Mizuno, Yuko; Zhu, Julia; Crepaz, Nicole; Beer, Linda; Purcell, David W.; Johnson, Christopher H.; Valverde, Eduardo E.; Skarbinski, Jacek
More than 1.1 million persons are living with HIV (PLWH) in the United States . Although many PLWH reduce risk behaviors after learning that they are infected , some continue to engage in risky behavior at some point after their diagnosis [3,4]. Maintaining safer behaviors over a lifetime can be challenging. Providing prevention interventions that reduce the risk of HIV transmission or acquisition of other sexually transmitted diseases (STDs), in addition to HIV treatment and care for improving the health of PLWH are critical components of the US National HIV/AIDS Strategy (NHAS) .
Meta-analyses [3,6] show that behavioral interventions for PLWH significantly reduce sexual risk behaviors. Research trials have shown evidence that brief one-on-one HIV risk-reduction interventions delivered by providers/clinicians during clinical care visits can reduce sexual risk behaviors of HIV-positive patients [7,8]. Evidence-based recommendations and clinical guidelines [9,10] emphasize that healthcare providers in clinic settings should offer prevention counseling during routine clinic visits to all PLWH regarding how they can protect themselves or their partners from getting HIV and other STDs. However, little is known regarding what percentage of PLWH who receive care in the United States have been exposed to HIV prevention counseling and whether prevention counseling is reaching PLWH who need it.
The primary objective of this article is to estimate prevalence of exposure to individual-level HIV/STD prevention counseling provided by healthcare workers, individual-level HIV/STD prevention counseling provided by prevention program workers, and small group HIV/STD risk-reduction interventions. These are the types of behavioral risk-reduction interventions that are more commonly implemented in clinical and nonclinical settings. The second objective is to describe the characteristics of the PLWH who received each of the risk-reduction interventions. We were particularly interested in determining whether HIV-infected persons who had fewer socioeconomic resources and engaged in high-risk sexual and drug using behavior were more or less likely to receive these interventions. These findings can provide information on the reach of HIV/STD risk-reduction interventions among PLWH receiving medical care in the United States and whether these behavioral interventions are appropriately targeted.
The Medical Monitoring Project (MMP) is a supplemental HIV surveillance system designed to produce nationally representative estimates of behavioral and clinical characteristics of HIV-infected adults receiving medical care in the United States [11–13]. MMP is a complex-sample, cross-sectional survey. For the 2009 data collection cycle, first 17 US states and territories were sampled from the 50 US states, Washington DC, and Puerto Rico based on probability proportional to size, then facilities providing HIV care, and finally adult persons aged 18 years or older receiving at least one medical care visit in participating facilities between January and April 2009. Data were collected via face-to-face interviews and medical record abstractions from June 2009 to May 2010. All sampled states and territories participated in MMP: California (including the separately funded jurisdictions of Los Angeles County and San Francisco), Delaware, Florida, Georgia, Illinois (including Chicago), Indiana, Michigan, Mississippi, New Jersey, New York (including New York City), North Carolina, Oregon, Pennsylvania (including Philadelphia), Puerto Rico, Texas (including Houston), Virginia, and Washington. Of 603 sampled facilities within these states or territories, 461 participated in MMP (facility response rate 76%), and of 9338 sampled persons, 4217 completed both an interview and a linked medical record abstraction (adjusted patient-level response rate 51%). Data were weighted based on known probabilities of selection at state or territory, facility, and patient levels. In addition, data were weighted to adjust for nonresponse using predictors of patient-level response including facility size, race/ethnicity, time since HIV diagnosis, and age group via linkage with the local HIV surveillance system.
Many of the variables of interest had a 12-month recall period (see below) and behaviors reported by those diagnosed less than 12 months ago could represent the behaviors that they had engaged in before they knew they had HIV. For the present analysis, we excluded persons who were diagnosed less than 12 months ago because we were interested in evaluating participants’ experience only after HIV diagnosis. We also excluded persons whose data were flagged as questionable by the interviewers because they were high on drugs or too sick to answer questions appropriately. Thus, this analysis includes information on 4092 participants. After weighting for probability of selection and nonresponse, these 4092 participants are estimated to represent the population of 409 283 HIV-infected adults diagnosed for at least 1 year who received medical care in the United States between January and April 2009.
MMP was determined to be a nonresearch activity in accordance with CDC's Guidelines for Defining Public Health Research and Public Health Non-Research. However, some participating states or territories and facilities obtained local Institutional Review Board (IRB) approval to conduct MMP when required locally.
We assessed exposure to three types of HIV/STD risk-reduction interventions in the past 12 months with the following questions: During the past 12 months, have you had a one-on-one conversation with a doctor, nurse, or other healthcare worker about ways to protect yourself or your partners from getting HIV or other STDs?; During the past 12 months, not including when you may have been tested for HIV, have you had a one-on-one conversation with an outreach worker, counselor, or prevention program worker about ways to protect yourself or your partners from getting HIV or other STDs?; During the past 12 months, have you participated in an organized session involving a small group of people to discuss ways to protect yourself or your partners from getting HIV or other STDs? These questions were asked consecutively in the interviews. We also created an overall measure of intervention exposure indicating exposure to any of the three types of HIV/STD risk-reduction interventions in the past 12 months.
We assessed the sociodemographic variables of age in years (18–24, 25–34, 35–44, 45–54, 55 or more), gender (men, women, transgender), race/ethnicity (non-Hispanic white, non-Hispanic black, Hispanic, other), education (less than high school, high school, more than high school), and household income (less than $20 000, 20 000–39 999, 40 000 or more). We also examined whether, in the past 12 months, a participant had been homeless, incarcerated, had health insurance, and was born in the United States. Number of years since HIV diagnosis was dichotomized into less than 5 years vs. 5 years or more.
Participants also reported whether they had engaged in behaviors in the past 12 months such as drinking before or during sex; using noninjection drugs before or during sex; using stimulant drugs such as crack, cocaine, or methamphetamine; and having any unprotected vaginal and/or anal sex with HIV-negative or unknown status partners. The participants were also categorized into four sexual risk groups based on self-reported sexual behavior in the past year or self-identified sexual orientation: MSM (men who reported sex with at least one man or men who self-identified as gay or bisexual), MSW only (men who reported sex with women only or men who self-identified as heterosexual), WSM (women who reported sex with at least one man or women who self-identified as heterosexual or bisexual), and other (people who were not categorized into any of the above). Information about self-identified sexual orientation was used for participants who did not report being sexually active in the past 12 months.
We also included three health status measures. Self-reported diagnosis of an STD indicates whether participants’ healthcare providers had told them they had syphilis, gonorrhea, chlamydia, herpes, genital warts, or any other STD in the past 12 months. Depression was measured using the Patient Health Questionnaire (PHQ-8), which consists of eight of the nine criteria on which the Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV) diagnosis of depressive disorders is based . Information about HIV viral load suppression (most recent viral load test documented as undetectable or ≤200 copies/ml) was obtained from participants’ medical records and was dichotomized into suppressed viral load vs. not suppressed viral load.
We conducted descriptive analyses by examining the frequency and weighted frequency of each selected correlate and outcome variable. We also conducted bivariate analyses to assess associations between the selected correlates with each outcome variable. Unadjusted prevalence ratios and 95% confidence intervals were calculated for bivariate analyses.
We conducted four separate multivariable logistic regression models to examine the associations between outcome variables and correlates. All variables with P value ≤0.05 from the bivariate test result were included in the multivariable model after testing for multicollinearity. Adjusted prevalence ratios (APRs) and 95% confidence intervals were calculated using the full model in multiple regression analyses. All estimates incorporated MMP sample weights to account for probability of selection and nonresponse and appropriately specified the subpopulation analyzed to the software. Variance estimation used Taylor series linearization to account for the complex sample design. All analyses were conducted using SAS System for Windows (release 9.2; SAS Institute Inc., Cary, North Carolina, USA) and SAS-Callable SUDAAN (release 10.0; Research Triangle Institute, Research Triangle Park, North Carolina, USA).
Table 1 describes the demographic and risk behavior characteristics of participants in the sample. A majority were between ages 35 and 54 (66%), men (71%), and racial/ethnic minorities (65%). Almost two-thirds (65%) had an annual income less than $20 000. Thirteen percent reported having unprotected sex with HIV-negative or unknown status partners and 11% reported using stimulant drugs. Almost half (47%) were MSM, and about a quarter each were MSW only (24%) and WSM (27%). Approximately 13% self-reported an STD diagnosis in the past 12 months, and a little less than three-quarters (72%) had most recent viral load documented in the medical record to be suppressed.
Table 1-a Demographi...Image Tools
Exposure to HIV/sexually transmitted disease risk-reduction interventions
Forty-four percent, an estimated 179 172 HIV-infected persons who were diagnosed for at least 1 year and received medical care in the United States, reported they had a one-on-one conversation with a healthcare provider about HIV/STD prevention. Thirty percent, an estimated 121 624 persons, reported they had such a conversation with a prevention program worker, and 16%, an estimated 65 881 persons, reported they had participated in a small group intervention in the past 12 months (Table 2). Overall, 52%, an estimated 211 820 persons, reported exposure to any of the three types of HIV/STD risk-reduction interventions. Among persons who self-reported unprotected sex with an HIV-negative or unknown status partner, only 61% received any risk-reduction interventions (Table 3). Among persons who self-reported an STD diagnosis in the 12 months prior to interview, only 63% received any risk-reduction interventions.
Correlates of exposure to HIV/sexually transmitted disease risk-reduction interventions
Table 3 shows bivariate and multivariable correlates of exposure to each type of HIV/STD risk-reduction intervention. Among the significant bivariate correlates of exposure to one-on-one conversations with a healthcare provider about HIV/STD prevention, multivariable analysis showed that younger age (except for 45–54), racial/ethnic minority status, lower education (< high school vs. >high school), lower annual income (<$20 000 vs. ≥$40 000), homelessness, diagnosed with HIV less than 5 years, unprotected sex with an HIV-negative or unknown status partner, and self-reported STD diagnosis remained significantly associated with exposure to prevention counseling by healthcare providers.
For exposure to one-on-one conversations with a prevention program worker about HIV/STD prevention, younger age, racial/ethnic minority status, lower income, homelessness, diagnosed with HIV less than 5 years, unprotected sex with an HIV-negative or unknown status partner, and self-reported STD diagnosis remained significant correlates in multivariable analysis. For participation in a small group intervention to discuss HIV/STD prevention, racial/ethnic minority status, lower income (<$20 000 vs. ≥$40 000), at least 5 years post-HIV diagnosis, stimulant drug use, unprotected sex with an HIV-negative or unknown status partner, and self-reported STD diagnosis remained significant correlates in multivariable analysis. Finally, younger age, racial/ethnic minority status, lower education, lower income (<$20 000 vs. ≥$40 000), homelessness, diagnosed with HIV less than 5 years, noninjection drug use before or during sex, unprotected sex with an HIV-negative or unknown status partner, and self-reported STD diagnosis were significantly associated with exposure to any of the three types of HIV/STD risk-reduction interventions in multivariable analysis.
For all the outcomes, MSM status was significantly associated with less exposure to HIV/STD risk-reduction interventions in bivariate analysis, but the association was no longer significant in multivariable analysis. Additional analyses (results not shown in Table 3) found that MSM status did not significantly predict intervention receipt when we adjusted for race and income in the multivariable models.
We found that less than half of our clinic-based sample reported receiving individual-level HIV/STD prevention counseling from healthcare providers, even though evidence-based guidelines [9,10] recommend providing risk-reduction counseling to all HIV-infected patients during their routine clinic visits. Exposure to individual-level prevention counseling from prevention program workers and to small group interventions was even lower. Exposure to any of the three types of interventions was reported by just more than half of HIV-infected adults receiving medical care in the United States. These figures are indicative of missed prevention opportunities and room for improvement in providing prevention counseling in the clinical setting.
Several barriers may limit the provision of prevention counseling. Time and resource constrains are significant barriers to implementing risk screening and risk-reduction prevention interventions, particularly in clinic settings [15–18]. Our estimate using weighted MMP data shows approximately 180 000 of HIV-infected persons in care received one-on-one prevention counseling from providers. This estimate could indicate the amount of provider time that has been used for prevention counseling. The estimate also suggests that additional resources (i.e. counseling for an additional 230 000 patients per year) are needed to provide services in accordance with recommended guidelines.
Other barriers to counseling include providers’ beliefs that behavioral change among HIV-infected patients is unlikely , or that they lack skills or feel uncomfortable in discussing risk behaviors with their patients [15,18,20]. However, training on brief risk screening methods that do not require much of providers’ time and on brief risk-reduction interventions can enhance comfort, skills, and motivation of providers [20–22]. Recently, Myers et al.  demonstrated that training for providers increased the delivery of prevention counseling, and suggested strategies that could be employed in clinic settings such as clinician training on behavioral prevention, establishment of formal written guidelines for delivering behavioral interventions, and development of peer support among clinicians. Implementing these strategies might increase the percentage of patients who receive risk-reduction counseling from their providers.
We found that people who had fewer resources and those who engaged in risk behaviors were more likely to receive HIV/STD risk-reduction interventions. Across the three types of HIV/STD risk-reduction interventions, minority race/ethnicity, low income, risky sexual behavior, and self-reported STD diagnosis consistently predicted intervention exposure. However, their levels of intervention exposure were not sufficiently high. For example, only half of those who had unprotected sex with an HIV-negative or unknown status partner reported receiving one-on-one prevention counseling from healthcare providers. Close to 40% of persons who had risky sexual behavior and 40% of those who self-reported an STD in the past year received no risk-reduction intervention of any kind, indicating substantial room for improvement in delivering interventions to those who need it the most.
One common multivariable correlate of intervention exposure that is worth noting is years since HIV diagnosis. Unlike other common multivariate correlates that we examined, the pattern of association was different for individual-level vs. small group interventions. Compared to those who had been diagnosed with HIV for 5 or more years, people who were more recently diagnosed with HIV were more likely to be exposed to individual-level interventions and less likely to participate in small group interventions. This finding suggests that individual and group-level interventions may reach different segments of the HIV-infected population. People who have been diagnosed with HIV longer may prefer a group format in which they may be more comfortable to meet, share stories with, and seek support from their peers to cope with HIV infection, whereas people who are more recently diagnosed with HIV may prefer to work on a one-on-one basis with healthcare providers or prevention program workers to address individual prevention needs as they learn to integrate their diagnosis into their lives.
We found significant bivariate associations indicating that MSM were less likely to receive HIV/STD risk-reduction interventions compared with non-MSM. This pattern is concerning because it suggests that MSM, the subgroup most affected by HIV in the United States, may be underutilizing HIV/STD risk-reduction interventions. These bivariate associations, however, were not significant when race and income were considered in multivariable analysis. This pattern suggests that the significant bivariate association between MSM status and lower exposure to interventions could be due to the fact that those identified as MSM were more likely to be white and of higher income (confirmed in additional analyses, results not shown), which are characteristics found to be associated with less exposure to risk-reduction interventions. It is possible that white and wealthier MSM may not be identified by healthcare workers or prevention program workers as being in need of prevention counseling. They may also be more likely than other MSM to receive care at facilities where those interventions may not be readily available (e.g. private practices).
Limitations of this analysis are as follows. First, the analysis focused only on HIV-infected persons receiving medical care who had been diagnosed for at least 1 year, and thus does not reflect the experiences of HIV-infected persons who are not receiving care or persons who are more recently diagnosed with HIV. As MMP recruits participants only from care facilities, it is reasonable to assume that the estimated proportions of all HIV-infected and diagnosed persons receiving prevention counseling are expected to be lower. Second, the combined response rate (which combined facility-level and patient-level response rates) is moderate and, thus, the estimates are subject to nonresponse bias. However, extensive nonresponse analysis was conducted using demographic and clinical information of respondents and nonrespondents via linkage with the local HIV surveillance system. Adjustments were made to reduce nonresponse bias of the MMP data as part of the process of developing analysis weights. Third, data are cross-sectional, and thus no causality could be established. Fourth, except for viral load data obtained from medical records, data are self-reported responses to interviewer-administered data collection and, thus, are subject to social desirability and recall biases. Related to this issue, providers and patients may have different perceptions of risk-reduction interventions. Thus, it is possible that providers might have delivered risk-reduction counseling, but patients might not perceive receiving such counseling. Similarly, some PLWH may not always be aware of the specific profession (e.g., healthcare providers vs. prevention program worker) of the person delivering counseling and the distinction between the two types of one-on-one counseling. Moreover, the measures of intervention exposure do not capture elements such as counseling frequency, content, intensity, and quality, nor do they capture exposure to other types of interventions such as structural level interventions.
Individual and small-group interventions for people living with HIV are recommended as an important component of comprehensive HIV care and treatment . Our analysis of a nationally representative sample of HIV-infected persons in HIV clinical care showed that those who had fewer resources or those who engaged in risk behaviors were more likely to receive HIV/STD risk-reduction interventions. However, levels of intervention exposure, particularly for individual-level prevention counseling delivered by healthcare providers, are low, given the fact that all of the participants in the sample are clinic patients and, thus, presumably should have had an opportunity to receive provider counseling. Those who engage in high-risk transmission behaviors may need to be prioritized for receipt of interventions with a goal to reach as close to 100% as possible. Because the MMP survey is conducted annually, CDC will monitor progress toward this goal to ensure that the delivery of risk-reduction interventions is maximized to achieve high impact prevention.
Y.M. conceptualized, interpreted the data, and wrote the article. J.Z. and C.J. provided statistical and data analysis support. L.B., E.V., and J.S. were involved in the conception, design, and implementation of Medical Monitoring Project (MMP). All authors contributed to data interpretation, article writing and/or review, and editing.
The authors would like to thank the participating MMP patients, facilities, and Provider and Community Advisory Board members. They also acknowledge the contributions of the MMP 2009 study group members (http://http://www.cdc.gov/hiv/pdf/research_mmp_studygroupmembers_2009.pdf).
The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the U.S. Centers for Disease Control and Prevention. Funding for the MMP is provided by a cooperative agreement (PS09–937) from the Centers for Disease Control and Prevention.
Conflicts of interest
There are no conflicts of interest.
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