Skip to main content
NCBI home page
Wiley Open Access Collection logoLink to Wiley Open Access Collection
. 2026 May 26;35(9):3708–3720. doi: 10.1111/jocn.70366

Prevalence of Loneliness and Social Isolation Among People Living With HIV: A Systematic Review and Meta‐Analysis

Qi Wen 1,2, Ting Zhao 1,2, Lloyd A Goldsamt 3, Xirongguli Halili 4, Ci Zhang 1,2, Xinyi Lai 1,2, Kexin Zheng 1,2, Honghong Wang 1,2,✉
PMCID: PMC13432012  PMID: 42191424

ABSTRACT

Aim

To estimate the prevalence of loneliness, social isolation, and their co‐occurrence among people living with HIV and to explore factors explaining heterogeneity between estimates.

Design

A systematic review and meta‐analysis.

Data Sources

PubMed, Cochrane Library, SciELO Citation Index (via Web of Science), Scopus, Embase, PsycArticles, and Cumulative Index to Nursing and Allied Health Literature (CINAHL) were searched from inception until November 1, 2024 for relevant studies.

Methods

Study eligibility, data extraction, and methodological quality assessment were conducted independently by two reviewers. Random‐effects meta‐analysis was used to estimate pooled prevalence. Subgroup analyses were performed.

Results

A total of 66 studies were included. The pooled prevalence of loneliness was 46.9% and that of social isolation was 25.9%. However, heterogeneity was very high across studies, and these pooled estimates should therefore be interpreted cautiously. Subgroup analyses suggested regional variation in both loneliness and social isolation. Other subgroup findings should be interpreted cautiously because some subgroup estimates were based on small numbers of studies.

Conclusion

Loneliness and social isolation are highly prevalent among people living with HIV. Population‐specific intervention strategies are needed to reduce this burden, and future studies should further examine contextual and demographic differences to guide intervention design.

Implications for the Profession and/or Patient Care

Routine HIV services should include screening and referral pathways for loneliness and social isolation.

Impact

This systematic review identified the pooled prevalence of loneliness and social isolation among people living with HIV, highlighting a substantial and clinically relevant burden. The findings may influence HIV nurses' practice and inform care approaches for other clinical populations experiencing loneliness and social isolation.

Reporting Method

This systematic review followed the PRISMA and MOOSE reporting guidelines.

Patient or Public Contribution

No patient or public contribution.

Keywords: acquired immunodeficiency syndrome, HIV, loneliness, prevalence, social isolation

What Is Already Known?

Loneliness and social isolation are critical global public health concerns among people living with HIV that can lead to adverse outcomes. The pooled prevalence of loneliness, social isolation, and their co‐occurrence among people living with HIV remains unknown.

What Does This Paper Contribute to the Wider Global Clinical Community?

First, this review estimates the pooled prevalence of loneliness and social isolation among people living with HIV. It also shows that evidence on their co‐occurrence remains limited. Second, the findings support routine screening and targeted support in HIV care, with potential relevance to other clinical populations experiencing loneliness or social isolation.

1. Background

Loneliness and social isolation (SI) have been increasingly recognized as global public health concerns for people living with HIV (PLWH) (Blanco, Baeza, et al. 2025; Cacioppo and Cacioppo 2018; Pollak et al. 2025; Wang, Peng, et al. 2023; Yoo‐Jeong and Nguyen 2024). According to the World Health Organization, loneliness is a subjective, negative emotional state that arises from a perceived gap between desired and actual social connections. In contrast, SI refers to the objective lack of roles, relationships, or interactions (World Health Organization 2025). As related yet distinct constructs, loneliness and SI may occur separately or together.

PLWH are particularly vulnerable to loneliness and SI due to a combination of external and internal factors. Externally, HIV‐related stigma and discrimination may manifest as social avoidance, gossip, verbal abuse, rejection, denial of health or social services, and loss of employment or educational opportunities (Joint United Nations Programme on HIV and AIDS 2021; Neuman and Obermeyer 2013). Internally, many PLWH experience internalized HIV stigma, leading to negative self‐perception, fear of rejection, and concerns about disclosure or transmission. As a coping mechanism, some withdraw from social interaction or self‐isolate, further intensifying loneliness and SI (Amal et al. 2024; Nipher Malika et al. 2024; Xie et al. 2017).

Growing evidence has linked loneliness, SI, and their co‐occurrence to a wide range of adverse health outcomes among PLWH. They are associated with depression, anxiety, substance use, risky sexual behaviours, and cognitive and functional decline (Greene et al. 2018; Grov et al. 2010; Hubach et al. 2015; Pollak et al. 2025). Studies in PLWH further suggest that social isolation is associated with increased hospitalization and mortality (Greysen et al. 2013; Marziali et al. 2021). Consistent with this, a 2023 meta‐analysis of general adults reported that loneliness and SI were associated with a 14% and 32% higher risk, respectively, of all‐cause mortality (Wang, Gao, et al. 2023).

Although many studies have investigated the prevalence estimates of loneliness and/or SI among PLWH, the reported prevalence varied widely, ranging from approximately 20% to 85% (Grosso et al. 2023; Sun et al. 2009). The heterogeneity may reflect differences in methodology, sample characteristics, cultural context, and measurement tools. For example, culture affects levels of loneliness: loneliness tends to be more prevalent in collectivistic than in individualistic cultural contexts (Lykes and Kemmelmeier 2014). To date, only one known systematic review has focused on the prevalence of loneliness and SI among PLWH, reporting a pooled loneliness prevalence of 33.9% from eight studies (Pollak et al. 2025). However, it was restricted to older PLWH and only provided the prevalence of loneliness. It failed to investigate the parallel pooled prevalence of loneliness, SI, and their co‐occurrence among PLWH and to explore potential sources of heterogeneity between estimates. This gap limits comprehensive analyses of prevalence levels and patterns.

To address this gap, this systematic review and meta‐analysis aimed to (1) estimate the prevalence of loneliness, SI, and their co‐occurrence among PLWH using meta‐analytic techniques, and (2) explore the sources of heterogeneity between study‐ and population‐level factors, as well as measurement tools.

2. Methods

This systematic review and meta‐analysis followed the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) guidelines (Moher et al. 2009) (See Data S1) and the Meta‐analysis of Observational Studies in Epidemiology (MOOSE) checklist (Brooke et al. 2021). This review was prospectively registered with PROSPERO (ID: CRD420251016419).

2.1. Literature Search

We searched PubMed, Cochrane Library, SciELO Citation Index (via Web of Science), Scopus, Embase, PsycArticles, and Cumulative Index to Nursing and Allied Health Literature (CINAHL) from inception to November 1, 2024. Search terms included “HIV/HIV Infections/Acquired Immunodeficiency Syndrome/HIV Seropositivity”, and “Social Alienation/Social Isolation/Loneliness/Ostracism”. Search strategies were tailored to each database (Appendix S1). In addition to database searches, we also screened key scientific journals, major conferences, grey literature, and randomized controlled trial (RCT) registries. Furthermore, the reference lists of eligible articles and relevant systematic reviews were manually screened to identify additional studies. These methods are further detailed in Appendix S2. No restrictions were applied on the language, publication year, or geographic region.

2.2. Eligibility Criteria

Studies were included if they: (1) involved PLWH aged 18 years or older; (2) reported extractable or convertible data on the prevalence of loneliness, SI, or their co‐occurrence; and (3) were cross‐sectional studies, cohort studies, or randomized controlled trials (RCTs) with extractable baseline (pre‐intervention) prevalence data. Conference abstracts, protocols, and reviews were not included, but their references were screened to identify additional eligible studies. If multiple publications used the same dataset, only the one with the largest sample was included. For longitudinal studies, we used data from the time point with the largest sample size. Studies were excluded if they: (1) lacked full‐text availability; (2) lacked sufficient data to calculate prevalence and no additional information was available from the authors; or (3) reported on mixed populations without stratified data for PLWH. Highly selected samples (e. g., injection drug users) were included in the qualitative synthesis but excluded from the meta‐analysis due to limited generalizability.

2.3. Study Selection and Data Collection

Two researchers independently screened titles, abstracts, and full texts, and extracted data. Disagreements were resolved through discussion with a third reviewer. A standardized data extraction form was developed and pilot‐tested. Extracted items included study characteristics, population characteristics, measurement tools, and prevalence estimates. Study authors were contacted as needed for missing or unclear information.

2.4. Risk of Bias

Risk of bias was assessed using the Joanna Briggs Institute (JBI) Prevalence Critical Appraisal Tool (Migliavaca et al. 2020; Munn et al. 2015). The tool consists of nine items, each rated as “Yes”, “No”, or “Unclear/Not Applicable”. Each “Yes” answer scored 1 point (others scored 0), for a maximum of 9 points. Based on total scores, studies were categorized as follows: low quality (1–3 points), moderate quality (4–6 points), or high quality (7–9 points) (Zhang et al. 2024). The full checklist is available in Appendix S3. Prior to formal quality assessment, two researchers conducted a pilot evaluation involving 2–3 studies of each type. They independently applied the assessment criteria and systematically cross‐checked their results to ensure consistency. Subsequently, two reviewers independently evaluated each study, with disagreements resolved by consensus with a third reviewer.

2.5. Statistical Analysis

Statistical analyses were performed in R version 4.4.3 using the meta, metafor, and weightr packages. A random‐effects model based on a proportions approach was used to pool prevalence estimates due to the potential heterogeneity (Borenstein et al. 2010). The Freeman–Tukey double arcsine transformation was applied to stabilize variances when pooling prevalence estimates, particularly because some study‐specific prevalence estimates approached 0 or 1, which can otherwise lead to variance instability and undue weighting of extreme estimates in meta‐analyses of prevalence (Barendregt et al. 2013). Heterogeneity was assessed using Cochran's Q test (p < 0.05). It was quantified by the I2 statistic and the between‐study variance (τ2), with τ2 estimated via restricted maximum likelihood. In addition to 95% confidence intervals, 95% prediction intervals were calculated for the main pooled prevalence estimates to better reflect between‐study variability and the range in which prevalence may be expected in a future similar study (Higgins et al. 2024; IntHout et al. 2016).

We explored potential sources of heterogeneity through subgroup analyses, using a Wald‐type estimator for pre‐specified variables, including geographic region, gender, age, highest educational level, relationship status, residence, living arrangement, employment status, sexual orientation, measurement tools, study design, publication year, and sample size, where sufficient data were available. To evaluate the robustness of the results, sensitivity analyses were conducted by (1) omitting each study one at a time (leave‐one‐out analysis) and (2) removing studies rated as low quality. Publication bias was assessed using funnel plots and Egger's test using both logit and arcsine transformations to ensure robustness (Egger et al. 1997). Two‐sided p < 0.05 was considered statistically significant.

3. Results

3.1. Study Selection

A total of 21,787 records were identified, including 20,075 from databases and 1712 from other sources. After removing 8403 duplicates and screening titles and abstracts, 920 full‐text articles were assessed for eligibility. Of these, 66 studies were included in the systematic review, and 60 were eligible for meta‐analysis. All included studies were published in English or Chinese. The PRISMA flow diagram is shown in Figure 1.

FIGURE 1.

FIGURE 1

Open in a new tab

PRISMA 2020 flow diagram for new systematic reviews which included searches of databases, registers and other sources. [Colour figure can be viewed at wileyonlinelibrary.com]

3.2. Loneliness

3.2.1. Study Characteristics

Forty‐one studies reported the prevalence of loneliness (Table S1). The mean age of participants ranged from 31.4 to 70.0 years. These studies were conducted in 18 countries, in addition to two multinational samples: 13 in Asia, 12 in North America, seven in Africa, six in Europe, one in South America, and two spanning multiple regions. Most studies were cross‐sectional (n = 37, 90.2%), with 3 cohort studies (7.3%) and 1 randomized controlled trial (2.4%). Sample sizes ranged from 64 to 2973 participants.

3.2.2. Pooled Prevalence of Loneliness

Across 39 studies with 17,664 participants, the pooled prevalence of loneliness among PLWH was 46.9% (95% CI, 39.1–54.7; 95% PI, 5.9–90.9). Considerable heterogeneity was observed across studies (I 2 = 98.6%, τ2 = 0.06, p < 0.001), indicating substantial between‐study variability and suggesting that prevalence may vary markedly across settings (Figure 2).

FIGURE 2.

FIGURE 2

Open in a new tab

Forest plot of the pooled prevalence of loneliness among people living with HIV using the Freeman–Tukey double arcsine transformation. [Colour figure can be viewed at wileyonlinelibrary.com]

Two additional studies were excluded from the meta‐analysis due to highly selective samples: one included only PLWH who were current smokers motivated to quit (prevalence: 63.6%, 166/261), and the other included only PLWH who had disclosed their HIV status (prevalence: 44.3%, 537/1212).

3.2.3. Subgroup Analysis

Subgroup analyses of the prevalence of loneliness by geographic region, gender, age, highest educational level, relationship status, residence, living arrangement, employment status, sexual orientation, measurement tools, study design, publication year, and sample size are summarized in Table 1.

TABLE 1.

Subgroup of the prevalence of loneliness among people living with HIV.

Subgroup Studies, No. Prevalence, % (95% CI) Q value p I 2 , %
Geographic region
Africa 7 38.5 (24.2–52.8) 386.86 < 0.001 98.4
Asia 13 58.3 (44.8–71.7) 3865.62 < 0.001 99.7
Europe 6 32.7 (15.6–49.9) 281.91 < 0.001 98.2
North America 11 44.9 (36.1–53.7) 363.04 < 0.001 97.2
South America 1 a 74.1 (65.8–82.3) 0.00 NA NA
Total between‐group variance NA NA 37.30 < 0.001 NA
Gender
Female 15 41.1 (31.4–50.8) 556.58 < 0.001 97.5
Male 14 38.5 (29.4–47.7) 601.98 < 0.001 97.8
Total between‐group variance NA NA 0.14 0.709 NA
Age
18–50 2 a 73.1 (62.2–84.0) 10.93 < 0.001 90.9
50–59 3 29.9 (6.4–53.3) 201.49 < 0.001 99.0
60— 5 31.9 (17.7–46.1) 124.27 < 0.001 96.8
Total between‐group variance NA NA 25.07 < 0.001 NA
Highest educational level
Primary or lower 4 29.0 (13.1–44.9) 39.29 < 0.001 92.4
Secondary 5 36.5 (23.9–49.0) 55.73 < 0.001 92.8
College or above 6 46.7 (32.7–60.8) 123.54 < 0.001 96.0
Total between‐group variance NA NA 2.77 0.250 NA
Relationship status
Single 4 34.1 (24.6–43.6) 14.23 0.003 78.9
Married/In a relationship 5 25.4 (12.8–37.9) 92.78 < 0.001 95.7
Divorced/Separated/widowed 3 41.3 (19.4–63.1) 23.08 < 0.001 91.3
Total between‐group variance NA NA 1.96 0.376 NA
Residence
Rural 6 31.7 (9.6–53.8) 707.25 < 0.001 99.3
Urban 3 21.1 (15.8–26.3) 10.99 0.004 81.8
Total between‐group variance NA NA 0.85 0.358 NA
Living arrangement
Living alone 5 52.3 (34.5–70.0) 222.72 < 0.001 98.2
Not living alone 2 a 19.0 (12.8–25.3) 7.59 0.006 86.8
Total between‐group variance NA NA 11.99 < 0.001 NA
Employment status
Unemployed/retired 4 36.3 (13.2–59.3) 288.65 < 0.001 99.0
Employed/student 3 24.9 (4.1–45.8) 90.18 < 0.001 97.8
Total between‐group variance NA NA 0.51 0.475 NA
Subgroup Studies, No. Prevalence, % (95% CI) Q value p value I 2 , %
Sexual orientation
Homosexual 3 32.4 (10.9–54.0) 56.71 < 0.001 96.5
Heterosexual 4 42.0 (28.8–55.3) 31.98 < 0.001 90.6
Bisexual/other 3 35.0 (0.9–69.2) 67.34 < 0.001 97.0
Total between‐group variance NA NA 0.61 0.738 NA
Measurement tools
Validated 27 45.7 (36.7–54.6) 5710.95 < 0.001 99.5
Non‐validated 12 48.9 (38.2–59.6) 787.94 < 0.001 98.6
Total between‐group variance NA NA 0.21 0.648 NA
Study design
Cross‐sectional 35 48.4 (41.3–55.5) 6399.48 < 0.001 99.5
Cohort Study 3 19.3 (6.4–32.3) 26.47 < 0.001 92.4
RCT (baseline data only) 1 a 67.7 (63.9–71.4) 0.00 NA NA
Total between‐group variance NA NA 64.20 < 0.001 NA
Publication year
1990— 1 a 14.8 (7.4–22.2) 0.00 NA NA
2000— 2 a 67.7 (34.0–100.0) b 26.38 < 0.001 96.2
2010— 11 61.6 (50.1–73.0) 3104.20 < 0.001 99.7
2020— 25 39.7 (32.2–47.1) 1596.65 < 0.001 98.5
Total between‐group variance NA NA 54.23 < 0.001 NA
Sample size
< 500 27 50.4 (41.5–59.2) 4331.90 < 0.001 99.4
> 500 12 38.5 (29.0–47.9) 1019.39 < 0.001 98.9
Total between‐group variance NA NA 3.24 0.072 NA
Open in a new tab

Note: Wide confidence intervals in some subgroups may also reflect sparse subgroup data, including relatively small numbers of contributing studies and participants. Caption: This table presents the results of subgroup analysis on the prevalence of loneliness among people living with HIV, stratified by geographic region, gender, age, educational level, relationship status, residence, living arrangement, employment status, sexual orientation, measurement tools, study design, publication year, and sample size. Statistical measures (Q value, p‐value, I2) indicate variability in prevalence within and between subgroups.

a

Subgroups represented by ≤ 2 studies should be interpreted cautiously because these estimates may be unstable and strongly influenced by sparse data.

b

95% CIs are back‐transformed from Freeman–Tukey (double‐arcsine) random‐effects models. With sparse, highly heterogeneous data, upper confidence limits may exceed 100% after back‐transformation; upper bounds exceeding 100% were truncated to 100.0% for presentation. The exact upper bound was 101.5% for the 2000‐ publication‐year subgroup.

Subgroup analyses revealed statistically significant differences in the prevalence of loneliness by geographic regions (Q = 37.30; p < 0.001), age (Q = 25.07; p < 0.001), and living arrangement (Q = 11.99; p < 0.001). Regionally, loneliness estimates were higher in Asia (58.3%, 95% CI 44.8–71.7) and lower in Europe (32.7%, 95% CI 15.6–49.9). Other subgroup findings, including age and living arrangement, should be interpreted cautiously because some subgroup estimates were based on one or two studies.

3.3. Social Isolation

3.3.1. Study Characteristics

Twenty‐seven studies reported the prevalence of SI (Table S1). The mean age of participants ranged from 31.7 to 63.0 years. Studies were conducted across continents: nine in North America, seven in Europe, six in Africa, four in Asia, and one in Oceania. In terms of study design, 25 (92.6%) were cross‐sectional, and 2 (7.4%) were cohort studies. Sample size ranged from 18 to 1608 participants.

3.3.2. Pooled Prevalence of Social Isolation

From 23 studies with 10,761 participants, the pooled prevalence of SI among PLWH was 25.9% (95% CI, 17.8–34.8; 95% PI, 0.0–73.8). Heterogeneity was also very high across studies (I 2 = 98.8%, τ2 = 0.05, p < 0.001), indicating considerable between‐study variability and suggesting that prevalence may vary markedly across settings (Figure 3).

FIGURE 3.

FIGURE 3

Open in a new tab

Forest plot of the pooled prevalence of social isolation among people living with HIV using the Freeman–Tukey double arcsine transformation. [Colour figure can be viewed at wileyonlinelibrary.com]

Four additional studies were excluded from the meta‐analysis due to highly selective samples or context‐specific assessments. One focused on veterans living with HIV (prevalence: 59.1%, 499/845), another on PLWH who inject drugs (prevalence: 53.0%, 122/230), and a third on PLWH referred for mental health or related services (prevalence: 10.7%, 11/103). The fourth assessed domain‐specific SI, reporting prevalence of 10.7% (32/300) in the community, 3.3% (10/300) in hospital settings, 13.3% (40/300) among siblings, and 12.3% (37/300) within religious groups.

3.3.3. Subgroup Analysis

The subgroup analyses of the prevalence of SI by geographic region, gender, age, measurement tools, study design, publication year, and sample size are summarized in Table 2.

TABLE 2.

Subgroup of the prevalence of social isolation among people living with HIV.

Subgroup Studies, No. Prevalence, % (95% CI) Q value p value I 2 , %
Geographic region
Africa 5 37.8 (20.3–55.3) 323.24 < 0.001 98.8
Asia 4 10.5 (0.0–26.1) b 146.79 < 0.001 98.0
Europe 5 37.0 (17.1–56.8) 576.96 < 0.001 99.3
North America 7 22.0 (13.2–30.7) 265.99 < 0.001 97.7
Oceania 1 a 35.9 (30.6–41.2) 0.00 NA NA
Total between‐group variance NA NA 14.95 0.005 NA
Gender
Female 7 22.9 (4.8–40.9) 1232.51 < 0.001 99.5
Male 3 18.5 (6.6–30.5) 15.33 < 0.001 87.0
Total between‐group variance NA NA 0.15 0.695 NA
Age
< 50 2 a 13.6 (0.0–34.0) b 9.60 0.002 89.6
≥ 50 5 25.7 (15.7–35.7) 67.01 < 0.001 94.0
Total between‐group variance NA NA 1.10 0.295 NA
Measurement tools
Validated 11 29.8 (16.6–42.9) 1859.22 < 0.001 99.5
Non‐validated 12 26.8 (17.9–35.8) 662.20 < 0.001 98.3
Total between‐group variance NA NA 0.13 0.720 NA
Study design
Cross‐sectional 21 27.7 (19.3–36.2) 2302.81 < 0.001 99.1
Cohort Study 2 a s 35.4 (24.9–45.9) 19.28 < 0.001 94.8
Total between‐group variance NA NA 1.24 0.265 NA
Publication year
2000— 4 36.2 (15.2–57.1) 205.21 < 0.001 98.5
2010— 7 14.4 (2.5–26.4) 292.30 < 0.001 97.9
2020— 12 34.1 (24.5–43.7) 1281.46 < 0.001 99.1
Total between‐group variance NA NA 7.05 0.030 NA
Sample size
< 500 14 26.6 (16.6–36.6) 918.16 < 0.001 98.6
> 500 9 31.0 (18.2–43.8) 1409.03 < 0.001 99.4
Total between‐group variance NA NA 0.28 0.595 NA
Open in a new tab

Note: Wide confidence intervals in some subgroups may also reflect sparse subgroup data, including relatively small numbers of contributing studies and participants. This table presents the results of subgroup analysis on the prevalence of social isolation among people living with HIV, stratified by geographic region, gender, age, measurement tools, study design, publication year, and sample size. Statistical measures (Q value, p‐value, I2) are provided to indicate the variability in prevalence within and between subgroups.

a

Subgroups represented by ≤ 2 studies should be interpreted cautiously because these estimates may be unstable and strongly influenced by sparse data.

b

95% CIs are back‐transformed from Freeman–Tukey (double‐arcsine) random‐effects models (REML with Hartung–Knapp). With sparse, highly heterogeneous data, lower confidence limits may fall below 0 after back‐transformation; negative lower bounds were truncated to 0.0 for presentation. The exact lower bounds were −5.0% for Asia and −6.8% for the < 50 age subgroup.

Subgroup analyses revealed statistically significant differences in the prevalence of SI by geographic region (Q = 14.95; p = 0.005) and publication year (Q = 7.05; p = 0.030). Regionally, higher SI estimates were observed in Africa (37.8%, 95% CI 20.3–55.3) and Europe (37.0%, 95% CI 17.1–56.8), whereas lower estimates were observed in Asia (10.5%, 95% CI 0.0–26.1). Other subgroup findings should be interpreted cautiously.

3.4. Co‐Occurring Loneliness and Social Isolation

Only two studies reported the prevalence of co‐occurring loneliness and SI (Table S1). Prevalence estimates were 12.3% (49/399) and 27.4% (40/146). Because the available evidence was sparse and highly heterogeneous (I2 = 93.7%, p < 0.001), no reliable pooled prevalence could be provided.

3.5. Publication Bias

For loneliness, funnel‐plot asymmetry suggested small‐study effects; Egger's test was significant under the arcsine transformation (p = 0.040) but not under the logit transformation (p = 0.170) (Figures S1 and S2). Conclusions regarding publication bias for loneliness were sensitive to the transformation method and should therefore be viewed cautiously. For SI, there was no clear evidence of small‐study effects or publication bias (Figures S3 and S4).

3.6. Sensitivity Analyses

Leave‐one‐out sensitivity analyses indicated that no single study had a statistically significant influence on the pooled estimates for either loneliness or SI (Tables S2 and S4). Sensitivity analyses also showed that the pooled estimates were robust to the exclusion of low‐quality studies (Tables S3 and S5).

3.7. Risk of Bias

Based on the JBI checklist, all included studies scored between 2 and 8 out of 9 (Table S6). Forty‐five studies (68.2%) scored 4 or above (moderate‐to‐high quality), while twenty‐one (31.8%) scored 3 or below (low quality). All studies met criterion 1 (appropriate sampling frame). By contrast, only one study (1.5%) met criterion 8 (appropriate statistical analysis), mainly because measures of precision such as confidence intervals were not reported (Figure S5). Other commonly problematic items were criterion 5 (sufficient coverage of the identified sample in the analysis), criterion 9 (adequate response rate), and criterion 2 (appropriate sampling), many of which were rated as unclear.

4. Discussion

4.1. Summary and Interpretation of Findings

To the best of our knowledge, this is the first systematic review and meta‐analysis to estimate the prevalence of loneliness and SI, and to explore their co‐occurrence among PLWH. The pooled prevalence of loneliness and SI was 46.9% and 25.9%, respectively, highlighting their significance as public health concerns among PLWH. However, heterogeneity was very high across studies, and the corresponding prediction intervals were wide (loneliness: 5.9–90.9; SI: 0.0–73.8), indicating that prevalence may vary markedly across settings. These pooled estimates should therefore be interpreted cautiously. Evidence on the co‐occurrence of loneliness and SI was very limited. Because only two studies were available and heterogeneity was substantial, no reliable pooled prevalence could be provided. This highlights an important evidence gap and suggests that future studies should examine co‐occurring loneliness and social isolation more systematically. Subgroup analyses suggested regional variation in both loneliness and social isolation. Other subgroup findings should be interpreted cautiously because some subgroup estimates were based on small numbers of studies. Measurement tools varied and were categorized by validation status; subgroup analyses found no statistically significant differences. Some variation was also observed by study design and publication year, although these findings should likewise be interpreted with caution. Overall, these patterns underscore the need for greater methodological standardization in future research.

Although these pooled estimates should be interpreted cautiously given the very high heterogeneity, the prevalence of loneliness among PLWH (46.9%) appeared to be higher than that reported for the general population (10.6%) in a global meta‐analysis (Surkalim et al. 2022), underscoring their unique social vulnerability. Notably, loneliness was nearly twice as prevalent as SI (25.9%). This disparity may stem from their conceptual distinction: loneliness refers to a perceived gap between desired and actual relationships, whereas SI reflects an actual lack of social contacts (Cacioppo and Cacioppo 2018; Ong et al. 2016; Valtorta and Hanratty 2012). This difference may also be interpreted through the HIV Stigma Framework, in which internalized stigma and disclosure concerns may increase loneliness by undermining perceived acceptance and support (Earnshaw et al. 2013; Turan et al. 2017). Persistent internalized stigma and fear of disclosure may contribute to loneliness by fostering feelings of exclusion and emotional disconnection (Ninnoni et al. 2023), even when social networks exist. Evidence on the co‐occurrence of loneliness and SI was very limited because only two studies assessed both constructs, and no reliable pooled prevalence could be provided. However, the available studies suggest that co‐occurring loneliness and SI may be associated with poorer patient‐reported outcomes, including greater depressive symptom burden and lower quality of life (Blanco, Gonzalez‐Baeza, et al. 2025; Yoo‐Jeong and Nguyen 2024). This area remains under‐investigated and warrants further research.

The prevalence of loneliness and SI varied substantially across geographic regions, which may reflect cultural, structural, and methodological differences. Loneliness estimates were higher in Asia (58.3%) and lower in Europe (32.7%). These differences may be consistent with the individualism–collectivism distinction (Luhmann et al. 2023; Lykes and Kemmelmeier 2014). Individuals in collectivist societies (e. g., parts of Asia), where maintaining close ties is culturally expected, may feel lonelier when their sense of connectedness is disrupted, even if objective ties are present. In contrast, individuals in individualistic cultures, where autonomy and flexible social ties are valued, may experience less loneliness, as they can pursue more meaningful and personally fulfilling relationships. This cultural distinction is further clarified by the culture–loneliness framework, which highlights that restrictive relational norms increase ideal–actual relationship discrepancies, thereby increasing loneliness (Heu et al. 2021). Stigma may further explain regional variation. It is more pervasive in parts of Asia, where it may heighten feelings of loneliness (Harris et al. 2020; N. Malika et al. 2025; Nipher Malika et al. 2024), but is less prominent in many European countries due to stronger welfare systems and anti‐stigma policies. SI showed a different pattern, with higher prevalence in Africa (37.8%) and Europe (37.0%). This may reflect demographic and structural conditions. For example, high rates of older adults living alone in Europe (Statistical Office of the European Union 2025a, 2025b) and limited access to HIV care in parts of Africa (Mlangeni et al. 2025; World Economic Forum 2021) may constrain social contact. In contrast, Asia showed the lowest SI prevalence (10.5%), potentially due to collectivist cultural norms favoring family cohabitation (Chadda and Deb 2013) and stronger engagement in HIV care and support services.

Age‐related patterns may warrant further investigation, but should be interpreted cautiously because some age categories were represented by only a small number of studies. The available data tentatively suggested lower loneliness but greater social isolation among older PLWH. One possible explanation is that older adults may prioritize emotionally meaningful relationships over the number of social interactions (Carstensen 1992), although this interpretation remains provisional.

Measurement variability likely contributed to the observed heterogeneity. For loneliness, multiple versions of the UCLA Loneliness Scale and other tools (e. g., single‐item measures) were employed (Hou et al. 2023; Nipher Malika et al. 2024; Ninnoni et al. 2023; Quach et al. 2024). SI was assessed using a range of tools such as the Lubben Social Network Scale, PROMIS‐SI, and various single‐item instruments (Abiodun et al. 2021; Blanco, Gonzalez‐Baeza, et al. 2025; Marg et al. 2019; Mesías‐Gazmuri et al. 2023; Neelamegam et al. 2024). Although tools were categorized as validated or non‐validated, subgroup analyses showed no statistically significant differences, suggesting that validation alone did not account for the variability. Additional exploratory analyses by specific tools/scales are presented in Tables S7 and S8 and should be interpreted cautiously because several instrument‐specific categories were represented by only one or two studies. These findings may reflect the lack of standardized, universally accepted measures for loneliness and SI among PLWH, which may limit comparability across studies and weaken the robustness of pooled estimates.

4.2. Implications for Research

This systematic review and meta‐analysis highlight loneliness and SI as prevalent and critical public health concerns among PLWH. Few studies reported on the co‐occurrence of loneliness and SI, underscoring the need for further research. Furthermore, future studies should further examine contextual and demographic differences to inform population‐specific interventions. Standardized tools with clear interpretive thresholds are needed. In addition, longitudinal and interventional designs are needed to clarify causal pathways and identify clinically relevant risk factors for targeted screening and intervention.

4.3. Limitations

This study has some limitations. First, although this review followed both the PRISMA and MOOSE reporting guidelines, these standards are not specifically designed for systematic reviews or meta‐analyses of prevalence (Borges Migliavaca et al. 2020). Meta‐analyses of prevalence can also be misleading when included samples are highly variable (Hoffmann et al. 2020). To address heterogeneity, we applied prespecified eligibility criteria, systematic quality appraisal, a random‐effects model, and extensive subgroup analyses. However, heterogeneity remained high and was not fully explained. Therefore, the pooled prevalence estimates of loneliness and social isolation in this study should be interpreted with caution. Some subgroup analyses were limited by missing or inconsistent sample characteristics, and several estimates were based on only a few studies, warranting cautious interpretation. In addition, variation in measurement tools and threshold definitions may have introduced misclassification bias. To improve comparability, we harmonized cut‐off values where thresholds were clearly reported. Moreover, we adopted a broad inclusion of different study types to obtain a broader pool of prevalence estimates, which may also have contributed to methodological heterogeneity. Although study design was assessed in subgroup analyses, it had a statistically significant influence on the prevalence of loneliness but not on that of SI. Finally, for loneliness, conclusions regarding publication bias were sensitive to the transformation method and should therefore be viewed cautiously. In addition, Egger's test itself has limited interpretability under substantial heterogeneity (Sterne et al. 2000).

5. Conclusions

This systematic review and meta‐analysis found a high prevalence of loneliness (46.9%) and SI (25.9%) among PLWH, indicating a substantial burden. These pooled estimates should be interpreted cautiously because between‐study heterogeneity was very high and prevalence may vary substantially across settings. Evidence on their co‐occurrence remains insufficient, and no reliable pooled prevalence could be derived. Subgroup analyses suggested regional variation in both outcomes. Other subgroup findings should be interpreted cautiously because some subgroup estimates were based on small numbers of studies. Future research should prioritize longitudinal and intervention studies to clarify causal mechanisms and inform targeted prevention and care strategies. Routine assessment of loneliness and SI should be integrated into HIV care, using standardized tools and ensuring broad population coverage.

6. Relevance for Clinical Practice

The high prevalence and poor outcomes associated with loneliness and social isolation among PLWH (Blanco, Gonzalez‐Baeza, et al. 2025; Greene et al. 2018) underscore the need to recognize these concerns as core components of person‐centered HIV care. Routine assessment is particularly important, as many PLWH may not disclose loneliness or limited social contact due to stigma or fear of judgment. Brief, standardized screening tools can support early identification and timely referral. Embedding screening and referral into existing HIV care pathways may strengthen person‐centered care and reduce related health burden.

Author Contributions

Qi Wen: writing – original draft, methodology, investigation, data curation, conceptualization. Ting Zhao: writing – review and editing, methodology, data curation, supervision, conceptualization. Lloyd A. Goldsamt: writing – review and editing, methodology. Xirongguli Halili: writing – review and editing, methodology. Ci Zhang: writing – review and editing, methodology. Xinyi Lai: writing – review and editing, data curation. Kexin Zheng: writing – review and editing, data curation. Honghong Wang: writing – review and editing, supervision, conceptualization.

Funding

The work was supported by the National Natural Science Foundation of China (grant number 82574215); the Hainan Provincial Department of Science and Technology, China (grant number ZDYF2024SHFZ042); and the Fundamental Research Funds for the Central Universities of Central South University (grant number 2025ZZTS0823). The funding sources had no involvement in study design, data collection, analysis, interpretation, or the decision to submit this manuscript for publication.

Ethics Statement

The authors have nothing to report.

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Appendix S1: Search strategy.

Appendix S2: Supplementary Search methods and sources.

Appendix S3: Joanna briggs institute prevalence critical appraisal tool.

Table S1: Study characteristics.

Table S2: Leave‐one‐out sensitivity analyses for pooled prevalence of loneliness.

Table S3: Sensitivity analysis excluding low‐quality studies for pooled prevalence of loneliness.

Table S4: Leave‐one‐out sensitivity analyses for pooled prevalence of social isolation.

Table S5: Sensitivity analysis excluding low‐quality studies for pooled prevalence of social isolation.

Table S6: Risk of bias of included studies.

Table S7: Exploratory subgroup analysis of loneliness by specific measurement tools/scales.

Table S8: Exploratory subgroup analysis of social isolation by specific measurement tools/scales.

References.

Figure S1: Funnel plot with egger's test (logit transformation) for publication bias in pooled prevalence of loneliness.

Figure S2: Funnel plot with egger's test (arcsine transformation) for publication bias in pooled prevalence of loneliness.

Figure S3: Funnel plot with egger's test (logit transformation) for publication bias in pooled prevalence of social isolation.

Figure S4: Funnel plot with egger's test (arcsine transformation) for publication bias in pooled prevalence of social isolation.

Figure S5: Risk of bias assessment overview.

JOCN-35-3708-s001.docx (1,002.4KB, docx)

Data S1: PRISMA 2020 Checklist.

JOCN-35-3708-s002.docx (34.2KB, docx)

Acknowledgements

The authors have nothing to report.

Data Availability Statement

The data that supports the findings of this study are available in the Supporting Information of this article.

References

  1. Abiodun, O. , Sodeinde K., Imhonopi G., Omotosho A., and Amaike C.. 2021. “Social Isolation Is Associated With Major Depressive Disorders Among Women Accessing HIV/AIDS Care in Nigeria.” AIDS Care 34, no. 6: 741–745. 10.1080/09540121.2021.1944595. [DOI] [PubMed] [Google Scholar]
  2. Amal, A. I. , Sukartini T., Kurniawati N. D., Sulistyaningsih D. R., Suyanto S., and Wahyuningsih I. S.. 2024. “Analysis of Coping Strategies and Self‐Stigma Among People Living With HIV (PLHIV): A Cross Sectional Study.” Open Public Health Journal 17: e18749445304007. 10.2174/0118749445304007240328052310. [DOI] [Google Scholar]
  3. Barendregt, J. J. , Doi S. A., Lee Y. Y., Norman R. E., and Vos T.. 2013. “Meta‐Analysis of Prevalence.” Journal of Epidemiology and Community Health 67, no. 11: 974–978. 10.1136/jech-2013-203104. [DOI] [PubMed] [Google Scholar]
  4. Blanco, J. R. , Baeza A. G., de Miguel Buckley R., De La Torre‐Lima J., Cano Smith J., and Olalla J.. 2025. “Loneliness and Social Isolation in People With HIV.” Current Opinion in HIV and AIDS 20, no. 2: 172–182. 10.1097/coh.0000000000000912. [DOI] [PubMed] [Google Scholar]
  5. Blanco, J. R. , Gonzalez‐Baeza A., Martinez‐Vicente A., et al. 2025. “Loneliness and Social Isolation in People With HIV Aged ≥ 50 Years. The no One Alone (NOA)‐GeSIDA Study Conducted by the GeSIDA 12021 Study Group.” HIV Medicine 26, no. 3: 399–414. 10.1111/hiv.13743. [DOI] [PubMed] [Google Scholar]
  6. Borenstein, M. , Hedges L. V., Higgins J. P., and Rothstein H. R.. 2010. “A Basic Introduction to Fixed‐Effect and Random‐Effects Models for Meta‐Analysis.” Research Synthesis Methods 1, no. 2: 97–111. 10.1002/jrsm.12. [DOI] [PubMed] [Google Scholar]
  7. Borges Migliavaca, C. , Stein C., Colpani V., Barker T. H., Munn Z., and Falavigna M.. 2020. “How Are Systematic Reviews of Prevalence Conducted? A Methodological Study.” BMC Medical Research Methodology 20, no. 1: 96. 10.1186/s12874-020-00975-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Brooke, B. S. , Schwartz T. A., and Pawlik T. M.. 2021. “MOOSE Reporting Guidelines for Meta‐Analyses of Observational Studies.” JAMA Surgery 156, no. 8: 787–788. 10.1001/jamasurg.2021.0522. [DOI] [PubMed] [Google Scholar]
  9. Cacioppo, J. T. , and Cacioppo S.. 2018. “The Growing Problem of Loneliness.” Lancet 391, no. 10119: 426. 10.1016/s0140-6736(18)30142-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Carstensen, L. L. 1992. “Social and Emotional Patterns in Adulthood: Support for Socioemotional Selectivity Theory.” Psychology and Aging 7, no. 3: 331–338. 10.1037//0882-7974.7.3.331. [DOI] [PubMed] [Google Scholar]
  11. Chadda, R. K. , and Deb K. S.. 2013. “Indian Family Systems, Collectivistic Society and Psychotherapy.” Indian Journal of Psychiatry 55, no. 2: 299–309. 10.4103/0019-5545.105555. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Earnshaw, V. A. , Smith L. R., Chaudoir S. R., Amico K. R., and Copenhaver M. M.. 2013. “HIV Stigma Mechanisms and Well‐Being Among PLWH: A Test of the HIV Stigma Framework.” AIDS and Behavior 17, no. 5: 1785–1795. 10.1007/s10461-013-0437-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Egger, M. , Davey Smith G., Schneider M., and Minder C.. 1997. “Bias in Meta‐Analysis Detected by a Simple, Graphical Test.” BMJ 315, no. 7109: 629–634. 10.1136/bmj.315.7109.629. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Greene, M. , Hessol N. A., Perissinotto C., et al. 2018. “Loneliness in Older Adults Living With HIV.” AIDS and Behavior 22, no. 5: 1475–1484. 10.1007/s10461-017-1985-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Greysen, S. R. , Horwitz L. I., Covinsky K. E., Gordon K., Ohl M. E., and Justice A. C.. 2013. “Does Social Isolation Predict Hospitalization and Mortality Among HIV+ and Uninfected Older Veterans?” Journal of the American Geriatrics Society 61, no. 9: 1456–1463. 10.1111/jgs.12410. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Grosso, T. M. , Hernández‐Sánchez D., Dragovic G., et al. 2023. “Identifying the Needs of Older People Living With HIV (≥ 50 Years Old) From Multiple Centres Over the World: A Descriptive Analysis.” AIDS Research and Therapy 20, no. 1: 1–10. 10.1186/s12981-022-00488-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Grov, C. , Golub S. A., Parsons J. T., Brennan M., and Karpiak S. E.. 2010. “Loneliness and HIV‐Related Stigma Explain Depression Among Older HIV‐Positive Adults.” AIDS Care 22, no. 5: 630–639. 10.1080/09540120903280901. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Harris, M. , Brouillette M. J., Scott S. C., et al. 2020. “Impact of Loneliness on Brain Health and Quality of Life Among Adults Living With HIV in Canada.” Journal of Acquired Immune Deficiency Syndromes 84, no. 4: 336–344. 10.1097/qai.0000000000002355. [DOI] [PubMed] [Google Scholar]
  19. Heu, L. C. , van Zomeren M., and Hansen N.. 2021. “Does Loneliness Thrive in Relational Freedom or Restriction? The Culture‐Loneliness Framework.” Review of General Psychology 25, no. 1: 60–72. 10.1177/1089268020959033. [DOI] [Google Scholar]
  20. Higgins, J. , Thomas J., Chandler J., et al. 2024. Cochrane Handbook for Systematic Reviews of Interventions. Cochrane. [Google Scholar]
  21. Hoffmann, F. , Eggers D., Pieper D., Zeeb H., and Allers K.. 2020. “An Observational Study Found Large Methodological Heterogeneity in Systematic Reviews Addressing Prevalence and Cumulative Incidence.” Journal of Clinical Epidemiology 119: 92–99. 10.1016/j.jclinepi.2019.12.003. [DOI] [PubMed] [Google Scholar]
  22. Hou, Y. , Cai C., Tang H., et al. 2023. “Sexual Behavior and Perceived Loneliness in Elderly People Living With HIV in China During the COVID‐19 Pandemic.” International Journal of Environmental Research and Public Health 20, no. 3: 2714. 10.3390/ijerph20032714. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Hubach, R. D. , Dodge B., Li M. J., et al. 2015. “Loneliness, HIV‐Related Stigma, and Condom Use Among a Predominantly Rural Sample of HIV‐Positive Men Who Have Sex With Men (MSM).” AIDS Education and Prevention 27, no. 1: 72–83. 10.1521/aeap.2015.27.1.72. [DOI] [PubMed] [Google Scholar]
  24. IntHout, J. , Ioannidis J. P., Rovers M. M., and Goeman J. J.. 2016. “Plea for Routinely Presenting Prediction Intervals in Meta‐Analysis.” BMJ Open 6, no. 7: e010247. 10.1136/bmjopen-2015-010247. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Joint United Nations Programme on HIV and AIDS . 2021. “HIV and Stigma and Discrimination”, https://www.unaids.org/sites/default/files/media_asset/07‐hiv‐human‐rights‐factsheet‐stigma‐discrmination_en.pdf.
  26. Luhmann, M. , Buecker S., and Rüsberg M.. 2023. “Loneliness Across Time and Space.” Nature Reviews Psychology 2, no. 1: 9–23. 10.1038/s44159-022-00124-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Lykes, V. A. , and Kemmelmeier M.. 2014. “What Predicts Loneliness? Cultural Difference Between Individualistic and Collectivistic Societies in Europe.” Journal of Cross‐Cultural Psychology 45, no. 3: 468–490. 10.1177/0022022113509881. [DOI] [Google Scholar]
  28. Malika, N. , Bogart L. M., Matovu J. K. B., et al. 2025. “Intersectional HIV Stigma in Sub‐Saharan Africa, Latin America and the Caribbean: Insights and Pathways Forward ‐ A Scoping Review.” PLOS Global Public Health 5, no. 2: e0004240. 10.1371/journal.pgph.0004240. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Malika, N. , Bogart L. M., Mutchler M. G., et al. 2024. “Loneliness Among Black/African American Adults Living With HIV: Sociodemographic and Psychosocial Correlates and Implications for Adherence.” Journal of Racial and Ethnic Health Disparities 11, no. 4: 2467–2474. 10.1007/s40615-023-01712-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Marg, L. Z. , Heidari O., Taylor J., et al. 2019. “A Multidimensional Assessment of Successful Aging Among Older People Living With Hiv in Palm Springs, California.” AIDS Research and Human Retroviruses 35, no. 11: 1174–1180. 10.1089/aid.2019.0048. [DOI] [PubMed] [Google Scholar]
  31. Marziali, M. E. , McLinden T., Card K. G., et al. 2021. “Social Isolation and Mortality Among People Living With HIV in British Columbia, Canada.” AIDS and Behavior 25, no. 2: 377–388. 10.1007/s10461-020-03000-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Mesías‐Gazmuri, J. , Folch C., Palacio‐Vieira J., et al. 2023. “Syndemic Conditions and Quality of Life in the PISCIS Cohort of People Living With HIV in Catalonia and the Balearic Islands: A Cross Sectional Study.” Health and Quality of Life Outcomes 21, no. 1: 42. 10.1186/s12955-023-02120-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Migliavaca, C. B. , Stein C., Colpani V., Munn Z., and Falavigna M.. 2020. “Quality Assessment of Prevalence Studies: A Systematic Review.” Journal of Clinical Epidemiology 127: 59–68. 10.1016/j.jclinepi.2020.06.039. [DOI] [PubMed] [Google Scholar]
  34. Mlangeni, N. , Lembani M., Adetokunboh O., and Nyasulu P. S.. 2025. “Structural Barriers and Facilitators to Accessing HIV Services for Marginalized Working Populations: Insights From Farm Workers in South Africa.” Health Policy and Planning 40, no. 1: 75–84. 10.1093/heapol/czae098. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Moher, D. , Liberati A., Tetzlaff J., and Altman D. G.. 2009. “Preferred Reporting Items for Systematic Reviews and Meta‐Analyses: The PRISMA Statement.” PLoS Medicine 6, no. 7: e1000097. 10.1371/journal.pmed.1000097. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Munn, Z. , Moola S., Lisy K., Riitano D., and Tufanaru C.. 2015. “Methodological Guidance for Systematic Reviews of Observational Epidemiological Studies Reporting Prevalence and Cumulative Incidence Data.” International Journal of Evidence‐Based Healthcare 13, no. 3: 147–153. 10.1097/xeb.0000000000000054. [DOI] [PubMed] [Google Scholar]
  37. Neelamegam, M. , Ahmad A., Chong M. L., et al. 2024. “Psychosocial Risk Factors and Cognitive Decline in People Living With HIV: Results From the Malaysian HIV and Aging (MHIVA) Study.” AIDS Care 36, no. 8: 1041–1049. 10.1080/09540121.2023.2254543. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Neuman, M. , and Obermeyer C. M.. 2013. “Experiences of Stigma, Discrimination, Care and Support Among People Living With HIV: A Four Country Study.” AIDS and Behavior 17, no. 5: 1796–1808. 10.1007/s10461-013-0432-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Ninnoni, J. P. , Agyemang S. O., Bennin L., et al. 2023. “Coping With Loneliness and Stigma Associated With HIV in a Resource‐Limited Setting, Making a Case for Mental Health Interventions; a Sequential Mixed Methods Study.” BMC Psychiatry 23, no. 1: 163. 10.1186/s12888-023-04643-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Ong, A. D. , Uchino B. N., and Wethington E.. 2016. “Loneliness and Health in Older Adults: A Mini‐Review and Synthesis.” Gerontology 62, no. 4: 443–449. 10.1159/000441651. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Pollak, C. , Cotton K., Winter J., and Blumen H.. 2025. “Health Outcomes Associated With Loneliness and Social Isolation in Older Adults Living With HIV: A Systematic Review.” AIDS and Behavior 29, no. 1: 166–186. 10.1007/s10461-024-04471-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Quach, L. T. , Ritchie C. S., Reynolds Z., et al. 2024. “HIV, Social Networks, and Loneliness Among Older Adults in Uganda.” AIDS and Behavior 28, no. 2: 695–704. 10.1007/s10461-023-04258-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Statistical Office of the European Union . 2025a. “Household Composition Statistics”, https://ec.europa.eu/eurostat/statistics‐explained/index.php?title=Household_composition_statistics.
  44. Statistical Office of the European Union . 2025b. “Proportion of Population Age 65 and Over”, https://ec.europa.eu/eurostat/databrowser/view/tps00028/default/table.
  45. Sterne, J. A. , Gavaghan D., and Egger M.. 2000. “Publication and Related Bias in Meta‐Analysis: Power of Statistical Tests and Prevalence in the Literature.” Journal of Clinical Epidemiology 53, no. 11: 1119–1129. 10.1016/s0895-4356(00)00242-0. [DOI] [PubMed] [Google Scholar]
  46. Sun, Y. H. , Sun L., Wu H. Y., et al. 2009. “Loneliness, Social Support and Family Function of People Living With HIV/AIDS in Anhui Rural Area, China.” International Journal of STD and AIDS 20, no. 4: 255–258. 10.1258/ijsa.2008.008348. [DOI] [PubMed] [Google Scholar]
  47. Surkalim, D. L. , Luo M., Eres R., et al. 2022. “The Prevalence of Loneliness Across 113 Countries: Systematic Review and Meta‐Analysis.” BMJ 376: e067068. 10.1136/bmj-2021-067068. [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Turan, B. , Hatcher A. M., Weiser S. D., Johnson M. O., Rice W. S., and Turan J. M.. 2017. “Framing Mechanisms Linking HIV‐Related Stigma, Adherence to Treatment, and Health Outcomes.” American Journal of Public Health 107, no. 6: 863–869. 10.2105/ajph.2017.303744. [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Valtorta, N. , and Hanratty B.. 2012. “Loneliness, Isolation and the Health of Older Adults: Do We Need a New Research Agenda?” Journal of the Royal Society of Medicine 105, no. 12: 518–522. 10.1258/jrsm.2012.120128. [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Wang, B. , Peng X., Liang B., et al. 2023. “Loneliness and Its Correlates Among Older Adults Living With HIV: A Multicenter Cross‐Sectional Study.” Journal of Affective Disorders 341: 228–235. 10.1016/j.jad.2023.08.130. [DOI] [PubMed] [Google Scholar]
  51. Wang, F. , Gao Y., Han Z., et al. 2023. “A Systematic Review and Meta‐Analysis of 90 Cohort Studies of Social Isolation, Loneliness and Mortality.” Nature Human Behaviour 7, no. 8: 1307–1319. 10.1038/s41562-023-01617-6. [DOI] [PubMed] [Google Scholar]
  52. World Economic Forum . 2021. “These 6 Maps Reveal Why Distance is Such a Crucial Factor in Tackling HIV in Africa”, https://www.weforum.org/stories/2021/12/hiv‐africa‐healthcare‐covid‐pandemic/.
  53. World Health Organization . 2025. From Loneliness to Social Connection: Charting a Path to Healthier Societies. Report of the WHO Commission on Social Connection. Geneva: World Health Organization. [Google Scholar]
  54. Xie, T. , Yang J. P., Simoni J. M., et al. 2017. “Unable To Be a Human Being in Front of Other People: A Qualitative Study of Self‐Isolation Among People Living With HIV/AIDS in China.” Journal of Clinical Psychology in Medical Settings 24, no. 3–4: 211–222. 10.1007/s10880-017-9513-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Yoo‐Jeong, M. , and Nguyen A. L.. 2024. “Combined Effects of Social Isolation and Loneliness on Patient‐Reported Outcomes in Older Adults With HIV.” AIDS Care 36: 1–8. 10.1080/09540121.2024.2339046. [DOI] [PMC free article] [PubMed] [Google Scholar]
  56. Zhang, X. , Liu J., Ni Y., et al. 2024. “Global Prevalence of Overweight and Obesity in Children and Adolescents: A Systematic Review and Meta‐Analysis.” JAMA Pediatrics 178, no. 8: 800–813. 10.1001/jamapediatrics.2024.1576. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Appendix S1: Search strategy.

Appendix S2: Supplementary Search methods and sources.

Appendix S3: Joanna briggs institute prevalence critical appraisal tool.

Table S1: Study characteristics.

Table S2: Leave‐one‐out sensitivity analyses for pooled prevalence of loneliness.

Table S3: Sensitivity analysis excluding low‐quality studies for pooled prevalence of loneliness.

Table S4: Leave‐one‐out sensitivity analyses for pooled prevalence of social isolation.

Table S5: Sensitivity analysis excluding low‐quality studies for pooled prevalence of social isolation.

Table S6: Risk of bias of included studies.

Table S7: Exploratory subgroup analysis of loneliness by specific measurement tools/scales.

Table S8: Exploratory subgroup analysis of social isolation by specific measurement tools/scales.

References.

Figure S1: Funnel plot with egger's test (logit transformation) for publication bias in pooled prevalence of loneliness.

Figure S2: Funnel plot with egger's test (arcsine transformation) for publication bias in pooled prevalence of loneliness.

Figure S3: Funnel plot with egger's test (logit transformation) for publication bias in pooled prevalence of social isolation.

Figure S4: Funnel plot with egger's test (arcsine transformation) for publication bias in pooled prevalence of social isolation.

Figure S5: Risk of bias assessment overview.

JOCN-35-3708-s001.docx (1,002.4KB, docx)

Data S1: PRISMA 2020 Checklist.

JOCN-35-3708-s002.docx (34.2KB, docx)

Data Availability Statement

The data that supports the findings of this study are available in the Supporting Information of this article.

Articles from Journal of Clinical Nursing are provided here courtesy of Wiley

RESOURCES