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Revista do Instituto de Medicina Tropical de São Paulo logoLink to Revista do Instituto de Medicina Tropical de São Paulo
. 2025 Aug 18;67:e53. doi: 10.1590/S1678-9946202567053

Factors related to loss to follow-up among people living with HIV: a systematic review

Zeca Manuel Salimo 1,2, Vivian Iida Avelino-Silva 3, Elizangela Farias da Silva 4, Yury Oliveira Chaves 5,6, Michele Rocha de Araujo El Kadri 6, Paulo Afonso Nogueira 5,6,7, Adele Schwartz Benzaken 1,8
PMCID: PMC12364488  PMID: 40834146

ABSTRACT

Loss to follow-up (LTFU) among people living with HIV (PLHIV) is a concerning reality in various healthcare services and can occur at any stage of HIV care. LTFU can lead to a decline in overall health and quality of life for PLHIV; moreover, antiretroviral therapy (ART) interruption increase the risk of HIV sexual transmission. This systematic review investigated factors related to LTFU among PLHIV. The review included sources from PubMed, Cochrane Library, Embase, and others. We included observational studies published in English, Spanish, or Portuguese, from January 1, 2004, to December 31, 2024. We identified 36 studies from 20 countries in North and South America, Europe, Asia, and Africa. The studies included 69,789 PLHIV, of whom 22% were classified as LTFU. The time frame used to define LTFU varied across studies, ranging from 14 to 365 days. The most frequently reported factors associated with LTFU were younger age, low educational level, financial instability, illicit drug use, stigma, absence of family and social support, and ART side effects. Other relevant factors included long commuting time to healthcare facilities, long waiting time at health units, and issues with provider-patient relationships. Multiple factors may contribute to LTFU among PLHIV in complex and context-dependent ways. To address this issue, healthcare services must develop a comprehensive understanding of the communities they assist, recognizing distinct subgroups and their specific needs. Public health policies should be implemented to promote continuous care for PLHIV, including early diagnosis, multidisciplinary assessment, and social support.

Keywords: HIV, Acquired immunodeficiency syndrome, Follow-up studies, Lost to follow-up, Risk factors

INTRODUCTION

Retention in follow-up is essential within clinical care for people living with HIV (PLHIV) 1 . The UNAIDS 95-95-95, aimed at ending the HIV/AIDS epidemic by 2030 2 , set the goals for 95% of PLHIV being aware of their serological status; with 95% of those diagnosed receiving antiretroviral treatment (ART), and with 95% of those on ART achieve an undetectable viral load 2 . Achieving these targets requires a thorough understanding of and substantial investment in strategies to promote patient adherence to uninterrupted care 3 . From a public health perspective, retention in care is also key for controlling the HIV epidemic since sexual transmission of HIV does not occur from PLHIV under ART with an undetectable viral load 4 . However, loss to follow-up (LTFU) remains a common occurrence among PLHIV in healthcare services worldwide 5-8 . For instance, Zago et al. 9 reported a 25% LTFU rate among PLHIV enrolled in a specialized HIV service in Vitoria city, Brazil. Similar findings were reported in the United States 8,10 , Mozambique 11-13 , Uganda 14,15 , and Zambia 16,17 .

Adherence is crucial for the effectiveness of HIV treatment 3,18 , involving dynamic and multifactorial processes encompassing physical, psychological, social, cultural, and behavioral aspects. It requires collaborative decision-making and shared responsibility between PLHIV, healthcare providers, and social support networks 18 . Although retention in care is relevant for managing any chronic condition, HIV-associated stigma may uniquely influence the risk of LTFU among PLHIV 19 . Such stigma may occur within healthcare services 20 , creating direct barriers continued care. Stigma may also originate from family, friends, coworkers, and other social interactions. In a study including 1,784 PLHIV in Brazil, 64% had suffered some form of stigma or discrimination due to their HIV status, and 46% reported being significantly affected by it 21 . Internalized stigma may also negatively influence treatment adherence 22 . Stigma may also affect the extent to which individuals tolerate the side effects of antiretrovirals without discontinuing treatment. For instance, stigmatizing side effects associated with first-generation antiretrovirals, such as lipodystrophy, may impact self-esteem and treatment adherence 23 .

LTFU is a complex issue with multiple determinants, including social and behavioral factors. It may be defined according to different criteria, including failure to pick up antiretroviral medications from the pharmacy or healthcare unit withing the expected timeframe; missing a scheduled appointment; or failing to attend follow-up visits within a specified period 24,25 . Some studies suggest increasing trends in LTFU among PLHIV 11,18 . Despite the significant challenges in ensuring retention in care and sustained ART adherence, LTFU-associated factors remain not fully understood.

This systematic review aims to summarize the available evidence on factors associated with LTFU among PLHIV. Understanding the determinants and context of LTFU in this population could provide valuable insights for developing interventions and strategies to address this pressing challenge.

MATERIALS AND METHODS

Search strategy and selection criteria

This systematic review followed the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines 26 . The initial research included the databases PubMed, Cochrane Library, and Embase. Additional articles, retrieved from citations of included articles, were also selected. We selected studies published from January 1, 2004, to December 31, 2024, reporting factors associated with LTFU among adult PLHIV. The following search terms were used: “loss to follow-up,” “discontinuation,” “drop out,” “out of care,” “abandonment,” “stopping,” “interruption,” and “unstable patients” (Supplementary Table S1). All articles were imported into EndNote reference management software, version X9 (Clarivate), whereby duplicates were excluded using the “Find Duplicates” function, as described by Bramer 27 . Two investigators (ZMS and EF da S) independently screened titles and abstracts to identify studies relevant to the research objectives. A third investigator (PAN) resolved any discrepancies. The screening process included peer-reviewed original studies published in English, Portuguese, and Spanish, with LTFU timeframes defined according to the Brazilian Ministry of Health guidelines. We included observational studies (cross-sectional, case-control, and cohort studies) that enrolled PLHIV aged 18 years and older, regardless of sex.

Full texts for studies selected based on title and abstract were reviewed by four independent reviewers (ZMS, EF da S, PAN, and ASB) to extract data on factors associated with LTFU among PLHIV. Title, journal, URL or DOI address, study location, year of publication, data source, study objectives, study design, sample size, total number of participants classified as LTFU stratified by sex, duration of LTFU, and factors associated with LTFU identified in each study were extracted and organized in a standardized form (Supplementary Table S2). Studies were then categorized according to study design, including cross-sectional, retrospective cohort, prospective cohort, and case-control. Our search did not identify clinical trials meeting the selection criteria. Studies with outcomes unrelated to the proposed topic or with a design outside our inclusion criteria were excluded.

Risk of bias assessment

All studies meeting the inclusion criteria underwent a risk of bias analysis conducted independently by two authors (ZMS and EFS) using the Cochrane Collaboration “Risk of Bias” tool 28 . Six criteria were evaluated across four types of bias: selection bias, performance and detection bias, attrition bias, and reporting bias (Supplementary Table S3).

Ethical considerations

This study is based exclusively on published literature and did not require approval from an ethics review board.

Data analysis

The SPSS statistical software (version 21.0, SPSS Inc., Chicago, IL, USA) was used for all analysis. From the extracted data, we calculated the percentage of LTFU stratified by sex for each study using the following formula: n/N*100%; n1/N1*100%; ΣF + M, in which: F: female; M: male; T: total; %: percentage; n: number of partial sample included in the study stratified by sex; N: total sample included in the study; n1: number of participants LTFU stratified by sex; N1: total number of participants LTFU among PLHIV.

Although some studies identified similar factors associated with LTFU, we observed substantial heterogeneity in terms of design and definitions, preventing us to perform a meta-analysis. Therefore, we opted for a narrative review. Factors associated with LTFU reported in the studies were categorized into three subgroups: sociodemographic factors, clinical factors, and service-related factors. We used GraphPad Prism version 9.02 to develop graphical representations of our findings.

RESULTS

Study selection

A total of 8,328 citations were identified via database searches and other sources, including publications retrieved from citations within the included articles. Of these, 8,165 were excluded after title and abstract screening. These A total of 114 duplicates, 7,852 studies unrelated to the topic, and 199 studies that did not meet at least one inclusion criteria were excluded. The remaining 163 studies were selected for full-text review, of which 127 were excluded. Ultimately, 36 articles were included in this systematic review (Figure 1).

Figure 1. Flowchart of the study selection process.

Figure 1

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Quality assessment and risk of bias

Studies selected for this analysis generally exhibited poor quality in terms of study design, with a moderate risk of bias (Supplementary Table S3).

Characteristics of studies included in the systematic review

A total of 36 primary studies from 20 different countries were included (Figure 2). The study designs were as follows: 12 cross-sectional studies, 18 retrospective cohort studies, five prospective cohort studies, and one case-control study (Table 1). These articles comprehensively addressed the topic by evaluating the characteristics of PLHIV who experienced LTFU, describing the participants and providing data on factors leading to LTFU among adult PLHIV. Some studies included a qualitative component, primarily comprising structured interviews.

Figure 2. Number of eligible studies analyzed per country.

Figure 2

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Table 1. Characteristics of studies included in the analysis.

Articles Number of participants Participants LTFU LTFU time (days) Age (years) Study duration (Months) Study design Location
F n (%) M n (%) T N F n1 (%) M n1 (%) T N1 (%) Mean Median
Muga et al. 37 10 (11.63) 76 (88.37) 86 7 (70.0) 22 (28.95) 29 (33.72) >30 32 - 35 Cross-sectional cohort study Barcelona, Spain
Cardoso and Arruda 7 16 (50.0) 16 (50.0) 32 UN UN 16 (50.0) >90 - 34.5 (30 -39) UN Retrospective cohort study Rio de Janeiro, Brazil
Yuan et al. 8 479 (14.0) 2935 (86.0) 3414 237 (49.4) 1104 (37.6) 1341 (39.3) ≥14 ≥18 - 78 Retrospective cohort study Vienna, USA
Robison et al. 38 186 (25.21) 552 (74.79) 738 18 (9.68) 77 (13.95) 95 (12.87) ≥365 ≥18 - 102 Retrospective cohort study Birmingham, England
Asad et al. 48 1070 (29.0) 2584 (71.0) 3654 59 (5.52) 130 (5.04) 183 (4.92) ≥90 ≥18 - 78 Cross-sectional cohort study Tennessee, USA
Duff et al. 41 45 (100.0) 0 45 14 (31.11) 0 14 (31.11) >90 ≥18 - 36 Retrospective cohort study Western Uganda
Miller et al. 42 396 (75.0) 129 (25.0) 528 UN UN 17 (3.22) >30 31 - 48 Prospective cohort study South Africa
Kranzer et al. 46 752 (65.2) 402 (34.8) 1154 172 (14.90) 115 (9.96) 287 (24.87) >30 - 31.9 (27.3-37.50 70 Retrospective cohort study Cape Town, South Africa
Geng et al. 6 2213 (61.0) 1415 (39.0) 3628 59 (2.31) 20 (1.41) 79 (2.18) ≥183 - 35 (30-42) 48 Prospective cohort study Mbarara, Uganda
Groh et al. 12 76 (45.68) 88 (54.32) 162 UN UN 162 (100.0) >60 30 - 12 Cross-sectional cohort study Zambezia, Mozambique
Schilkowsky et al. 35 340 (36.0) 605 (64.0) 945 51 (15.0) 104 (17.19) 155 (16.40) >90 35 - 115 Prospective cohort study Rio de Janeiro, Brazil
Musheke et al. 16 17 (68.0) 8 (32.0) 25 17 (68.0) 8 (32.0) 25 (100.0) >30 ≥18 - 7 Prospective cohort study Lusaka, Zambia
Zago et al. 9 87 (46.3) 101 (53.7) 250 22 (25.28) 40 (39.60) 62 (24.8) >90 - 39.5 (33-48) 12 Case-control study Vitoria, Brazil
Tran et al. 39 862 (25.0) 2587 (75.0) 3449 104 (12.06) 426 (16.47) 530 (15.37) >90 ≥18 - 48 Prospective cohort study Vietnam
Hughes et al. 10 1212 (30.87) 2714 (69.13) 3926 101 (8.34) 117 (4.31) 218 (5.55) >90 ≥18 - 9 Cross-sectional cohort study USA
McManus et al. 49 205 (6.0) 3208 (94.0) 3413 108 (52.68) 2241 (69.85) 2349 (68.82) ≥365 42.3 - 96 Cross-sectional cohort study Australia
Vuylsteke et al. 29 376 (90.82) 38 (9.18) 414 UN UN 195 (47.0) ≥90 32 - 36 Retrospective cohort study Côte d’Ivoire
Samji et al. 47 1451 (19.0) 6182 (81.0) 7633 573 (39.49) 1287 (20.81) 1860 (24.37) >90 - 38 (32-44) 132 Cross-sectional cohort study Canada
Agbaji et al. 30 8005 (66.6) 4008 (33.4) 12013 2126 (26.6) 1236 (30.8) 3362 (27.98) >360 - 34 (29-41) 12 Retrospective cohort study Nigeria
Marega et al. 11 76 (51.0) 73 (49.0) 149 77 (51.0) 73 (49.0) 149 (100.0) >60 35 - 12 Cross-sectional cohort study Chiure, Mozambique
Rodrigues and Maksud 44 3 (37.5) 5 (62.5) 8 3 (37.5) 5 (62.5) 8 (100.0) >90 ≥18 - 6 Retrospective cohort study Rio de Janeiro, Brazil
Pires et al. 54 206 (69.8) 89 (30.2) 295 54 (26.2) 32 (36.0) 86 (29.2) >60 - 40 (18-62) 12 Cross-sectional cohort Nampula, Mozambique
Akilimali et al. 55 479 (68.8) 238 (31.2) 717 48 (10.02) 38 (15.97) 86 (12.0) ≥90 38.2 - 96 Retrospective cohort study Goma, Congo
Shabalala et al. 36 84 (58) 61 (42) 52 UN UN 11 (21.15) >30 ≥18 - 34 Retrospective cohort study Swaziland
Ibiloye et al. 31 549 (77.3) 161 (22.7) 710 UN UN 166 (23.4) >90 - 30 (24-35) 7 Retrospective cohort study Nasarawa, Nigeria
Seifu et al. 50 850 (58.0) 589 (42.0) 1439 106 (12.47) 107 (18.17) 213 (14.8) ≥90 33.5 - 12 Retrospective cohort study Jigjiga, Ethiopia
Opio et al. 15 391 (60.5) 255 (39.5) 646 35 (8.95) 12 (4.70) 216 (33.4) >90 ≥18 - 24 Retrospective cohort study Wakiso, Uganda
Assemie et al. 53 180 (54.5) 150 (45.5) 330 UN UN 73 (22.12) >90 33.3 - 12 Cross-sectional cohort study Pawi, Ethiopia
Balogun et al. 52 4065 (66.6) 2043 (33.4) 6108 168 (62.7) 100 (37.3) 268 (4.4) >180 - 39 (34-45) 6 Cross-sectional cohort Lagos, Nigeria
Kiwanuka et al. 32 4857 (64.3) 2696 (35.7) 7553 746 (15.36) 434 (16.09) 1180 (15.62) >90 ≥18 - 55 Retrospective cohort study Musaka, Uganda
Palombi and Moda 33 UN UN 82 UN UN 82 (100.0) >60 ≥18 - 3 Retrospective cohort study Mangunde, Mozambique
Nsoh et al. 43 204 (75.3) 67 (24.7) 271 204 (100.0) 67 (100.0) 271 (100.0) >30 33 - 12 Cross-sectional cohort study Nkolndongo, Cameroon
Siti-Azrin et al. 56 38 (13.8) 238 (86.2) 276 12 (19.0) 51 (81.0) 63 (22.82) >90 ≥18 - 19 Retrospective cohort study Selangor, Malaysia
Ma et al. 34 124 (4.95) 2382 (95.05) 2506 24 (19.35) 288 (12.09) 312 (12.45) >30 - 31 (26-40) 192 Retrospective cohort study Jinan, China
Seong et al. 59 223 (7.03) 2949 (92.97 3172 91 (40.80) 1315 (44.59) 1406 (44.33) ≥365 - 35 (27-44) 120 Cross-sectional cohort study Korea
Modipane et al. 51 18 (90.0) 2 (20.0) 20 18 (100.0) 2 (100.0) 20 (100.0) >90 ≥18 - 3 Retrospective cohort study Sekhukhune, South Africa
Total 30143 (43.19) 39646 (56.81) 69789 6138 (20.36) 9451 (23.84) 15589 (22.33)  
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F = female; M = male; T = total; % = percentage; n = number of partial sample included in the study stratified by gender; N = total sample included in the study; n1 = number of participants who LTFU stratified by gender; N1 = total number of participants who LTFU among PLHIV; UN = undetermined; > = greater than; ≥ = greater or equal.

Table 1 summarizes the characteristics of all studies included in this systematic review, including number of participants, number of PLHIV who were LTFU stratified by sex, duration of LTFU, study design, study period and location. Regarding participants’ characteristics, the most common age range was 18 to 44 years of age, with a predominance of males (57%) (Table 1). Common socioeconomic issues included low education 11,29-34 , unemployment 6,16,31,34-36 , illicit drugs use 9,35,37-40 , and economic difficulties 6,10-12,16,32,38,41-43 .

The number of participants varied across studies, ranging from as few as eight PLHIV from a study conducted in Rio de Janeiro, Brazil 44 , to as many as 12,013 participants in a study conducted in Nigeria 30 . Our review included a total of 69,789 PLHIV, of whom 15,589 (22.33%) were LTFU. Among the latter, 61% were male; the percentage of women living with HIV who were subsequently LTFU was 20%, compared to 24% among men. The criteria for defining LTFU varied by country but generally involved not collecting ART from the health unit’s pharmacy for more than 90 days.

Factors related to LTFU among PLHIV

Structured interviews and medical records analysis were the most common methods to identify factors associated with LTFU 9,11,30,33,35,41,44-46 . For better organization, we categorized these factors into three subgroups: sociodemographic, clinical, and service-related factors.

Sociodemographic factors related to LTFU among PLHIV

Risk factors identified in this category included: sex, younger age (18–34 years), single marital status, low education or illiteracy, economic difficulties, unemployment or unstable employment, work obligations, childcare responsibilities, food insecurity, lack of family or social support, stigma, self-concealment of HIV status, limited knowledge about HIV and ART, and disbelief in ART. Additional relevant factors included belief in traditional medicine and religion, perceived physical improvement, disability, patient self-transfer, Black skin color, current smoker, use of illicit drugs, and criminal history (Figure 3).

Figure 3. Sociodemographic factors related to LTFU among PLHIV.

Figure 3

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Twelve studies found that younger PLHIV were more likely to experience LTFU, specifically those aged 18 to 34 years 8,10,15,16,29,30,35,38,39,47-49 . Schilkowsky et al. 35 observed that the risk of LTFU was higher among PLHIV aged 18 to 29 years, with a reduction of approximately 5.0% for each additional year of age. A similar study in Lusaka, Zambia, identified that PLHIV aged 25 to 34 years were at higher risk of LTFU 16 . In Canada, the adjusted hazard ratio (aHR) for LTFU among younger PLHIV was 1.26 (aHR = 1.26; 95% CI: 1.17–1.81) 47 . In Nigeria, one study found that the risk of LTFU among PLHIV decreases with increasing age (aHR = 0.99; 95% CI: 0.98–0.99) 30 . These findings were consistent across multiple studies 8,10,15,16,29,30,35,38,39,47-49 , showing that younger age is a significant predictor of LTFU among PLHIV.

Six studies linked LTFU among PLHIV with the female sex 10,16,37,39,47,48 . Muga et al. 37 reported that approximately 70% of female PLHIV in Spain were LTFU during clinical follow-up , compared to 28.95% of males, indicating a 7.9-fold risk among women (RR = 7.9; 95% CI: 0.0–69.5). Similar findings were reported in Zambia 16 and Canada 47 , where LTFU among women was 68.0% and 34.49%, respectively, compared to 32.0% and 20.81% among men. Other studies 10,39,48 reported similar trends. However, contrasting results were observed in South Africa, in which LTFU was more frequent among men (16.6%) than women (11.1%) 46 . Similar results were reported in Ethiopia 50 .

Two studies reported associations between being single and increased risk of LTFU among PLHIV 30,35 . Schilkowsky et al. 35 found that single participants had a 1.5 times higher risk of LTFU compared to their married counterparts (aHR = 1.502; 95% CI: 1.007–2.240). A similar study conducted in Nigeria reported a risk ratio of 1.24 for single PLHIV (aHR = 1.24; 95% CI: 1.12–1.38) 30 .

Two studies associated Black ethnicity with higher LTFU rates among PLHIV 8,48 . In a U.S.-based study, Black PLHIV had higher risk of LTFU, with a relative risk (RR) of 1.28 (95% CI: 1.13–1.45) compared to White participants 8 . Another U.S. study reported a similar finding (RR = 1.46; 1.08–1.99; P = 0.015) 48 .

Three studies found that perceived physical improvement was associated with LTFU 51-53 . In Nigeria, 6.7% of PLHIV were lost to follow-up because they felt healthy 52 . In Ethiopia, 32.9% of PLHIV stopped taking ART because they believed they had been cured 53 . Similar observations were made in South Africa 51 . Conversely, PLHIV with physical or mental disabilities were also at high risk of LTFU 48 .

Seven studies associated low educational levels or illiteracy to higher rates of LTFU 11,29-34 . In Nigeria, PLHIV with low education levels had an increased risk of LFTU (aHR = 1.24; 95%CI: 1.12–1.40) 30 . Similar findings were observed in other studies conducted in Nigeria 31 Mozambique 11 , Uganda 32 , Côte d’Ivoire 29 , and China 34 .

Ten studies associated LTFU among PLHIV with economic difficulties 6,10-12,16,31,32,38,41,42 . In Western Uganda, 93% of PLHIV who were LTFU reported low economic conditions, often related with difficulties in accessing transportation to healthcare facilities 41 . Similar findings were reported in South Africa 42 and Zambia 16 . In Mozambique, 162 PLHIV were classified as LTFU due to financial difficulties related to food and transportation 12 ; this was observed in another report from Mozambique 11 . In Uganda, PLHIV without a personal telephone number for follow-up contact had a higher risk of LTFU (aHR = 1.69; 95%CI: 1.50–1.91) 32 . Other studies reported similar results 6,10,31,38 .

Six studies linked LTFU among PLHIV to unemployment or unstable employment 6,16,31,34-36 . In a Brazilian study, LTFU risk was significantly higher among PLHIV with unstable jobs 35 ; similar findings were reported in Eswatini 36 . Musheke et al. 16 reported that fear of job loss contributed to LTFU among PLHIV in Zambia. In Nigeria, unemployed individuals had an increased risk of LTFU (aHR = 1.8; 95%CI: 1.2–2.6) 31 . Work responsibilities and childcare commitments were also associated with LTFU 6 .

Three studies associated LTFU among PLHIV with food insecurity 12,33,54 . Food insecurity was the most frequently reported factor among PLHIV who were LTFU, affecting approximately 42.9% of cases 33 . Similar findings were reported in Mozambique 12,54 .

Migration or nomadism was also linked to LTFU among PLHIV 33,36,51 . In Eswatini, patient mobility in search of better living conditions was the key contributor to LTFU 36 . Similarly, Moda and Palombi 33 reported that 11.4% of LTFU cases among PLHIV in Chibabava, Mozambique, were influenced by nomadism. Additionally, self-transfer of patients was associated with a higher risk of LTFU in South Africa 51 .

Six studies found that a lack of family and social support contributed to LTFU 6,7,10,11,16,36 . In a Brazilian study, emotional distress and family issues were linked to LTFU 7 . In Zambia, fear of losing family support was a significant contributor to LTFU 16 . Marega et al. 11 identified that the absence of a confidant was associated with LTFU among PLHIV in Mozambique. In Eswatini, the lack of a social support was also related to LTFU 36 , and similar results were reported in the United States 10 . In Uganda, PLHIV discontinued care after being advised by their families not to return to the healthcare unit (aHR = 4.2; 95%CI: 0.5–14.0) 15 .

Seven studies reported associations between stigma and LTFU 11,15,16,33,41,43,54 . In a study conducted in Uganda, 58% of LTFU cases were attributed to stigma related to HIV status 41 . Similar findings were observed in Mozambique 11,54 . Musheke et al. 16 reported that fear of anticipated stigma was a significant contributor to LTFU in Zambia. Nsoh et al. 43 identified stigma as the most prominent predictor of treatment interruption (47.5%) among PLHIV in Cameroon; similar results were reported in Uganda 15 .

Four studies showed that LTFU among PLHIV was related to non-disclosure of serological status 16,41,50,55 . In Uganda, fear of having their serological status discovered—along with associated stigma—were significant reasons for LTFU, affecting 58% of participants 16 . Similar observations were reported in Zambia 41 . In The Republic of the Congo, PLHIV who did not share their HIV status had a significantly higher risk of LTFU (aHR = 2.28; 95%CI: 1.46–2.29) 55 . Likewise, in Ethiopia, non-disclosure was related to higher risk of LTFU (aHR = 2.8; 95%CI: 2.22–5.23) 50 .

Lack of knowledge about HIV and ART was related to LTFU among PLHIV in a study performed in Zambia 16 . Contributing factors included disbelief in the effectiveness of ART to improve quality of life, as well as a preference for traditional medicine and religious beliefs in healing 16 . Likewise, Duff et al. 41 reported that 60% of PLHIV who abandoned ART in Uganda were unaware of highly active antiretroviral therapy (HAART).

Six studies identified that illicit drug use contributed to LTFU among PLHIV 9,10,35,37,38,47,49 . In a Brazilian study, drug users had 2.3 times higher odds of experiencing LTFU compared to non-users (adjusted odds ratio [aOR] = 2.3; 95%CI: 1.03–5.07) 9 . In Canada, the risk was also elevated among drug users (aHR = 1.46; 95% CI: 1.09–1.89) 36 , with similar observations reported in Spain 37 . Schilkowsky et al. 35 , in a study from Rio de Janeiro, Brazil, found that LTFU was associated both with illicit drug use and with having a criminal record. Similar findings were reported in England 38 , the United States 10 , and Australia 49 . Moreover, a U.S. study found that current smoking was also related to higher risk of LTFU (RR = 1.33; 95% CI: 1.18–1.50) 8 .

Clinical factors related to LTFU among PLHIV

Several clinical factors have been associated with LTFU among PLHIV. These include long delay between diagnosis and the first appointment; delays or failure in delivering laboratory test results; low CD4+ T cell counts; viral load >1,000 copies/mL; advanced disease stage; absence of initial adherence counseling; delays or interruptions in medication delivery; issues with ART adherence; and ART regimen modification. Additional contributing factors include delayed initiation of ART; adherence issues within the first 6 months of ART; prior episodes of LTFU; missing visits in ART dispensation days; high pill burden; ART-related side effects or drug toxicity; and treatment failure (Figure 4).

Figure 4. Clinical factors related to LTFU among PLHIV.

Figure 4

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The time interval between HIV diagnosis and the first medical appointment has been linked to LTFU among PLHIV 35 . A Brazilian study found a statistically significant difference (p = 0.0051) in this lag time between diagnosis and first medical consultation among PLHIV who were lost to follow-up (average delay of 1 year and 4 months for the LTFU group, compared to 7.5 months for those in regular follow-up 35 . These findings suggest that a longer interval between diagnosis and the first appointment is related to higher likelihood of LTFU, similar to a finding reported in the United States 10 .

Two studies found a relationship between delays or non-delivery of laboratory test results and LTFU among PLHIV 16,44 . In Zambia, one study found that some participants reported that they discontinued care due to not receiving test results 16 . Similarly, a study from Brazil identified that delays in delivering laboratory results contributed to LTFU 44 .

Four studies associated LTFU among PLHIV with CD4+ T cell counts <350 cells/mm3, viral load >1,000 copies/mL, and advanced disease stage 9-11,32,41 . A Brazilian study found higher odds of LTFU among PLHIV with CD4+ counts <200 cells/mm3 (aOR = 1.5; 95%CI: 1.03–2.10) and among those with viral load >1,000 copies/mL (aOR = 2.0; 95%CI: 1.34–3.09) 9 . In Uganda, Kiwanuka et al. 32 reported an increased risk of ART non-adherence among PLHIV with CD4+ cell counts of 200-350 μ/ml (aHR = 1.21; 95%CI: 1.01–1.45) and among those at WHO clinical stage 3 or 4 at baseline (aHR = 1.35; 95%CI: 1.10–1.65). Similar findings were reported in Uganda 41 , Mozambique 11 , and the United States 10 . Conversely, two studies conducted in Canada 47 and South Africa 46 also reported LTFU among PLHIV with CD4+ counts ≥350 cells/mm 3 . Additionally, a study from Malaysia found that tuberculosis co-infection was strongly related to LTFU (aOR = 2.0; 95%CI: 1.1–3.7, p = 0.025) 56 .

Two studies reported that LTFU among PLHIV was associated with delays in the delivery of medications 16,44 . In Zambia, participants indicated that abandonment of treatment was driven by unavailability of antiretroviral medications at their health unit, leading to frustration and fatigue due to prolonged waiting times 16 . Similarly, Rodrigues and Maksud 44 reported that delays in medication delivery at scheduled monthly visits contributed significantly to LTFU among PLHIV in Rio de Janeiro, Brazil. Additionally, the lack of initial adherence counseling was also related to LTFU among PLHIV in Côte d’Ivoire 29 .

Seven studies reported that delayed ART initiation was associated with a higher risk of LTFU among PLHIV 8,29,32,34,46,47,49 . In Uganda, patients who initiated ART more than seven days after diagnosis had a higher risk of LTFU (aHR = 1.69; 95%CI: 1.50–1.91) 32 . Similar findings were reported in studies from Canada 47 and South Africa 46 . In China, Ma et al. 34 found that delayed ART initiation was related to a higher risk of LTFU (aHR = 1.43; 95%CI: 1.10–1.85). Other studies also reported similar results 8,29,49 .

Three studies associated the type of ART regimen or a regimen switch with LTFU among PLHIV 34,47,56 . In Canada, patients who initiated treatment with zidovudine had a 2.47-fold higher risk of LTFU compared to those receiving tenofovir (aHR = 2.47; 95%CI: 1.92–3.20) 47 . A study in China reported that patients starting ART with tenofovir alafenamide fumarate had a higher risk of LTFU compared to those receiving zidovudine (aHR = 5.19; 95%CI: 3.29–8.21) 34 . Interestingly, in Malaysia, a history of ART regimen switch was significantly associated with LTFU (aOR = 5.3; 95%CI: 2.2–13.1; p<0.001) 56 .

The frequency of missed ART dispensation visits was also related to LTFU among PLHIV 30 . In Nigeria, PLHIV with an average adherence rate <95% for medication pickup appointments had significantly higher risk of LTFU (aHR = 2.13; 95%CI 1.9–2.40) 30 . A history of prior or short-term LTFU was also identified as a predictor of subsequent LTFU 49 .

Five studies associated ARV side effects with LTFU among PLHIV 7,12,16,36,53 . In a Brazilian study, ART side effects were the primary reason reported for discontinuing care 7 . Similarly, ART side effects accounted for 8.0% of LFTU cases in rural districts of Mozambique 12 . Similar results were observed in Zambia 16 and Eswatini 36 . Additional factors contributing to LFTU included high pill burden, drug toxicity, and treatment failure, as reported by a study from the United States 8 .

Service-related factors related to LTFU among PLHIV

In the risk factors category, LTFU among PLHIV was associated with long distances between patients’ residences and healthcare facilities, logistical issues within health units, and extended waiting times for care. Notably, poor patient-provider relationships were also reported as significant contributors to LTFU (Figure 5).

Figure 5. Service-associated factors related to LTFU among PLHIV.

Figure 5

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In a study from Zambia, long distances between patients’ residences and the healthcare unit was related to LTFU among PLHIV, resulting in 25 participants being LTFU 16 . Seven studies identified several service-related factors contributing to LTFU, including logistical issues, disorganization within healthcare services, and long waiting times for care 11,16,33,36,41,42,44 . For instance, a study from South Africa reported that logistical issues—such as inadequate referral and transfer processes, lack of patient advocates, and limited outpatient hours on weekends—exacerbated LTFU 42 . In Zambia, PLHIV reported long wait times, poor quality of care, and fatigue due to lengthy clinical appointments as reasons for LFTU 16 . Similar issues were reported in Mozambique 11,33 , Brazil 44 , Uganda 41 , and Eswatini 36 .

Six studies associated LTFU with poor patient-provider relationships 12,16,36,41,44,55 . In Mozambique, 42% of LTFU were attributed to poor relationships and/or conflicts between healthcare providers and PLHIV 12 . A similar finding was reported in Eswatini 36 . In Zambia, participants cited rudeness from facility staff as a reason for LTFU 16 . Likewise, in a study from Uganda, 32% of LTFU cases were linked to poor relationship between doctors and patients 41 , and similar findings were observed in Brazil 44 .

DISCUSSION

In this study, we systematically investigated the available evidence regarding factors related to LTFU among PLHIV, based on 36 original observational studies conducted across 20 countries. Our analysis identified three main categories of factors contributing to LTFU: sociodemographic, clinical, and service-related factors.

Although several studies identified similar factors related to LTFU, the underlying motivations are multifactorial, complex, and context-specific. Healthcare services must consider the diverse experiences and the needs of different population groups, each of which faces distinct challenges in how they live, experience illness, and access care 18 . Overlooking these specific characteristics may increase the risk of LTFU, compromising the quality of life of PLHIV and hindering the progress towards achieving the UNAIDS 95-95-95 targets to end the HIV epidemic by 2030 2 .

Several studies in our analysis found that PLHIV aged 18–34 years and those who are single are at higher risk of LTFU 8,10,15,16,29,30,35,38,39,47-49 . This increased risk among the youth may be influenced by factors related to cognitive, sexual, psychological, and physical development 57 . These findings highlight the need to intensify counseling programs on HIV/AIDS and ART within healthcare settings to improve retention rates among young PLHIV.

Our findings also indicate females may be at greater risk of LTFU among PLHIV 10,16,37,39,47,48 ; this results, however, are inconsistent across studies 10,39,48 , suggesting that gender-related factors influencing LTFU are contextual. In Zambia, economic dependence and fear of losing a spouse influenced many women to avoid disclosing their HIV status, resulting in LTFU 16 . Empowering women and intensifying human rights awareness could help address this barrier. In Canada, Samji et al. 47 suggested that the higher risk among women could be partially attributed to ART initiation during pregnancy, followed by treatment discontinuation. Healthcare units should closely monitor pregnant women living with HIV, as they may be particularly vulnerable to LTFU. Additionally, women may experience more frequent and severe ART side effects and toxicities compared to men, due to physiological differences and the influence of sex hormones on drug metabolism 47 .

Factors such as low education or illiteracy, migration or nomadism, unemployment or unstable employment, low economic status, and food insecurity are closely linked to poverty. These variables significantly contributed to LTFU among PLHIV in many studies 11,12,16,30,32-36,54,58 . For example, financial constraints limiting access to transportation and nutrition, as well as the need for frequent relocation in search of better living conditions (nomadism), are poverty-related factors associated with LTFU 33 . Public policies that promote employment opportunities and provide financial support for individuals living in poverty could positively impact retention in care for PLHIV.

Discrimination, lack of family and social support, as well as stigma, can significantly discourage PLHIV from continuing in care 7,11,16,33,36,41,54 . Without social and psychological support, patients may lose confidence and consequently self-exclude from care 11 . To address these issues, we suggest implementing public policies that promote social inclusion, provide emotional support, and combat HIV-related stigma. Additionally, educational programs should emphasize themes of love, respect, and inclusion for all individuals, regardless of their HIV status.

Disbelief in ART is another factor contributing to treatment discontinuation. Studies showed that some patients place greater trust in traditional medicine and faith healing 16 . Rather than viewing faith and traditional medicine as obstacles to ART adherence, healthcare providers and peer navigators should be trained to educate patients about the benefits of ART while respecting their beliefs. Use of illicit drugs and a criminal history have also been related to LTFU among PLHIV 9,35,37,47 . Healthcare units should pay special attention to this group, as they often face significant social exclusion that can undermine their confidence and retention in care 35 .

Regarding clinical and laboratory monitoring of PLHIV, timely medical consultations and prompt ART initiation after diagnosis are crucial. Delays between diagnosis and the first appointment have been associated with increased risk of LTFU 35 . It is also essential that laboratory test results are delivered promptly during routine consultations and clearly explained to the patient 10,11,26,52,59 . Explaining the implications of test results and potential consequences of ART abandonment can help mitigate LTFU.

During routine follow-up, patients who frequently miss ART medication pickup appointments should be informed about risks associated with LTFU for PLHIV 30 . A dedicated team should make all efforts to contact or visit these patients to understand and address their needs, concerns, and barriers to care. Previous studies showed that key factors contributing to LTFU include delays in medication delivery, ART regimen issues, treatment adjustments during the first six months of therapy, delayed ART initiation, high pill burden, drug toxicity, treatment failure, and side effects 7,12,16,30,32,34,36,46 . When ART regimen modifications occur, patients should be carefully informed about the reasons for change, potential side effects, and the expected duration of side effects 18 .

Healthcare services are also crucial in preventing LTFU among PLHIV. Distance between a patient’s residence and the healthcare unit can affect LTFU, particularly for economically disadvantaged patients who struggle with transportation costs. Several studies have identified this as a key factor affecting retention in care 11,16 . Thus, health programs should consider restructuring and decentralizing HIV services, including ART distribution sites. Logistical challenges, disorganized services, and long waiting times have also been associated with increased risk of LTFU 11,16,33,36,41,44 . Finally, poor patient-provider relationships have been identified as significant factors related to LTFU 12,16,36,41,44 . HIV services should implement training programs for healthcare providers that emphasize not only technical aspects but also empathy, respect, and human rights.

Limitations

Although some studies identified similar factors associated with LTFU, we observed substantial heterogeneity in study design and definitions, precluding our ability to proceed with a meta-analysis. Therefore, we opted for a narrative review approach.

CONCLUSION

LTFU among PLHIV can occur at any stage of clinical care. Sociodemographic, clinical, and health service-related factors may contribute to this outcome. Common sociodemographic factors include young age, low education, financial difficulties, illicit drugs use, stigma, and lack of family and social support. Clinical and service-related contributors include delayed ART initiation, medication side effects, long distances to healthcare facilities, and long waiting times. These factors disrupt treatment continuity, hindering the health and quality of life of PLHIV and undermining efforts to control the HIV epidemic. Appropriate measures to ensure ART adherence should be developed considering diverse community, cultural, and environmental contexts. Healthcare services and providers must understand the specific needs and challenges of the populations they serve. Additionally, public and healthcare policies should be developed and implemented to ensure continuous care for PLHIV, from diagnosis to retention in care.

ACKNOWLEDGMENTS

The authors thank the Postgraduate Program in Tropical Medicine at the Amazonas State University for making this study possible. They would also like to express their gratitude to the Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES) for granting a four-year scholarship to ZMS.

Appendix 1.

Supplementary Material available from: https://doi.org/10.48331/scielodata.MCFLHW

Funding Statement

FUNDING: This research received support from Fundacao de Amparo a Pesquisa do Estado do Amazonas (FAPEAM, edital Nº 038/2022, PDPG/CAPES/FAPEAM, Coordenador/Auxilio Financeiro).

Footnotes

FUNDING: This research received support from Fundacao de Amparo a Pesquisa do Estado do Amazonas (FAPEAM, edital Nº 038/2022, PDPG/CAPES/FAPEAM, Coordenador/Auxilio Financeiro).

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