Abstract
Tobacco smoking is highly prevalent among people living with HIV (PLWH), yet there is a lack of data on smoking behaviours and effective treatments in this population. Understanding factors influencing tobacco smoking and cessation is crucial to guide the design of effective interventions. This systematic review and meta-analysis of studies conducted in both high-income (HICs) and low- and middle-income countries (LMICs) synthesised existing evidence on associated factors of smoking and cessation behaviour among PLWH. Male gender, substance use, and loneliness were positively associated with current smoking and negatively associated with smoking abstinence. The association of depression with current smoking and lower abstinence rates were observed only in HICs. The review did not identify randomised controlled trials conducted in LMICs. Findings indicate the need to integrate smoking cessation interventions with mental health and substance use services, provide greater social support, and address other comorbid conditions as part of a comprehensive approach to treating tobacco use in this population. Consistent support from health providers trained to provide advice and treatment options is also an important component of treatment for PLWH engaged in care, especially in LMICs.
Similar content being viewed by others
Avoid common mistakes on your manuscript.
Introduction
Tobacco use is substantially greater in people living with human immunodeficiency virus (HIV) (PLWH), compared to the general population [1]. The double burden of tobacco smoking and HIV transmission is particularly high in low-resource countries [2,3,4,5]. Although improved access to antiretroviral therapy (ART) has significantly reduced HIV-related morbidity and mortality, tobacco smoking threatens to diminish those gains [6,7,8,9,10,11,12]. Compared to PLWH who do not use tobacco, PLWH who smoke have higher rates of tobacco- and HIV-related diseases and poorer adherence and treatment response to ART [13,14,15]. Besides, AIDS-related deaths are higher in smokers living with HIV than in their non-smoking counterparts, resulting in the difference in life expectancy between these two groups of about 12.3 years [16]. Given the high prevalence of tobacco smoking and its detrimental health effects on PLWH, promoting smoking cessation is essential to address this modifiable risk factor, especially among populations in low- and middle-income countries (LMICs) where the burden is heavier, and the gaps in the literature on effective interventions to address tobacco smoking among PLWH are greater [2, 17, 18].
Despite the availability of evidence-based smoking cessation interventions targeting PLWH, many intervention components are not tailored to the unique needs of PLWH to maintain long-term smoking abstinence [18]. Furthermore, studies have shown that compared to the general population, PLWH had lower quit rates and readiness to quit, which were associated with drug abuse, greater emotional issues, and fewer quit attempts [19, 20]. Many studies have identified characteristics of smoking PLWH and determinants of their quitting behaviour. However, no existing systematic review has attempted to scrutinise the associated factors of tobacco smoking and smoking cessation of PLWH to inform future interventions.
A thorough understanding of the demographic, social, behavioural, and cultural factors that affect smoking and cessation behaviour of PLWH is crucial to determine appropriate approaches to reduce tobacco use among this population. Therefore, we conducted a systematic review to synthesise and meta-analyse factors influencing smoking and cessation behaviours, including current tobacco smoking and smoking cessation among PLWH. The differences in associated factors between high-income countries (HICs) and LMICs were also examined in our sub-analyses to understand the unique needs of PLWH in the two settings.
Methods
Search Strategies
The Preferred Reporting Items for Systematic Reviews and Meta-analyses Protocols (PRISMA-P) checklist was used to develop the systematic review protocol (see Online Appendix) [21]. A systematic search was conducted through four databases (PubMed, Scopus, PsycINFO, and Web of Science).
The search strategies utilised Boolean operation, MeSH terms and text words related to HIV transmission, tobacco smoking and smoking cessation (Table S1). The scope of this review was restricted to peer-reviewed studies published between 2011 and 2023 in the English language and conducted on human subjects.
In this review, current smoking and smoking cessation were the primary outcomes of interest. Current smoking status was defined as participants’ self-reported current daily or intermittent tobacco smoking by the study entry. Smoking cessation was defined as self-reported quitting behaviour (e.g., ever quitting, former smoking, quitting after testing HIV-positive, and quitting in the past six months) or clinically confirmed abstinence (e.g., carbon monoxide-verified 7-day point prevalence abstinence). Secondary outcomes included intention to quit, quit attempts, adherence, uptake, and receipt of smoking cessation aids/programmes/interventions.
Our study aimed to explore associated factors of current smoking and smoking cessation rather than the effect of interventions on smoking cessation in a particular trial. Therefore, the analysis included both observational and interventional studies to comprehensively assess what could influence smoking cessation in PLWH [22, 23].
Study Selection
Two reviewers independently reviewed and screened titles, abstracts, and full text of the selected articles in Rayyan–QCRI. For inclusion criteria, studies must: (1) be published in the English language and peer-reviewed journals; (2) empirically explore the relationship between predictors of current smoking and cessation behaviour; and (3) be conducted on PLWH. We included observational (i.e., cross-sectional and cohort studies) and experimental (i.e., randomised-controlled trials/RCTs and quasi-experimental studies) study designs. Pilot or qualitative studies, non-research articles and abstract-only papers were excluded. If the two reviewers could not reach an agreement, a third reviewer was consulted to reach a consensus. We contacted authors for non-reported estimates. Papers eligible for the systematic review were exported to Endnote X9.
Quality Assessment
Study quality was assessed using the Cochrane risk-of-bias tool (RoB) for randomised trials and the NIH/NILBI tool for quantitative observational studies [24, 25]. For the RoB tool, grading can be ‘Low’ or ‘High’ risk of bias or can express ‘Some concerns’. Studies that fulfilled 70% of the criteria of the NILBI tool were classified as good quality.
Data Extraction and Analysis
We extracted data from eligible studies using a standardised data extraction template (Tables S2–S4). Associated factors of the outcomes of interest were extracted for meta-analyses only if they had been assessed in at least two studies, in which at least one association was statistically significant, and if the definitions and measurements of the factors could be harmonised. Non-harmonisable factors were not meta-analysed but narratively synthesised. If studies only reported stratified analysis, each stratified analysis was considered an independent data set.
If available, we reported findings from the adjusted multivariate analyses. Odds ratios (ORs) were the effect measure of interest for the meta-analysis. Other effect measures, such as relative risks (RRs), hazard ratios (HRs), and coefficients (\(\beta\)), were converted to odds ratios (ORs) for consistency [26]. Non-convertible estimates, such as prevalence ratios (PR), were narratively summarised or separately meta-analysed if they met the criteria for meta-analysis. We estimated the pooled effects (pOR and pPR) separately for factors examined by different analytical methods like Poisson and logistic models, and single and multilevel models due to non-convertible measures.
The effect sizes were extracted with 95% confidence intervals (CIs). If not reported, 95%CIs were estimated based on either standard errors or p-values [27]. The pooled effect of each factor was calculated using random effect meta-analysis (due to anticipated heterogeneity) with an inverse variance weighting method that summarises effect sizes from individual studies. The weight assigned to each study was the inverse of that study’s variance. Forest plots were used to visualise the pooled effect size of each factor. We also performed the sub-analyses to compare the pooled effects between HICs and LMICs.
I2 statistics were used to quantify heterogeneity across studies [28]. An I2 value of 25–50% was classified as low, 50–75% as moderate and ≥ 75% as high heterogeneity [29]. Random-effect meta-regression was performed for factors measured in at least ten studies if moderate to high heterogeneity was suspected. Besides univariate models of meta-regression, we also built multivariate models using a stepwise removal approach. The adjusted \({R}^{2}\) reflects the proportion of between-study variance that can be explained by the model.
Meta-analysis was performed using Stata 17 SE (Stata Corp., College Station, Texas) and command metan [30]. We assessed publication bias using funnel plots and Egger’s test if at least ten studies were included in the meta-analysis.
Results
Study Selection, Characteristics, and Quality Assessment
The search identified 8210 articles. After removing duplicates and articles based on titles, abstracts and full texts, 146 full-text articles were assessed, and 80 articles with 131,854 participants (range: 76–31,270) were included in this review [2, 19, 20, 31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107]. Of the 80 articles, 59 were conducted in HICs (51 of those in the US) and 21 in LMICs. The 80 eligible studies included cross-sectional (n = 45), cohort (n = 27), and RCT design (n = 8, all from the US). The studies explored risk factors of current smoking (n = 41), smoking abstinence (n = 24, none from LMICs) and other smoking-related outcomes (n = 26) among PLWH (some studies assessed multiple outcomes). Fifty-three of the 80 studies were included in the meta-analysis, 35 from HICs and 18 from LMICs; 38 included data on factors associated with current smoking status and 16 on those factors associated with cessation (the study by Miles et al. [66] examined both outcomes). We conducted a narrative synthesis of 27 of the total 80 studies (Fig. 1). See Table 1 for additional study characteristics.
All RCTs were rated as low risk of bias except for the study by Humfleet et al. which did not adjust for age differences between intervention groups [55]. Among cohort and cross-sectional studies (n = 72), two (2.8%) and twelve studies (16.7%) were graded as poor and fair quality, respectively, due to small sample sizes, self-reported data, and uncontrolled confounders, as well as attrition in cohort studies. See Tables S5 and S6 for quality grading elements.
Findings from Quantitative Synthesis
Table 2 describes eligible studies exploring factors associated with current smoking and smoking abstinence, which were included in meta-analyses.
Meta-analyses of Factors Associated with Tobacco Smoking and Smoking Cessation
The meta-analyses summarised 24 factors associated with current smoking and 10 associated with smoking abstinence. Operational definitions of these factors are presented in Table S7. Figure 2a–c shows the forest plots of alcohol use (n = 16), male gender (n = 22), and illicit drug use (n = 13), as these factors are eligible for heterogeneity and publication bias assessment (factors analysed by at least ten studies). See Figs. S1–S3 for the forest plots of other factors.
Factors Associated with Current Smoking
Men were 3.26 times more likely than women to be current smokers (n = 22; 95%CI 2.09–5.10) (Fig. 2a). This result was consistent in sub-analyses of male gender in studies from HICs (n = 10; pOR 1.35 95%CI 1.03–1.77) and LMICs (n = 12; pOR 6.26 95%CI 2.76–14.19). No tertiary education also increased the odds of current smoking (n = 5; pOR 2.11; 95%CI 1.70–2.62) (Table 3). Compared to non-Hispanic White, non-Hispanic Black ethnicity was associated with current smoking (n = 3; pOR 1.68; 95%CI 1.04–2.71). This finding was consistent in studies using the Poisson regression analytical approach (n = 2: pPR 1.09; 95%CI 1.02–1.15) (Table 3). Compared to single, divorced, or widowed PLWH, married PLWH (n = 6; pOR 0.72; 95%CI 0.55–0.95) were less likely to smoke. The reverse association was reported for those divorced or widowed versus those married or in a stable relationship (n = 3; pOR 2.14; 95%CI 1.05–4.37) (Table 3).
Alcohol use and illicit drug use were positively associated with current smoking (Fig. 2b, c). The results remained consistent with hazardous alcohol use in both logistic (n = 6, pOR 1.89; 95%CI 1.33–2.69) and Poisson models (n = 3, pPR 1.41; 95%CI 1.03–1.93) and across different types of drug use (Table 3). The effects of alcohol, hazardous alcohol, illicit drug, and marijuana use on current smoking in LMICs were larger than those in HICs (Table 4). Having smoking partners (n = 2; pOR 6.78; 95%CI 2.03–22.64) or the presence of other smokers in living and social environments (n = 3; multilevel pOR 2.33; 95%CI 0.92–5.88) was associated with current smoking (Table 3).
The meta-analysis of studies in HIC studies showed a positive relationship between depressive symptoms and current smoking (n = 4; pOR 1.18; 95%CI 1.05–1.32) (Table 4). This relationship was not demonstrated in LMIC studies.
Other medical conditions, including chronic obstructive pulmonary disease (COPD) (n = 3; pOR 1.96; 95%CI 0.97–3.94), cardiovascular diseases (CVDs) (n = 4; pOR 1.32; 95%CI 0.98–1.79) and Tuberculosis (n = 4; pOR 1.08 95%CI 0.77–1.53) were positively associated with current smoking, and PLWH who received ART were less likely to smoke (n = 7; pOR 0.92; 95%CI 0.67–1.28) (Table 3). However, these associations were not statistically significant.
Factors Associated with Smoking Abstinence
Men were less likely to quit smoking (n = 2; pOR 0.60; 95%CI 0.37–0.98), and older age was associated with higher abstinence rates (n = 2; pOR 1.08; 95%CI 1.03–1.14) (Table 5).
Those who use cocaine (n = 2; pOR 0.18; 95%CI 0.08–0–44) or displayed hazardous alcohol consumption (n = 4; pOR 0.50; 95%CI 0.39–0.64) were also less likely to abstain from smoking (Table 5). Nicotine dependence was associated with a low likelihood of abstinence rates (n = 4; pOR 0.82; 95%CI 0.75–0.88) (Table 5). However, those who had attempted to quit smoking in the last 12 months were more likely to abstain from smoking (n = 2; pOR 2.65; 95%CI 1.37–5.14) (Table 5).
People with higher UCLA loneliness scores were less likely to quit (n = 2; pOR 0.95; 95%CI 0.91–0.99) (Table 5). Besides, PLWH in HIC with a history of depression had a 21% lower likelihood of quitting smoking (n = 3; pOR 0.79; 95%CI 0.68–0.93) (Table 5). We did not find significant associations between smoking abstinence rates and medication adherence and self-efficacy.
Heterogeneity Assessment
We observed moderate-to-high heterogeneity (\({I}^{2}\) ≥ 50%) in nine out of sixteen factors significantly associated with current smoking (Table 3). However, we assessed high heterogeneity in only three factors associated with current smoking: male gender (n = 22; \({I}^{2}\) = 94.9%; p < 0.001), alcohol use (n = 16; \({I}^{2}\) = 90.3%; p < 0.001), and illicit drug use (n = 13; 91.1%; p < 0.001) as they met the criteria for meta-regression.
Study characteristics, including geographical location (continents), ethnicity, gender, country income level, study quality, outcome definition, the proportion of current and female smokers, sample size and year, were utilised for explanatory meta-regression models (Table S8). For alcohol use, studies conducted in LMICs had 1.22 times (95%CI 0.44–1.99) higher log pOR than those in HICs, and good quality studies reduced the log pOR compared with fair quality studies (\(\beta\) − 1.65; 95%CI − 3.60 to 0.29). This model explained 47.3% out of 86.2% between-study variance. Similarly, 66.4% out of 88.5% heterogeneity in effect sizes of male gender factor was explained by the proportion of current smokers and female smokers. Gender, country income level, outcome definition, and proportion of current smokers explained total between-study variations in effect sizes of illicit drug use.
Assessment of Small Study Effect
Funnel plots for male gender, alcohol use and illicit drug use were created to identify potential publication bias (Fig. 3a–c). Asymmetry could be subjectively seen in the plots for male gender and alcohol use. The funnel plots of illicit drug use were relatively symmetric yet lacked small studies to the left. Egger’s test confirmed the asymmetry of the funnel plot of alcohol use (0 < 0.01), which indicated small-study effects (presence of publication bias). The test did not detect small-study effects of male gender (p = 0.05) illicit drug use (p = 0.58) (Table S9).
Narrative Syntheses of Factors Associated with Current Smoking and Smoking Abstinence
Significant effect sizes of other factors influencing current smoking and smoking abstinence from 26 studies not eligible for meta-analysis are presented in Table S10.
Current Smoking
Findings from the narrative review were largely consistent with those from the meta-analyses as associations of current smoking with loneliness (living alone or homeless), substance use, and depression were frequently reported. Studies by Brath et al. and Mdege et al. found that those having a daily smoking partner (OR 8.78; 95%CI 4.49–17.17) or more than two smokers among the five closest friends (OR 3.97; 95%CI 2.08–7.59) were more likely to be current smokers [2, 19]. In addition, those of Hispanic or Latino ethnicity were less likely to smoke compared to White ethnicity. Other demographic factors, such as higher education and higher socioeconomic status, were associated with a lower likelihood of current smoking. Furthermore, low BMI, chronic diseases such as COPD and asthma, and detectable HIV viral load were associated with higher odds of current smoking.
Smoking Abstinence and Other Smoking Cessation-Related Outcomes
Other factors significantly associated with abstinence rates and the secondary outcomes (intention to quit, quit attempt, adherence, uptake, and receipt of smoking cessation aids) were sorted into categories based on their relation and recurrence across eligible studies. These categories and their relationships were conceptually illustrated in Fig. 4. According to the model, smoking abstinence was influenced proximally by intention to quit, quit attempt, uptake, receipt, and adherence to smoking cessation aids or interventions. Distal factors, including medical conditions (e.g., pulmonary diseases, pain, and CVDs), self-efficacy, social support, depression or anxiety, nicotine dependence, substance use, and provider involvement, were indirectly associated with smoking cessation. These associations concurred with the findings from the meta-analysis.
Discussion
Gender Differences in Smoking
Gender differences in tobacco smoking were consistent with the Demographic and Health Survey data from 28 LMICs that reported 24.4% smoking prevalence in men and 1.3% among women living with HIV [108]. This has been explained by gender inequality that can manifest as the greater social power of men and social pressure against women smoking [109]. Indeed, the qualitative assessment by Thirlway et al. [110] revealed that smoking was widely common and socially accepted among men in Uganda. Smoking-related stigma among women could result in underreporting and create challenges in documenting the true smoking prevalence in this population [110].
The Impact of Psychological Distress
This review found a strong association between depression and current smoking, as well as between depression and smoking abstinence. However, a systematic review has shown some inconsistency regarding the direction of this association [111]. From the qualitative studies, smoking was mainly described as a strategy for dealing with stress and depression in PLWH, which commonly resulted from several stressors, namely financial pressure, stigma, health concerns, traumatic events, and lack of social support [110, 112, 113]. Most of these stressors were identified as factors associated with smoking and unsuccessful abstinence in the descriptive synthesis, which could imply their interrelations with depression.
Furthermore, the meta-analyses found that those who were single, divorced or widowed had a higher likelihood of being current smokers, and loneliness contributed to lower abstinence rates. These results demonstrated that a lack of social support among PLWH is a risk factor for continued tobacco use.
Our review observed a positive association between adverse health conditions (e.g., CVDs, Tuberculosis and COPD) and tobacco smoking. Earlier studies found that some PLWH described worries about adverse health outcomes as their motivation to quit smoking, while others mentioned that smoking helped them feel better when they were too sick [110, 112, 113]. A qualitative study has found that life incidents and lifelong smoking habits are the primary reasons people with COPD do not quit smoking [114]. More studies, therefore, should be conducted to explore these associations further.
Substance Use and Tobacco Smoking
This review found that alcohol, cocaine, crack, marijuana, and injection drug use significantly impacted tobacco smoking and cessation in PLWH, especially in LMICs. Among those substances, alcohol use emerged as a major determinant for current smoking in both meta-analyses and narrative syntheses. This result was in line with findings about alcohol use paired with tobacco smoking that was described as a stress-coping strategy in qualitative studies [110, 113]. Alcohol consumption was also demonstrated to increase smoking relapse through different mechanisms ranging from biochemical pathways to stress-coping theory [115, 116]. Other studies showed the other direction of the association that tobacco smoking was linked to the risk of other substance use and relapse [117, 118].
Despite the concurrence of smoking, substance use, and social and psychological challenges experienced by PLWH, their interrelationships have not been explicitly explored in the literature.
The Role of Healthcare Providers
Substantial evidence, primarily from HICs, showed that smoking cessation interventions implemented in clinical settings delivered by healthcare providers could increase cessation rates [17]. However, our systematic review identified only four quantitative studies that described the influence of providers on disseminating knowledge and skills to quit smoking, illustrating a gap in research in healthcare settings that serve PLWH [34, 64, 77, 78]. Specifically, PLWH whose smoking status was assessed by a physician in the last 12 months were 3.34 times more likely to report readiness to quit [34]. Provider recommendations about smoking cessation also significantly increased the likelihood of interest in quitting and increased perceived risk related to smoking [77, 78]. Qualitative studies also revealed the vital role of healthcare providers in providing support, advice and treatment of tobacco use for PLWH [110, 112, 113]. This finding was consistent with two reports from Matthews et al. and Pacek et al. in high-income contexts, showing the importance of HIV care provider support regarding smoking cessation [78, 119].
Failure to screen for tobacco use, lack of training, and competing healthcare needs and priorities may create barriers to engaging PLWH in treatment [120]. Unfortunately, most providers in LMICs have limited access to training resources to deliver tobacco use treatment for PLWH [112, 121]. PLWH’s regular contact with the healthcare system presents an important opportunity to intervene. Thus, provider training for tobacco use treatment among PLWH is greatly needed in LMICs.
Strengths and Limitations
To our knowledge, this systematic review is the first to apply descriptive and quantitative methods to synthesise evidence about factors influencing smoking and cessation behaviour among PLWH. Findings from our different approaches provided a more comprehensive understanding of predictors of tobacco smoking and cessation behaviour in this understudied population. The review revealed the lack of RCTs of smoking cessation intervention for PLWH in LMICs.
Several drawbacks of the study need to be discussed. Eligible studies have measured smoking abstinence differently, either based on self-reporting or biochemical verification of tobacco smoking. Even though self-reported data have been shown to be accurate, the potential bias cannot be fully ignored [122]. Similarly, biochemical confirmation of smoking abstinence increases the rigour and validity of cigarette smoking and abstinence measurements. However, this measure is not practical to measure long-term abstinence due to costs and implementation challenges [123]. Hence, the results should be interpreted in the context of this limitation. This study did not consider levels of tobacco smoking, such as heavy or light smoking since all included studies mainly reported current smoking as a binary variable. Similarly, pooling reported effect size estimates was challenging due to different time points of abstinence rate assessment. The intention to use the follow-up time as an explanatory factor of potential heterogeneity was not fulfilled due to the small number of studies assessing factors associated with smoking abstinence.
We attempted to harmonise independent variables such as age, education, substance use, and depression from eligible studies based on definitions and measurement scales to make them plausible for the meta-analysis. This process was rigorously conducted to minimise the risk of selection bias and inaccuracy. The poor precision of certain pooled effect sizes, such as smoking partners and crack use, could be due to either the small number of studies or the wide variation in the effect sizes of individual studies.
Finally, heterogeneity of some significant determinants of current smoking remained unexplained due to the few studies. The small number of studies or imprecision of effect sizes may also lead to false low heterogeneity; therefore, the findings should be interpreted in the broader context of existing research.
Conclusion
Smoking is more prevalent in PLWH, who are less likely to quit than the general population. Although studies have explored tobacco smoking and smoking cessation behaviour among the PLWH population, there is a lack of particular reviews that include both HICs and LMICs and a full range of study designs to guide the development and implementation of effective treatments.
This review provided a comprehensive summary of multiple factors associated with smoking and cessation in PLWH, which have implications for future intervention design. Particularly, interventions for PLWH need to be tailored to sociocultural and gender differences and should integrate with screening and treatment for mental health and substance use that addresses these risk factors to optimise cessation outcomes. Given the essential role of HIV care providers, professional training that enables them to effectively assess and assist patients in smoking cessation should be offered. Lastly, RCTs should be conducted to examine the effectiveness of smoking cessation aids/interventions for PLWH in LMICs where the need is greater. Successful implementation of such interventions would reduce the burden of HIV/AIDS and HIV-related comorbidities and increase treatment outcomes in PLWH.
Data Availability
Not applicable.
Code Availability
Stata 17 SE (Stata Corp., College Station, Texas).
References
Johnston PI, Wright SW, Orr M, et al. Worldwide relative smoking prevalence among people living with and without HIV: a systematic review and meta-analysis. AIDS. 2021. https://doi.org/10.1097/QAD.0000000000002815.
Mdege ND, Makumbi FE, Ssenyonga R, et al. Tobacco smoking and associated factors among people living with HIV in Uganda. Nicotine Tob Res. 2021;23(7):1208–16.
UNAIDS. Global AIDS update. Geneva: The Joint United Nations Programme on HIV/AIDS; 2016.
World Health Organization. WHO global report on trends in prevalence of tobacco smoking 2000–2025. 2nd ed. Geneva: World Health Organization; 2018.
World Health Organization. Tobacco. 2020. https://www.who.int/news-room/fact-sheets/detail/tobacco. Accessed 15 Dec 2020.
Altekruse SF, Shiels MS, Modur SP, et al. Cancer burden attributable to cigarette smoking among HIV-infected people in North America. AIDS. 2018;32(4):513–21.
Ande A, McArthur C, Ayuk L, et al. Effect of mild-to-moderate smoking on viral load, cytokines, oxidative stress, and cytochrome P450 enzymes in HIV-infected individuals. PLoS ONE. 2015;10(4): e0122402.
Collaboration ATC. Life expectancy of individuals on combination antiretroviral therapy in high-income countries: a collaborative analysis of 14 cohort studies. The Lancet. 2008;372(9635):293–9.
Feldman JG, Minkoff H, Schneider MF, et al. Association of cigarette smoking with HIV prognosis among women in the HAART era: a report from the women’s interagency HIV study. Am J Public Health. 2006;96(6):1060–5.
Helleberg M, Afzal S, Kronborg G, et al. Mortality attributable to smoking among HIV-1-infected individuals: a nationwide, population-based cohort study. Clin Infect Dis. 2013;56(5):727–34.
Lifson AR, Neuhaus J, Arribas JR, van den Berg-Wolf M, Labriola AM, Read TR. Smoking-related health risks among persons with HIV in the strategies for management of antiretroviral therapy clinical trial. Am J Public Health. 2010;100(10):1896–903.
The RESPOND study group. The interrelationship of smoking, CD4+ cell count, viral load and cancer in persons living with HIV. AIDS. 2021;35(5):747–57.
O’Cleirigh C, Valentine SE, Pinkston M, et al. The unique challenges facing HIV-positive patients who smoke cigarettes: HIV viremia, ART adherence, engagement in HIV care, and concurrent substance use. AIDS Behav. 2015;19(1):178–85.
Shuter J, Bernstein SL. Cigarette smoking is an independent predictor of nonadherence in HIV-infected individuals receiving highly active antiretroviral therapy. Nicotine Tob Res. 2008;10(4):731–6.
Ale BM, Amahowe F, Nganda MM, et al. Global burden of active smoking among people living with HIV on antiretroviral therapy: a systematic review and meta-analysis. Infect Dis Poverty. 2021;10(1):12.
Helleberg M, May MT, Ingle SM, et al. Smoking and life expectancy among HIV-infected individuals on antiretroviral therapy in Europe and North America. AIDS. 2015;29(2):221–9.
Mann-Jackson L, Choi D, Sutfin EL, et al. A qualitative systematic review of cigarette smoking cessation interventions for persons living with HIV. J Cancer Educ. 2019;34(6):1045–58.
Moscou-Jackson G, Commodore-Mensah Y, Farley J, DiGiacomo M. Smoking-cessation interventions in people living with HIV infection: a systematic review. J Assoc Nurses AIDS Care. 2014;25(1):32–45.
Brath H, Grabovac I, Schalk H, Degen O, Dorner TE. Prevalence and correlates of smoking and readiness to quit smoking in people living with HIV in Austria and Germany. PLoS ONE. 2016;11(2):e0150553.
De Socio GV, Maggi P, Ricci E, et al. Smoking habits in human immunodeficiency virus-infected people from Italy: a cross-sectional analysis of the STOPSHIV cohort. AIDS Res Hum Retrovir. 2020;36(1):19–26.
Shamseer L, Moher D, Clarke M, et al. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: elaboration and explanation. BMJ. 2015;350: g7647.
Boon MH, Burns J, Craig P, et al. Value and challenges of using observational studies in systematic reviews of public health interventions. Am J Public Health. 2022;112(4):548–52.
Paul M, Leeflang MM. Reporting of systematic reviews and meta-analysis of observational studies. Clin Microbiol Infect. 2021;27(3):311–4.
National Institutes of Health. Quality assessment tool for observational cohort and cross-sectional studies. 2014. https://www.nhlbi.nih.gov/health-topics/study-quality-assessment-tools. Accessed 16 May 2022.
Sterne JAC, Savovic J, Page MJ, et al. RoB 2: a revised tool for assessing risk of bias in randomised trials. BMJ. 2019;366: l4898.
VanderWeele TJ, Ding P. Sensitivity analysis in observational research: introducing the E-value. Ann Intern Med. 2017;167(4):268–74.
Altman DG, Bland JM. How to obtain the P value from a confidence interval. BMJ. 2011;343: d2304.
Borenstein M. Introduction to meta-analysis. Chichester: Wiley; 2009.
Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ. 2003;327(7414):557–60.
Harris RJ, Deeks JJ, Altman DG, Bradburn MJ, Harbord RM, Sterne JAC. Metan: fixed- and random-effects meta-analysis. Stand Genomic Sci. 2008;8(1):3–28.
Aigner CJ, Gritz ER, Tamí-Maury I, Baum GP, Arduino RC, Vidrine DJ. The role of pain in quitting among human immunodeficiency virus (HIV)–positive smokers enrolled in a smoking cessation trial. Subst Abuse. 2017;38(3):249–52.
Akhtar-Khaleel WZ, Cook RL, Shoptaw S, et al. Trends and predictors of cigarette smoking among HIV seropositive and seronegative men: the multicenter AIDS cohort study. AIDS Behav. 2016;20(3):622–32.
Akhtar-Khaleel WZ, Cook RL, Shoptaw S, et al. Long-term cigarette smoking trajectories among HIV-seropositive and seronegative MSM in the multicenter AIDS cohort study. AIDS Behav. 2016;20(8):1713–21.
Amiya RM, Poudel KC, Poudel T, et al. Physicians are a key to encouraging cessation of smoking among people living with HIV/AIDS: a cross-sectional study in the Kathmandu Valley, Nepal. BMC Public Health. 2011. https://doi.org/10.1186/1471-2458-11-677.
Ashare RL, Thompson M, Serrano K, et al. Placebo-controlled randomized clinical trial testing the efficacy and safety of varenicline for smokers with HIV. Drug Alcohol Depend. 2019;200:26–33.
Batista J, de Fátima Pessoa Militão de Albuquerque MF, Ximenes RA, et al. Prevalence and socioeconomic factors associated with smoking in people living with HIV by sex, in Recife, Brazil. Rev Bras Epidemiol. 2013;16(2):432–43.
Bauer A-M, Hosie Quinn M, Lubitz SF, et al. Medication adherence and rate of nicotine metabolism are associated with response to treatment with varenicline among smokers with HIV. Addict Behav. 2021;112:106638.
Bhatta DN, Subedi A, Sharma N. Tobacco smoking and alcohol drinking among HIV infected people using antiretroviral therapy. Tob Induc Dis. 2018. https://doi.org/10.18332/tid/86716.
Browning KK, Wewers ME, Ferketich AK, Diaz P, Koletar SL, Reynolds NR. Adherence to tobacco dependence treatment among HIV-infected smokers. AIDS Behav. 2016;20(3):608–21.
Buchberg MK, Gritz ER, Kypriotakis G, Arduino RC, Vidrine DJ. The role of BMI change on smoking abstinence in a sample of HIV-infected smokers. AIDS Care. 2016;28(5):603–7.
Bui TC, Piñeiro B, Vidrine DJ, Wetter DW, Frank-Pearce SG, Vidrine JI. Quitline treatment enrollment and cessation outcomes among smokers linked with treatment via ask-advise-connect: comparisons among smokers with and without HIV. Nicotine Tob Res. 2020;22(9):1640–3.
Chew D, Steinberg MB, Thomas P, Swaminathan S, Hodder SL. Evaluation of a smoking cessation program for HIV infected individuals in an urban HIV clinic: challenges and lessons learned. AIDS Res Treat. 2014. https://doi.org/10.1155/2014/237834.
Cioe PA, Gamarel KE, Pantalone DW, Monti PM, Mayer KH, Kahler CW. Characteristics of intermittent smokers and their association with quit intentions in a sample of heavy-drinking HIV-infected men who have sex with men. AIDS Care. 2017;29(6):759–66.
Colón-López V, González-Barrios D, De León S, et al. Population-based study of tobacco use among people living with HIV in Puerto Rico. Subst Use Misuse. 2018;53(3):420–5.
Cropsey KL, Willig JH, Mugavero MJ, et al. Cigarette smokers are less likely to have undetectable viral loads: results from four HIV clinics. J Addict Med. 2016;10(1):13–9.
de Dios MA, Stanton CA, Cano MÁ, Lloyd-Richardson E, Niaura R. The influence of social support on smoking cessation treatment adherence among HIV+ smokers. Nicotine Tob Res. 2016;18(5):1126–33.
De Socio GV, Ricci E, Maggi P, et al. Is It feasible to impact on smoking habits in HIV-infected patients? Mission impossible from the STOPSHIV project cohort. J Acquir Immune Defic Syndr. 2020;83(5):496–503.
Donnelly RE, Minami H, Hecht J, et al. Relationships among self-efficacy, quality of life, perceived vulnerability, and readiness to quit smoking in people living with HIV. J Smok Cessat. 2021. https://doi.org/10.1155/2021/6697404.
Edwards SK, Dean J, Power J, Baker P, Gartner C. Understanding the prevalence of smoking among people living with HIV (PLHIV) in Australia and factors associated with smoking and quitting. AIDS Behav. 2020;24(4):1056–63.
Egbe CO, Londani M, Parry CDH, et al. Tobacco use and nicotine dependence among people living with HIV who drink heavily in South Africa: a cross-sectional baseline study. BMC Public Health. 2019;19(1):1684.
Elf JL, Variava E, Chon S, et al. Prevalence and correlates of smoking among people living with HIV in South Africa. Nicotine Tob Res. 2018;20(9):1124–31.
Gamarel KE, Finer Z, Resnicow K, et al. Associations between internalized HIV stigma and tobacco smoking among adolescents and young adults living with HIV: the moderating role of future orientations. AIDS Behav. 2020;24(1):165–72.
Gamarel KE, Neil TB, et al. A longitudinal study of persistent smoking among HIV-positive gay and bisexual men in primary relationships. Addict Behav. 2016;66:118–24.
Huber M, Ledergerber B, Sauter R, et al. Outcome of smoking cessation counselling of HIV-positive persons by HIV care physicians. HIV Med. 2012;13(7):387–97.
Humfleet GL, Hall SM, Delucchi KL, Dilley JW. A randomized clinical trial of smoking cessation treatments provided in HIV clinical care settings. Nicotine Tob Res. 2013;15(8):1436–45.
Iliyasu Z, Gajida AU, Abubakar IS, Shittu O, Babashani M, Aliyu MH. Patterns and predictors of cigarette smoking among HIV-infected patients in northern Nigeria. Int J STD AIDS. 2012;23(12):849–52.
Kilibarda B, Baros S, Foley K, Milovanovic M, Mravcik V. Smoking among stigmatized populations in Serbia. J Subst Use. 2019;24(5):497–504.
Kim SS, Cooley ME, Lee SA, DeMarco RF. Prediction of smoking abstinence in women living with human immunodeficiency virus infection. Nurs Res. 2020;69(3):167–75.
Kruse GR, Bangsberg DR, Hahn JA, et al. Tobacco use among adults initiating treatment for HIV infection in rural Uganda. AIDS Behav. 2014;18(7):1381–9.
Lam JO, Levine-Hall T, Hood N, et al. Smoking and cessation treatment among persons with and without HIV in a U.S. integrated health system. Drug Alcohol Depend. 2020;213:108128.
LaRowe LR, Rother Y, Powers JM, Zvolensky MJ, Vanable PA, Ditre JW. Pain self-efficacy, race, and motivation to quit smoking among persons living with HIV (PLWH). Addict Behav. 2020;105:106318.
Lasser KE, Lunze K, Cheng DM, et al. Depression and smoking characteristics among HIV-positive smokers in Russia: a cross-sectional study. PLoS ONE. 2018;13(2):e0189207.
Luo X, Duan S, Duan Q, et al. Tobacco use among HIV-infected individuals in a rural community in Yunnan Province, China. Drug Alcohol Depend. 2014;134:144–50.
McQueen A, Shacham E, Sumner W, Overton ET. Beliefs, experience, and interest in pharmacotherapy among smokers with HIV. Am J Health Behav. 2014;38(2):284–96.
Mdodo R, Frazier EL, Dube SR, et al. Cigarette smoking prevalence among adults with HIV compared with the general adult population in the United States: cross-sectional surveys. Ann Intern Med. 2015;162(5):335–44.
Miles DRB, Bilal U, Hutton HE, et al. Tobacco smoking, substance use, and mental health symptoms in people with HIV in an urban HIV clinic. J Health Care Poor Underserved. 2019;30(3):1083–102.
Moadel AB, Bernstein SL, Mermelstein RJ, Arnsten JH, Dolce EH, Shuter J. A randomized controlled trial of a tailored group smoking cessation intervention for HIV-infected smokers. J Acquir Immune Defic Syndr. 2012;61(2):208–15.
Musumari PM, Tangmunkongvorakul A, Srithanavibooncha K, et al. Socio-behavioral risk factors among older adults living with HIV in Thailand. PLoS ONE. 2017;12(11):e0188088.
Mutemwa M, Peer N, De Villiers A, Faber M, Kengne AP. Tobacco smoking and associated factors in human immunodeficiency virus-infected adults attending human immunodeficiency virus clinics in the Western Cape province, South Africa. South Afr J HIV Med. 2020. https://doi.org/10.4102/sajhivmed.v21i1.1072.
Mwiru RS, Nagu TJ, Kaduri P, Mugusi F, Fawzi W. Prevalence and patterns of cigarette smoking among patients co-infected with human immunodeficiency virus and tuberculosis in Tanzania. Drug Alcohol Depend. 2017;170:128–32.
Nguyen NP, Tran BX, Hwang LY, et al. Prevalence of cigarette smoking and associated factors in a large sample of HIV-positive patients receiving antiretroviral therapy in Vietnam. PLoS ONE. 2015;10(2): e0118185.
Nguyen NT, Tran BX, Hwang LY, et al. Motivation to quit smoking among HIV-positive smokers in Vietnam. BMC Public Health. 2015;15:326.
Ompad DC, Kingdon M, Kupprat S, et al. Smoking and HIV-related health issues among older HIV-positive gay, bisexual, and other men who have sex with men. Behav Med. 2014;40(3):99–107.
Pacek LR, Harrell PT, Martins SS. Cigarette smoking and drug use among a nationally representative sample of HIV-positive individuals. Am J Addict. 2014;23(6):582–90.
Pacek LR, Latkin C, Crum RM, Stuart EA, Knowlton AR. Current cigarette smoking among HIV-positive current and former drug users: associations with individual and social characteristics. AIDS Behav. 2014;18(7):1368–77.
Pacek LR, Latkin C, Crum RM, Stuart EA, Knowlton AR. Interest in quitting and lifetime quit attempts among smokers living with HIV infection. Drug Alcohol Depend. 2014;138:220–4.
Pacek LR, McClernon FJ, Rass O, Sweizter MM, Johnson MW. Perceived risk of developing smoking-related disease among persons living with HIV. AIDS Care. 2018;30(10):1329–34.
Pacek LR, Rass O, Johnson MW. Positive smoking cessation-related interactions with HIV care providers increase the likelihood of interest in cessation among HIV-positive cigarette smokers. AIDS Care. 2017;29(10):1309–14.
Quinn MH, Bauer A-M, Flitter A, et al. Correlates of varenicline adherence among smokers with HIV and its association with smoking cessation. Addict Behav. 2020;102:106151.
Regan S, Meigs JB, Grinspoon SK, Triant VA. Determinants of smoking and quitting in HIV-infected individuals. PLoS ONE. 2016;11(4): e0153103.
Reisen CA, Bianchi FT, Cohen-Blair H, et al. Present and past influences on current smoking among HIV-positive male veterans. Nicotine Tob Res. 2011;13(8):638–45.
Shahrir S, Crothers K, McGinnis KA, et al. Receipt and predictors of smoking cessation pharmacotherapy among veterans with and without HIV. Prog Cardiovasc Dis. 2020;63(2):118–24.
Shahrir S, Tindle HA, McGinnis KA, et al. Contemplation of smoking cessation and quit attempts in human immunodeficiency virus-infected and uninfected veterans. Subst Abuse. 2016;37(2):315–22.
Shapiro AE, Tshabangu N, Golub JE, Martinson NA. Intention to quit smoking among human immunodeficiency virus infected adults in Johannesburg, South Africa. Int J Tuberc Lung Dis. 2011;15(1):140–2.
Shelley D, Tseng T-Y, Gonzalez M, et al. Correlates of adherence to varenicline among HIV+ smokers. Nicotine Tob Res. 2015;17(8):968–74.
Shirley DK, Kesari RK, Glesby MJ. Factors associated with smoking in HIV-infected patients and potential barriers to cessation. AIDS Patient Care STDS. 2013;27(11):604–12.
Shuter J, Kim RS, An LC, Abroms LC. Feasibility of a smartphone-based tobacco treatment for HIV-infected smokers. Nicotine Tob Res. 2018;22(3):398–407.
Shuter J, Kim RS, Durant S, Stanton CA. Brief report: long-term follow-up of smokers living with HIV after an intensive behavioral tobacco treatment intervention. J Acquir Immune Defic Syndr. 2020;84(2):208–12.
Shuter J, Moadel AB, Kim RS, Weinberger AH, Stanton CA. Self-efficacy to quit in HIV-infected smokers. Nicotine Tob Res. 2014;16(11):1527–31.
Shuter J, Morales DA, Considine-Dunn SE, An LC, Stanton CA. Feasibility and preliminary efficacy of a web-based smoking cessation intervention for HIV-infected smokers: a randomized controlled trial. J Acquir Immune Defic Syndr. 2014;67(1):59–66.
Sims OT, Jackson A, Guo Y, Truong DN, Odame EA, Mamudu HM. A cross-sectional analysis of tobacco use and concurrent alcohol and substance use among patients living with HIV/HCV co-infection: findings from a large urban tertiary center. J Clin Psychol Med Settings. 2021. https://doi.org/10.1007/s10880-020-09744-2.
Stanton CA, Pap GD, et al. Outcomes of a tailored intervention for cigarette smoking cessation among Latinos living with HIV/AIDS. Nicotine Tob Res. 2015;17(8):975–82.
Stanton CA, Kumar PN, Moadel AB, et al. A multicenter randomized controlled trial of intensive group therapy for tobacco treatment in HIV-infected cigarette smokers. J Acquir Immune Defic Syndr. 2020;83(4):405–14.
Stewart DW, Jones GN, Minor KS. Smoking, depression, and gender in low-income African Americans with HIV/AIDS. Behav Med. 2011;37(3):77–80.
Taniguchi C, Hashiba C, Saka H, Tanaka H. Characteristics, outcome and factors associated with success of quitting smoking in 77 people living with HIV/AIDS who received smoking cessation therapy in Japan. Jpn J Nurs Sci. 2020. https://doi.org/10.1111/jjns.12264.
Teixeira LSL, Ceccato M, Carvalho WDS, et al. Prevalence of smoking and associated factors in people living with HIV undergoing treatment. Rev Saude Publica. 2020;54:108.
Torres TS, Luz PM, Derrico M, et al. Factors associated with tobacco smoking and cessation among HIV-infected individuals under care in Rio de Janeiro, Brazil. PLoS ONE. 2014;9(12): e115900.
Triant VA, Grossman E, Rigotti NA, et al. Impact of smoking cessation interventions initiated during hospitalization among HIV-infected smokers. Nicotine Tob Res. 2020;22(7):1170–7.
Tseng T-Y, Krebs P, Schoenthaler A, et al. Combining text messaging and telephone counseling to increase varenicline adherence and smoking abstinence among cigarette smokers living with HIV: a randomized controlled study. AIDS Behav. 2017;21(7):1964–74.
Uthman OA, Ekström AM, Moradi TT. Influence of socioeconomic position and gender on current cigarette smoking among people living with HIV in sub-Saharan Africa: disentangling context from composition. BMC Public Health. 2016. https://doi.org/10.1186/s12889-016-3637-1.
Vidrine DJ, Frank SG, Savin MJ, et al. HIV care initiation: a teachable moment for smoking cessation? Nicotine Tob Res. 2018;20(9):1109–16.
Vidrine DJ, Kypriotakis G, Li L, et al. Mediators of a smoking cessation intervention for persons living with HIV/AIDS. Drug Alcohol Depend. 2015;147:76–80.
Vijayaraghavan M, Penko J, Vittinghoff E, Bangsberg DR, Miaskowski C, Kushel MB. Smoking behaviors in a community-based cohort of HIV-infected indigent adults. AIDS Behav. 2014;18(3):535–43.
Zhang C, Li X, Liu Y, Zhou Y, Shen Z, Chen Y. Impacts of HIV stigma on psychosocial well-being and substance use behaviors among people living with HIV/AIDS in China: across the life span. AIDS Educ Prev. 2018;30(2):108–19.
Zyambo CM, Burkholder GA, Cropsey KL, et al. Predictors of smoking cessation among people living with HIV receiving routine clinical care. AIDS Care. 2019;31(11):1353–61.
Asfar T, Perez A, Shipman P, et al. National estimates of prevalence, time-trend, and correlates of smoking in US people living with HIV (NHANES 1999–2016). Nicotine Tob Res. 2021;23(8):1308–17.
Barré T, Mercié P, Marcellin F, et al. HCV cure and cannabis abstinence facilitate tobacco smoking quit attempts in HIV-HCV co-infected patients (ANRS CO13 HEPAVIH cohort study). AIDS Behav. 2021;25(12):4141–53.
Mdege ND, Shah S, Ayo-Yusuf OA, Hakim J, Siddiqi K. Tobacco use among people living with HIV: analysis of data from Demographic and Health Surveys from 28 low-income and middle-income countries. Lancet Glob Health. 2017;5(6):e578–92.
Waldron I. Patterns and causes of gender differences in smoking. Soc Sci Med. 1991;32(9):989–1005.
Thirlway F, Nyamurungi KN, Matovu JKB, Miti AK, Mdege ND. Tobacco use and cessation in the context of ART adherence: insights from a qualitative study in HIV clinics in Uganda. Soc Sci Med. 2021;273:113759.
Fluharty M, Taylor AE, Grabski M, Munafo MR. The association of cigarette smoking with depression and anxiety: a systematic review. Nicotine Tob Res. 2017;19(1):3–13.
Chockalingam L, Ha TV, Bui Q, Hershow RB, Hoffman I, Go VF. Barriers and facilitators to smoking cessation among HIV-infected people who inject drugs (PWID) in Hanoi, Vietnam: a qualitative study. Cancer Causes Control. 2021;32(4):391–9.
Krishnan N, Gittelsohn J, Ross A, et al. Qualitative exploration of a smoking cessation trial for people living with HIV in South Africa. Nicotine Tob Res. 2018;20(9):1117–23.
Eklund BM, Nilsson S, Hedman L, Lindberg I. Why do smokers diagnosed with COPD not quit smoking?—a qualitative study. Tob Induc Dis. 2012;10(1):17.
Drobes D. Concurrent alcohol and tobacco dependence mechanisms and treatment. Alcohol Res Health. 2008;26:136.
Shiffman S, Balabanis M. Do drinking and smoking go together? Alcohol Health Res World. 1996;20(2):107–10.
Weinberger AH, Platt J, Esan H, Galea S, Erlich D, Goodwin RD. Cigarette smoking is associated with increased risk of substance use disorder relapse: a nationally representative, prospective longitudinal investigation. J Clin Psychiatry. 2017;78(2):e152–60.
NIDA. Cigarette smoking increases the likelihood of drug use relapse. 2018.
Matthews AK, Vargas M, Kuhns L, Shappiva N, King AC. A qualitative examination of barriers and motivators to smoking cessation among HIV positive African American MSM smokers. J Health Dispar Res Pract. 2014;7(2):4.
Crothers K, Goulet JL, Rodriguez-Barradas MC, et al. Decreased awareness of current smoking among health care providers of HIV-positive compared to HIV-negative veterans. J Gen Intern Med. 2007;22(6):749–54.
Nguyen N, Nguyen T, Chapman J, et al. Tobacco cessation in Vietnam: exploring the role of village health workers. Glob Public Health. 2018;13(9):1265–75.
Kobak KA, Greist JH, Jefferson JW, Katzelnick DJ. Computer-administered clinical rating scales. A review. Psychopharmacology (Berlin). 1996;127(4):291–301.
Benowitz NL, Bernert JT, Foulds J, et al. Biochemical verification of tobacco use and abstinence: 2019 update. Nicotine Tob Res. 2020;22(7):1086–97.
Acknowledgements
The authors wish to thank the Sahlgrenska Academy for the financial support of this project (Dnr: GU 2019/2122) and MPH. Kanya Anindya for her valuable comments and advice on this manuscript.
Funding
Open access funding provided by University of Gothenburg. The work has been supported by the Sahlgrenska Academy recruitment grant received by Prof Ng (Dnr: GU 2019/2122) during 2019–2024.
Author information
Authors and Affiliations
Contributions
THLH conceptualised the overall idea and conducted this review. VMN was a second reviewer who screened and assessed article quality and extracted data from eligible articles. LA, GGA, DS and NN, with THLH conceived the study scope, designed the study, and identified search strategies. THLH drafted the manuscript, and LA, GGA, DS and NN provided input for critical revision of the manuscript. All authors have edited and approved the final version for publication.
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Ethical Approval
Not applicable.
Consent to Participate
Not applicable.
Consent for Publication
Not applicable.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
About this article
Cite this article
Hoang, T.H.L., Nguyen, V.M., Adermark, L. et al. Factors Influencing Tobacco Smoking and Cessation Among People Living with HIV: A Systematic Review and Meta-analysis. AIDS Behav 28, 1858–1881 (2024). https://doi.org/10.1007/s10461-024-04279-1
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10461-024-04279-1