Abstract
Objectives. We examined the associations between depressive symptoms and sexual identity and behavior among women with or at risk for HIV.
Methods. We analyzed longitudinal data from 1811 participants in the Women’s Interagency HIV Study (WIHS) from 1994 to 2013 in Brooklyn and the Bronx, New York; Chicago, Illinois; Washington, DC; and Los Angeles and San Francisco, California, by comparing depressive symptoms by baseline sexual identity and ongoing sexual behavior. We controlled for age, socioeconomic status, violence history, and substance use.
Results. In separate analyses, bisexual women and women who reported having sex with both men and women during follow-up had higher unadjusted odds of depressive symptoms compared with heterosexuals and women who reported only having male sexual partners (adjusted odd ratio [AOR] = 1.36; 95% confidence interval [CI] = 1.10, 1.69 and AOR = 1.21; 95% CI = 1.06, 1.37, respectively). Age was a significant effect modifier in multivariable analysis; sexual minority women had increased odds of depressive symptoms in early adulthood, but they did not have these odds at midlife. Odds of depressive symptoms were lower among some sexual minority women at older ages.
Conclusions. Patterns of depressive symptoms over the life course of sexual minority women with or at risk for HIV might differ from heterosexual women and from patterns observed in the general aging population.
Depression is a major health concern for women. According to the Centers for Disease Control and Prevention (CDC), 10% of US women reported any depression and 5% reported major depression in the previous 2 weeks.1 Depression has been reported in 19% to 62%2–4 of HIV-infected women and is associated with reduced cognitive function,5 decreased adherence to highly active antiretroviral therapy (HAART),6 higher rates of unprotected sex among substance users,7 and increased mortality.2,6
Women with or at risk for HIV are often exposed to factors such as poverty,8 substance use, and violence,9–11 which can independently and jointly contribute to depression. A recent study found that any combination of intimate partner violence (IPV), substance use, and HIV infection increased the odds of depression.12 Lower socioeconomic status (SES) in women12 and HIV infection4,5 were also independently associated with depression. However, studies showed no association among HIV stage, HAART use,4,8 CD4 count,8,13 or viral load and depression.4,8,13
There is a strong association between sexual minority status (i.e., women who identify as lesbian or bisexual or have female sex partners) and poor mental health. In a US survey, lifetime major depression was reported by 42% of lesbians, 52% of bisexuals, and 27% of heterosexual women (P < .01); in the same study, major depression was reported by 15% of women who have sex with women (WSW), 51% of women who have sex with men and women (WSMW), and 27% of women who have sex with men (WSM; P < .01).14 In this study, we examined 2 aspects of sexual orientation15–17: sexual identity and sexual behavior. Although sexual attraction is also considered part of an individual’s sexual orientation, data on attraction was not collected in the original study.
Despite the strong association between sexual minority status and depression, it is unknown whether sexual minority status acts as an independent predictor or effect modifier of depressive symptoms among women affected by HIV, substance use, and violence. Our original hypothesis was that lesbian, bisexual, and WSMW (but not WSW) would have higher odds of depression, with race/ethnicity acting as a potential effect modifier.
METHODS
Details of the Women’s Interagency HIV Study (WIHS) were previously reported.18,19 Briefly, 4137 women (3061 HIV+ and 1076 HIV−) were enrolled in 3 cohorts (1994–1995, 2001–2002, and 2011–2012) at sites in Brooklyn and the Bronx, New York; Chicago, Illinois; Washington, DC; and Los Angeles and San Francisco, California. Participants underwent detailed interviews and physical examinations every 6 months. This study was approved by the institutional review board at each participating site and the WIHS Executive Committee. All participants provided written informed consent.
WIHS eligibility requirements were previously described18,19; relevant to our analysis, HIV-uninfected women must have had any sex with a high-risk male partner (i.e., HIV-infected or multiple partners without condom use) or used injection drugs in the last year to be eligible. Women included in our analyses had 2 or more follow-up visits, 1 or more sexual partners, and reported sexual identity (excluding “other”). For the identity analysis, 829 women were not eligible, and 1144 women were excluded because of missing data (1287 and 1039, respectively, for the behavioral sample), mostly from the California sites, where abuse data were not collected at all visits. Women who were excluded did not differ from the analysis groups in Centers for Epidemiologic Studies—Depression (CES-D) scores, sexual identity, or behavior.
Exposures and Outcomes
For the primary exposures, participants were asked their sexual identity (heterosexual or straight, bisexual, lesbian or gay, other) at baseline. At each visit, they were asked how many men and women they had vaginal, oral, or anal sex with since their last visit. We created a sexual behavior variable, which was defined as the gender of partners over the past 3 years (men only, women only, or both men and women). This variable was updated at each visit, such that sexual behavior at visit 6 was defined by partners from visits 1 through 6, sexual behavior at visit 7 was defined by partners from visits 2 through 7, etc. Therefore, sexual identity was constant for each participant, whereas sexual behavior could change over time. In addition, the sample for the behavioral analysis was smaller, because data from the first 5 visits were not included; the index visit was the first visit for when the sexual behavior variable could be created. We also distinguished same-sex identity or behavior from bisexual identity and behavior, because these effects could cancel out when they were combined.15
The primary outcome, depressive symptoms, was assessed by the CES-D.20 The CES-D contains 20 questions, asking participants how they felt in the past week, and was previously validated in sexual minority women.21 Participants were assessed every 6 months, except in 1999, 2000, and 2002, when they were assessed annually. The responses were summed, with the positive affect questions reverse coded. The scale ranges from 0 to 60, and the standard cutoff of 16 or greater was used to indicate depressive symptoms.6,22 We also recalculated the CES-D by removing the somatic items (did not feel like eating, had trouble keeping my mind on what I was doing, felt that everything I did was an effort, sleep was restless, talked less than usual, could not get going) and using 16 or greater as the cutoff, because past research suggested confounding between the somatic subscale and HIV symptoms.13,23
Baseline covariates included childhood sexual abuse (reported age 17 years or younger to any sexual abuse question), education (< high school, high school or equivalent, > high school), and race/ethnicity (non-Hispanic White, non-Hispanic African American, Hispanic, other). Covariates updated at each visit included annual household income (< $6000, $6000–12 000, $12 000–18 000, > $18 000), health insurance, stable housing (living in own house or apartment), partnered status (married or living with partner), parity (cumulative number of children born), substance use (marijuana and cocaine, crack, or heroin use), smoking, risky drinking (≥ 3 drinks/day or ≥ 7 drinks/week24), sexual abuse, IPV, and physical violence. Sexual abuse, emotional or psychological IPV, and physical violence were assessed annually starting in 1999; data were carried backward 1 visit for these 3 variables. HIV serostatus was determined by enzyme-linked immunosorbent assay, confirmed with Western blot, and repeated at each visit for HIV-uninfected women, which allowed for the serostatus to change over time.
Analysis
We used bivariate analysis with the χ2 test to assess categorical variables and the Kruskal–Wallis test for nonnormal continuous variables to compare sociodemographic characteristics and depressive symptoms by sexual identity and sexual behavior. We used the Fisher exact χ2 test for small cell sizes. To account for temporality, we modeled the covariates on the CES-D scores at the following visit. We also tested the interactions between the primary explanatory variables (sexual identity or behavior) and all other covariates. We entered all the covariates, interactions, and polynomials of age and year with P < .2 into generalized estimating equations with an exchangeable correlation structure and logit link to account for within-subject correlation because of repeated measurements over time. We used backward selection at P < .05 to determine the final models; we included the study site, cohort, and visit year to control for temporal and geographic differences. To present the results from the interaction, we calculated the adjusted odds ratios (AORs) at each age and also calculated the predicted probabilities. Because of the small cell size, we did not present the data for women older than 60 years and for lesbians or WSW younger than 30 years.
We performed 2 sensitivity analyses. The first used women who survived throughout follow-up, to examine survivor bias. The second used the CES-D scale without the somatic component to account for potential confounding from HIV symptoms. All analyses were conducted in SAS version 9.3 (SAS Institute, Cary, NC).
RESULTS
The characteristics at baseline for the sexual identity sample and the index visit for the sexual behavior sample are shown in Table 1. The sexual identity sample included 108 lesbian (1486 visits), 177 bisexual (2450 visits), and 1879 heterosexual (26 270 visits) women; 13% of the sample identified as lesbian or bisexual. In the sexual behavior sample, there were 95 WSW, 137 WSMW, and 1579 WSM at the index visit. Sexual identity and behavior were not completely concordant, because heterosexual women reported female partners at 4% of follow-up visits, and lesbians reported male partners at 24% of follow-up visits.
TABLE 1—
Sample Characteristics at Baseline and Index Visit, by Sexual Identity and Sexual Behavior: Women’s Interagency HIV Study; Brooklyn and the Bronx, NY; Chicago, IL; Washington, DC; and Los Angeles and San Francisco, CA; 1994–2013
| Sexual Identity Sample |
Sexual Behavior Sample |
|||||||
| Characteristic | Lesbian (n = 108) | Bisexual (n = 177) | Heterosexual (n = 1879) | P | WSW (n = 95) | WSMW (n = 137) | WSM (n = 1579) | P |
| Total visits | 1486 | 2450 | 26 270 | . . . | 1231 | 1583 | 20 587 | . . . |
| CES-D | ||||||||
| ≥ 16, % | 50.0 | 55.9 | 44.5 | .009 | 46.3 | 47.5 | 41.8 | .32 |
| Mean (SD) | 17.4 (12.3) | 19.6 (14.2) | 15.91 (12.8) | .002 | 15.9 (12.6) | 18.1 (14.6) | 15.2 (12.4) | .11 |
| Range | 0–48 | 0–54 | 0–58 | . . . | 0–51 | 0–60 | 0–54 | . . . |
| Nonsomatic CES-D | ||||||||
| ≥ 16, % | 33.3 | 38.4 | 27.8 | .007 | 20.0 | 32.1 | 25.4 | .09 |
| Mean (SD) | 11.1 (9.0) | 13.3 (10.6) | 10.7 (9.4) | .006 | 9.9 (9.3) | 12.1 (10.6) | 10.0 (9.1) | .15 |
| Range | 0–34 | 0–39 | 0–42 | . . . | 0–38 | 0–42 | 0–39 | . . . |
| HIV positive, % | 62.0 | 68.9 | 73.4 | .02 | 61.1 | 58.4 | 73.6 | < .001 |
| Age, y | ||||||||
| Mean (SD) | 37.5 (7.6) | 38.4 (8.8) | 36.6 (8.7) | .02 | 40.2 (7.1) | 35.1 (7.1) | 38.2 (8.3) | < .001 |
| Range | 19–60 | 20–60 | 18–72 | . . . | 22–56 | 22–51 | 20–72 | . . . |
| Enrollment cohort, % | .37 | .001 | ||||||
| 1 | 68.5 | 61.0 | 62.2 | 72.6 | 52.6 | 66.4 | ||
| 2 | 27.8 | 29.4 | 28.7 | 27.4 | 47.5 | 33.6 | ||
| 3 | 3.7 | 9.6 | 9.1 | NA | NA | NA | ||
| Race/ethnicity, % | .16 | .39 | ||||||
| Non-Hispanic Black | 62.0 | 61.6 | 66.6 | 60.0 | 71.5 | 64.3 | ||
| Non-Hispanic White | 13.0 | 11.9 | 11.3 | 10.5 | 11.0 | 11.7 | ||
| Hispanic | 22.2 | 19.8 | 19.2 | 26.3 | 13.9 | 20.9 | ||
| Other | 2.8 | 6.8 | 2.9 | 3.2 | 3.7 | 3.1 | ||
| Highest education, % | .13 | .22 | ||||||
| < high school | 42.6 | 39.0 | 35.2 | 37.9 | 33.6 | 35.5 | ||
| High school/equivalent | 23.2 | 25.4 | 32.0 | 22.1 | 29.9 | 32.4 | ||
| > high school | 34.3 | 35.6 | 32.7 | 40.0 | 36.5 | 32.1 | ||
| Household income,a % | .06 | .26 | ||||||
| < $6000 | 23.2 | 29.4 | 26.3 | 29.5 | 26.3 | 22.5 | ||
| $6000–12 000 | 42.6 | 31.6 | 28.9 | 25.3 | 33.6 | 29.8 | ||
| $12 000–18 000 | 8.3 | 10.7 | 13.5 | 14.7 | 16.1 | 14.3 | ||
| > $18 000 | 25.9 | 28.3 | 31.4 | 30.5 | 24.1 | 33.5 | ||
| Employed,a % | 35.2 | 27.1 | 32.4 | .28 | 40.0 | 40.2 | 37.8 | .79 |
| Insured,a % | 81.5 | 78.0 | 82.2 | .38 | 80.0 | 71.5 | 82.8 | .004 |
| Stable housing,a % | 67.6 | 66.7 | 73.4 | .07 | 75.8 | 67.9 | 79.5 | .005 |
| Partnered,a % | 29.6 | 30.5 | 38.2 | .03 | 28.4 | 25.6 | 33.4 | .11 |
| Has ever had children, % | 58.3 | 74.0 | 80.2 | < .001 | 57.9 | 70.1 | 81.4 | < .001 |
| Childhood sexual abuse, % | 37.0 | 46.9 | 23.6 | < .001 | 42.1 | 35.8 | 24.2 | < .001 |
| Sexual abuse,a % | 2.8 | 5.1 | 3.0 | .32 | 2.1 | 2.9 | 2.2 | .75b |
| Emotional IPV,a % | 14.8 | 11.9 | 7.5 | .004 | 6.3 | 8.8 | 5.2 | .2 |
| Physical violence,a % | 8.3 | 10.2 | 6.9 | .23 | 5.3 | 13.1 | 3.4 | < .001 |
| Smoking status,a % | < .001 | .001 | ||||||
| Current smoker | 69.4 | 72.9 | 52.7 | 66.3 | 64.2 | 52.8 | ||
| Former smoker | 20.4 | 16.4 | 16.6 | 25.3 | 17.5 | 20.1 | ||
| Never smoked | 10.2 | 10.7 | 30.7 | 8.4 | 18.3 | 27.1 | ||
| Risky drinking,a % | 22.2 | 21.6 | 18.1 | .31 | 19.0 | 20.4 | 14.9 | .14 |
| Marijuana use, a % | 27.8 | 33.9 | 22.3 | .001 | 26.3 | 36.5 | 19.6 | < .001 |
| Crack/cocaine/heroin use,a % | 25.9 | 29.4 | 19.2 | .001 | 14.7 | 26.3 | 13.6 | < .001 |
| Sexual identity, % | . . . | < .001 | ||||||
| Lesbian | . . . | . . . | . . . | 73.7 | 13.1 | 0.3 | ||
| Bisexual | . . . | . . . | . . . | 21.1 | 39.4 | 4.9 | ||
| Heterosexual | . . . | . . . | . . . | 5.3 | 47.5 | 94.9 | ||
Note. AOR = adjusted odds ratio; CES-D = Centers for Epidemiologic Studies—Depression; IPV = intimate partner violence; WSM = women who have sex with men; WSMW = women who have sex with men and women; WSW = women who have sex with women. Percentages may not add to 100 because of rounding.
During previous 6 months.
Fisher exact test.
The sexual identity sample was mostly African American (65%) and had low income, with 56% reporting household incomes of less than $12 000 per year. Substance use was high, with 20% reporting recent crack, cocaine, or heroin use. At baseline, 72% of the participants were HIV-infected; 19 women (16 heterosexual and 3 bisexual) seroconverted during the study.
At baseline, 46% of the identity sample had CES-D scores of 16 or greater, including 56% of bisexuals compared with 45% of heterosexuals. When using the nonsomatic CES-D scale, 29% of participants had depressive symptoms. During follow-up, 77% of the identity sample met the criteria for depressive symptoms at least once (Table 2), and 23% met the criteria for chronic depressive symptoms (≥ 75% visits2,6). Characteristics of the sexual behavior sample were similar to those described previously. For heterosexuals and WSM, depressive symptoms increased with age (Figure 1).
TABLE 2—
Prevalence of Depression Over Follow-Up: Women’s Interagency HIV Study; Brooklyn and the Bronx, NY; Chicago, IL; Washington, DC; and Los Angeles and San Francisco, CA; 1994–2013
| Group | Ever CES-D ≥ 16 | ≥ 75% of Visits With CES-D ≥ 16 | Median Proportion of Visits When CES-D ≥ 16 |
| Identity sample (n = 2164), % | 77.1 | 23.3 | 32.0 |
| Lesbian (n = 108) | 84.3 | 17.6 | 33.0 |
| Bisexual (n = 177) | 84.7 | 27.1 | 42.0 |
| Heterosexual (n = 1879) | 76.0 | 23.3 | 29.0 |
| Behavioral sample (n = 1811),a % | 74.1 | 22.9 | 26.0 |
| WSW only (n = 71) | 78.9 | 16.9 | 25.0 |
| WSM+WSMW (n = 238) | 81.9 | 21.9 | 32.0 |
| WSW+WSM+WSMW (n = 54) | 88.9 | 18.5 | 36.0 |
| WSM only (n = 1443) | 72.0 | 23.6 | 25.0 |
Note. CES-D = Centers for Epidemiologic Studies—Depression; WSM = women who have sex with men; WSMW = women who have sex with men and women; WSW = women who have sex with women.
Not shown are 5 women who reported as WSW and WSM during follow-up.
FIGURE 1—
Predicted mean probabilities of depressive symptoms by age and (a) sexual identity and (b) sexual behavior: Women’s Interagency HIV Study; Brooklyn and the Bronx, NY; Chicago, IL; Washington, DC; and Los Angeles and San Francisco, CA; 1994–2013
Note. AOR = adjusted odds ratio; CES-D = Centers for Epidemiologic Studies—Depression; WSM = women who have sex with men; WSMW = women who have sex with men and women; WSW = women who sex with women. Dark circles indicated the ages when the AOR was significantly different from either WSM or hetersexual in the final models.
In the unadjusted analysis (not shown), bisexuals had higher odds of depressive symptoms compared with heterosexuals (OR = 1.36; 95% confidence interval [CI] = 1.10, 1.69; P = .004); the association for lesbians was not significant (OR = 1.00; 95% CI = 0.78, 1.28; P = .99). In the adjusted model, the interaction between sexual identity and age was highly significant (P = .001; Table 3). Bisexuals had higher odds of depression from ages 25 to 34 years; the ORs decreased with age and were almost protective at age 60 years (P = .05). For lesbians, the odds of depressive symptoms were increased at age 30 years (P = .05), but the odds of depressive symptoms were significantly decreased at ages 47 to 60 years. Figure 1 illustrates the trend over age for the 3 groups.
TABLE 3—
Adjusted Odds Ratios of Depressive Symptoms, With Age and Sexual Identity or Behavior Interaction: Women’s Interagency HIV Study; Brooklyn and the Bronx, NY; Chicago, IL; Washington, DC; and Los Angeles and San Francisco, CA; 1994–2013
| Variable | CES-D ≥ 16, AOR (95% CI) |
| Sexual identity modela | |
| Lesbian vs heterosexual, at same age, y | |
| 30 | 1.51 (0.99, 2.30) |
| 35 | 1.23 (0.89, 1.70) |
| 40 | 1.00 (0.77, 1.30) |
| 45 | 0.82 (0.63, 1.06) |
| 50 | 0.66 (0.48, 0.92) |
| 55 | 0.54 (0.35, 0.83) |
| 60 | 0.44 (0.26, 0.76) |
| Bisexual vs heterosexual, at same age, y | |
| 25 | 1.66 (1.11, 2.46) |
| 30 | 1.45 (1.06, 2.00) |
| 35 | 1.27 (0.99, 1.65) |
| 40 | 1.12 (0.89, 1.40) |
| 45 | 0.98 (0.78, 1.24) |
| 50 | 0.86 (0.65, 1.14) |
| 55 | 0.75 (0.53, 1.07) |
| 60 | 0.66 (0.43, 1.02) |
| HIV positive | 1.25 (1.09, 1.44) |
| Education (Ref: > high school) | |
| < high school degree | 2.07 (1.78, 2.41) |
| High school degree/equivalent | 1.48 (1.27, 1.73) |
| Employed | 0.83 (0.78, 0.89) |
| Income, $ (Ref: > 18 000) | |
| < 6000 | 1.19 (1.09, 1.30) |
| 6000–12 000 | 1.09 (1.01, 1.18) |
| 12 000–18 000 | 1.08 (1.00, 1.17) |
| Childhood sexual abuse | 1.38 (1.20, 1.58) |
| Sexual abuse | 1.41 (1.19, 1.66) |
| Emotional IPV | 1.20 (1.05, 1.38) |
| Physical violence | 1.45 (1.26, 1.67) |
| Smoking status (Ref: never smoked) | |
| Current smoker | 1.19 (1.03, 1.38) |
| Former smoker | 1.05 (0.90, 1.22) |
| Marijuana use | 1.12 (1.03, 1.21) |
| Crack/cocaine/heroin use | 1.32 (1.21, 1.46) |
| Sexual behavior modelb | |
| WSW vs WSM, at same age, y | |
| 30 | 1.85 (1.20, 2.86) |
| 35 | 1.55 (1.10, 2.17) |
| 40 | 1.30 (0.98, 1.71) |
| 45 | 1.09 (0.83, 1.42) |
| 50 | 0.91 (0.66, 1.25) |
| WSMW vs WSM, at same age, y | |
| 25 | 1.75 (1.27, 2.39) |
| 30 | 1.53 (1.20, 1.96) |
| 35 | 1.35 (1.12, 1.62) |
| 40 | 1.18 (1.03, 1.35) |
| 45 | 1.04 (0.91, 1.18) |
| 50 | 0.91 (0.78, 1.07) |
| 55 | 0.80 (0.64, 0.99) |
| 60 | 0.70 (0.53, 0.93) |
| HIV positive | 1.29 (1.10, 1.50) |
| Education (Ref: > high school) | |
| < high school degree | 2.03 (1.71, 2.41) |
| High school degree/equivalent | 1.48 (1.24, 1.76) |
| Employed | 0.81 (0.75, 0.88) |
| Income, $ (Ref: > $18 000) | |
| < 6000 | 1.19 (1.08, 1.31) |
| 6000–12 000 | 1.09 (1.00, 1.19) |
| 12 000–18 000 | 1.09 (0.99, 1.19) |
| Childhood sexual abuse | 1.36 (1.17, 1.59) |
| Sexual abuse | 1.50 (1.22, 1.85) |
| Emotional IPV | 1.22 (1.02, 1.44) |
| Physical violence | 1.39 (1.17, 1.66) |
| Smoking status (Ref: never smoked) | |
| Current smoker | 1.27 (1.07, 1.52) |
| Former smoker | 1.16 (0.96, 1.39) |
| Marijuana use | 1.12 (1.02, 1.24) |
| Crack/cocaine/heroin use | 1.33 (1.19, 1.49) |
Note. AOR = adjusted odds ratio; CES-D = Centers for Epidemiologic Studies—Depression; CI = confidence interval; IPV = intimate partner violence; WSM = women who have sex with men; WSMW = women who have sex with men and women; WSW = women who sex with women.
Includes year, year2, cohort, and site.
The unadjusted association between WSMW and depressive symptoms was significant (OR = 1.21; 95% CI = 1.06, 1.37; P = .003) compared with WSM; the association for WSW was not significant (OR = 1.12; 95% CI = 0.86, 1.46; P = .39). In the adjusted analysis, again, the only significant interaction was between age and sexual behavior (P = .001). The trends were similar to the results for the identity sample. WSMW at ages 25 to 41 years showed increased odds of depressive symptoms and decreased odds of depressive symptoms at ages 55 to 60 years compared with WSM. WSW at ages 30 to 39 years showed increased odds of depressive symptoms, whereas the protective effect at older ages did not reach significance.
HIV status was significantly associated with depressive symptoms (sexual identity model: AOR = 1.25; 95% CI = 1.09, 1.44; sexual behavior model: AOR = 1.29; 95% CI = 1.10, 1.50). Measures of low SES were also associated with depressive symptoms. In particular, women with less than a high school degree had twice the odds of depressive symptoms compared with those with more than high school degree; household income less than $6000 was also associated with increased odds, whereas employment was protective. Childhood sexual abuse, recent sexual abuse, IPV, and physical violence were all significantly associated with depressive symptoms. Recent use of crack, cocaine or heroin, and marijuana, and current smoking were all associated with increased odds of depressive symptoms. Other covariates, including race/ethnicity, parity, partner status, stable housing, insurance, and risky drinking were not significant and were not included in the final models.
Although we controlled for HIV status, residual confounding could remain between HIV symptoms and the somatic portion of the CES-D scale. As shown in Table 1, the rates of depressive symptoms decreased for all groups when the somatic component was removed, as would be expected. In the identity sample, 62% of visits that met criteria for depressive symptoms using the full CES-D also met the cutoff using the nonsomatic scale, with no differences by HIV status (sensitivity 62% among HIV-infected and 61% among HIV-uninfected). This suggested that HIV status did not bias the full CES-D measure. When we used the nonsomatic scale as the outcome with the final models, HIV remained significant, although it was slightly attenuated (AOR = 1.18; 95% CI = 1.01, 1.38; P = .03 identity sample). However, sensitivity of the nonsomatic CES-D did vary by sexual identity (69% for bisexuals, 55% for lesbians, and 62% for heterosexuals) and by sexual behavior (66% for WSMW, 46% for WSW, and 61% for WSM). This might explain why the age interactions were no longer significant in the full models using the nonsomatic CES-D (P = .05 for the identity sample and P = .07 for the behavioral sample; data available as a supplement to this article at http://www.ajph.org).
The second sensitivity analysis among women who survived follow-up examined whether the decreasing trend of depressive symptoms among sexual minorities was possibly caused by higher mortality rates among depressed sexual minority women. Eighty percent of the sample survived throughout follow-up, with no difference by sexual identity (P = .94) or sexual behavior (P = .86). Although the predicted probabilities of depressive symptoms were slightly lower overall, the results were very similar and suggested that mortality did not explain this pattern (see data available as a supplement to this article at http://www.ajph.org).
DISCUSSION
Depressive symptoms were highly prevalent in this sample; at baseline, 45% of heterosexual women, 50% of lesbians, and 56% of bisexuals had clinically significant depressive symptoms (CES-D scores ≥ 16). This was explained, in part, by low SES and the high rates of violence, substance use, and HIV infection, all of which were found to be independently associated with depressive symptoms. However, even in this vulnerable population, sexual minority status was an independent predictor of depressive symptoms.
Sexual minority women were at increased odds for depressive symptoms in their early 30s and at decreased odds for depressive symptoms after age 55 years, with some variation by identity and behavior. Much research has focused on depression in sexual minority youths,7,25-29 and there is growing interest in the unique challenges facing sexual minority seniors.30,31 However, we were unaware of any study that examined depressive symptoms in a longitudinal cohort that included sexual minority women. Because this was a sample of women with or at risk for HIV, these results were not generalizable to all sexual minority women. Additional research is needed to validate this finding. However, a retrospective study found that lesbians and bisexuals reported significantly higher levels of stress as adolescents compared with heterosexual women, but there were no differences in these levels as adults.32
It is plausible that youth and young adulthood present a uniquely challenging time for sexual minority women, leading to increased depressive symptoms. Perhaps these challenges, related to sexual identity, helped sexual minority women develop resiliency (the ability to adapt and thrive when faced with hardships33) and coping skills.34 For instance, sexual identity disclosure can be stressful, but can also lead to personal growth, increased self-esteem, and social support.35–37 Other research showed that increased identity integration (i.e., disclosure and involvement in lesbian, gay, bisexual, and transgender activities) and family and friend support led to decreased depression in lesbian, gay, bisexual, and transgender youths27,29 and older adults.30
These processes might not be the same for lesbians and bisexuals; Koh and Ross found suicidal ideation was higher in undisclosed lesbians and in disclosed bisexual women.32 In addition, sexual identity and sexual behaviors might be discordant because of drug use, transactional sex,38,39 or personal or cultural pressures to bear children.40 Explanations for the observed pattern of depressive symptoms might differ for women in these situations.
Physical symptoms of HIV might have inflated depressive symptoms among infected women; the inclusion of HIV status in the model and the sensitivity analysis using the nonsomatic CES-D scale suggested this was not the case. However, our analysis also revealed that WSW and lesbians showed larger reductions in depressive symptoms without the somatic subscale. This might be unique to this sample, or these women might express more physical symptoms of depression. The observed trend in depressive symptoms could also be explained if the most depressed sexual minority women died earlier. However, the sensitivity analysis of survivors suggested this was not the case. We found no effect of parity; more refined measures of childcare, family structure, and perinatal depression41 could explain some of the differences observed.
Although the research was limited, most studies suggested a U-shaped curve for depressive symptoms over the life span that decreased until ages 50 to 60 years and then increased in later years.42,43 However, heterosexuals and WSM in our sample showed generally increasing depressive symptoms from ages 30 to 60 years. One study found a similar increasing trend in women with lower education, as a measure of SES.44 An international study also found that depression generally decreased with age, but increased in middle age among those with physical comorbidities.45 Further research could elucidate whether lower income populations, which are possibly facing long-term stress, have different depressive patterns over the life span.
Study Limitations
There were several imitations to our study. We only assessed sexual identity at baseline; women, especially sexual minorities, often change their identities over time, potentially leading to misclassification.46,47 Sample sizes for women in their 20s and 60s were small; a broader age range would be more informative. Some covariates could conceptually be considered mediators (abuse) or outcomes (substance use) of depression and would likely attenuate the reported associations. However, because substance use was part of the inclusion criteria, and women with no male partners must have used illicit drugs to be enrolled or to have contracted HIV, we felt it was important to include them in the model. Most covariates were based on self-report. Although we controlled for some traumatic events, such as recent abuse, we were unable to distinguish reactive depressive episodes from clinical depression.
Strengths of our study included the large sample size and follow-up time; we were able to differentiate between lesbians and bisexuals, and between WSW and WSMW. Sensitivity analyses addressed possible additional confounders of mortality and HIV symptoms.
Conclusions
In this cohort of predominantly low-income minority women with or at risk for HIV, sexual minority status was a predictor of depressive symptoms in adulthood. Further research could identify factors that explain why some women showed decreasing depressive symptoms with age, and if these factors could be used to design future interventions, possibly by improving coping skills and resiliency. In addition, depressive symptoms were very high in the sample; more than 70% of women reported depressive symptoms at least once, and 23% reported chronic depressive symptoms. This highlighted the need for mental health care access for low-income women of all ages. Overall, our sample showed a different pattern of depressive symptoms than that reported in higher SES populations; further research is needed to determine how depression affects lower income women across their lifetime and how to effectively meet their needs.
Acknowledgments
Data in this article were collected by the Women’s Interagency HIV Study (WIHS). WIHS (Principal Investigators): UAB-MS WIHS (Michael Saag, Mirjam-Colette Kempf, and Deborah Konkle-Parker), U01-AI-103401; Atlanta WIHS (Ighovwerha Ofotokun and Gina Wingood), U01-AI-103408; 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; Miami WIHS (Margaret Fischl and Lisa Metsch), U01-AI-103397; UNC WIHS (Adaora Adimora), U01-AI-103390; 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) and UL1-TR000454 (Atlanta CTSA).
Note. 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).
Human Participant Protection
Institutional review board approval was obtained from all 6 participating sites; women gave written, informed consent before participating in the study.
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