Skip to main content
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2016 May 1.
Published in final edited form as: AIDS Behav. 2015 May;19(5):931–940. doi: 10.1007/s10461-014-0901-1

Longitudinal Trends in Sexual Behaviors with Advancing Age and Menopause Among Women With and Without HIV-1 Infection

Tonya N Taylor 1,2,, Jeremy Weedon 3, Elizabeth T Golub 4, Stephen E Karpiak 5,6, Monica Gandhi 7, Mardge H Cohen 8, Alexandra M Levine 9, Howard L Minkoff 10, Adebola A Adedimeji 11, Lakshmi Goparaju 12, Susan Holman 13, Tracey E Wilson 14
PMCID: PMC4370800  NIHMSID: NIHMS630511  PMID: 25245474

Abstract

We assessed changes in self-reported sexual activity (SA) over 13 years among HIV-infected and uninfected women. The impact of aging and menopause on SA and unprotected anal or vaginal intercourse (UAVI) was examined among women in the Women’s Interagency HIV Study (WIHS), stratifying by HIV status and detectable viral load among HIV-infected women. Generalized mixed linear models were fitted for each outcome, adjusted for relevant covariates. HIV-uninfected women evidenced higher levels of SA and UAVI than HIV-infected. The odds of SA declined by 62–64 % per decade of age. The odds of SA in a 6-month interval for women aged 40–57 declined by 18–22 % post-menopause (controlling for age). Among HIV+/detectable women only, the odds of any UAVI decreased by 17 % per decade of age; the odds of UAVI were unchanged pre-menopause, and then decreased by 28 % post-menopause. Elucidating the factors accounting for ongoing unprotected sex among older women should inform interventions.

Keywords: Sexual activity, Sexual risk behaviors, Aging, Menopause, Women’s Interagency HIV Study (WIHS)

Introduction

Although sexual activity (SA) continues into older ages among adults in the US [1, 2], there are gender-specific declines in SA with age, along with lower levels of condom use and lower levels of safer sex practice [35]. In one national survey, the prevalence of SA for both men and women declined with age, and at all ages women were less likely than men to report SA [1]. From a national probability sample of men and women ages 14–94, the prevalence of vaginal intercourse and condom use for both men and women declined with age [3, 6, 7]. A national survey of men and women over 50 years of age found that 14–17 % reported penile-vaginal intercourse (PVI), and only 20–25 % used condoms during their most recent PVI episode [4]. Another survey of adults ages 50 and older found that only 27 % had ever been tested for HIV; among those tested, 84 % said that their chances of acquiring HIV was “none” [8]. Finally, according to the Centers for Disease Control and Prevention (CDC), the diagnoses of HIV infection occurred at the following rates (per 100,000) in 2011 amongst older age groups: 17.5 (50–54 years of age); 11.4 (55–59 years of age); and 6.9 (60-years of age) [9].

Systematic studies of SA in older HIV-infected adults are sparse, although there is evidence that HIV-infected older adults engage in unprotected intercourse [1012]. For example, in the Research on Older Adults with HIV (ROAH) study, more than one-third of sexually active older adults with HIV reported engaging in unprotected anal or vaginal intercourse (UAVI), and 18 %reported unprotected sex with a serodiscordant partner [1315]. Identified risk factors for unprotected sex among older adults with HIV include low levels of knowledge about HIV transmission, recent substance use, sexual concurrency, partner characteristics (i.e., new, ongoing, casual), unstable housing, loneliness, high CD4 count, and poor psychological well being [1113, 1620]. Studies also suggest that safer sex practices among people with suppressed viral load decline since these individuals realize that the risk of transmitting HIV is lower when HIV viral loads are undetectable [2123].

Little is known about how gender, aging and age-related physical factors such as menopause affect the sexual behaviors of women living with HIV [2427]. Menopause represents a biological milestone of the aging process; perimenopausal women may experience urogenital changes including vaginal dryness [28] and mucosal thinning, which can both increase HIV acquisition and transmission rates [29]. Postmenopausal women with HIV, like their HIV-uninfected counterparts, may not use condoms as frequently because they no longer require contraception. Although condom use has been shown to decline with age [10, 30, 31], more research is needed to further explore the role of menopause on sexual behavior.

To explore the relationship between aging, SA and UAVI among women with and without HIV-1 infection, this study examined data from the Women’s Interagency HIV Study (WIHS), the largest longitudinal cohort study of HIV-infected and uninfected women in the United States. Previous studies from the WIHS have reported that menopausal symptoms do not affect condom use among older women with HIV [32]. In this analysis, we extend this work by examining the relationship of aging, menopause and sexual behavior among HIV-infected and uninfected women over 13 years of follow-up (1998–2011). We posit that older age is associated with a decline in SA and UAVI for both HIV-infected and uninfected women; that women with HIV infection will show a greater decline in sexual behavior as they age as compared to HIV-negative women; and that among HIV-infected women, the impact of age on sexual behavior will be influenced by viral load and menopause status. These findings can be used to help tailor secondary HIV prevention strategies specifically for older heterosexual women with HIV.

Materials and Methods

Participants

The WIHS is a multicenter, prospective study established in 1993 to investigate HIV disease progression in women in the United States. WIHS participants in this analysis were drawn from six consortia (Washington, DC; San Francisco, CA Bay Area; Los Angeles, CA; Brooklyn, NY; Bronx, NY; and Chicago, IL). The WIHS enrolled women in 1994–95 and 2001–02. Women recruited in the first cohort were either at-risk HIV-uninfected or HIV-infected women. At-risk HIV-uninfected women with self-reported high-risk behaviors, such as injection drug use, having a sexually transmitted disease, having unprotected sex with three or more men or protected sex with more than five men, or having exchanged sex for drugs, money, or shelter were recruited to ensure comparability with the HIV-infected women [33, 34]. In the second wave of recruitment, HIV-infected women with an AIDS-related clinical condition or who acquired HIV perinatally were excluded. Study recruitment and protocols have previously been described [33, 34].

For this study, we examined data from 66,055 WIHS person-visits representing 3,847 women over 13 years of follow-up. We retained 39,812 person-visits, contributed by 1,927 HIV-infected and 742 HIV-uninfected women. We excluded data from participants and visits using a three-phase process that included the following: (1) all visits for all women (17,322 person visits and 764 participants) in the pre-highly active antiretroviral therapy (ART)era (1993–1997); (2) post-event visits for women with a hysterectomy, the removal of either ovary, and visits during which participants reported being pregnant or trying to become pregnant (8,325 person-visits and 328 participants); and (3) HIV-seroconversion (308 person-visits and 18 participants). We excluded all person-visits prior to ART so we could focus on sexual risk behaviors in the ART era. We excluded participants who reported a hysterectomy or an oophorectomy because they may not use condoms as frequently since they no longer require contraception. We also excluded participants who were pregnant or intended on becoming pregnant because most reported unprotected intercourse in order to conceive. In addition, for analyses of menopause, we limited analysis to those visits in which the participants were between 40 and 57 years of age (N = 21,272 visits involving 1,808 women). This age range was selected to reduce the degree of multicollinearity between age and menopause status by constraining age to a menopause-plausible range [3537].

Study Procedures

WIHS participants complete semiannual study visits in English or Spanish. Each visit includes a standardized, interviewer-administered questionnaire assessing sexual behavior, medical and obstetric/gynecological history, psychosocial factors, and socio-demographics, as well as a physical and gynecological examination. Self-reported measures are selected based on their demonstrated reliability and validity in populations similar to the WIHS. In addition to other tests, blood samples are collected to test for HIV RNA levels. Institutional review boards at each of the study centers approved the study procedures, and informed written consent was obtained from all participants.

Measures

Sexual Behavior

At each study visit, women reported whether they had vaginal or anal sex and the number of vaginal, anal and/or oral sex partners during the past 6 months. UAVI was determined based on assessment of condom use consistency (“always” versus “sometimes” or “never”) for vaginal and anal sex separately. Sexually active women who reported “sometimes” or “never” to either question about condom use were categorized as having UAVI in the past 6 months.

Age and Menopause

After investigation of the functional relationship between age and the outcomes of interest, chronological age was used as a continuous variable. Menopausal status was determined by self-reported vaginal bleeding patterns. Due to irregularities in menstrual cycle patterns, many WIHS participants were not easily categorized via this self-report measure for menopause [38]. For the purpose of this study, we chose a conservative approach for defining the onset of menopause by using self-report data for three consecutive study visits at which no menses were reported during the prior 6 months. Menopause onset was defined as the date of the second of these three study visits (i.e., 12 months with no menses).

Viral Load Suppression

Plasma HIV-1 RNA quantification was performed using the isothermal nucleic acid sequence-based amplification method in laboratories certified by the National Institutes of Health Virology Quality Assurance program, with a lower limit of detection set at 48 copies/milliliters (mL). Presence of detectable plasma HIV-RNA among HIV-infected women was designated as HIV+/detectable, versus HIV +/undetectable in those with non-detectable HIV-RNA. Viral load status was imputed for up to two consecutive visits at which HIV-1 RNA was not recorded if the status at the previous visit was the same for the subsequent visit.

Covariates

At enrollment, WIHS participants provided information about their race/ethnicity (Black, White, Latina, or other), educational attainment (less than high school versus high school or higher), quantity and frequency of drug and alcohol use, symptoms of depression, physical function, and follow-up duration (number of visits since baseline). Depression was assessed using the Center for Epidemiologic Studies-Depression (CES-D) scale [39]; CES-D scores were dichotomized, with ≥16 indicating depressive symptoms [39]. Physical function was assessed with a subscale from the medical outcomes study (MOS) measures [40]. The physical function subscale scores were continuous, ranging from 0 to 100, with 100 representing the highest perceived physical ability [40]. For the purposes of analysis, quintile groups were formed from these scores. Drug use was assessed via self-reported use of crack, cocaine, heroin, or other injection drugs in the previous 6 months (Y/N). Alcohol use was dichotomized as heavy (≥7 drinks/week) versus light/moderate (<7 drinks/week) [41]. In addition to these variables, duration of follow-up was included as covariate in our models.

Statistical Analysis

Justification of the Model

In order to assess the suitability of treating age as a linear predictor of the two outcomes of interest (SA and UAVI), we first constructed logistic regression models to estimate log-odds of each outcome by age category [42]. For these analyses, we stratified age into 5-year groups, starting with ages 18–22 (the youngest participant was 18 years of age). Plots of these age-category-specific log-odds estimates (Fig. 1) were then used to assess the adequacy of using age as a linear predictor in the main regression models. As can be seen in Fig. 1, there was indeed a linear relationship between age and the two outcomes; therefore, in the main analyses, age was included as a continuous variable.

Fig. 1.

Fig. 1

Linearity of relationship of age to log-odds of sexual behaviors: (a) Any sexual activity (SA). (b) Any unprotected sexual activity (UAVI) among those sexually active. Age is grouped in 5-year categories beginning with youngest subject in study. VL+ detectable plasma HIV-RNA, VL− non-detectable plasma HIV-RNA, HIV- HIV−uninfected

Application of the Model

Descriptive statistics were generated as means and standard deviations (SD), and were stratified by HIV status. Generalized mixed linear models were constructed separately for age as a linear predictor (based upon results of the suitability analysis) and for menopausal status, with predictors of interest including HIV status. Since age and menopausal status are strongly associated, an unconstrained analysis that included both age and menopause as simultaneous predictors would have resulted in multicollinearity. Therefore, we included age as a predictor of interest in an analysis of all participants, ignoring menopause. In a second analysis, we used menopause as a predictor of interest, controlling for age. In this analysis we avoided the issue of multicollinearity by constraining age to a menopause-plausible range.

The outcomes were modeled as Bernoulli-distributed; a logit link-function was applied. Autocorrelation among observations coming from the same subject on successive visits was modeled as a first-order autoregressive, first-order moving average (ARMA 1, 1) process. Satterthwaite adjustments were made to denominator degrees of freedom. All of the seven plausible covariates (race, education, heavy drinking, current drug use, depression, physical function and follow-up duration) were added to each model. Since only age, menopause and HIV status are considered predictors of interest in this paper, effects of other risk factors appearing in the above list of covariates are not reported. Analyses were conducted using SAS 9.2 (SAS Institute, Cary, NC).

Results

Sample Characteristics

Baseline characteristics of the study population, stratified by HIV status, are shown in Table 1. The majority of the participants were ≥30 years old, Black, had at least a high school education and were premenopausal. HIV-uninfected women were younger (p<0.0001). A larger proportion of White and Hispanic women were HIV+/undetectable (p = 0.0020) compared to Black women. The majority of participants were sexually active, with the HIV-uninfected women reporting more SA (87 %) than HIV+/detectable (74 %) or HIV+/ undetectable (73 %) women (p < 0.0001). More than a quarter of the HIV+/detectable (29 %) and HIV+/undetectable (28 %) women reported UAVI. The HIV-uninfected women, however, reported twice (60 %)as much UAVI as did women with HIV (p < 0.0001) (see Fig. 2).

Table 1.

Characteristics of the Study Population at baseline and across study (by) visits

Baseline characteristics HIV+/detectable
N = 1371
N (%)
HIV+/undetectable
N = 556
N (%)
HIV−
N = 742
N (%)
p value
Age
   18–29 248 (18.1) 111 (20.0) 274 (36.9) <0.0001
   30–39 625 (45.6) 251 (45.1) 282 (38.0)
   40–49 435 (31.7) 156 (28.1) 163 (22.0)
   50–59 56 (4.1) 35 (6.3) 20 (2.7)
   60+ 7 (0.5) 3 (0.5) 3 (0.4)
Race
   White 187 (13.6) 92 (16.6) 97 (13.1) 0.0020
   Hispanic 349 (25.5) 184 (33.1) 202 (27.2)
   Black 790 (57.6) 260 (46.8) 414 (55.8)
   Other 45 (3.3) 20 (3.6) 29 (3.9)
Education
   High school graduate 850 (62.2) 332 (59.8) 478 (65.1) 0.1423

Characteristics across study
(by) visits
HIV +/detectable
N = 16326
N (%)
HIV +/undetectable
N = 12519
N (%)
HIV−
N = 10967
N (%)
p value

Age
   18–29 1429 (8.8) 689 (5.5) 2150 (19.6) <0.0001
   30–39 5897 (36.1) 3705 (29.6) 3628 (33.1)
   40–49 6547 (40.1) 5440 (43.5) 3686 (33.6)
   50–59 2233 (13.7) 2325 (18.6) 1283 (11.7)
   60+ 220 (1.4) 360 (2.9) 220 (2.0)
Menopausal status
   Yes 2755 (16.9) 2691 (21.5) 1394 (12.7) <0.0001
Heavy drinking
   Yes 1366 (8.4) 481 (3.9) 1180 (10.8) <0.0001
Recent drug use
   Yes 4027 (24.9) 1951 (15.7) 3404 (31.2) <0.0001
CES-D score ≥16
   Yes 5587 (42.1) 3518 (32.1) 3090 (32.4) <0.0001
Physical Function* 71.1(28.4) 74.2 (27.5) 79.0 (26.1) <0.001

HIV+/detectable detectable plasma HIV-RNA, HIV+/undetectable non-detectable plasma HIV-RNA, HIV− HIV-uninfected

*

Mean (Standard deviation) calculated

Fig. 2.

Fig. 2

Percent of any SA and UAVI at baseline and averaged across all visits. HIV+/detectable detectable plasma HIV-RNA, HIV+/undetectable non-detectable plasma HIV-RNA, HIV- HIV-uninfected

Characteristics of the study sample by visits and virologic grouping (detectable vs. undetectable) are shown in Table 1. HIV-uninfected women had the highest levels of alcohol and current drug use (both p < 0.0001), the HIV+/undetectable group had the highest occurrence of menopause (p < 0.0001) and the HIV+/detectable women had the highest levels of depressive symptoms (p < 0.0001). Across visits, there were similar (p > 0.05) declines in SA in all groups. SA in HIV+/ detectable women declined to 69 %, in HIV+/undetectable women to 65 %, and SA amongst HIV-uninfected women declined to 70 %. Reported levels of UAVI across all visits also declined over time, although HIV-uninfected women reported significantly (p < 0.0001) more UAVI during the 13 years of follow-up than HIV+/detectable or HIV+/undetectable women (54, 25, 22 %, respectively) (see Fig. 2).

Self-Reported Sexual Activity and Age

Adjusted odds ratios (ORs) of any SA by 10-year age increase, stratified by HIV status are shown in Table 2. In a logistic regression model controlling for the aforementioned covariates, we found that for every 10-year age change, the odds of any SA declined by 62 % for HIV+/detectable women, 64 % for HIV+/undetectable women and 62 % for HIV- women. Differences in SA among virologic groups in terms of age effect were statistically non-significant (F [2, 8858] = 0.37, p = 0.693).

Table 2.

Adjusted odds ratios of any sexual activity (SA) and unprotected anal or vaginal intercourse (UAVI) for age and menopause by virologic group

Number of visits HIV+/VL+
HIV+/VL−
HIV−
p value
OR 95 % CI OR 95 % CI OR 95 % CI
Any SA
   Any sex for 10-year age change N = 32,395 0.38 0.34–0.41 0.36 0.33–0.40 0.38 0.33–0.44 0.693
   Any sex for menopause controlling for age N = 17,501 0.78 0.68–0.90 0.75 0.64–0.87 0.82 0.65–1.04 0.724
UAVI
   Unprotected sex for 10-year age change N = 21,382 0.83 0.74–0.92 0.91 0.81–1.01 0.96 0.83–1.10 0.036
   Unprotected sex for menopause controlling for age N = 9,906 0.72 0.58–0.88 0.85 0.69–1.06 1.04 0.74–1.48 0.099

Analyses of UAVI included only subjects with self-reported sexual activity

All of the seven plausible covariates (race, education, heavy drinking, current drug use, depression, physical function and follow-up duration) were added to each model

HIV+/VL+ detectable plasma HIV-RNA, HIV+/VL− non-detectable plasma HIV-RNA, HIV− HIV-uninfected

Self-Reported Sexual Activity and Menopausal Status

Adjusted ORs of any SA by menopause, stratified by HIV status, are shown in Table 2. The odds of any SA in a 6-month interval for women aged 40–57 declined by 22 % for HIV+/detectable women, 25 % for HIV+/undetectable women and 18 % for HIV-uninfected women after menopause. These declines were statistically significant only for the women with HIV. Differences in effect of menopause among virologic groups are statistically non-significant (F [2, 12311] = 0.32, p = 0.724).

Self-Reported UAVI and Age

Adjusted ORs of any UAVI by 10-year age change, stratified by HIV status, are shown in Table 2. The ORs for UAVI in a 6 month interval by decade of age, were limited to those visits where there was reported SA (N = 21382 visits or 84 % of original sample of 25,992). The odds of UAVI declined by 17 % for HIV+/detectable women, 9 % for HIV+/undetectable women and 4 % for HIV-uninfected women per decade of age. The decline was only statistically significant for the HIV+/detectable women. Differences among virologic groups in age effect are statistically significant (F [2, 7490] = 3.33, p = 0.036). Pairwise testing yields: HIV+/detectable women versus HIV+/undetectable women (F [1,20296] = 7.84, p = 0.038); HIV+/detectable women versus HIV-uninfected women (F [1,3966] = 3.80, p = 0.051); HIV+/undetectable women versus HIV-uninfected women (F [1,4366] = 0.56, p = 0.454).

Self-Reported UAVI and Menopause (Age 40–57)

Data on UAVI at 6 month intervals for sexually active women aged 40–57 were available for 9906 visits; 83 % of original sample. Adjusted ORs of any UAVI for these women, stratified by HIV status, are shown in Table 2. Odds of UAVI for these women declined by 28 % for HIV+/detectable women and 15 % for HIV+/undetectable women; and odds of UAVI for HIV-uninfected women increased by 4 % after menopause. The decline was only statistically significant for the HIV+/detectable women. Differences in UAVI between virologic groups in terms of the effect of menopause were not statistically significant (F [2, 7088] = 2.32, p = 0.099).

Discussion

Findings from WIHS

We found that older age is associated with an overall decrease in SA and UAVI among both HIV-infected and HIV-uninfected women, after accounting for race/ethnicity, education, heavy drinking, recent drug use, depressive symptoms and physical function. Regardless of HIV status, 65–87 % of the women in this study at baseline and across 13 years of follow-up were sexually active. We found that women with HIV did not show a greater decline in SA as they aged, compared to HIV-uninfected women. We also found that UAVI decreased over time, and HIV-infected women maintained a pattern of reporting less UAVI than HIV-uninfected women. However, after 13 years of follow-up we found 22–25 % of the HIV-infected women continued to engage in UAVI.

We found that for women aged 40–57, the odds of any SA declined after menopause only for women with HIV. Although the odds ratios for any SA associated with menopause were statistically significant for the women with HIV, we cannot definitively assert that there is any menopause effect among the HIV-uninfected women. We also found that UAVI declined significantly among women ages 40–57 who had a detectable HIV viral load.

Studies of UAVI in HIV-Infected Adults

In a cross-sectional survey of 1,000 older adults with HIV in New York City, 50 % were found to be sexually active and approximately a third reported UAVI, which was significantly associated with loneliness and recent substance use [13, 18]. That study also found that among those who engaged in UAVI, 18 % had unprotected sex with a serodiscordant partner. Other cross-sectional studies have found a prevalence of UAVI of 33 %and 42 %among sexually active older adults with HIV [13, 17, 43]. These findings are considerably higher than those found in this study. Our lower risk estimates might be due to the impact of a larger cohort and a significant duration of follow-up or due to the participants in each of these studies, who represent both men and women.

The decline in SA among older adults could be accounted for by diminishing sexual function. The most commonly reported causes of sexual dysfunction among older women are a lack of interest in sex, failure to achieve orgasm and poor vaginal lubrication [4447], though poor health, instead of chronological age, may underlie some of these problems. Poor physical and mental health affects sex drive and has been found to be associated with a decline in SA among older adults [4850]. Postmenopausal women may be less likely to use condoms because they no longer need contraception. Although condom use has been shown to decline with age among women with HIV [30, 31] recent studies found no association with menopause and condom use among women with HIV [31]. More research is needed to explore the role of menopause on sexuality and the sexual behavior of older women [5155].

Identifying Women at Risk

Our findings demonstrate that there is a proportion of older women with HIV who may benefit from support in maintaining safer sex practices. Future research will be useful to delineate which women are at greatest risk. However, there are a number of plausible psychosocial and interpersonal factors that can be posited, based on research in other populations. Among older adults with HIV, high levels of psychological distress and poor mental health (e.g., depression, loneliness, anxiety, and chronic stress) are common [15, 18, 5658] and have been well documented in the WIHS cohort [5965]. Impaired mental health, in turn, has been found to be a determinant of sexual risk behavior among men living with HIV or AIDS [66]. Studies have demonstrated consistent associations between unprotected sex and depression, anxiety [43, 6769], and loneliness [18]. Older adults with HIV are particularly isolated from supportive social networks and are less likely to disclose their status due to the double stigma of AIDS and ageism, both of which lead to stress and poorer mental health outcomes [7074]. To compensate for these changes, many older adults use alcohol, tobacco, and/or illicit drugs which are factors for sexual risk [14, 7577]. These changing psychosocial and intrapersonal factors highlight the need to understand the context of sexual behavior among older women with HIV.

Limitations

Our study had some limitations. First, only a few sexual risk behavior measures were obtained at each semiannual study visit, limiting our ability to examine additional sexual risk patterns such as partner concurrency and the HIV serostatus of sexual partners. Consequently, we were unable to estimate the risk of potential transmission to sexual partners among women reporting inconsistent condom use. Second, we used self-reported measures to categorize sexual behavior and menopausal status, which involves a possibility of bias and misclassification. Third, participants were recruited from urban sites, so the applicability of our findings to non-urban populations remains unclear. Finally, 96 % of WIHS at the Brooklyn, Bronx and Chicago sites speak English and only 4 % Spanish; therefore, these findings may not represent the sexual behaviors of non-English speaking populations of older women with HIV. Despite these shortcomings, however, we know of no other data set that is able to assess intra-individual changes in sexual risk behaviors among women with HIV from a longitudinal perspective.

Strengths

This study also had several strengths. Exploring sexual behavior among HIV-infected women in a large cohort over time is an innovative area of investigation. To date, there have been few investigations of the relative impact of aging or menopause on SA or UAVI in HIV-infected persons. Our longitudinal analysis allowed us to ascertain the gradual decline in SA and UAVI among HIV-infected women, while the HIV-uninfected women maintained levels of SA and UAVI. This is significant because the HIV-uninfected women in WIHS were matched according to their risk behaviors for HIV. These data suggest that among women at risk for HIV, risk behaviors do not change as women grow older, which points to an urgent need to target HIV prevention messaging to this population.

Conclusions

In summary, the decline in SA and UAVI over time among women with and without HIV was dependent on age; however, more than two-thirds of the HIV-infected women in the WIHS were sexually active, and 22 %engaged in UAVI over 13 years of follow-up. The sexual risk behaviors of older women with and without HIV-1 infection are neglected areas of research in part due to the assumptions that as women age they no longer engage in SA or sexual risk behaviors. These findings suggest that as women age they may need additional support for maintaining safer sex practices.

Acknowledgments

This work was supported by the National Institute of Mental Health (1 KO1 MH095670, Taylor, PI). Data in this manuscript were collected by the Women’s Interagency HIV Study (WIHS). The contents of this publication are solely the responsibility of the authors and do not represent the official views of the National Institutes of Health (NIH). WIHS (Principal Investigators): Bronx WIHS (Kathryn Anastos), U01-AI-035004; Brooklyn WIHS (Howard Minkoff and Deborah Gustafson),U01-AI-031834; Chicago WIHS (Mardge Cohen), U01-AI-034993;Metropolitan Washington WIHS (Mary Young), U01-AI-034994; Connie Wofsy Women’s HIV Study, Northern California (Ruth Greenblatt, Bradley Aouizerat, and Phyllis Tien), U01-AI-034989; WIHS Data Management and Analysis Center (Stephen Gange and Elizabeth Golub), U01-AI-042590; Southern California WIHS (Alexandra Levine and Marek Nowicki), U01-HD-032632 (WIHS I – WIHS IV). The WIHS is funded primarily by the National Institute of Allergy and Infectious Diseases (NIAID), with additional co-funding from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), the National Cancer Institute (NCI), the National Institute on Drug Abuse (NIDA), and the National Institute on Mental Health (NIMH). Targeted supplemental funding for specific projects is also provided by the National Institute of Dental and Craniofacial Research (NIDCR), the National Institute on Alcohol Abuse and Alcoholism (NIAAA), the National Institute on Deafness and other Communication Disorders (NIDCD), and the NIH Office of Research on Women’s Health. WIHS data collection is also supported by UL1-TR000004 (UCSF CTSA). The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the National Institutes of Health.

Contributor Information

Tonya N. Taylor, Email: Tonya.Taylor@downstate.edu, Special Treatment and Research Program, SUNY Downstate Medical Center, Brooklyn, NY, USA; College of Medicine, SUNY Downstate Medical Center, 450 Clarkson Avenue, 1240, Brooklyn, NY 11203, USA.

Jeremy Weedon, Statistical Design & Analysis Research Division, SUNY Downstate Medical Center, Brooklyn, NY, USA.

Elizabeth T. Golub, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA

Stephen E. Karpiak, School of Nursing, New York University, New York, NY, USA AIDS Community Research Initiative of America (ACRIA), New York, NY, USA.

Monica Gandhi, School of Medicine, University of California, San Francisco (UCSF), San Francisco, CA, USA.

Mardge H. Cohen, Department of Medicine, Cook County Health and Hospital System and Rush University, Chicago, IL, USA

Alexandra M. Levine, Department of Pathology, City of Hope National Medical Center, Duarte, CA, USA

Howard L. Minkoff, Department of Obstetrics and Gynecology, Maimonides Medical Center, Brooklyn, NY, USA

Adebola A. Adedimeji, Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA

Lakshmi Goparaju, Department of Medicine, Georgetown University Medical Center, Washington, DC, USA.

Susan Holman, Special Treatment and Research Program, SUNY Downstate Medical Center, Brooklyn, NY, USA.

Tracey E. Wilson, School of Public Health, SUNY Downstate Medical Center, Brooklyn, NY, USA

References

  • 1.Lindau ST, Schumm LP, Laumann EO, Levinson W, O’Muircheartaigh CA, Waite LJ. A study of sexuality and health among older adults in the United States. N Engl J Med. 2007;357(8):762–774. doi: 10.1056/NEJMoa067423. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Waite LJ, Laumann EO, Das A, Schumm LP. Sexuality: measures of partnerships, practices, attitudes, and problems in the AIDS Behav national social life, health, and aging study. J Gerontol B. 2009;64(Suppl 1):i56–i66. doi: 10.1093/geronb/gbp038. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Reece M, Herbenick D, Schick V, Sanders SA, Dodge B, Fortenberry JD. Condom use rates in a national probability sample of males and females ages 14 to 94 in the United States. J Sex Med. 2010;7(s5):266–276. doi: 10.1111/j.1743-6109.2010.02017.x. [DOI] [PubMed] [Google Scholar]
  • 4.Schick V, Herbenick D, Reece M, Sanders SA, Dodge B, Middlestadt SE, Fortenberry JD. Sexual behaviors, condom use, and sexual health of Americans over 50: implications for sexual health promotion for older adults. J Sex Med. 2010;7(s5):315–329. doi: 10.1111/j.1743-6109.2010.02013.x. [DOI] [PubMed] [Google Scholar]
  • 5.Karraker A, DeLamater J, Schwartz CR. Sexual frequency decline from midlife to later life. J Gerontol B. 2011;66(4):502–512. doi: 10.1093/geronb/gbr058. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Herbenick D, Reece M, Schick V, Sanders SA, Dodge B, Fortenberry JD. Sexual behavior in the United States: results from a national probability sample of men and women ages 14–94. J Sex Med. 2010;7(s5):255–265. doi: 10.1111/j.1743-6109.2010.02012.x. [DOI] [PubMed] [Google Scholar]
  • 7.Herbenick D, Reece M, Schick V, Sanders SA, Dodge B, Fortenberry JD. Sexual behaviors, relationships, and perceived health status among adult women in the United States: results from a national probability sample. J Sex Med. 2010;7(s5):277–290. doi: 10.1111/j.1743-6109.2010.02010.x. [DOI] [PubMed] [Google Scholar]
  • 8.Adekeye OA, Heiman HJ, Onyeabor OS, Hyacinth HI. The new invincibles: HIV screening among older adults in the US. PloS One. 2012;7(8):e43618. doi: 10.1371/journal.pone.0043618. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.CDC. HIV Surveillance Report, 2011. Centers for Disease Control and Prevention. 2013
  • 10.Schable B, Chu SY, Diaz T. Characteristics of women 50 years of age or older with heterosexually acquired AIDS. Am J Public Health. 1996;86(11):1616–1618. doi: 10.2105/ajph.86.11.1616. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Cooperman NA, Arnsten JH, Klein RS. Current sexual activity and risky sexual behavior in older men with or at risk for HIV infection. AIDS Educ Prev. 2007;19(4):321–333. doi: 10.1521/aeap.2007.19.4.321. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Lovejoy TI, Heckman TG, Sikkema KJ, Hansen NB, Kochman A, Suhr JA, Garske JP, Johnson CJ. Patterns and correlates of sexual activity and condom use behavior in persons 50-plus years of age living with HIV/AIDS. AIDS Behav. 2008;12(6):943–956. doi: 10.1007/s10461-008-9384-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Golub SA, Tomassilli JC, Pantalone DW, Brennan M, Karpiak SE, Parsons JT. Prevalence and correlates of sexual behavior and risk management among HIV-positive adults over 50. Sex Transm Dis. 2010;37(10):615–620. [PubMed] [Google Scholar]
  • 14.Golub SA, Botsko M, Gamarel KE, Parsons JT, Brennan M, Karpiak SE. Dimensions of psychological well-being predict consistent condom use among older adults living with HIV. Ageing Int. 2011;36(3):346–360. [Google Scholar]
  • 15.Karpiak SE, Brennan M. The emerging population of older adults with HIV and introduction to the ROAH study. In: Brennan M, Karpiak SE, Shippy R, Cantor M, editors. Older adults with HIV: an in-depth examination of an emerging population Hauppauge. NY: Nova Science Publishers; 2009. pp. 1–12. [Google Scholar]
  • 16.Zablotsky D, Kennedy M. Risk factors and HIV transmission to midlife and older women: knowledge, options, and the initiation of safer sexual practices. J Acquir Immune Defic Syndr. 2003;1(33 Suppl 2):S122–S130. doi: 10.1097/00126334-200306012-00009. [DOI] [PubMed] [Google Scholar]
  • 17.Aidala AA, Lee G, Garbers S, Chiasson MA. Sexual behaviors and sexual risk in a prospective cohort of HIV-positive men and women in New York City, 1994–2002: implications for prevention. AIDS Educ Prev. 2006;18(1):12–32. doi: 10.1521/aeap.2006.18.1.12. [DOI] [PubMed] [Google Scholar]
  • 18.Grov C, Golub SA, Parsons JT, Brennan M, Karpiak SE. Loneliness and HIV-related stigma explain depression among older HIV-positive adults. AIDS Care. 2010;22(5):630–639. doi: 10.1080/09540120903280901. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Önen NF, Shacham E, Stamm KE, Overton ET. Comparisons of sexual behaviors and STD prevalence among older and younger individuals with HIV infection. AIDS Care. 2010;22(6):711–717. doi: 10.1080/09540120903373573. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Lovejoy TI, Heckman TG, Sikkema KJ, Hansen NB, Kochman A. Changes in sexual behavior of HIV-infected older adults enrolled in a clinical trial of standalone group psychotherapies targeting depression. AIDS Behav. 2014:1–8. doi: 10.1007/s10461-014-0746-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Crepaz N, Hart TA, Marks G. Highly active antiretroviral therapy and sexual risk behavior: a meta-analytic review. JAMA. 2004;292(2):224–236. doi: 10.1001/jama.292.2.224. [DOI] [PubMed] [Google Scholar]
  • 22.Wilson TE, Gore ME, Greenblatt R, Cohen M, Minkoff H, Silver S, Robison E, Levine A, Gange SJ. Changes in sexual behavior among HIV-infected women after initiation of HAART. Am J Public Health. 2004;94(7):1141–1146. doi: 10.2105/ajph.94.7.1141. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Wilson TE, Feldman J, Vega MY, Gandhi M, Richardson J, Cohen MH, McKaig R, Ostrow D, Robison E, Gange SJ. Acquisition of new sexual partners among women with HIV infection: patterns of disclosure and sexual behavior within new partnerships. AIDS Educ Prev. 2007;19(2):151–159. doi: 10.1521/aeap.2007.19.2.151. [DOI] [PubMed] [Google Scholar]
  • 24.Emlet CA. HIV/AIDS in the elderly: a hidden population. Home Care Provid. 1997;2(2):69–75. doi: 10.1016/s1084-628x(97)90045-9. [DOI] [PubMed] [Google Scholar]
  • 25.Engle L. Old AIDS. Body Posit. 1998;11(1):14–21. [PubMed] [Google Scholar]
  • 26.Casau NC. Perspective on HIV infection and aging: emerging research on the horizon. Clin Infect Dis. 2005;41(6):855–863. doi: 10.1086/432797. [DOI] [PubMed] [Google Scholar]
  • 27.Levin J. HIV accelerates aging. A call for investigation. Posit Aware. 2009;20(3):36. [PubMed] [Google Scholar]
  • 28.Bachmann GA, Leiblum SR. The impact of hormones on menopausal sexuality: a literature review. Menopause. 2004;11(1):120–130. doi: 10.1097/01.GME.0000075502.60230.28. [DOI] [PubMed] [Google Scholar]
  • 29.Senanyake P. Women and reproductive health in a graying world. International Journal of Gynecology and Obstetrics. 2000;70(1):59–67. doi: 10.1016/s0020-7292(00)00224-1. [DOI] [PubMed] [Google Scholar]
  • 30.Allison-Ottey S, Weston C, Hennawi G, Nichols M, Eldred L, Ferguson RP. Sexual practices of older adults in a high HIV prevalence environment. Md Med J. 1999;48(6):287–291. [PubMed] [Google Scholar]
  • 31.Massad LS, Evans CT, Wilson TE, Golub ET, Sanchez-Keeland L, Minkoff H, Weber K, Watts DH. Contraceptive use among U.S. women with HIV. J Womens Health (Larchmt) 2007;16(5):657–666. doi: 10.1089/jwh.2006.0204. [DOI] [PubMed] [Google Scholar]
  • 32.Massad LS, Evans CT, Wilson TE, Golub ET, Goparaju L, Howard A, Greenblatt RM, Weber K, Schilder K. Impact of menopause on condom use by HIV-seropositive and comparison seronegative women. J Acquir Immune Defic Syndr. 2008;47(3):401–402. doi: 10.1097/qai.0b013e31815e7466. [DOI] [PubMed] [Google Scholar]
  • 33.Barkan SE, Melnick SL, Preston-Martin S, Weber K, Kalish LA, Miotti P, Young M, Greenblatt R, Sacks H, Feldman J. The Women’s Interagency HIV Study. WIHS Collaborative Study Group. Epidemiology. 1998;9(2):117–125. [PubMed] [Google Scholar]
  • 34.Bacon MC, von Wyl V, Alden C, Sharp G, Robison E, Hessol N, Gange S, Barranday Y, Holman S, Weber K, Young MA. The Women’s Interagency HIV Study: an observational cohort brings clinical sciences to the bench. Clin Diagn Lab Immunol. 2005;12(9):1013–1019. doi: 10.1128/CDLI.12.9.1013-1019.2005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Fantry LE, Zhan M, Taylor GH, Sill AM, Flaws JA. Age of menopause and menopausal symptoms in HIV-infected women. AIDS Patient Care & STDs. 2005;19(11):703–711. doi: 10.1089/apc.2005.19.703. [DOI] [PubMed] [Google Scholar]
  • 36.Clark RA, Cohn SE, Jarek C, Craven KS, Lyons C, Jacobson M, Kamemoto L. Perimenopausal symptomatology among HIV-infected women at least 40 years of age. JAIDS Journal of Acquired Immune Deficiency Syndromes. 2000;23(1):99–100. doi: 10.1097/00126334-200001010-00016. [DOI] [PubMed] [Google Scholar]
  • 37.Schoenbaum EE, Hartel D, Lo Y, Howard AA, Floris-Moore M, Arnsten JH, Santoro N. HIV infection, drug use, and onset of natural menopause. Clin Infect Dis. 2005;41(10):1517–1524. doi: 10.1086/497270. [DOI] [PubMed] [Google Scholar]
  • 38.Wilson TE, Jean-Louis G, Schwartz R, Golub ET, Cohen MH, Maki P, Greenblatt R, Massad LS, Robison E, Goparaju L, Lindau S. HIV infection and women’s sexual functioning. J Acquir Immune Defic Syndr. 2010;54(4):360–367. doi: 10.1097/QAI.0b013e3181d01b14. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Radloff L. The CES-D scale: a self-report depression scale for research in the general population. Appl Psychol Meas. 1977;1:385–401. [Google Scholar]
  • 40.Bozzette SA, Hays RD, Berry SH, Kanouse DE, Wu AW. Derivation and properties of a brief health status assessment instrument for use in HIV disease. JAIDS Journal of Acquired Immune Deficiency Syndromes. 1995;8(3):253–265. doi: 10.1097/00042560-199503010-00006. [DOI] [PubMed] [Google Scholar]
  • 41.Cook RL, Zhu F, Belnap BH, Weber K, Cook JA, Vlahov D, Wilson TE, Hessol NA, Plankey M, Howard AA, Cole SR, Sharp GB, Richardson JL, Cohen MH. Longitudinal trends in hazardous alcohol consumption among women with human immunodeficiency virus infection, 1995–2006. Am J Epidemiol. 2009;169(8):1025–1032. doi: 10.1093/aje/kwp004. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Rodriguez G. Lecture Notes on Generalized Linear Models, Chapter 3. 2007 [cited 2014 August 12]; http://data.princeton.edu/wws509/notes/.
  • 43.Illa L, Brickman A, Saint-Jean G, Echenique M, Metsch L, Eisdorfer C, Bustamante-Avellaneda V, Sanchez-Martinez M. Sexual risk behaviors in late middle age and older HIV seropositive adults. AIDS Behav. 2008;12(6):935–942. doi: 10.1007/s10461-008-9370-8. [DOI] [PubMed] [Google Scholar]
  • 44.Laumann EO, Paik A, Rosen RC. Sexual dysfunction in the United States: prevalence and predictors. JAMA. 1999;281(6):537–544. doi: 10.1001/jama.281.6.537. [DOI] [PubMed] [Google Scholar]
  • 45.Nicolosi A, Laumann EO, Glasser DB, Moreira ED, Jr, Paik A, Gingell C. Sexual behavior and sexual dysfunctions after age 40: the global study of sexual attitudes and behaviors. Urology. 2004;64(5):991–997. doi: 10.1016/j.urology.2004.06.055. [DOI] [PubMed] [Google Scholar]
  • 46.Laumann EO, Waite LJ. Sexual dysfunction among older adults: Prevalence and risk factors from a nationally representative US probability sample of men and women 57–85 years of age. J Sex Med. 2008;5(10):2300–2311. doi: 10.1111/j.1743-6109.2008.00974.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.DeLamater J, Karraker A. Sexual functioning in older adults. Current psychiatry reports. 2009;11(1):6–11. doi: 10.1007/s11920-009-0002-4. [DOI] [PubMed] [Google Scholar]
  • 48.Lindau ST, Gavrilova N, Anderson D. Sexual morbidity in very long term survivors of vaginal and cervical cancer: a comparison to national norms. Gynecol Oncol. 2007;106(2):413–418. doi: 10.1016/j.ygyno.2007.05.017. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49.Lindau ST, Gavrilova N. Sex, health, and years of sexually active life gained due to good health: evidence from two US population based cross sectional surveys of ageing. BMJ. 2010;340:c810. doi: 10.1136/bmj.c810. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50.Lindau ST, Abramsohn E, Gosch K, Wroblewski K, Spatz ES, Chan PS, Spertus J, Krumholz HM. Patterns and loss of sexual activity in the year following hospitalization for acute myocardial infarction (a United States National Multisite Observational Study) Am J Cardiol. 2012;109(10):1439–1444. doi: 10.1016/j.amjcard.2012.01.355. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51.McCoy NL, Davidson JM. A longitudinal study of the effects of menopause on sexuality. Maturitas. 1985;7(3):203–210. doi: 10.1016/0378-5122(85)90041-6. [DOI] [PubMed] [Google Scholar]
  • 52.Roughan PA, Kaiser FE, Morley JE. Sexuality and the older woman. Clinics in geriatric medicine. 1993;9(1):87–106. [PubMed] [Google Scholar]
  • 53.Dennerstein L, Smith A, Morse C, Burger H. Sexuality and the menopause. Journal of Psychosomatic Obstetrics & Gynecology. 1994;15(1):59–66. doi: 10.3109/01674829409025630. [DOI] [PubMed] [Google Scholar]
  • 54.Rheaume C, Mitty E. Sexuality and intimacy in older adults. Geriatric Nursing. 2008;29(5):342–349. doi: 10.1016/j.gerinurse.2008.08.004. [DOI] [PubMed] [Google Scholar]
  • 55.Pitkin J. Sexuality and the menopause. Best Pract Res Clin Obstet Gynaecol. 2009;23(1):33–52. doi: 10.1016/j.bpobgyn.2008.10.011. [DOI] [PubMed] [Google Scholar]
  • 56.Kalichman SC. HIV transmission risk behaviors of men and women living with HIV-AIDS: prevalence, predictors, and emerging clinical interventions. Clinical Psychology: Science and Practice. 2000;7(1):32–47. [Google Scholar]
  • 57.Morrison MF, Petitto JM, Ten Have T, Gettes DR, Chiappini MS, Weber AL, Brinker-Spence P, Bauer RM, Douglas SD, Evans DL. Depressive and anxiety disorders in women with HIV infection. Am J Psychiatry. 2002;159(5):789–796. doi: 10.1176/appi.ajp.159.5.789. [DOI] [PubMed] [Google Scholar]
  • 58.Rabkin JG. HIV and depression: 2008 review and update. Curr HIV/AIDS Rep. 2008;5(4):163–171. doi: 10.1007/s11904-008-0025-1. [DOI] [PubMed] [Google Scholar]
  • 59.Richardson J, Barkan S, Cohen M, Back S, FitzGerald G, Feldman J, Young M, Palacio H. Experience and covariates of depressive symptoms among a cohort of HIV infected women. Soc Work Health Care. 2001;32(4):93–111. doi: 10.1300/J010v32n04_05. [DOI] [PubMed] [Google Scholar]
  • 60.Cook JA, Cohen MH, Burke J, Grey D, Anastos K, Kirstein L, Palacio H, Richardson J, Wilson T, Young M. Effects of depressive symptoms and mental health quality of life on use of highly active antiretroviral therapy among HIV-seropositive women. J Acquir Immune Defic Syndr. 2002;30(4):401–409. doi: 10.1097/00042560-200208010-00005. [DOI] [PubMed] [Google Scholar]
  • 61.Cook JA, Grey D, Burke J, Cohen MH, Gurtman AC, Richardson JL, Wilson TE, Young MA, Hessol NA. Depressive symptoms and AIDS-related mortality among a multisite cohort of HIV-positive women. Am J Public Health. 2004;94(7):1133–1140. doi: 10.2105/ajph.94.7.1133. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 62.Cook JA, Grey D, Burke-Miller J, Cohen MH, Anastos K, Gandhi M, Richardson J, Wilson T, Young M. Effects of treated and untreated depressive symptoms on highly active antiretroviral therapy use in a US multi-site cohort of HIV-positive women. AIDS Care. 2006;18(2):93–100. doi: 10.1080/09540120500159284. [DOI] [PubMed] [Google Scholar]
  • 63.Cook JA, Grey DD, Burke-Miller JK, Cohen MH, Vlahov D, Kapadia F, Wilson TE, Cook R, Schwartz RM, Golub ET, Anastos K, Ponath C, Goparaju L, Levine AM. Illicit drug use, depression and their association with highly active antiretroviral therapy in HIV-positive women. Drug Alcohol Depend. 2007;89(1):74–81. doi: 10.1016/j.drugalcdep.2006.12.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 64.Galarraga O, Salkever DS, Cook JA, Gange SJ. An instrumental variables evaluation of the effect of antidepressant use on employment among HIV-infected women using antiretroviral therapy in the United States: 1996–2004. Health Econ. 2010;19(2):173–188. doi: 10.1002/hec.1458. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 65.Massad LS, Agniel D, Minkoff H, Watts DH, D’Souza G, Levine AM, Darragh TM, Young M, Cajigas A, Weber K. Effect of stress and depression on the frequency of squamous intraepithelial lesions. J Low Genit Tract Dis. 2011;15(1):42–47. doi: 10.1097/LGT.0b013e3181e66a82. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 66.Parsons JT, Halkitis PN, Wolitski RJ, Gomez CA. Correlates of sexual risk behaviors among HIV-positive men who have sex with men. AIDS Educ Prev. 2003;15(5):383–400. doi: 10.1521/aeap.15.6.383.24043. [DOI] [PubMed] [Google Scholar]
  • 67.Clement U. Psychological correlates of unprotected intercourse among HIV-positive gay men. Journal of Psychological & Human Sexuality. 1992;5(1):133–155. [Google Scholar]
  • 68.Marks G, Bingman C, Duval T. Negative affect and unsafe sex in HIV-positive men. AIDS Behav. 1998;13(4):798–810. [Google Scholar]
  • 69.Reisner SL, Mimiaga MJ, Skeer M, Bright D, Cranston K, Isenberg D, Bland S, Barker TA, Mayer KH. Clinically significant depressive symptoms as a risk factor for HIV infection among black MSM in Massachusetts. AIDS Behav. 2009;13(4):798–810. doi: 10.1007/s10461-009-9571-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 70.Heckman TG, Kochman A, Sikkema KJ, Kalichman SC, Masten J, Goodkin K. Late middle-aged and older men living with HIV/AIDS: race differences in coping, social support, and psychological distress. J Natl Med Assoc. 2000;92(9):436–444. [PMC free article] [PubMed] [Google Scholar]
  • 71.Emlet CA, Poindexter CC. Unserved, unseen, and unheard: integrating programs for HIV-infected and HIV-affected older adults. Health Soc Work. 2004;29(2):86–96. doi: 10.1093/hsw/29.2.86. [DOI] [PubMed] [Google Scholar]
  • 72.Emlet CA. An examination of the social networks and social isolation in older and younger adults living with HIV/AIDS. Health Soc Work. 2006;31(4):299–308. doi: 10.1093/hsw/31.4.299. [DOI] [PubMed] [Google Scholar]
  • 73.Emlet CA. “You’re awfully old to have this disease”: experiences of stigma and ageism in adults 50 years and older living with HIV/AIDS. Gerontologist. 2006;46(6):781–790. doi: 10.1093/geront/46.6.781. [DOI] [PubMed] [Google Scholar]
  • 74.Emlet CA. Experiences of stigma in older adults living with HIV/AIDS: a mixed-methods analysis. AIDS Patient Care STDS. 2007;21(10):740–752. doi: 10.1089/apc.2007.0010. [DOI] [PubMed] [Google Scholar]
  • 75.Rabkin JG, McElhiney MC, Ferrando SJ. Mood and substance use disorders in older adults with HIV/AIDS: methodological issues and preliminary evidence. AIDS. 2004;18:43–48. [PubMed] [Google Scholar]
  • 76.Zanjani F, Mavandadi S, TenHave T, Katz I, Durai NB, Krahn D, Llorente M, Kirchner J, Olsen E, Van Stone W. Longitudinal course of substance treatment benefits in older male veteran at-risk drinkers. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences. 2008;63(1):98–106. doi: 10.1093/gerona/63.1.98. [DOI] [PubMed] [Google Scholar]
  • 77.Siconolfi DE, Halkitis PN, Barton SC, Kingdon MJ, Perez-Figueroa RE, Arias-Martinez V, Karpiak S, Brennan-Ing M. Psychosocial and demographic correlates of drug use in a sample of HIV-positive adults ages 50 and older. Prevention science. 2013;14(6):618–627. doi: 10.1007/s11121-012-0338-6. [DOI] [PubMed] [Google Scholar]

RESOURCES