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. Author manuscript; available in PMC: 2023 Nov 5.
Published in final edited form as: J Nurs Scholarsh. 2023 Apr 20;55(3):751–760. doi: 10.1111/jnu.12900

Mental health, substance use, and risky sexual behaviors among women living with HIV

Caroline D Deaterly 1, Deepthi S Varma 2, Yancheng Li 2, Preeti Manavalan 3, Robert L Cook 2
PMCID: PMC10626942  NIHMSID: NIHMS1939663  PMID: 37132071

Abstract

Introduction:

Risky sexual behavior has been explored in women living with HIV (WLHIV) internationally but is not well studied in WLHIV in the United States (U.S.). This merits further investigation due to the negative reproductive and HIV health outcomes associated with risky sexual behavior, such as the increased risk for HIV transmission and infertility from sexually transmitted infections (STIs). The aims of this study are to (1) describe sexual behaviors in a cohort of WLHIV in Florida, (2) determine whether demographic characteristics, substance use, and mental health symptoms are associated with risky sexual behavior in a cohort of WLHIV in Florida, and (3) explore whether the relationship between substance use and mental health symptoms and risky sexual behavior differs in reproductive-age (age 18–49), compared to non-reproductive-age WLHIV (age 50+).

Design:

This was a cross-sectional analysis of data from a multisite cohort study done in Florida.

Methods:

Data were collected from a sample of 304 participants who were recruited into the Florida Cohort Study from 9 clinical and community sites in Florida between 2014 to 2017. The predictor variables of interest were mental health symptoms, substance use, and demographic variables. The outcome variable of interest was risky sexual behavior which was defined as reporting ≥1 of the following: (1) at least one STI diagnosis in the past 12 months, (2) two or more sexual partners in the past 12 months, or (3) any inconsistent condom use in the past 12 months. Descriptive statistics, bivariate analysis, and logistic regression (p < 0.1) were conducted on the variables of interest.

Results:

The mean age of the sample was 47.8 years, and approximately half (51.6%) of the sample was of reproductive-age. Reporting ≥1 risky sexual behavior was reported in over half (51.6%) of the reproductive-age WLHIV in the sample and 32% of the non-reproductive-age WLHIV in the sample. Binge drinking, alcohol-related problems, marijuana use, and age were all significantly associated with self-reporting ≥1 risky sexual behaviors in all WLHIV. Self-reporting binge drinking, marijuana use, and a high alcohol-related problems score respectively were associated with increased odds of self-reporting ≥1 risky sexual behavior in all WLHIV. Neither mental health symptoms nor race/ethnicity or education were significantly associated with self-reporting ≥1 risky sexual behavior in all WLHIV. Self-reporting severe anxiety symptoms and high alcohol-related problems scores respectively were associated with increased odds of self-reporting ≥1 risky sexual behavior only in reproductive-age WLHIV from the sample.

Conclusion:

Marijuana use, binge drinking, and alcohol-related problems appear to have a relationship with risky sexual behavior in WLHIV regardless of age. Reproductive-age also appears to influence risky sexual behavior in WLHIV, and specific reporting severe anxiety symptoms and high alcohol-related problems in reproductive-age WLHIV increases the odds of engaging in risky sexual behavior.

Clinical Significance:

This study holds clinical significance for nurses and other clinicians working in reproductive health settings and clinics with WLHIV. Results indicate that it could be beneficial to do more screening for mental health symptoms (particularly anxiety) and alcohol use in younger reproductive-age WLHIV.

Keywords: mental health symptoms, reproductive-age, risky sexual behavior, substance use, women living with HIV

INTRODUCTION

A clear understanding of sexual behaviors and the influences on risky sexual behavior in women living with HIV (WLHIV) is imperative. Sexual behaviors influence outcomes such as inflammation caused by STIs and can increase the transmission of HIV and the concentration of the virus in the genital tract (Cohen et al., 2012; Kalichman, 2013). Most research regarding risky sexual behaviors in WLHIV has been conducted in low and middle-income countries, primarily sub-Saharan Africa and Asia with risky sexual behaviors being highly prevalent (between 12 and 57%) in WLHIV (Balis, 2020; Widman et al., 2012). International studies also report risky sexual behaviors are strongly associated with alcohol use, mental health conditions, and demographic factors in both men and women living with HIV (Adedimeji et al., 2014; Balis, 2020; Hutton et al., 2012; Kiene et al., 2017; Nakiganda et al., 2017; Parks et al., 2012; Patrick et al., 2012; Scott-Sheldon et al., 2013; Shukla et al., 2016; Wondemagegn & Berkessa, 2020; Yaya et al., 2014). However, there is a dearth of studies on risky sexual behaviors specifically in WLHIV in the United States.

WLHIV represent a significant portion of people living with HIV, as almost 7000 women were diagnosed with HIV in the U.S. in 2019 and almost one-quarter of people living with HIV in the U.S. are women (Centers for Disease Control and Prevention, 2021; Philbin et al., 2020). In the state of Florida over a quarter (27%) of people living with HIV are women (Floridahealth.gov, 2017). Worldwide women and girls represent over half.

(20.2 million) of the people living with HIV (UNAIDS, 2022). It is crucial to understand the prevalence of risky sexual behaviors in WLHIV and the variables that influence risky sexual behaviors. WLHIV experience poor health outcomes including higher morbidity and mortality rates, poorer antiretroviral (ART) medication adherence, poorer viral suppression, and are more likely to receive an acquired immunodeficiency syndrome (AIDS) diagnosis compared to men living with HIV (Centers for Disease Control and Prevention, 2021; Philbin et al., 2020; Rice et al., 2018). More importantly, reproductive-age WLHIV experience a high burden of adverse HIV health outcomes (Grewe et al., 2016; Meditz et al., 2011; Momplaisir et al., 2018; Murphy et al., 2013; Sheth et al., 2021), and are more likely to report poor long-term HIV health outcomes compared to men and older women (Sheth et al., 2021). These poor HIV health outcomes are especially seen in postpartum women and mothers living with HIV (Adams et al., 2015; Buchberg et al., 2015; Malee et al., 2014). It is crucial to understand the unique factors and variables that are associated with risky sexual behaviors in reproductive-age WLHIV, as this can help our understanding of why this population experiences more adverse health outcomes including HIV and reproductive health outcomes.

Substance use and mental health-related factors may also be associated with risky sexual behaviors in WLHIV. Evidence suggests a high prevalence of unhealthy alcohol use and marijuana use among WLHIV, particularly among WLHIV of reproductive age, compared with women in the general population (Barai et al., 2016; Frazier et al., 2020; Shokoohi et al., 2018; Yee et al., 2021). WLHIV have a higher burden of anxiety and depressive symptoms compared to women in the general population (Bernard et al., 2017; Yousuf et al., 2020). Given the high prevalence of alcohol and marijuana use and anxiety and depressive symptoms in WLHIV, substance use and uncontrolled anxiety and depression may be contributing to risky sexual behaviors in this high-risk population. Due to the overlap of substance use and mental health symptoms and their potential impact on risky sexual behaviors; Syndemic Theory is an appropriate theoretical model to guide this study. Syndemic Theory is a theoretical model that explains how a group of health conditions (i.e., substance use and mental health symptoms) can work together to create negative health outcomes and increase the burden of disease (Douglas-Vail, 2016; Tsuyuki et al., 2017). Additionally, this theory has been used extensively in previous literature to examine the burden of HIV (Douglas-Vail, 2016).

Florida is part of the group of southern states in the U.S. where 52% of new HIV cases occur (HIV in the Southern United States—Centers for disease, 2022). Exploring risky sexual behaviors among WLHIV in Florida may be the critical first step in decreasing the incidence of HIV and impacting efforts toward ending the HIV epidemic in the US. In this study, we performed a secondary analysis on a representative sample of WLWH from the state of Florida enrolled in the Florida Cohort Study. The Florida Cohort Study is an ongoing cross-sectional analysis of de-identified survey data from multiple clinical and community settings in Florida. The purpose of the Florida Cohort Study is to assess how community, clinic, and individual factors influence HIV clinical outcomes and healthcare access in people living with HIV in Florida (Ibañez et al., 2021). The aims of this study were to (1) describe sexual behaviors in a cohort of WLHIV in Florida, (2) determine whether demographic characteristics, substance use, and mental health symptoms are associated with risky sexual behaviors in a cohort of WLHIV in Florida, and (3) explore whether the relationship between substance use and mental health symptoms and risky sexual behaviors differs in reproductive-age (age 18–49), compared to non-reproductive-age WLHIV (age 50+).

METHODS

The study design is a secondary analysis of baseline data from the cross-sectional analysis of the Florida Cohort Study collected between 2014 and 2017 and has been previously described in detail elsewhere (Ibañez et al., 2021). Briefly, participants were recruited face-to-face by study research assistants or partnering research staff. Participants could also be recruited from flyers placed around partnering clinical sites. Participants and data were collected from 9 community clinics and health departments across the state of Florida. Upon agreeing to participate in the study and signing an informed consent form, participants completed a self-administered and de-identified questionnaire. The questionnaire was completed via paper or electronic device using Research Electronic Data Capture (REDCap), a secure data collection software program used by the University of Florida. The questionnaire was completed in approximately 30–45 min and included topics on substance use, demographics, sexual behaviors, and mental health. Participants were compensated $25 upon completion of this survey. This survey and the Florida Cohort Study (protocol #201500849) received prior approval from both the University of Florida and the Florida Department of Health Institutional Review Boards.

Participants

We analyzed data on 304 WLHIV enrolled in the Florida Cohort Study. Women were eligible if they self-reported that they were assigned female at birth, had a confirmed HIV diagnosis, were 18 years of age or older, and resided in the state of Florida. WLHIV from this sample were asked about their sexual orientation and the sex of their sex partners in the Florida Cohort Survey. Data including labs on viral load, CD4 counts, and HIV treatment engagement were collected for the Florida Cohort Study but not used in this analysis.

Measures

Risky sexual behavior measure

For this study risky sexual behavior was defined based on self-report of one or more of the following: (1) at least one sexually transmitted infection (STI) diagnosis in the past 12 months, (2) two or more sexual partners in the past 12 months or (3) any inconsistent condom use in the past 12 months. While previous literature does not have a uniform definition of risky sexual behavior in PLWH, previous studies have largely defined risky sexual behavior as any inconsistent condom use, multiple sexual partners, and STI diagnosis (Cook et al., 2006; Crepaz & Marks, 2002; Du et al., 2015; Shukla et al., 2016).

Mental health symptoms measure

Mental health symptoms were assessed with the Patient Health Questionnaire Depression Scale (PHQ-8) to assess depressive symptoms, and the Generalized Anxiety Disorder-7 (GAD-7) to assess anxiety symptoms. Anxiety scores were categorized with scores of 1–4 indicating no symptoms, 5–9 mild, 10–14 moderate, and ≥15 severe anxiety symptoms (Barrera et al., 2016). Depression scores were categorized as scores from 1 to 4 indicating no symptoms, 5–9 mild, 10–14 moderate, and ≥15 severe depressive symptoms (Barrera et al., 2016). The PHQ-8 and GAD-7 are both valid and reliable tools that have been used in clinical settings and research settings to assess symptoms of mental health condition measures (Pressler et al., 2011; Spitzer et al., 2006). Anxiety and depressive symptoms were exclusively analyzed in this analysis due to the common occurrence and higher burden of anxiety and depressive symptoms WLHIV experience (Bernard et al., 2017; Yousuf et al., 2020). The Cronbach α for the PHQ-8 was 0.87 and 0.91 for the GAD-7. Validity measure using confirmatory factor analysis testing a single-factor model indicated adequate fit for the GAD-7 (χ2 (14) = 101.04, p < 0.0001, CFI = 0.9387, RMSEA = 0.1474, Standardized RMR = 0.0397). Validity measure using confirmatory factor analysis and testing a single-factor model indicated adequate fit for the PHQ-8 (χ2 (20) =124.89, p < 0.0001, CFI = 0.8861, RMSEA = 0.1379, Standardized RMR = 0.0631).

Substance use measure

Alcohol-related problems were measured via two measures, (1) the Short Inventory of Problems Revised (SIP-2R) and (2) heavy drinking and binge drinking which were categorized based on the validated National Institute of Health on Alcohol Abuse and Alcoholism (NIAAA) guidelines for heavy drinking (>7 drinks per week) and binge drinking (>4 drinks/occasion) (Cook et al., 2017). The SIP-2R measures alcohol-related problems outside of the volume of alcohol consumed i.e., alcohol-related problems (Fisk et al., 2021). The SIP-2R is a 15-item self-reported measure that looks at interpersonal, intrapersonal, physical, impulse control, and social responsibility as domains for alcohol-related problems. The SIP-2R is a reliable and validated measure that has been used in previous research (Feinn et al., 2003). For this study categories of 0, 1–5, 6–10, and 11–15 were used for an overall SIP-2R score, with higher scores representing higher problems. The internal consistency and reliability (Cronbach α) of the SIP-2R was 0.96. Self-reported marijuana use was defined as self-reporting any use in the past 3 months (yes or no). Validity measure using confirmatory factor analysis and testing a single-factor model indicate adequate fit for the SIP-2R (χ2 (90) =477.47, p < 0.0001, CFI = 0.8283, RMSEA = 0.1578, Standardized RMR = 0.0600).

Although other drug use information was available, we focused on alcohol and marijuana in this analysis because they were the most common substances used in this sample.

Socio-Demographic measures

Age was categorized as reproductive age (18–49 years of age) or non-reproductive-age (50+ years of age), based on the World Health Organization (WHO) definition of reproductive-age (World Health Organization, 2022). Ethnicity and race were categorized as Hispanic, non-Hispanic white, non-Hispanic Black, and non-Hispanic other. Education was categorized as < high school, high school diploma or equivalent, and > high school.

ANALYTIC APPROACH

SAS 9.4 (SAS Institute, Cary, NC) was used for statistical analysis. Descriptive statistics, bivariate analysis (chi-square analysis), and logistic regression were conducted. Bivariate analysis was conducted on the entire sample (n = 304), and anxiety and depressive symptoms, heavy drinking, binge drinking, alcohol-related problems score, any marijuana use, and socio-demographic variables (age, race and ethnicity, education) were used as predictors for the outcome of self-reporting one or more risky sexual behavior. Bivariate analyses were also done separately on the reproductive-age women in the sample (n = 157) and non-reproductive-age women (n = 147) with mental health symptoms and substance use variables as predictors of the outcome of self-report of one or more of the risky sexual behavior. Separate logistic regression analyses, including only the statistically significant variables from bivariate analyses (p < 0.1), were then performed on the whole sample (n = 304), reproductive-age WLHIV (n = 157), and non-reproductive-age WLHIV (n = 147). As this was a secondary analysis of existing data, the sample size was fixed at the number of women in the existing dataset.

RESULTS

Sample characteristics

The mean age of this sample (n = 304) was 47.8 years. Approximately half (51.6%) of the sample was of reproductive-age and 48.3% of the sample was of non-reproductive-age. Reproductive-age WLHIV compared to non-reproductive-age WLHIV had a higher frequency of reporting ≥1 risky sexual behavior, and each of the individual behaviors assessed included inconsistent condom use, ≥ 1 STI, and ≥ 2 sexual partners (see Table 1). Additionally, reproductive-age WLHIV reported yes to marijuana use and binge drinking at a higher frequency than non-reproductive-age WLHIV.

TABLE 1.

Demographic variables in reproductive-age WLHIV vs. non-reproductive-age WLHIV.

Variables reproductive-age (18–49) n (%) Variables non-reproductive-age (50+) n (%)
Age n = 157(51.6%) Age n = 147 (48.3%)
 18–29 14 (4.6) 50–59 118 (38.8)
 30–39 53 (17.4) 60–64 17 (5.5)
 40–49 90 (29.6) >65 12 (3.9)
Race/Ethnicity n = 157 Race/Ethnicity n = 147
 Hispanic 16 (10.2) Hispanic 26 (17.7)
 Not Hispanic, white 25 (16.0) Not Hispanic, white 26 (17.7)
 Not Hispanic, black 108 (68.7) Not Hispanic, black 93 (63.3)
 Not Hispanic, other 8 (5.1) Not Hispanic, other 2 (1.3)
Education n = 156 Education n = 146
 <High School 77 (49.4) <High school 64 (43.8)
 High school diploma or Equivalent 47 (30.1) High school diploma or Equivalent 42 (28.8)
 >High school 32 (20.5) >High school 40 (27.4)
≥1 risky sexual behavior n = 157 ≥1 risky sexual behavior n = 147
 Yes 81 (51.6) Yes 47 (32.0)
 No 76 (48.4) No 100 (68.0)
Inconsistent condom use n = 151 Inconsistent condom use n = 145
 Yes 57 (37.8) Yes 30 (20.7)
 No 94 (62.2) No 115 (79.3)
≥1 STI n = 154 ≥1 STI n = 142
 Yes 23 (15.0) Yes 16 (11.3)
 No 131 (85.0) No 126 (88.7)
≥2 sexual partners n = 153 ≥2 sexual partners n = 141
 Yes 30 (19.6) Yes 14 (10.0)
 No 123 (80.4) No 127 (90.0)
Anxiety symptoms n = 151 Anxiety symptoms n = 138
 1–4 None-Minimal 64 (42.4) 1–4 None-Minimal 58 (42.0)
 5–9 Mild 38 (25.2) 5–9 Mild 35 (25.4)
 10–14 Moderate 24 (15.9) 10–14 Moderate 20 (14.5)
 ≥15 Severe 25 (16.5) ≥15 Severe 25 (18.1)
Depressive symptoms n = 149 Depressive symptoms n = 132
 1–4 None-Minimal 40 (26.9) 1–4 None-Minimal 45 (34.1)
 5–9 Mild 55 (36.9) 5–9 Mild 36 (27.3)
 10–14 Moderate 29 (19.5) 10–14 Moderate 24 (18.2)
 ≥15 Severe 25 (16.7) ≥15 Severe 27 (20.4)
Marijuana use n = 131 Marijuana use n = 125
 Yes 45 (34.3) Yes 33 (26.4)
 No 86 (65.7) No 92 (73.6)
Heavy drinking n = 153 Heavy drinking n = 134
 Yes 13 (8.5) Yes 14 (10.5)
 No 140 (91.5) No 120 (89.5)
Binge drinking n = 156 Binge drinking n = 140
 Yes 53 (34.0) Yes 45 (32.1)
 No 103 (66.0) No 95 (67.9)
SIP-2R n = 148 SI P-2R n = 138
 0 109 (73.7) 0 103 (74.6)
 1–5 20 (13.5) 1–5 15 (10.9)
 6–10 8 (5.4) 6–10 12 (8.7)
 11–15 11 (7.4) 11–15 8 (5.8)
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Note: Descriptive statistics were performed. SIP-2R is a measure of alcohol-related problems on a scale from 0 to 15.

Abbreviation: SD, standard deviation.

Bivariate analysis of factors associated with having ≥1 risky sexual behavior

In the total sample (n = 304), neither anxiety nor depression symptoms were significantly associated with ≥1 risky sexual behavior (Table 2). Women were more likely to engage in risky sexual behavior if they reported marijuana use, reported binge drinking or had a higher alcohol-related problem score (see Table 2). Age was also significantly associated with ≥1 risky sexual behavior, as 63.2% of reproductive-age WLHIV reported at least 1 risky sexual behavior compared to 36.7% of non-reproductive-age women (p = 0.0005). Race and education were not significantly associated with reporting ≥1 risky sexual behavior in WLHIV.

TABLE 2.

The proportion of WLHIV reporting ≥1 risky sexual behavior according to mental health symptoms, substance use, and demographic variables (n = 304).

Variables Yes to ≥1 risky sexual behaviors, n (%) p-value
Anxiety symptoms n = 123 0.30
 1–4 None-Minimal 45 (36.8)
 5–9 Mild 32 (43.8)
 10–14 Moderate 20 (45.4)
 ≥15 Severe 26 (52.0)
Depressive symptoms n = 118 0.56
 1–4 None-Minimal 32 (37.6)
 5–9 Mild 38 (41.7)
 10–14 Moderate 22 (41.5)
 ≥15 Severe 26 (50.0)
Heavy drinking n = 121 0.13
 Yes 15 (55.5)
 No 106 (40.7)
Binge drinking n = 125 0.05*
 Yes 49 (50.0)
 No 76 (38.3)
Marijuana use n = 106 0.03*
 Yes 40 (51.2)
 No 66 (37.0)
SIP-2R n = 120 0.01*
 0 80 (37.7)
 1–5 16 (45.7)
 6–10 10 (50.0)
 11–15 14 (73.6)
Age n = 128 0.0005*
 18–49years 81 (63.2)
 50+ years 47 (36.7)
Race/Ethnicity n = 128 0.95
 Hispanic 17 (40.4)
 Not Hispanic, white 22 (43.1)
 Not Hispanic, black 84 (41.7)
 Not Hispanic, other 5 (50.0)
Education n = 128 0.87
 <High school 60 (42.5)
 High school diploma or equivalent 36 (40.4)
 >High school 32 (44.4)
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Note: Proportion differences reporting yes to ≥1 risky sexual behavior were tested using the Chi-square test. SIP-2R is a measure of alcohol-related problems on a scale from 0 to 15.

*

Indicates statistical significance (p < 0.1).

Bivariate analysis reproductive-age WLHIV

Among the reproductive-age WLHIV in this sample, anxiety symptoms and alcohol-related problems were significantly associated with ≥1 risky sexual behavior (seen in Table 3). Depression symptoms, binge drinking, heavy drinking, and marijuana use were not significantly associated with having ≥1 risky sexual behavior. Additionally, race and education were not significantly associated with reporting ≥1 risky sexual behavior in reproductive-age WLHIV.

TABLE 3.

The proportion of reproductive-age WLHIV (n = 157) and non-reproductive-age WLHIV (n = 147) reporting >1 risky sexual behavior according to mental health symptoms, substance use, and demographic variables as predictors.

Variables Reproductive-age (N = 157)
 p-value Non-reproductive-age (N = 147)
 p-value
Yes to ≥1 risky sexual behaviors n (%) Yes to ≥1 risky sexual behaviors n (%)
Anxiety symptoms n = 80 0.07* n = 43 0.75
 1–4 None-Minimal 29 (45.3) 16 (27.5)
 5–9 Mild 19 (50.0) 13 (37.1)
 10–14 Moderate 13 (54.1) 7 (35.0)
 ≥15 Severe 19 (76.0) 7 (28.0)
Depressive symptoms n = 80 0.16 n = 38 0.48
 1–4 None-Minimal 17 (42.5) 15 (33.3)
 5–9 Mild 28 (50.9) 10 (27.7)
 10–14 Moderate 18 (62.0) 4 (16.6)
 ≥15 Severe 17 (68.0) 9 (33.3)
Heavy drinking n = 78 0.16 n = 43 0.36
 Yes 9 (69.2) 6 (42.8)
 No 69 (49.2) 37 (30.8)
Binge drinking n = 80 0.10 n = 45 0.32
 Yes 48 (46.6) 17 (37.7)
 No 32 (60.3) 28 (29.4)
Marijuana use n = 69 0.11 n = 37 0.32
 Yes 28 (62.2) 12 (36.3)
 No 41 (47.6) 25 (27.1)
SIP-2R n = 77 0.02* n = 43 0.50
 0 51 (46.7) 29 (28.1)
 1–5 10 (50.0) 6 (40.0)
 6–10 6(75.0) 4 (33.3)
 11–15 10 (90.9) 4 (50.0)
Race/Ethnicity n = 81 0.96 n = 47 0.80
 Hispanic 9 (56.2) 8 (30.7)
 Not Hispanic, white 12 (48.0) 10 (38.4)
 Not Hispanic, black 56 (51.8) 28 (30.1)
 Not Hispanic, other 4 (50.0) 1 (50.0)
Education n = 81 0.54 n = 47 0.57
 <High school 37 (48.0) 23 (35.9)
 High school diploma or equivalent 25 (53.1) 11 (26.1)
 >High school 19 (59.3) 13 (32.5)
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Note: Proportion differences reporting yes to ≥1 risky sexual behaviors were tested using the chi-square test. SIP-2R is a measure of alcohol-related problems on a scale from 0 to 15.

*

Indicates statistical significance (p < 0.1).

Bivariate analysis Non-Reproductive age WLHIV

Among the non-reproductive-age WLHIV in this sample, none of the assessed variables were significant predictors of reporting ≥1 risky sexual behavior in non-reproductive-age WLHIV.

Logistic regression

In the total sample of WLHIV (N = 304), binge drinking (OR: 1.60, 95% CI: 0.97–2.64, χ2: 3.48 p = 0.06), marijuana use (OR: 1.68, 95% CI: 0.96–2.92, χ2: 3.40 p = 0.06), and alcohol-related problems scores between 11–15 (OR: 4.68, 95% CI: 1.58–13.7, χ2: 7.83 p = 0.0051) were each significantly associated with a higher odds of reporting risky sexual behavior. In the subgroup analyses, severe anxiety symptoms and alcohol-related problems were significantly associated with risky sexual behavior only in reproductive-age WLHIV (Table 4). Specifically, severe anxiety symptoms were associated with higher odds of reporting risky sexual behavior (OR: 3.82, 95% CI: 1.34–10.82, χ2:6.36 p = 0.01), and persons with an alcohol-related problem score of 11–15 (vs. 0–5) had significantly higher odds of reporting risky sexual behavior (OR: 11.37, 95% CI: 1.40–91.91, χ2:5.19 p = 0.02).

TABLE 4.

Logistic Regression of Significant Predictors of Self-Reporting Risky Sexual Behavior in Reproductive-age WLHIV (n = 157) and all WLHIV (n = 304).

Predictor variable (all WLHIV), n = 304 Point estimate 95% CI Chi-square p-value
Binge drinking 1.60 0.97 2.64 3.48 *0.06
Marijuana use 1.68 0.96 2.92 3.40 *0.06
SIP-2R 11–15 (11–15 vs. 0) 4.68 1.58 13.7 7.83 *0.0051
Predictor variable (Reproductive-age), n = 157 Point estimate 95% CI Chi-square p-value
Anxiety symptoms Severe (≥15 severe vs. 1–4 none) 3.82 1.34 10.8 6.36 *0.01
SIP-2R 11–15 (11–15 vs. 0) 11.37 1.40 91.9 5.19 *0.02
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Note: Logistic regression was done on all WLHIV (n = 304) and reproductive-age WLHIV (n = 157). SIP-2R is a measure of alcohol-related problems on a scale from 0 to 15.

*

Indicates statistical significance (p < 0.1).

DISCUSSION

This study described sexual behaviors, determined whether demographic characteristics, substance use, and mental health symptoms are associated with risky sexual behavior, and explored whether the relationship between substance use and mental health symptoms and risky sexual behavior differs in reproductive-age vs. non-reproductive-age in a cohort of WLHIV in Florida. One of the key findings from this study is that there is a higher frequency of high-risk sexual behavior specifically in younger reproductive-age women. The significance of age and being of reproductive-age in association with risky sexual behavior in WLHIV may be due to a lack of education and knowledge at a younger age about the adverse health outcomes associated with risky sexual behavior. The neurochemical changes associated with reproductive age (i.e., pregnancy and postpartum, and postmenopausal) could also reduce engagement in risky sexual behavior in older women (Malee et al., 2014).

Results also indicated that age, alcohol use, and marijuana were associated with risky sexual behavior in women. In reproductive-age WLHIV in the sample, anxiety symptoms and alcohol-related problems were associated with risky sexual behavior. These findings are consistent with results from international studies looking at risky sexual behavior in WLHIV in middle- and lower-income countries which found risky sexual behavior is strongly associated with alcohol use, mental health conditions, and demographic variables in WLHIV (Adedimeji et al., 2014; Nakiganda et al., 2017; Shukla et al., 2016). This current study also examined the relationship between marijuana use and alcohol use on risky sexual behavior but did not specifically examine substance use disorder (SUD). Previous research suggests that more extreme measures of substance use including problematic alcohol consumption measures are more likely to be significantly associated with risky sexual behavior and STIs compared to more general measures (Cook & Clark, 2005). Therefore, future research in this area is needed.

This study holds clinical significance for nurses in both the U.S. and globally who provide nursing care to WLHIV with mental health symptoms or who use substances. Nurses can use the results gleaned from this current study as a guide to not only provide a referral to mental health and substance use services but can also provide counseling and education on safe sex practices. Literature and clinical guidelines exist for screening mental health symptoms, and substance use (CDC, 2014; CDC, 2022). Additionally, literature that explores how to reduce risky sexual behavior in young reproductive-age WLHIV is limited (Brothers et al., 2016). What needs further evaluation is whether current tools recommended for screening (screening for mental health symptoms and substance use) are working effectively and are regularly used with reproductive-age WLHIV. Further research is also needed to determine gaps that exist in the screening and referral system for substance use and mental health care in WLHIV in the U.S. and globally.

LIMITATIONS

It is important to note some of the limitations of this study. As participants from this study were largely recruited from healthcare settings and clinics, the sample may be representative of women who are more engaged in healthcare, and thus participants may be more health-conscious and have better health outcomes compared with the general population of WLHIV. It is also important to note that data collection for this sample of WLHIV in Florida was conducted from 2014 to 2017, and thus the results from this data may represent outdated trends and behaviors in WLHIV. However, very little research after 2017 has been done on risky sexual behavior specifically in reproductive-age WLHIV in the U.S. Recent literature from 2017 onward that has been done on risky sexual behavior in WLHIV and PLWH are reported mainly from low and middle-income countries, primarily in sub-Saharan Africa (Balis, 2020; Molla & Gregory, 2017). However, recent literature in the U.S. found that women with 12-month behavioral health disorders (diagnosis of a 12-month DSM-IV [The Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition]) were more likely to engage in substance use and risky sexual behavior (Cook et al., 2018).

The risky sexual behavior measure was not based on a standard, validated, measurement, but on definitions used from previous studies on the topic of risky sexual behavior in people living with HIV. An additional limitation of this study is that only depressive and anxiety symptoms were analyzed for this study, and other mental health conditions that are less common were not included. Similarly, the analysis focused on alcohol and marijuana use, which were the most used substances, but other drugs might also be related to risky sexual behavior. Additionally, this study did not specifically examine substance use disorder (SUD).

CONCLUSION

Marijuana use, binge drinking, and alcohol-related problems appear to have a relationship with risky sexual behavior in WLHIV regardless of age. Reproductive-age also appears to influence risky sexual behavior in WLHIV. Additionally, reporting severe anxiety symptoms and high alcohol-related problems in reproductive-age WLHIV appears to increase the odds of engaging in risky sexual behavior as well. This study holds clinical significance for nurses and other clinicians providing healthcare to WLHIV and indicates that it could be beneficial to do more screening for mental health and alcohol use in younger reproductive-age WLHIV. Future research should focus on implementation science aimed at determining if the current tools recommended for screening for mental health symptoms and substance use are working effectively and if these screening tools are regularly provided to WLHIV by nurses and other clinicians in the U.S. and globally. Additionally, future research should focus on what gaps in the screening and referral system for alcohol use and mental health care might exist for WLHIV receiving nursing care in the U.S. and globally.

ACKNOWLEDGMENTS

We would like to thank all the participants and study staff who committed time to make the Florida Cohort Study possible. This study is supported by the following grants U24AA022002, U24AA022003, and T32AA025877. Sigma Theta Tau: Alpha Theta Chapter University of Florida College of Nursing.

Funding information

National Institute on Alcohol Abuse and Alcoholism, Grant/Award Number: T32AA025877, U24AA022002 and U24AA022003

Footnotes

CONFLICT OF INTEREST STATEMENT

The authors report no conflicts of interest or competing interest.

CLINICAL RESOURCE

Florida Department of Health. HIV/AIDS. https://www.floridahealth.gov/diseases-and-conditions/aids/.

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