, 246–256. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Lopes M, Olfson M, Rabkin J, Hasin DS, Alegria AA, Lin KH, Grant BF, Blanco C, 2012. Gender, HIV status, and psychiatric disorders: results from the National Epidemiologic Survey on Alcohol and Related Conditions. J Clin Psychiatry 73(3), 384–391. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. McNulty MC, Schneider JA, 2018. Care continuum entry interventions: seek and test strategies to engage persons most impacted by HIV within the United States. Aids 32(4), 407–417. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Murray K, Oraka E, 2014. Racial and ethnic disparities in future testing intentions for HIV: United States, 2007–2010: results from the National Health Interview Survey. AIDS Behav 18(7), 1247–1255. [DOI] [PubMed] [Google Scholar]
  28. National Institutes of Health, 2015. NIH HIV/AIDS Research Priorities and Guidelines for Determining AIDS Funding. Bethesda, MD. [Google Scholar]
  29. Office of National AIDS Policy, 2015. National HIV/AIDS Strategy for the United States. Updated to 2020. Office of National AIDS Policy, Washington, DC. [Google Scholar]
  30. Panagiotoglou D, Olding M, Enns B, Feaster DJ, Del Rio C, Metsch LR, Granich RM, Strathdee SA, Marshall BDL, Golden MR, Shoptaw S, Schackman BR, Nosyk B, Localized HIVMSG, 2018. Building the Case for Localized Approaches to HIV: Structural Conditions and Health System Capacity to Address the HIV/AIDS Epidemic in Six US Cities. AIDS Behav. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Paz-Bailey G, Raymond HF, Lansky A, Mermin J, 2014. Using the National HIV Behavioral Surveillance System to inform HIV prevention efforts in the United States. AIDS Behav 18 Suppl 3, S233–236. [DOI] [PubMed] [Google Scholar]
  32. Pellowski JA, 2013. Barriers to care for rural people living with HIV: a review of domestic research and health care models. J Assoc Nurses AIDS Care 24(5), 422–437. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Peters PJ, Pontones P, Hoover KW, Patel MR, Galang RR, Shields J, Blosser SJ, Spiller MW, Combs B, Switzer WM, Conrad C, Gentry J, Khudyakov Y, Waterhouse D, Owen SM, Chapman E, Roseberry JC, McCants V, Weidle PJ, Broz D, Samandari T, Mermin J, Walthall J, Brooks JT, Duwve JM, Investigation IHO, 2016. HIV Infection Linked to Injection Use of Oxymorphone in Indiana, 2014–2015. New Engl J Med 375(3), 229–239. [DOI] [PubMed] [Google Scholar]
  34. Riddell J.t., Amico KR, Mayer KH, 2018. HIV Preexposure Prophylaxis: A Review. JAMA 319(12), 1261–1268. [DOI] [PubMed] [Google Scholar]
  35. Risher KA, Kapoor S, Daramola AM, Paz-Bailey G, Skarbinski J, Doyle K, Shearer K, Dowdy D, Rosenberg E, Sullivan P, Shah M, 2017. Challenges in the Evaluation of Interventions to Improve Engagement Along the HIV Care Continuum in the United States: A Systematic Review. AIDS Behav 21(7), 2101–2123. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Rubio JM, Olfson M, Perez-Fuentes G, Garcia-Toro M, Wang S, Blanco C, 2014. Effect of First Episode Axis I Disorders on Quality of Life. Journal of Nervous and Mental Disease 202(4), 271–274. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Rubio JM, Olfson M, Villegas L, Perez-Fuentes G, Wang S, Blanco C, 2013. Quality of life following remission of mental disorders: findings from the National Epidemiologic Survey on Alcohol and Related Conditions. J Clin Psychiatry 74(5), e445–450. [DOI] [PubMed] [Google Scholar]
  38. Schafer KR, Albrecht H, Dillingham R, Hogg RS, Jaworsky D, Kasper K, Loutfy M, MacKenzie LJ, McManus KA, Oursler KA, Rhodes SD, Samji H, Skinner S, Sun CJ, Weissman S, Ohl ME, 2017. The Continuum of HIV Care in Rural Communities in the United States and Canada: What Is Known and Future Research Directions. J Acquir Immune Defic Syndr 75(1), 35–44. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Shuper PA, Joharchi N, Rehm J, 2014. Personality as a predictor of unprotected sexual behavior among people living with HIV/AIDS: a systematic review. AIDS Behav 18(2), 398–410. [DOI] [PubMed] [Google Scholar]
  40. Sionean C, Le BC, Hageman K, Oster AM, Wejnert C, Hess KL, Paz-Bailey G, Grp NS, 2014. HIV Risk, Prevention, and Testing Behaviors Among Heterosexuals at Increased Risk for HIV Infection - National HIV Behavioral Surveillance System, 21 US Cities, 2010. Mmwr-Morbid Mortal W 63(14), 1–39. [PubMed] [Google Scholar]
  41. Statistics, N.C.f.H., 2016. National Health Interview Survey. Tables of Summary Health Statstics [Google Scholar]
  42. Substance Abuse and Mental Health Services Administration, 2014. Results from the 2013 National Survey on Drug Use and Health: Summary of National Findings, NSDUH Series H-48, HHS Publication No. (SMA) 14–4863 Substance Abuse and mental Health Services Administration, Rockville, MD. [Google Scholar]
  43. Sullivan PS, Jones JS, Baral SD, 2014. The global north: HIV epidemiology in high-income countries. Current Opinion in Hiv and Aids 9(2), 199–205. [DOI] [PubMed] [Google Scholar]
  44. Thornton AC, Delpech V, Kall MM, Nardone A, 2012. HIV testing in community settings in resource-rich countries: a systematic review of the evidence. HIV Med 13(7), 416–426. [DOI] [PubMed] [Google Scholar]
  45. UNAIDS, 2014. 90-90-90: an ambitious treatment target to help end the AIDS epidemic. [Google Scholar]
  46. Van Handel M, Kann L, Olsen EO, Dietz P, 2016. HIV Testing Among US High School Students and Young Adults. Pediatrics 137(2), e20152700. [DOI] [PubMed] [Google Scholar]
  47. Zheng MY, Suneja A, Chou AL, Arya M, 2014. Physician barriers to successful implementation of US Preventive Services Task Force routine HIV testing recommendations. J Int Assoc Provid AIDS Care 13(3), 200–205. [DOI] [PMC free article] [PubMed] [Google Scholar]

RESOURCES