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. Author manuscript; available in PMC: 2024 Sep 5.
Published in final edited form as: J Psychiatr Res. 2023 May 12;163:230–239. doi: 10.1016/j.jpsychires.2023.05.033

Influence of childhood trauma, HIV infection, alcohol use disorder, and resilience on health-related quality of life in adulthood

Stephanie A Sassoon a,*, Rosemary Fama a,b, Anne-Pascale Le Berre b, Eva M Müller-Oehring a,b, Natalie M Zahr b, Adolf Pfefferbaum a,b, Edith V Sullivan b
PMCID: PMC11376962  NIHMSID: NIHMS2017835  PMID: 37230007

Abstract

Experience of childhood trauma, especially physical, emotional, and sexual abuse, carries a risk for developing alcohol use disorder (AUD) and engaging in risky behaviors that can result in HIV infection. AUD and HIV are associated with compromised self-reported health-related quality of life (HRQoL) possibly intersecting with childhood trauma. To determine whether poor HRQoL is heightened by AUD, HIV, their comorbidity (AUD + HIV), number of trauma events, or poor resilience, 108 AUD, 45 HIV, 52 AUD + HIV, and 67 controls completed the SF-21 HRQoL, Brief Resilience Scale (BRS), Ego Resiliency Scale (ER-89), and an interview about childhood trauma. Of the 272 participants, 116 reported a trauma history before age 18. Participants had a blood draw, AUDIT questionnaire, and interview about lifetime alcohol consumption. AUD, HIV, and AUD + HIV had lower scores on HRQoL and resilience composite comprising the BRS and ER-89 than controls. Greater resilience was a significant predictor of better quality of life in all groups. HRQoL was differentially moderated in AUD and HIV: more childhood traumas predicted poorer quality of life in AUD and controls, whereas higher T-lymphocyte count contributed to better quality of life in HIV. This study is novel in revealing a detrimental impact on HRQoL from AUD, HIV, and their comorbidity, with differential negative contribution from trauma and beneficial effect of resilience to quality of life. Channeling positive effects of resilience and reducing the incidence and negative impact of childhood trauma may have beneficial effects on health-related quality of life in adulthood independent of diagnosis.

Keywords: Childhood trauma, Alcohol use disorder, HIV infection, Comorbidities, Resilience, Quality of life

1. Introduction

Trauma during childhood, especially physical, emotional and sexual abuse, carries a heightened risk for later-life engagement in hazardous behaviors, including alcohol misuse and unsafe sex with the potential of acquiring HIV infection (HIV) (Patock-Peckham et al., 2020; Troeman et al., 2011). Indeed, the prevalence of childhood trauma in adults with alcohol use disorder (AUD) or HIV is high. A recent epidemiological study of participants (n = 2064) in the Environmental Risk Longitudinal Twin Study born in England and Wales in 1994–5 found that 31% reported being exposed to a significant trauma by age 18; 16% of these trauma-exposed participants also had a history of alcohol dependence by age 18 (Lewis et al., 2019). A systematic literature review established that the rate of childhood maltreatment in those with HIV infection was higher than that of the general population; rates of childhood sexual abuse alone in those with HIV ranged from 32% to 76% (Spies et al., 2012). Comorbidity of childhood trauma and alcohol dependence is associated with a more severe clinical profile and a poorer treatment outcome than those with trauma or alcohol dependence alone (Brady and Back, 2012). Similarly, co-occurrence of HIV infection and childhood trauma have negative effects on mental health, HIV-related treatment outcome, and longevity (LeGrand et al., 2015; Pence, 2009; Young-Wolff et al., 2019). The detrimental effects of trauma and their relationship to the emergence of AUD and acquisition of HIV result in substantial personal and societal economic costs (Bingham et al., 2021; Gelles and Perlman, 2012; Sacks et al., 2015). Consequently, identification of factors that modulate outcome, such as resilience, may enhance preventative efforts.

The construct of resilience has been a focus of study for years; however, there is no single agreed upon operational definition (Luthar and Chicchetti, 2000; Vella and Pai, 2019). Southwick and Charney (2012) refer to resilience as a multidimensional construct, defined as an individual’s ability to bounce back from hardship and trauma. Resilience has also been defined as healthy adaptation in the face of threat or adversity or the ability to bounce back from stress having positive influences on health and well-being across the lifespan (Windle et al., 2011). Increasing interest in the study of resilience from policy makers, funding entities, and practitioners (Smith et al., 2008) has prompted research into understanding how childhood trauma affects resilience, functional capacity, and health (Oral et al., 2016). Resilience is protective against the development of AUD (Long et al., 2017), AUD relapse (Yamashita and Yoshioka, 2016), acquisition of HIV infection (McNair et al., 2018), and progression of HIV to AIDS (Liboro et al., 2021). Furthermore, resilience is related to outcome, such as symptom development in AUD (Sheerin et al., 2021), and medication adherence and immune functioning in HIV (Dulin et al., 2018). Resilience may play an especially protective role in reducing incidence of AUD (Cusack et al., 2021; Wingo et al., 2014) and HIV infection (Dale et al., 2015) in those with a history of childhood trauma.

Health-related quality of life (HRQoL) is a multidimensional construct that provides information about functioning in the domains of emotional, cognitive, social, and physical performance. The Centers for Disease Control and Prevention (CDC) define health-related quality of life as “an individual’s or a group’s perceived physical and mental health over time;” health-related quality of life has been demonstrated to be a powerful predictor of morbidity and mortality [CDC; cdc.gov/hrqol/index.htm]. The concept of health-related quality of life, comprising subjective rating of cognitive functioning, emotional wellbeing, energy/fatigue, current health perceptions, pain, physical functioning, role functioning, and social functioning, is gaining traction as an essential primary and secondary endpoint in assessment of outcome in healthcare research and practice (Levola et al., 2014; Owczarek, 2010).

HRQoL assessments can inform disease prevention, treatment, and rehabilitation efforts, particularly in those with chronic conditions, such as childhood trauma (Edwards et al., 2004), AUD (Donovan et al., 2005; Longabaugh et al., 1994), and HIV (Alford et al., 2021). Several studies report an association between the construct of resilience and quality of life. Fumaz et al. (2015) reported that resilience “plays a fundamental role in well-being” in a sample of long-term diagnosed HIV-infected participants. More recently, Hopkins et al. (2022) reported that psychological resilience was an independent correlate of health-related quality of life in a sample of predominately African American adults with HIV.

A history of childhood trauma is associated with poorer overall quality of life in adulthood in clinical (Warshaw et al., 1993), non-clinical (Beilharz et al., 2020), and targeted population-based (Corso et al., 2008) samples. Data from recent population-based studies indicate that childhood maltreatment, particularly sexual abuse, emotional abuse, and physical neglect, was associated with increased somatization and poorer physical HRQoL (Downing et al., 2021; Piontek et al., 2021). Further, more adverse childhood experiences correlated with poorer physical HRQoL, where physical HRQoL was both directly and indirectly related to adverse childhood experiences (Martin-Higarza et al., 2020). Although AUD was associated with poorer physical, cognitive, mental, and social HRQoL (Levola et al., 2014; Ugochukwu et al., 2013), physical HRQoL was not affected in a prospective observational study of treatment-seeking patients with AUD (Daeppen et al., 2014). Moreover, HRQoL was diminished even further by co-existing medical conditions, including HIV infection, with HRQoL reduction rates even greater than those associated with AUD alone.

Persons living with HIV infection without significant comorbidities may now have comparable life expectancies to those without HIV due in part to the efficacy of antiretroviral therapy (Marcus et al., 2020). As individuals age with HIV, AUD, or their comorbidity, the chronic nature of these diseases, in conjunction with the long-term effects of childhood trauma, suggests that individuals must endure and cope with sequelae of these conditions for decades, making it critical to examine how disease burden and resilience affect HRQoL. For instance, irrespective of alcohol history, persons living with HIV infection who have experienced childhood trauma exhibit poorer verbal and visual memory in adulthood compared to their counterparts with HIV but without childhood trauma (Sassoon et al., 2017). Additionally, the comorbidity of AUD and HIV was associated with lower total HRQoL scores than those of either diagnosis alone. Poorer overall HRQoL was associated with current AUD rather than AUD in remission (regardless of HIV status), and poorer overall HRQoL was associated with depression in AUD, HIV, and their comorbidity (Rosenbloom et al., 2007).

Limited information is available regarding the role of resilience in persons with AUD and HIV who have experienced childhood trauma, and how frequency of trauma, resilience, and disease-related factors interact to affect overall HRQoL. To address these lacunae, this study had three aims: (1) to determine whether greater number of trauma events, poor resilience composite scores, and poor HRQoL scores were compounded by AUD + HIV comorbidity relative to single diagnosis or healthy controls; (2) to assess whether lower levels of resilience, measured by the resilience composite scores, and more trauma events experienced were independently associated with poorer HRQoL among AUD, HIV, and their comorbidity; and (3) to test the relationship of disease-related variables with trauma and resilience to AUD, HIV, and their comorbidity.

2. Material and methods

2.1. Participants

A total of 272 study participants included 108 individuals with AUD, 45 with HIV, 52 with AUD + HIV comorbidity, and 67 with neither diagnosis (controls, CTL) (Table 1 for demographic information and statistics). Participants were recruited from the greater San Francisco Bay area through outreach at transitional sober living environments, community treatment programs, support group meetings, or community functions such as AIDS Walk, referrals from medical centers, response to flyers or Internet postings, or through word of mouth and were part of a larger ongoing longitudinal study on the effects of HIV infection and alcohol use on brain structure and function.

Table 1.

Demographics of the four groups (N = 272).

AUD HIV AUD + HIV CTL p value
% or Mean (SD) % or Mean (SD) % or Mean (SD) % or Mean (SD)
n = 108 45 52 67
BACKGROUND DEMOGRAPHICS
 Sex (% Men) 71.30% 71.11% 61.54% 52.24% 0.05
 Ethnicity (% Non-Cau.) 60.19% 46.67% 84.62% 46.97% <0.001 [AUD + HIV > AUD, HIV, CTL]
 Age 53.56 (9.46) 57.52 (7.80) 57.20 (6.16) 56.28 (11.59) 0.03 [pairwise comparisons not sig.]
 Median Age; Age Range 55; 26–76 57; 39–78 57; 44–79 56; 27–87
 Education (yrs) 13.25 (2.67) 13.80 (2.39) 13.42 (2.17) 16.07 (2.33) <0.001 [CTL > AUD, HIV, AUD + HIV]
 Socioeconomic Status (SES)a 42.67 (16.41) 37.89 (15.22) 41.90 (13.72) 25.72 (11.62) <0.001 [CTL < AUD, HIV, AUD + HIV]
 Lifetime Drug Abuse (%) 72.90% 46.67% 71.15% 1.47% <0.001 [CTL < AUD, HIV, AUD + HIV]
 Drug Abuse Remission (months)b 124 ± 131; 72 131 ± 134; 98 117 ± 125; 69 – 0.92 (CTL not incl.)
CHILDHOOD TRAUMA HISTORY
 Childhood Trauma History (%) 48.15% 42.22% 51.92% 26.87% 0.02 [CTL < AUD, AUD + HIV]
 Childhood Trauma Age of Onset 8.75 (4.77) 8.43 (5.23) 9.52 (4.95) 8.12 (4.69) 0.79
 Number of Childhood Trauma Eventsc,b 90 (115); 29 111 (127); 99 84 (127); 3 60 (85); 12 0.61
 Participants by Number of Trauma Events 1 trauma: 12 1 trauma: 5 1 trauma: 11 1 trauma: 5
2–99 traumas: 21 2–99 traumas: 6 2–99 traumas: 6 2–99 traumas: 9
>100 traumas: 19 > 100 traumas: 8 >100 traumas: 10 >100 traumas: 4
AUD-RELATED DEMOGRAPHICS
 AUD Age of Onset 26.01 (9.97) – 23.87 (8.94) – 0.19
 AUD Sobriety (months)b 8.90 (27.00); 2.00 – 16.11 (43.27); 0.20 – 0.27
 AUDIT Score 18.14 (11.24); 20 1.98 (2.01); 1 9.31 (10.07); 4.5 1.97 (1.67); 2 <0.001 [(C=HIV) < ALC < ALC + HIV]
 Lifetime Alcohol Consumption (kg)b 1284 (971); 977 80 (108); 41 1034 (985); 726 38 (53); 14 <0.001 [(CTL=HIV) < (ALC = ALC + HIV)]
HIV-RELATED DEMOGRAPHICS
 HIV Age of Onset – 35.69 (9.51) 35.71 (8.18) – 0.99
 Length of time with HIV (years) – 21.17 (8.61) 21.69 (6.21) – 0.79
 AIDS Status (%) – 58.14% 62.00% – 0.71
 HAART Medications (%) – 88.37% 96.00% – 0.24
 Log Viral Load – 2.02 (1.04) 1.99 (1.06) – 0.89
 CD4 T Lymphocyte Countb – 569 (262); 514 617 (350); 604 – 0.48
RESILIENCE MEASURES
 Resilience Composite Score (z-score) −0.21 (0.82) −0.08 (0.89) −0.15 (0.85) 0.55 (0.66) <0.001 [CTL < AUD, HIV, AUD + HIV]
  ER-89 41.25 (7.68) 43.11 (8.46) 43.20 (8.53) 47.00 (5.51) <0.001 [CTL < AUD, HIV, AUD + HIV]
  BRS 21.44 (4.68) 21.62 (5.07) 20.82 (4.52) 25.32 (4.04) <0.001 [CTL < AUD, HIV, AUD + HIV]
HEALTH-RELATED QUALITY OF LIFE
 HRQoL Score 72.82 (17.08) 73.68 (15.99) 68.01 (18.66) 86.95 (9.70) <0.001 [CTL < AUD, HIV, AUD + HIV]
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a

Lower value = higher SES.

b

Mean (SD); median.

c

For those with trauma history.

2.2. Procedures

This study abided by the principles of the Declaration of Helsinki. Procedures were reviewed and approved by the Institutional Review Boards of SRI International (Advarra FWA00023875; SRI FWA00007933) and Stanford University (FWA00000935). All participants provided written informed consent prior to study participation and received modest monetary stipends for participation. See Supplemental Material for eligibility criteria and full descriptions of procedures for clinical diagnosis and resilience measures.

2.2.1. Clinical assessment for alcohol use disorder (AUD) history

All 272 participants underwent psychiatric and substance use assessment by senior clinical research staff using the Structured Clinical Interview for DSM-IV-TR and DSM-5 (SCID) (First et al., 2002, 2015) to establish lifetime DSM-IV-TR criteria for alcohol dependence/abuse or DSM-5 AUD. Estimation of lifetime alcohol consumption was obtained with a semi-structured lifetime alcohol history interview in all but 2 participants (Skinner, 1982; Skinner and Sheu, 1982). All participants completed the Alcohol Use Disorder Identification Test (AUDIT) (Babor et al., 2001), a 10-item screening instrument to identify hazardous alcohol consumption.

2.2.2. HIV infection status

Hematological analysis confirmed HIV status with an antibody test and yielded CD4 T lymphocyte counts and viral load parameters.

2.2.3. Childhood trauma interview

Historical childhood trauma information was collected by senior clinical research staff through a customized in-person interview following Turner and Lloyd (2004). Individuals with a history of childhood trauma endorsed experiencing at least 1 of 13 types of life traumas before the age of 18 (Sassoon et al., 2017; Turner and Lloyd, 2004). All 272 participants completed the trauma interview; 116 reported experiencing at least 1 life trauma before age 18 years. For each type of reported trauma, the participant estimated the number of times that type of trauma occurred [max score per trauma type was 99 (too many to count)]; trauma types were then summed to yield a total number of childhood life trauma events experienced for each participant.

2.2.4. Resilience measures

Two resilience measures were administered to 264 of the 272 participants: Ego Resiliency Scale [ER-89 (Block and Kremen, 1996)] and Brief Resilience Scale [BRS (Smith et al., 2008)]. Given the high correlation of the ER-89 and the BRS scores (r = 0.48, p < 0.001) among the total group and among the CTL, AUD, HIV and AUD + HIV groups individually (all p’s < 0.004), the ER-89 and BRS scores were combined to produce a resilience composite score. Individual scores for each measure were converted to z-scores, and the mean of the two scores was used as a resilience composite score.

2.2.5. Health-related quality of life (HRQoL)

The SF-21 (Bozzette et al., 1995), derived from the Short Form (SF-36) of the Medical Outcome Study (Ware and Sherbourne, 1992), is widely used (Alford et al., 2021; Weber et al., 2016) and evaluated HRQoL herein. The SF-21 is a 21-item questionnaire, yielding a total score representing current self-reported quality of life in eight areas: cognitive functioning, emotional well-being, energy/fatigue, current health perceptions, pain, physical functioning, role functioning, and social functioning. A standardized total score ranging from 0 (poor quality of life) to 100 (excellent quality of life) was calculated, reflecting self-rating of coping in these 8 combined functional areas of life (cf, (Rosenbloom et al., 2007)).

2.3. Statistical analyses

2.3.1. Demographic analyses

Initial one-way ANOVAs, Kruskal-Wallis, t-tests, Mann-Whitney U, and chi-square tests compared demographic variables, including percentage of those with a history of childhood trauma in the four groups: AUD, HIV, AUD + HIV, and CTL.

2.3.2. Analyses of study aims

Aim 1:

To examine whether more trauma events, poor resilience, and poor HRQoL were compounded in AUD + HIV compared to single-diagnosis groups or the CTL group, one-way ANOVAs compared number of childhood traumas, resilience composite scores, and HRQoL scores among the four groups. Tukey HSD tests for multiple comparisons were conducted to follow-up significant ANOVA results.

Aims 2 & 3:

To assess whether lower levels of resilience, measured by the resilience composite scores, and more trauma events experienced were independently associated with poorer HRQoL among AUD, HIV, and their comorbidity, and to determine which disease-related variables contributed to HRQoL scores, Pearson correlations and simultaneous multiple regressions were conducted for each group. Pearson correlations tested significance of all potential regression variables selected to be studied, i.e., the resilience composite scores, number of childhood trauma events, disease-related variables (the AUDIT score and lifetime alcohol consumption for all participants and CD4 T-lymphocyte count and HIV log viral load for participants with HIV infection), and demographic variables (age, sex, and SES which incorporates education) on HRQoL scores among all four participant groups, with α = 0.05, to determine which were significant. For each group, only the variables that were significantly correlated with HRQoL scores were entered as variables in simultaneous multiple regressions. A conservative correction of α = 0.013 was used to protect against family-wise error in main analyses (ANOVAs and regressions).

All statistical analyses were conducted with IBM SPSS Statistics Version 27 (IBM Corp. Released 2020. IBM SPSS Statistics for Windows, Version 27.0. Armonk, NY: IBM Corp).

3. Results

3.1. Demographics and trauma among groups

Among those reporting trauma, the numbers of trauma events reported were comparable across all four groups. Further, in all groups, those with trauma history had similar trauma age of onset (~8–9 years old). Those with AUD history (AUD, AUD + HIV) had similar mean AUD age of onset (mid-20s), and those with HIV infection had similar mean HIV infection age of onset (mid-30s). For individuals who were comorbid with AUD and HIV infection and who experienced trauma, the typical timeline was, first, experiencing a childhood trauma, followed by onset of AUD, followed by acquisition of HIV.

In the AUD and AUD + HIV groups, history of childhood trauma occurred before the onset of the alcohol diagnosis in all but one case. Similarly, HIV participants reporting childhood trauma experienced those events before learning of their HIV seropositive status. Trauma types endorsed are presented in Table 2. Fewer CTLs reported childhood trauma than the two AUD groups (AUD and AUD + HIV); age of trauma onset, for those who did report experiencing a traumatic event, was statistically similar across the four groups. The types of traumas most likely to be endorsed were related to physical, sexual, and emotional abuse and were of similar proportions among the four groups (73.1% in AUD, 85.7% in HIV, 70.4% in AUD + HIV, and 76.5% in CTL), [χ2 (3) = 1.72, p = 0.63].

Table 2.

Incidence of types of childhood life traumas reported by participants with a history of trauma (N = 116 of 272).

Types of Childhood Life Traumas AUD HIV AUD + HIV CTL
with Trauma with Trauma with Trauma with Trauma
(n = 52 of 108) (n = 19 of 45) (n = 27 of 52) (n = 18 of 67)
Lost home in natural disaster 2 (4%) 0 (0%) 1 (4%) 0 (0%)
Life threatening accident, injury, illness 6 (12%) 0 (0%) 4 (15%) 1 (6%)
Forced sexual intercourse 8 (15%) 3 (16%) 11 (41%) 3 (17%)
Forced sexual touching 15 (29%) 3 (16%) 10 (37%) 7 (39%)
Physical abuse by parent/guardian 20 (38%) 9 (47%) 9 (33%) 7 (39%)
Physical abuse by boyfriend/girlfriend 2 (4%) 1 (5%) 3 (11%) 2 (11%)
Physical abuse by someone else 5 (10%) 2 (11%) 4 (15%) 5 (28%)
Physically assaulted or mugged 6 (12%) 3 (16%) 6 (22%) 2 (11%)
Emotional abuse by parent/guardian 25 (48%) 11 (58%) 8 (30%) 9 (50%)
Threatened with weapon/shot at (no injury) 10 (19%) 1 (5%) 3 (11%) 0 (0%)
Injured with weapon or shot at 1 (2%) 0 (0%) 0 (0%) 0 (0%)
Chased by someone where thought could get hurt 17 (33%) 2 (11%) 9 (33%) 4 (22%)
Car crash where someone was killed/badly injured 3 (6%) 0 (0%) 3 (11%) 3 (17%)
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3.2. Aim 1: diagnostic group differences in trauma events, resilience composite scores, and HRQoL scores

The mean number of childhood trauma events did not differ among the groups [F (3, 112) = 0.61, p = 0.61]. The majority of the specific childhood trauma events experienced in all groups was related to physical, sexual, and emotional abuse compared to other types of trauma such as illness, natural disasters, severe accidents, or weapons-related violence. In most cases, traumas were ongoing through childhood rather than an infrequent occurrence.

To determine whether resilience composite scores and HRQoL were differentially affected in AUD + HIV than in either single diagnosis or CTL, ANOVAs compared the four diagnostic groups (Fig. 1). For all clinical groups (AUD, HIV, and AUD + HIV), mean resilience composite scores were significantly lower (all p’s < 0.001) than the mean for CTL [F (3, 260) = 12.93, p < 0.001]. Similarly, mean HRQoL scores for AUD, HIV, and AUD + HIV were all significantly lower (all p’s < 0.001) than the mean for CTL [F (3, 268) = 16.97, p < 0.001]. Although the mean HRQoL score in the AUD + HIV group was numerically lower than those of AUD and HIV, group differences were not statistically significant. Results did not change when controlling for group differences in demographics, i.e., sex, ethnicity, age, and SES (which incorporates education).

Fig. 1.

Fig. 1.

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Mean comparisons of HRQoL scores, number of childhood trauma events, and resilience composite scores among the CTL, AUD, HIV, and AUD + HIV groups.

Comparison of those in the clinical groups with history of substance use disorder (including cocaine, opioids, sedatives, stimulants, hallucinogens) to those without showed no significant differences in HRQoL [F (1, 197) = 2.29, p = 0.13], resilience composite score [F (1, 194) = 0.621, p = 0.43], or number of trauma events [F (1, 197) = 0.97, p = 0.33].

3.3. Aims 2 & 3

3.3.1. Correlations of regression predictor variables with HRQoL scores

Next, we explored whether poorer resilience, a greater number of childhood trauma events, and poorer disease-related variables predicted poorer HRQoL scores in ALC, HIV, and AUD + HIV. Simple correlations (Table 3), as a preamble to regressions, were conducted between resilience composite scores, number of childhood trauma events, disease-related factors (AUDIT score, lifetime alcohol consumption, CD4 T lymphocyte count, HIV log viral load), and demographic variables (sex, age, and SES) against HRQoL scores within each of the four groups to determine which variables were significantly associated with HRQoL score; those variables were entered into regression models to predict HRQoL score of each group. Intercorrelations of independent variables for each group appear in Supplementary Tables 1–4.

Table 3.

Correlations of resilience, disease-related, and demographic variables with HRQoL scores.

AUD HIV AUD + HIV CTL
— Health-Related Quality of Life Score —
Variables
Sex r −0.13 0.05 −0.23 −0.07
p-value 0.18 0.76 0.11 0.57
n 108 45 52 67
Age r −0.02 0.01 0.14 −0.08
p- value 0.86 0.97 0.33 0.54
n 108 45 52 67
Socioeconomic Scale (Lower score = Higher SES) r −0.13 −0.16 −0.21 −0.05
p- value 0.18 0.29 0.14 0.68
n 108 45 52 67
Number of Childhood Trauma Events r −0.31 0.15 −0.11 −0.39
p- value 0.001 0.32 0.44 <0.001
n 108 45 52 67
Resilience Composite Score r 0.52 0.52 0.37 0.49
p- value <0.001 <0.001 0.010 <0.001
n 107 45 50 62
AUDIT Score r −0.20 −0.08 −0.08 −0.01
p- value 0.03 0.58 0.57 0.92
n 108 45 52 67
Lifetime Alcohol Consumption (kg) r −0.11 0.01 0.02 −0.06
p- value 0.26 0.94 0.90 0.66
n 107 45 52 66
CD4 T Lymphocyte Count r 0.35 0.01
p- value N/A 0.03 0.96 N/A
n 37 46
Log Viral Load r 0.01 0.12
p- value N/A 0.96 0.45 N/A
n 35 43
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Based on these correlational analyses, the resilience composite score was entered into regressions predicting HRQoL in all four groups. Number of childhood trauma events was entered into regressions predicting HRQoL of AUD and CTL. AUDIT score was entered as a predictor of HRQoL in AUD, whereas CD4 T lymphocyte count was entered as a predictor of HRQoL in HIV. None of the demographic variables were entered into any of the regressions, as none were significant predictors of HRQoL in any group.

3.4. Multiple regression predicting HRQoL score in AUD

In AUD, multiple regression determined the best linear combination of resilience composite score, number of childhood trauma events, and AUDIT score for predicting HRQoL (Table 4 for statistics). The model was significant, with 30% of the variance of HRQoL scores in AUD explained by the model. Two of the three variables were significant predictors. The resilience composite contributed the most to the prediction of HRQoL score (Table 4, and Fig. 2 for correlation plot), with higher resilience predicting greater HRQoL, and number of childhood trauma events predicting a poorer HRQoL score.

Table 4.

Multiple regressions predicting HRQoL in each subject group.

Predicting HRQoL in the AUD Group
Coefficients Beta t-value p-value
Resilience Composite Score 0.47 5.53 <0.001
# Trauma Events −0.23 −2.74 0.01
AUDIT Score −0.04 −0.49 0.63
F (3,103) = 16.20 R2 = 0.32 Adjusted R2 = 0.30 p<0.001
Predicting HRQoL in the HIV Group
Coefficients Beta t-value p-value
Resilience Composite Score 0.55 4.26 <0.001
CD4 T Lymphocyte Count 0.34 2.64 0.01
F (2,34) = 12.72 R2 = 0.43 Adjusted R2 = 0.39 p<0.001
Predicting HRQoL in the AUD + HIV Group
Coefficients Beta t-value p-value
Resilience Composite Score 0.37 2.72 0.01
F (1,48) = 7.42 R2 = 0.13 Adjusted R2 = 0.12 p=0.01
Predicting HRQoL in the Control Group
Coefficients Beta t-value p-value
Resilience Composite Score 0.48 4.76 <0.001
# Trauma Events −0.41 −4.15 <0.001
F (2, 59) = 20.73 R2 = 0.41 Adjusted R2 = 0.39 p<0.001
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Fig. 2.

Fig. 2.

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Correlations of resilience composite scores (r = 0.52, p < 0.001), number of childhood trauma events (r = −0.31, p = 0.001) and HRQoL in the AUD group.

3.5. Multiple regression predicting HRQoL in HIV

Resilience composite score and CD4 T lymphocyte count were entered into the regression model predicting HRQoL score in HIV. Both predictors were significant, with 39% of the variance in HRQoL in the HIV group explained by the model. Higher resilience composite score predicted better HRQoL in HIV. Further, a greater number of CD4 T lymphocytes predicted greater HRQoL (Table 4, and Fig. 3 for correlation plot).

Fig. 3.

Fig. 3.

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Correlations of resilience composite scores (r = 0.52, p < 0.001), CD4 T lymphocyte count (r = 0.35, p = 0.03) and HRQoL in the HIV group.

3.6. Multiple regression predicting HRQoL in AUD + HIV

In predicting HRQoL score in the AUD + HIV group, only one variable, resilience composite score, was entered into the regression. Higher resilience composite scores predicted greater HRQoL, with 12% of the variance in HRQoL score accounted (Table 4, and Fig. 4 for correlation plot).

Fig. 4.

Fig. 4.

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Correlation of resilience composites scores (r = 0.37, p = 0.009) and HRQoL in the AUD + HIV group.

3.7. Multiple regression predicting HRQoL in CTL

Resilience composite score and number of childhood trauma events were entered into the regression predicting HRQoL score in CTL. Both variables were significant predictors, accounting for 39% of the variance. A greater number of trauma events was associated with poorer HRQoL scores. Further, higher resilience composite scores predicted greater HRQoL in CTL (Table 4, and Fig. 5 for correlation plot).

Fig. 5.

Fig. 5.

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Correlations of resilience composite scores (r = 0.49, p < 0.001), number of childhood trauma events (r = −0.39, p < 0.001), and HRQoL in the CTL group.

4. Discussion

This study examined how frequency of childhood trauma and resilience affects health-related quality of life (HRQoL) in persons with AUD and HIV infection. Trauma, AUD, and HIV comprise a “trimorbidity” that has been rarely studied despite evidence that trauma during childhood increases risk of AUD and HIV infection (Patock-Peckham et al., 2020; Troeman et al., 2011).

The clinical groups (AUD, HIV, and AUD + HIV) rated their overall HRQoL more poorly than did controls regardless of history of childhood trauma, supporting earlier findings (Rosenbloom et al., 2007); however, a compounded effect of AUD and HIV comorbidity was not observed. Nonetheless, our findings of poorer levels of resilience among the three clinical groups compared to controls were consistent with previous reports (Long et al., 2017; Sanchez et al., 2022; Sheerin et al., 2021), with all groups experiencing a similar number of childhood trauma events and types of trauma.

Our results suggest that resilience plays a critical role as one overarching factor in independently predicting HRQoL well-being in adulthood, being the most salient contributor in this study. Indeed, greater resilience, shown previously to be associated with lower levels of self-reported depression (Spies and Seedat, 2014), consistently predicted health-related quality of life in all four groups.

In addition, a greater number of childhood trauma events, of which recurring physical, sexual, or emotional abuse were the most commonly reported, independently predicted detrimental effects on HRQoL in both the AUD group and control group. This finding is consistent with a recent report of a dosage effect of childhood adversity on quality of life (Martin-Higarza et al., 2020), and now extends this to individuals with AUD.

This study is novel in showing a detrimental impact of AUD and HIV infection on HRQoL even in individuals with HIV or AUD + HIV who were in disease remission. A meta-analysis reported that alcohol consumption promotes worsening of HIV/AIDS symptoms and negatively affects support-seeking (Shuper et al., 2010). Our participants who were comorbid for HIV infection and AUD were high alcohol consumers over their lifetime, and had a mean total lifetime consumption equivalent to AUD, with relatively comparable sobriety lengths. Although more than 50% of participants with HIV infection in our study (HIV, AUD + HIV) had a history of an AIDS-defining event, they had low viral loads, relatively healthy T lymphocyte counts (>500 cells/mm3), were almost all on HAART medications, and were ostensibly unimpaired functionally as indicated by high Karnofsky scores. Regardless of the temporal separation of contributing factors (trauma occurring during childhood, whereas AUD history was more recent, and HIV infection was considered stable), trauma, AUD, and HIV infection histories all had significant detrimental effects on quality of life.

Disease-related variables also demonstrated an association with self-reported quality of life. Higher T lymphocyte count was associated with better HRQoL in individuals with HIV, recognizing the relevance of a healthier immune system to quality of life in those with HIV. While higher AUDIT scores were related to poorer HRQoL in AUD, AUDIT scores were not a significant independent predictor of HRQoL. Neither alcohol-related variable (AUDIT score or amount of lifetime alcohol consumed) was related to HRQoL in AUD + HIV; this may be due to differences in AUD characteristics between the AUD groups, i.e., lower severity and lower variability in AUDIT scores in AUD + HIV than AUD alone.

These results highlight resilience as a potential target for interventions in people with significant adverse life experiences such as history of childhood trauma, AUD, or HIV, or as a target for prevention for at-risk populations. Indeed, resilience can be modified and enhanced neurobiologically and behaviorally toward improving clinical outcomes (Wu et al., 2013). Relevantly, one study reported that an intervention aimed at building psychosocial resilience was associated with improved self-esteem and decreased distress in men with HIV infection who later decreased HIV-associated risk behaviors (Safren et al., 2021).

Taken together, our findings are consistent with reports that AUD, HIV, and childhood trauma have negative effects on quality of life, whereas resilience can offer a protective effect (Long et al., 2017).

4.1. Limitations

Given its cross-sectional design, neither change in HRQoL nor assessment of whether childhood trauma disrupted normal development could be determined. Traumas that occurred throughout childhood and adolescence were considered together without reference to potential differential effects relative to specific developmental periods (Hambrick et al., 2019). In addition, although we had a control group, a smaller proportion of control than clinical participants reported having a childhood trauma history. Further, we did not examine a group of individuals specifically diagnosed with post-traumatic stress disorder (PTSD); only 11 of our 117 participants with a childhood trauma history met criteria to receive a diagnosis of PTSD. By volunteering to be part of a research study, our participants may have had higher levels of resilience and lower levels of depression than may be typical in this population. Also, while the two measures of resilience used in this study, the BRS and the ER-89, were significantly correlated with each other in all groups, resilience is a complex construct and it is possible that the unique contributions of each measure in assessing resilience might be detectable in larger samples (Watters et al., 2023).

Further, group comparisons may be limited by differences in demographics across groups. The CTL group has a wider age range (although means and medians are similar among groups), and results may not generalize to younger or older individuals. Additionally, sex, ethnicity, and SES (which incorporated years of education) were significantly different across groups; although results did not change when accounting for these differences, comparison between groups may be limited by these differences.

5. Conclusion

This study examined whether a history of trauma experienced during childhood affected quality of life in middle-aged adults who had acquired AUD, HIV, or their comorbidity in adulthood and examined the potential role of resilience in HRQoL judgments. HRQoL has become a well-established and meaningful multidimensional outcome measure in healthcare research and practice, particularly in older adults (Fang et al., 2015) with real-world significance. The construct of resilience independently influenced HRQoL. History of childhood trauma, considered a pervasive public health crisis (Magruder et al., 2016), was reported by 43% of our total sample. Critically, the cascade of events that ultimately could lead to AUD and HIV infection in individuals who experience childhood trauma may be prevented by early identification and intervention (Brady and Back, 2012) targeting resilience (Safren et al., 2021). Prevention and intervention strategies in those at heightened risk for trauma, AUD, or HIV infection may be tailored to enhance resilience for better health-related quality of life, which can continue to be affected even in later life.

Supplementary Material

Sassoon_supplement1
Sassoon_supplement3
Sassoon_supplement2
Sassoon_supplement4
Sassoon_supplement5

Acknowledgement

This work was supported by funding from the National Institute on Alcohol Abuse and Alcoholism (AA017347, AA005965, AA010723).

Footnotes

Declaration of competing interest

None.

CRediT author statement

Stephanie A. Sassoon: Conceptualization, Data curation, Investigation, Formal acquisition, Project administration, Methodology, Writing – original draft, Writing – review and editing; Rosemary Fama: Conceptualization, Data curation, Investigation, Methodology, Writing – original draft, Writing – review and editing; Anne-Pascale Le Berre: Conceptualization, Investigation, Methodology, Writing – review and editing; Eva M. Müller-Oehring: Investigation, Methodology, Writing – review and editing; Natalie M. Zahr: Investigation, Project administration, Resources, Writing – review and editing; Adolf Pfefferbaum: Investigation, Project administration, Supervision, Resources, Writing – review and editing; Edith V. Sullivan: Conceptualization, Investigation, Methodology, Project administration, Resources, Supervision, Writing – original draft, Writing – review and editing.

Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.jpsychires.2023.05.033.

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