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. Author manuscript; available in PMC: 2025 Nov 1.
Published before final editing as: AIDS Care. 2024 May 1:1–8. doi: 10.1080/09540121.2024.2339046

Combined Effects of Social Isolation and Loneliness on Patient-Reported Outcomes in Older Adults with HIV

Moka Yoo-Jeong 1, Annie L Nguyen 2
PMCID: PMC11527796  NIHMSID: NIHMS1983833  PMID: 38691674

Abstract

Social isolation exists when one has limited or lacks social contact with others and is distinct from loneliness, an affective state on the perception of isolation. Social isolation and loneliness (SI/L) are recognized as risks to well-being among older adults. Less in known about the combined effects of SI/L in older persons with HIV (OPWH). Using cross-sectional data on OPWH (age ≥50) recruited from an outpatient HIV clinic in Atlanta, GA (N=146), we aimed to 1) describe the overlap between SI/L and 2) examine the separate and combined effects of SI/L on patient-reported outcomes including quality-of-life (QoL), HIV-related stigma, and depressive symptoms. Social isolation and loneliness were assessed using Social Network Index and the PROMIS-Social Isolation Scale, respectively. Participants were grouped into four categories based on established cutoffs: ‘lonely only,’ ‘isolated only,’ ‘both lonely and isolated (two risks),’ or ‘neither.’ Among participants (mean age=56.53), 26.7% (n=39) were considered ‘lonely only,’ 12.3% (n=18) ‘isolated only,’ 15.1% (n=22) ‘two risks,’ and 45.9% (n=67) ‘neither.’ Adjusted regression models showed that participants with two risks had more depressive symptoms and lower QoL than those considered ‘neither’ or ‘isolated only’ (p<.001). The adjusted proportional odds model showed that the odds of stigma were 1.22 and 6.06 higher for participants with two risks in comparison to those considered ‘neither’ (p<.001) or ‘lonely only’ (p=.016). Results demonstrate the combined effects of SI/L on patient-reported outcomes among OPWH. Findings not only fill a gap in research exploring the influence of SI/L in later life, but also highlight the need for approaches targeting OPWH who are lonely and socially isolated.

Keywords: loneliness, social isolation, depressive symptoms, quality of life, stigma, older adults, HIV

INTRODUCTION

Social isolation and loneliness are dogged issues faced by a growing number of people and are particularly salient at older ages. Social and health-related conditions such as the onset of mobility limitations, retirement, economic constraints, widowhood, and death or loss of loved ones contribute to diminishing social contacts over time. These conditions increase the risk for isolation, particularly in the absence of positive friendship ties with remaining social contacts (Seeman, 2000). While social isolation refers to the objective state of having minimal contact with other individuals, loneliness is a psychological state that can result from experiencing isolation. One definition of loneliness refers to the “discrepancy between a person’s preferred and actual level of social contact” (Ong et al., 2016).

Both isolation and loneliness are associated with poor health outcomes. A possible mechanism is that biological stress reactivity is augmented in the context of isolation and loneliness, with resulting physiological cascades. Social isolation and loneliness are associated with cognitive decline (Lara et al., 2019), frailty progression (Gale et al., 2018), increased mortality (Holt-Lunstad et al., 2015; A. Steptoe et al., 2013), and multiple studies have consistently established positive links between loneliness and depression and between social isolation and cardiovascular disease (Courtin & Knapp, 2017).

Older persons with HIV (OPWH) are at particular risk for exposure to the social and health conditions that increase vulnerability to isolation and loneliness. People living with HIV often face barriers to employment due to physical and mental constrains or discrimination (Perri et al., 2021) and long-term survivors of HIV may have faced decades of exclusion from the social networking benefits of joining the workforce. While combination antiretroviral therapy has transformed HIV to a manageable chronic condition, the effects of long-term medication use along with long-term HIV infection increases the risk for mobility limiting conditions such osteoporosis (Walker Harris & Brown, 2012), physical impairment (Erlandson et al., 2012), and frailty (Erlandson & Piggott, 2021). OPWH have been characterized as facing high levels of social isolation (Brennan-Ing et al., 2017; Shippy & Karpiak, 2005) and loneliness (Greene et al., 2017).

While many studies have established the independent effects social isolation and loneliness on the health of general older adult populations as well as OPWH, less attention has been paid to their combined effects. A recent study by Barnes et al. (2022) showed that among a random sample of older adults in the United States, those who were both lonely and isolated had higher rates of emergency room visits and medical costs compared to those who were just lonely or just isolated. However, the extent to which loneliness and social isolation have a cumulative effect on patient-related outcomes among OPWH are unknown.

This study examined the overlap of isolation and loneliness among OPWH by identifying typologies (both isolated and lonely, isolated only, lonely only, neither isolated nor lonely) and the relationship between these typologies with relevant HIV-related patient-reported outcomes (depressive symptoms, quality-of-life [QoL], stigma.) We hypothesized that there would be an additive effect with each additional risk factor such that those who are not isolated or lonely would have the best outcomes while those who are isolated and lonely would exhibit the poorest outcomes.

METHODS

This study is a secondary analysis of a cross-sectional study that tested the relationship between psychosocial factors and retention in HIV care among OPWH (Yoo-Jeong et al., 2021). The parent study was approved by the university’s Institutional Review Board and the recruiting clinic’s Research Oversight Committee before start of the study. A sample of older PWH were recruited from an outpatient HIV clinic in Atlanta, GA from 2016 to 2017 through flyers, word of mouth, and healthcare provider referrals. Eligible individuals were 50 years old or older, living with HIV, and had at least one medical visit established in the recruiting clinic. Participants completed the informed consent prior to completion of one-time study survey. After data collection, participants were incentivized with $25 for their time. More information about the parent study is described elsewhere (Yoo-Jeong et al., 2021; Yoo-Jeong et al., 2020).

Measures

Independent Variables

Social Isolation—

Social Network Index (SNI) assesses frequency of interaction with 12 categories of social relationships, including: (1) spouse, (2) parents, (3) parents-in-law, (4) children, (5) close relatives, (6) neighbors, (7) close friends, (8) coworkers/colleagues, (9) classmates/teachers, (10) fellow volunteers, (11) members from organizations such as social clubs, professional organizations, support groups, etc., and (12) religious group members. Having “regular contact” was defined as physically seeing or talking on the phone with someone at least once every two weeks (Cohen et al., 1997). Having regular contact with at least one person from one of the categories is assigned one point with a maximum score of 12. A total score of 12 denotes a strong social network. Following established procedures from previous studies (Aberaraw et al., 2020; Aung et al., 2016; Musich et al., 2019), SNI scores were dichotomized to define no social isolation (range=4-12) and isolation (range=0-3).

Loneliness—

Patient-Reported Outcomes Measurement Information System (PROMIS)-Social Isolation (SI) Short Form v2.0 8a was used to assess loneliness. This scale uses 8-items that are derived from social relationship scales and the UCLA-Loneliness Scale on a 5-point Likert scale (1=“Never” to 5=“Always”) (Celia et al., 2010). Following the score conversion table in the scoring instruction, the total raw scores were converted into a standardized T-score with a mean of 50 and a standard deviation (SD) of 10. Hence, a T-score of 50 represents an average score and a T-score of 60 represents one SD higher score of loneliness than the average persons in the United States (PROMIS, 2015). Cronbach’s alpha for our sample was 0.95. T-scores were dichotomized to define not lonely (scores <50) and lonely (scores ≥50).

Social Isolation & Loneliness Categorization--

Participants were categorized into groups based on their social isolation (SNI=0-3) and loneliness (PROMIS-SI≥50) statuses. Four groups were created for each possible combination: (1) lonely and isolated (Isolated+/Lonely+); (2) lonely only (Isolated−/Lonely+); (3) isolated only (Isolated+/Lonely−); or (4) neither (Isolated−/Lonely−).

Dependent Variables

HIV-related Stigma—

Internalized AIDS-Related Stigma Scale (Kalichman et al., 2009) contains six items that are rated dichotomously (1=“Agree”, 0=“Disagree”), with scores ranging from 0 to 6. A higher score indicates greater HIV-related stigma. This scale shows good internal reliability (α= .73 to .76) and criterion validity. The Cronbach’s alpha for our sample was 0.83.

Depressive Symptoms—

Center for Epidemiologic Studies Depression Scale Revised (CESD-R) (Eaton et al., 2004) contains 20 items that assess nine symptoms of depression (dysphoria, anhedonia, appetite, sleep, concentration, worthlessness, fatigue, agitation, and suicidal ideation) in accordance with the Diagnostic and Statistical Manual (DSM-V) diagnostic criteria for Major Depressive Disorder. Participants answer 0= “Not at all or less than one day” to 3= “Nearly every day for 2 weeks,” with possible scores ranging from 0 to 60. A score ≥ 16 indicates at risk for clinical depression. The scale has good validity and internal consistency (Van Dam & Earleywine, 2011). This revised scale does not include an item on loneliness. Cronbach’s alpha for our sample was 0.93.

Quality-of-life—

The RAND-36 is a well-validated (test-retest reliability r = 0.94; internal consistency, Cronbach’s alpha 0.96) (VanderZee et al., 1996) in the HIV population (Riley et al., 2003) and widely used health-related, quality-of-life measure. The scale includes 36 items that assess perceived health status during the last 4 weeks (Hays & Morales, 2001). Scores range from 0-100, with higher scores indicating better quality-of-life.

Demographic and Clinical Characteristic Covariates

Self-reported demographic data on age, sex assigned at birth (born male; born female; I choose not to answer), race (African American or Black; White; Asian; Alaska Native or American Indian; Native Hawaiian or Other Pacific Islander; Multiracial; Other), sexual orientation (homosexual, gay, or lesbian; heterosexual or straight; a man who has sex with men; bisexual; other; I choose not to answer), monthly income, education (never attended school; grades 1 through 8; grades 9 through 11; grade 12 or GED; some college, associate’s degree or technical degree; bachelor’s degree; any post graduate studies), unstable housing status in the past 12-months (yes; no), living arrangement, marital status, and years living with HIV were collected. CD4+T cell count and HIV-1 RNA viral load were collected from participant’s electronic medical records on or near the survey completion date (all data were at least within 2 months before or after the survey completion date). Drug use was measured 10-item Drug Abuse Screening Test (DAST-10; Skinner, 1982) that assesses drug use in the past 12 months. Scores 0–2 indicate no to low level of problems related to drug abuse and ≥3 suggest a risky drug use. Alcohol use was measured using Alcohol Use Disorders Identification Test (AUDIT-10; Saunders et al., 1993), a 10-item screening tool scored on a scale of 0-4 to assess for hazardous alcohol consumption in the previous 12 months. Total score ranges from 0 to 40 with a score of ≥8 suggest a risky use of alcohol.

Data analysis

Descriptive statistics were employed to calculate the means and standard deviations of the continuous variables and the percentage and frequency of the categorical variables. Due to low response rates for some categorical demographic covariates, we collapsed categories to have adequate cell sizes. These were race (African American; Non-African American), sexual orientation (heterosexual; non-heterosexual), and education (less than high school; high school/GED; greater than high school). Demographic and clinical covariates were compared between the four Isolated/Lonely groups using analysis of variance (ANOVA) or chi-square tests, as appropriate. Multiple pairwise comparisons were examined to compare significant difference across four Isolation/Lonely groups on outcome variables using Bonferroni adjustments.

Multiple linear regression models were used to assess the effects of Isolated/Lonely groups on continuous outcome variable (Depressive Symptoms, Quality of Life) and chi-square test for proportional odds model was used to assess the Social Isolation/Lonely groups on ordinal outcome variable (HIV-related stigma). Age, past unstable housing, education, sex assigned at birth, and race were included as covariates. For all models, two risks group (Isolation+/Lonely+) was designated as the reference group. All analyses were conducted using SAS and p < 0.05 was considered statistically significant.

RESULTS

Demographic and clinical factors of each Isolated/Lonely group are displayed in Table 1. Almost half of our participants (n=70) reported living alone and nearly 60% of participants reported of being Single or never married (n=86). Among our participants, 15.1% (n=22) were classified as both lonely and isolated (Isolated+/Lonely+), 26.7% (n=39) as lonely only (Isolated− /Lonely+), 12.3% (n=18) as isolated only (Isolated+/Lonely−), and 45.9% (n=67) as neither (Isolated−/Lonely−). Isolated+/Lonely+ group had a higher proportion of individuals with past unstable housing compared to the rest of the groups (p=.029). Groups were comparable on all other demographic and disease characteristics.

Table 1.

Demographic and Clinical Characteristics by Isolated/Lonely Groups (N=146).

Neither (Isolated−/Lonely−) n=67 Both (Isolated+/Lonely+) n=22 Isolated only (Isolated+/Lonely−) n=18 Lonely only (Isolated−/Lonely+) n=39 p-value
Demographics
Age .709
 50-55 31 (46.3%) 11 (50%) 11 (61.1%) 18 (46.2%)
 >55 36 (53.7%) 11 (50%) 7 (38.9%) 21 (53.8%)
Sex at birth .635
 Born male 39 (58.2%)a 17 (77.3%) 12 (66.7%) 22 (56.4%)
 Born female 27 (40.3) 5 (22.7%) 6 (33.3%) 17 (43.6%)
Race .920
 African American (AA)/Black 58 (86.6%) 18 (81.8%) 16 (88.9%) 33 (84.6%)
 Not AA 9 (13.4%) 4 (18.2%) 2 (11.1%) 6 (15.4%)
Sexual orientation .819
 Heterosexual 44 (65.7%) 12 (54.5%) 11 (61.1%) 25 (64.1%)
 Not heterosexual 23 (34.3%) 10 (45.5%) 7 (38.9%) 14 (35.9%)
Monthly Income .377
 ≤$1,000 49 (73.1%) 17 (77.3%) 12 (66.7%) 23 (59%)
 >$1,000 18 (26.9%) 5 (22.7%) 5 (27.8%) 16 (41%)
Education level .687
 <High school 16 (23.9%) 4 (18.2%) 6 (33.3%) 6 (15.4%)
 High school grad / GED 26 (38.8%) 9 (40.9%) 6 (33.3%) 13 (33.3%)
 Some college or more 25 (37.3%) 9 (40.9%) 6 (33.3%) 20 (51.3%)
Past unstable housing 5 (7.5%) 7 (31.85) 1 (5.6%) 4 (10.3%) .029
Living Alone 27 (40.3%) 15 (68.2%) 8 (44.4%) 20 (51.3%) .142
Single/Never Married 35 (52.2%) 14 (63.6%) 12 (66.7%) 25 (64.1%) .852
Clinical Characteristics
Years with HIV 18.30 (8.21) 16.45 (8.49) 17.11(9.17) 19.15 (8.29) .628
CD4a 581.08 (336.08) 486.68 (243.48) 579.39 (363.02) 480.64 (216.61) .289
Viral suppressionb 23 (34.3%) 6 (27.3%) 8 (44.4%) 12 (30.8%) .682
Drug use 1.22 (2.05) 1.45 (2.09) 0.41 (0.71) 1.26 (1.71) .328
Alcohol use 3.07 (4.02) 3.91 (5.25) 2.12 (3.08) 3.08 (4.51) .640
Outcome Variables
Depressive Symptoms 6.79 (6.60) 19.91 (11.34) 5.94 (5.43) 15.03 (11.82) <.001
HIV-related Stigma 1.15 (1.35) 3.23 (2.23) 1.56 (1.58) 2.72 (2.14) <.001
Quality of Life 72.09 (19.31) 47.73 (25.44) 64.72 (20.97) 54.10 (20.96) <.001
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Note.

a

1 not reported;

b

<40 copies/ML; Values are mean (SD) or n (%); Bold p-values are significant at p < .05

Depressive Symptoms

Participants with both risks (Isolated+/Lonely+) had the highest average depressive symptoms score (mean=19.91, SD=11.34) as compared to all other groups. Participants who are isolated only (Isolated+/Lonely−) had the lowest average depressive symptom score (mean=5.94, SD = 5.43) as compared to the other three groups. A follow-up pairwise comparison using Bonferroni adjustments showed significant differences among four groups, with Isolated+/Lonely+ participants showing more depressive symptoms. Specifically, in comparison to Isolated+/Lonely+ group, significant differences were found in Isolated−/Lonely− (mean=10.79; p<.001) and Isolated+/Lonely− (mean=10.04; p<.001) groups. Second highest depression score was found in Isolated−/Lonely+ group (mean=19.16) and its differences were found in Isolated−/Lonely− (p<.001) and Isolated+/Lonely− (p=.004) groups.

Multivariable regression model revealed significant association in Isolated/Lonely groups on depressive symptoms (R2=0.328, p<.001) when controlling for covariates (Table 2). Specifically, participants who had no risks (Isolated−/Lonely−) had lower depressive symptoms (B=−12.54, p<.001) compared to participants with two risks (Isolated+/Lonely+). Participants who were isolated only (Isolated+/Lonely−) had lower depressive symptoms (B=−13.40, p<.001, respectively) compared to those with two risks (Isolated+/Lonely+).

Table 2.

Adjusted Models Assessing Isolated/Lonely Groups on Depressive Symptoms, Quality of Life, and Stigma.

B (SE) p-value Significant pairwise differences
Outcome: Depressive Symptoms
A: Isolated−/Lonely+ * −4.188 (2.446) .0892 A>B,C
B: Isolated−/Lonely− * −12.537 (2.267) <.001 B<A, D
C: Isolated+/Lonely− * −13.402 (2.896) <.001 C<A, D
D: Isolated+/Lonely+ -- D> B, C
Outcome: Quality of Life
A: Isolated−/Lonely+ * 5.073 (5.930) .394 A<B
B: Isolated−/Lonely− * 23.406 (5.495) <.001 B>A, D
C: Isolated+/Lonely− * 16.845 (7.021) .018
D: Isolated+/Lonely+ -- D<B
Odds Ratio (95% Wald CI) p-value Significant pairwise differences
Outcome: Stigma
A: Isolated−/Lonely+ * 1.218 (0.463, 3.206) .016 A>B, C
B: Isolated−/Lonely− * 6.060 (2.374, 15.468) <.001 B<D, A
C: Isolated+/Lonely− * 4.081 (1.262, 13.197) .116 C<D, A
D: Isolated+/Lonely+ -- D>B, C
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Note.

*

Compared to D (Isolated+/Lonely+) group; Adjusted by age, past unstable housing, education, sex, and race. Bold values are significant at p < 0.05.

Quality of Life

Participants with both risks (Isolated+/Lonely+) had the lowest average quality of life score (mean=47.73, SD=25.44) as compared to all other groups. The highest mean quality of life score was shown in participants with no risks (Isolated−/Lonely−; mean=72.09, SD=19.31). A follow-up pairwise comparison using Bonferroni adjustments showed significant differences in Isolated−/Lonely+ (mean=53.78, p<.001) and Isolated+/Lonely+ (mean=48.71, p<.001) groups as compared to Isolated−/Lonely− group. Second highest quality of life score was found in Isolated+/Lonely− group (mean=65.55) but it had no significant differences in comparison to other groups.

Multiple linear regression revealed significant associations in Isolated/Lonely groups on quality of life (R2=0.201, p<.001), controlling for demographic factors (Table 2). Specifically, participants who had no risks (Isolated−/Lonely−) had higher quality of life (B=23.41, p<.001) compared to participants with two risks (Isolated+/Lonely+). Participants who were isolated only (Isolated+/Lonely−) had higher quality of life (B=16.85, p=.02) compared to two risks (Isolated+/Lonely+).

HIV-related Stigma

Participants with both risks (Isolated+/Lonely+) had the highest average stigma score (mean=3.23, SD=2.23) as compared to all other groups. A follow-up pairwise comparison using Bonferroni adjustments showed significant differences among four groups with Lonely+ participants showing poorer outcomes. Specifically, there were significant differences in Isolated+/Lonely+ group in comparison to Isolated+/Lonely− (OR=4.081, CI=1.262, 13.197; p=.018) and Isolated−/Lonely− (OR=6.06, CI= 2.374, 15.468; p<.001) groups. There were significant differences in Isolated−/Lonely+ group in comparison to Isolated−/Lonely− (OR=0.20, CI= 0.095,0.427; p<.001) and Isolated+/Lonely− (OR=0.299, CI=0.107, 0.836; p=.0214) groups. There were no differences in stigma between Isolated+/Lonely+ and Isolated−/Lonely+ groups.

The chi-square test for proportional odds model showed a significant association in Isolated/Lonely groups on HIV-related stigma (X2=98.55; p<.001), controlling for covariates. The odds of stigma were 1.22 and 6.06 higher for participants with two risks (Isolated+/Lonely+) in comparison to participants who were lonely only (Isolated−/Lonely+; p=.016) and neither (Isolated−/Lonely−; p<.001), respectively.

DISCUSSION

OPWH are a rapidly growing subpopulation of HIV with an increased risk for social isolation and loneliness. While there are studies that assessed social isolation and loneliness among OPWH, no studies to date have tested its combined effects on patient-reported outcomes. To fill this gap in the literature, we assessed the overlap between loneliness and social isolation typologies by classifying OPWH by isolation and loneliness statuses: both lonely and isolated (Isolated+/Lonely+), lonely only (Isolated−/Lonely+), socially isolated only (Isolated+/Lonely−), or neither (Isolated−/Lonely−). We also sought to assess the combined effects of loneliness and social isolation on patient-reported outcomes including quality of life (QoL), stigma, and depressive symptoms.

Almost 54% of our sample were either lonely, isolated, or both. Of the 54%, 15% were classified as both lonely and isolated. These rates of either lonely, isolated, or both are much higher than the rates of those older adults without HIV who are older than our sample (Barnes et al., 2022), highlighting the critical issues of social isolation and loneliness in OPWH. Individuals with both SI/L had the greatest risk for poor patient-reported outcomes. Specifically, participants who were ‘both isolated and lonely’ had significantly higher depressive symptoms and lower QoL compared to those who were considered as ‘neither’ or ‘isolated only.’ Similarly, internalized HIV-related stigma was significantly higher for those who were ‘both isolated and lonely’ in comparison to ‘neither’ or ‘lonely only.’ Our findings that demonstrate the greatest risk for poor patient-reported outcomes in people with both isolation and loneliness are consistent with a recent study that tested the combined effects of these two constructs among older adults without HIV (Barnes et al., 2022).

We also found a magnitude of differences in poor patient-reported outcomes for lonely individuals (regardless of being isolated or not) than those who are not lonely. In other words, OPWH who were lonely (either with isolation or no isolation) exhibited worse patient-reported outcomes thank those who were not lonely. Our findings may suggest that loneliness may contribute more strongly to patient-reported outcomes, and that social isolation may not necessarily exert negative influences on patient-reported outcomes unless the person feels lonely. Our findings align with the extent literature in the general older populations without HIV that demonstrate the differential impact of social isolation and loneliness on various health outcomes. However, it is contrary to other studies in the general older adults without HIV where social isolation, not loneliness, was found to be the significant predictor of increased mortality and cognitive decline (Andrew Steptoe et al., 2013; Yu et al., 2021). However, these studies did not assess the extent to which both SI/L are associated with outcomes and did not test patient-reported outcomes. For example, while someone who are socially isolated can have optimal patient-reported outcomes, they may lack tangible and instrumental support that can help with finances or transportation, which may confer cascade of risks for increased health care utilization and place isolated individuals at a significantly higher risk for mortality and cognitive decline (Alcaraz et al, 2018). Longitudinal research is needed to disentangle the bidirectional and reciprocal relationships among SI/L, patient-reported and health outcomes, to ultimately identify the pathways that can explain differential associations of SI/L on health in OPWH.

Among all demographic and clinical characteristics considered, past unstable housing was the only covariate that was significantly different in four Isolation/Lonely groups. Previous research demonstrates that people who experience unstable housing and homelessness face intersectional stigma, exclusion, and marginalization that negatively affect wellbeing and health (Wenzel et al., 2019). All our participants who had past unstable housing were Black/African Americans. While race was not related to SI/L in our sample, we suspect that the intersection of multiply marginalized social positions of race and past housing status may influence and shape the experiences of SI/L. Historically, Black/African Americans are disproportionately affected by several sociodemographic and neighborhood environmental conditions that are directly related to SI/L (Taylor et al, 2023). There may be additional systemic inequities that compound the daily experiences and exposure to social disadvantages. Access to social services and resources may be prohibited among this group, further creating the hierarchies in social determinants that may lead to disparities in social health. Qualitative and mixed methods are needed to elicit the interactive and synergistic effects of marginalized identities and systems of influence on the experiences of SI/L in OPWH. Studies are needed to understand what it is that contribute to both SI/L among this vulnerable population of individuals aging with HIV and address systemic and structural inequities that may be pervasive in shaping the vicious cycle of marginalization, which in turn could influence social isolation and loneliness.

Limitations

Our study findings should be interpreted with limitations in mind. Our secondary data analysis of a cross-sectional design precludes causality statements. Our sample primarily consisted of Black/African Americans; therefore, the findings cannot be assumed to generalize to those who are non-African Americans. Our measure of social isolation was based on self-reported measure that asks frequent contact with 12-types of social relationships. While the measure that we used (SNI) has been validated and used in many other studies, there is potential for recall bias where individuals may be more or less objectively isolated than one perceives one to be. Additionally, while our measure used to assess loneliness has been widely used in other study population, it has not been applied to OPWH, and thus the validity of this measurement has not been specifically tested in this population. Further, this measure does not use a specific time frame and only asks for frequency/persistence of loneliness, failing to capture a broad sense of loneliness severity (Qualter et al., 2021). Studies that elucidate whether chronicity or intensity of loneliness have any discrete effects on patient-reported outcomes are needed. Lastly, we only considered patient-reported outcomes and no other health outcomes that other gerontological studies have investigated, including mortality and cognitive decline. More longitudinal studies that assess for long-term outcomes in combined effects of social isolation and loneliness are needed, as well as efforts to mitigate both issues among OPWH.

Conclusions

Our findings revealed that patient-reported outcomes were greatly affected among those who are both isolated and lonely, highlighting the potential combined effects of isolation and loneliness. Efforts to reduce both isolation and loneliness among OPWH are needed. We also observed that OPWH who endorsed loneliness regardless of social isolation had worse outcomes than those who did not report loneliness, warranting focused attention on finding effective strategies to mitigate loneliness in this ever-growing subpopulation of HIV.

Acknowledgements

This work was supported in part by the National Institute of Nursing Research [F31NR015975] and the National Institute on Aging [K01AG064986]. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Footnotes

Disclosure Statement

The authors report no real or perceived vested interests that relate to this article that could be construed as a conflict of interest.

REFERENCES

  1. Aberaraw R, Boka A, Teshome R, & Yeshambel A (2020). Social networks and quality of life among female breast cancer patients at Tikur Anbessa specialized hospital, Addis Ababa, Ethiopia 2019. BMC women’s health, 20(1), 50–50. 10.1186/s12905-020-00908-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Alcaraz KI, Eddens KS, Blase JL, Diver WR, Patel AV, Teras LR, … Gapstur SM (2018). Social Isolation and Mortality in US Black and White Men and Women. American Journal of Epidemiology, 188(1), 102–109. doi: 10.1093/aje/kwy231 [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Aung MN, Moolphate S, Aung TNN, Katonyoo C, Khamchai S, & Wannakrairot P (2016). The social network index and its relation to later-life depression among the elderly aged ≥80 years in Northern Thailand. Clinical interventions in aging, 11, 1067–1074. 10.2147/CIA.S108974 [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Barnes TL, MacLeod S, Tkatch R, Ahuja M, Albright L, Schaeffer JA, & Yeh CS (2022, Jul). Cumulative effect of loneliness and social isolation on health outcomes among older adults. Aging Ment Health, 26(7), 1327–1334. 10.1080/13607863.2021.1940096 [DOI] [PubMed] [Google Scholar]
  5. Brennan-Ing M, Seidel L, & Karpiak SE (2017). Social Support Systems and Social Network Characteristics of Older Adults with HIV. Interdiscip Top Gerontol Geriatr, 42, 159–172. 10.1159/000448561 [DOI] [PubMed] [Google Scholar]
  6. Celia D, Riley W, Stone A, Rothrock N, Reeve B, Yount S, Amtmann D, Bode R, Buysse D, Choi S, Cook K, Devellis R, DeWalt D, Fries JF, Gershon R, Hahn EA, Lai JS, Pilkonis P, Revicki D, Rose M, Weinfurt K, & Hays R (2010, Nov). The Patient-Reported Outcomes Measurement Information System (PROMIS) developed and tested its first wave of adult self-reported health outcome item banks: 2005-2008. J Clin Epidemiol, 63(11), 1179–1194. 10.1016/i.iclinepi.2010.04.011 [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Cohen S, Doyle WJ, Skoner DP, Rabin BS, & Gwaltney JM Jr. (1997, Jun 25). Social ties and susceptibility to the common cold. Jama, 277(24), 1940–1944. [PubMed] [Google Scholar]
  8. Courtin E, & Knapp M (2017, May). Social isolation, loneliness and health in old age: a scoping review. Health Soc Care Community, 25(3), 799–812. 10.1111/hsc.12311 [DOI] [PubMed] [Google Scholar]
  9. Eaton WW, Smith C, Ybarra M, Muntaner C, & Tien A (2004). Center for Epidemiologic Studies Depression Scale: review and revision (CESD and CESD-R). [Google Scholar]
  10. Erlandson KM, Allshouse AA, Jankowski CM, Duong S, Mawhinney S, Kohrt WM, & Campbell TB (2012, Nov-Dec). Comparison of functional status instruments in HIV- infected adults on effective antiretroviral therapy. HIV Clin Trials, 13(6), 324–334. 10.1310/hct1306-324 [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Erlandson KM, & Piggott DA (2021, Jun). Frailty and HIV: Moving from Characterization to Intervention. Curr HIV/AIDS Rep, 18(3), 157–175. 10.1007/s11904-021-00554-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Gale CR, Westbury L, & Cooper C (2018, May 1). Social isolation and loneliness as risk factors for the progression of frailty: the English Longitudinal Study of Ageing. Age Ageing, 47(3), 392–397. 10.1093/ageing/afx188 [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Greene M, Hessol NA, Perissinotto C, Zepf R, Hutton Parrott A, Foreman C, Whirry R, Gandhi M, & John M (2017, Nov 18). Loneliness in Older Adults Living with HIV. AIDS Behav. 10.1007/s10461-017-1985-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Hays RD, & Morales LS (2001, Jul). The RAND-36 measure of health-related quality of life. Ann Med, 33(5), 350–357. 10.3109/07853890109002089 [DOI] [PubMed] [Google Scholar]
  15. Holt-Lunstad J, Smith TB, Baker M, Harris T, & Stephenson D (2015, Mar). Loneliness and social isolation as risk factors for mortality: a meta-analytic review. Perspect Psychol Sci, 10(2), 227–237. 10.1177/1745691614568352 [DOI] [PubMed] [Google Scholar]
  16. Kalichman SC, Simbayi LC, Cloete A, Mthembu PP, Mkhonta RN, & Ginindza T (2009, Jan). Measuring AIDS stigmas in people living with HIV/AIDS: the Internalized AIDS-Related Stigma Scale. AIDS Care, 21(1), 87–93. 10.1080/09540120802032627 [DOI] [PubMed] [Google Scholar]
  17. Lara E, Caballero FF, Rico-Uribe LA, Olaya B, Haro JM, Ayuso-Mateos JL, & Miret M (2019, Nov). Are loneliness and social isolation associated with cognitive decline? Int J Geriatr Psychiatry, 34(11), 1613–1622. 10.1002/gps.5174 [DOI] [PubMed] [Google Scholar]
  18. Musich S, Wang SS, Slindee L, Kraemer S, & Yeh CS (2019). Association of Resilience and Social Networks with Pain Outcomes Among Older Adults. Population health management, 22(6), 511–521. 10.1089/pop.2018.0199 [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Ong AD, Uchino BN, & Wethington E (2016). Loneliness and Health in Older Adults: A Mini-Review and Synthesis. Gerontology, 62(4), 443–449. 10.1159/000441651 [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Perri M, Craig-Neil A, Gaspar M, Hunter C, Kendall C, Alexander O, & Pinto AD (2021, Jan 14). A qualitative study of barriers to employment experienced by people living with HIV in Toronto and Ottawa. Int J Equity Health, 20(1), 36. 10.1186/s12939-020-01356-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. PROMIS. (2015). PROMIS social isolation: a brief guide to the PROMIS social isolation instruments. https://www.assessmentcenter.net/documents/PROMIS%20Social%20Isolation%20Scoring%20Manual.pdf
  22. Qualter P, Petersen K, Barreto M, Victor C, Hammond C, & Arshad SA (2021, Nov 16). Exploring the Frequency, Intensity, and Duration of Loneliness: A Latent Class Analysis of Data from the BBC Loneliness Experiment. Int J Environ Res Public Health, 18(22). 10.3390/iierph182212027 [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Riley ED, Bangsberg DR, Perry S, Clark RA, Moss AR, & Wu AW (2003, Dec). Reliability and validity of the SF-36 in HIV-infected homeless and marginally housed individuals. Qual Life Res, 12(8), 1051–1058. 10.1023/a:1026166021386 [DOI] [PubMed] [Google Scholar]
  24. Saunders JB, Aasland OG, Babor TF, de la Fuente JR, & Grant M (1993). Development of the Alcohol Use Disorders Identification Test (AUDIT): WHO Collaborative Project on Early Detection of Persons with Harmful Alcohol Consumption--II. Addiction, 88(6), 791–804. doi: 10.1111/j.1360-0443.1993.tb02093.x [DOI] [PubMed] [Google Scholar]
  25. Seeman TE (2000, Jul-Aug). Health promoting effects of friends and family on health outcomes in older adults. Am J Health Promot, 14(6), 362–370. 10.4278/0890-1171-14.6.362 [DOI] [PubMed] [Google Scholar]
  26. Shippy RA, & Karpiak SE (2005, May). The aging HIV/AIDS population: fragile social networks. Aging Ment Health, 9(3), 246–254. 10.1080/13607860412331336850 [DOI] [PubMed] [Google Scholar]
  27. Skinner HA (1982). The drug abuse screening test. Addict Behav, 7(4), 363–371. doi: 10.1016/0306-4603(82)90005-3 [DOI] [PubMed] [Google Scholar]
  28. Steptoe A, Shankar A, Demakakos P, & Wardle J (2013). Social isolation, loneliness, and all-cause mortality in older men and women. Proceedings of the National Academy of Sciences, 110(15), 5797–5801. 10.1073/pnas.1219686110 [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Taylor HO, Tsuchiya K, Nguyen AW, & Mueller C (2023). Sociodemographic Factors and Neighborhood/Environmental Conditions Associated with Social Isolation Among Black Older Adults. Journal of Aging and Health, 35(3–4), 294–306. doi: 10.1177/08982643221118427 [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Van Dam NT, & Earleywine M (2011). Validation of the Center for Epidemiologic Studies Depression Scale—Revised (CESD-R): Pragmatic depression assessment in the general population. Psychiatry research, 186(1), 128–132. [DOI] [PubMed] [Google Scholar]
  31. VanderZee KI, Sanderman R, Heyink JW, & de Haes H (1996). Psychometric qualities of the RAND 36-Item Health Survey 1.0: a multidimensional measure of general health status. Int J Behav Med, 3(2), 104–122. 10.1207/s15327558iibm0302_2 [DOI] [PubMed] [Google Scholar]
  32. Walker Harris V, & Brown TT (2012, Jun). Bone loss in the HIV-infected patient: evidence, clinical implications, and treatment strategies. J Infect Dis, 205 Suppl 3, S391–398. 10.1093/infdis/iis199 [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Wenzel SL, Rhoades H, LaMotte-Kerr W, & Duan L (2019). Everyday discrimination among formerly homeless persons in permanent supportive housing. J Soc Distress Homeless, 28(2), 169–175. 10.1080/10530789.2019.1630959 [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Yoo-Jeong M, Haardorfer R, Holstad M, Hepburn K, & Waldrop-Valverde D (2021, 2021/01/01). Is Social Isolation Related to Emotion Dysregulation and Retention in Care Among Older Persons Living with HIV? AIDS and Behavior, 25(1), 171–181. 10.1007/s10461-020-02957-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Yoo-Jeong M, Hepburn K, Holstad M, Haardorfer R, & Waldrop-Valverde D (2020, Jul). Correlates of loneliness in older persons living with HIV. AIDS Care, 32(7), 869–876. 10.1080/09540121.2019.1659919 [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Yu B, Steptoe A, Chen Y, & Jia X (2021, Jan 22). Social isolation, rather than loneliness, is associated with cognitive decline in older adults: the China Health and Retirement Longitudinal Study. Psychol Med, 1–8. 10.1017/s0033291720001026 [DOI] [PubMed] [Google Scholar]

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