Economic Burden of Self-Reported Tobacco Smoking Compared with Non-Smoking: Systematic Review and Meta-Analysis of Direct Health Care Costs

Abstract

Background

Tobacco smoking remains a global public health challenge, contributing to preventable mortality and morbidity and imposing substantial burdens on health care costs. We investigated whether direct health care costs differ substantially between self-reported tobacco smokers and non-smokers.

Methods

This systematic literature review was conducted in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Medline PubMed, Embase, PubMed Central, and Scopus were searched to identify studies of direct health care costs between smokers and non-smokers for participants aged ≥18 years. All observational, prospective, retrospective, and non-randomized comparative studies were considered. Data extraction included mean annual health care costs (± SD) for both groups. Mean differences (MD) in annual health care costs between smokers and non-smokers, expressed in 2025 US dollars, were compared and adjusted for a 12-month period and inflated to 2025 using consumer price indices.

Results

Of 873 studies identified, 11 were included in quantitative synthesis, which compared 19,759,529 smokers with 206,913,108 non-smokers for direct health care costs. Mean age ranged from 34.5–60.6 years for smokers and 34.3–65.1 years for non-smokers. Mean annual health care costs ranged from $65,640–$1297.1 for smokers and $54,564–$724.4 for non-smokers. Annual incremental direct health care costs for smokers versus non-smokers ranged from –$458 (95% CI [confidence interval]: –2011.0 to 1,095.0) to $11,076 (95% CI: 10,211.9 to 11,940.1) in 2025 US dollars. Meta-analysis revealed smoking generally incurred greater health care costs than non-smoking, with a mean annual incremental cost of $1916.5 (95% CI: –439.9 to 4,272.9). The result was not statistically significant (MD = 1,916.5; p = 0.111). Substantial heterogeneity was observed (I² = 99.9%). Sensitivity analysis excluding studies of chronic disease yielded a reduced incremental cost for the general population, with a statistically significant difference (MD = 583.9, p = 0.02), although heterogeneity remained high (I² = 98.0%).

Conclusion

This meta-analysis supports the assertion that smoking substantially increases direct health care costs compared with non-smoking, particularly for the general population.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12325-025-03318-0.

Key Summary Points

This systematic literature review helps fill the gap in studies that directly compare the economic burden between self-reported tobacco smokers and non-smokers

Differences in direct health care costs between self-reported tobacco smokers and non-smokers can inform tobacco control policies and enhance strategies aimed at reducing the economic burden of tobacco smoking

Meta-analysis revealed that self-reported tobacco smokers generally incurred greater health care costs than non-smokers

Sensitivity analysis excluding studies of patients with chronic disease yielded a reduced incremental cost for the general population (p = 0.02)

Introduction

In 2019, an estimated 1.1 billion people worldwide were active tobacco smokers, collectively consuming 7.4 trillion cigarette-equivalent units of tobacco [1]. Despite decades of global public health initiatives, smoking remains a substantial challenge, contributing to preventable mortality and morbidity [1]. The continued high prevalence of smoking reflects not only its deeply entrenched cultural and socioeconomic factors but also the limitations of current tobacco control policies, which have struggled to curb its widespread reach. This enduring public health issue is compounded by the fact that smoking is a primary driver of chronic diseases, such as cardiovascular diseases, cancer, and respiratory illnesses, leading to a long-term burden on individuals and health care systems alike [1]. Smoking’s impact extends far beyond the individual, affecting broader societal structures through health care costs, loss of productivity, and increased strain on health care resources.

A comprehensive study in 2022 by Dai et al. systematically examined the dosage-response relationship between smoking and a broad spectrum of health outcomes, revealing the profound and multifaceted impact smoking has on public health [2]. They evaluated the health effects associated with smoking for 36 selected health outcomes and found that eight had strong to very strong evidence of an association with smoking. Moreover, 21 had weak to moderate evidence of association and seven had no evidence of association. The findings from this study underscore that smoking is not only a leading cause of immediate and acute diseases but also a contributor to long-term, chronic conditions. The study’s depth also calls attention to the complexity of addressing smoking’s effects in a diverse population by suggesting that existing public health measures may not be sufficient to reduce the prevalence of or mitigate the broader societal impacts of smoking, particularly in high-risk communities.

In addition to the well-documented health consequences, smoking imposes a substantial economic burden, not only through direct health care costs but also through lost productivity associated with tobacco-attributable morbidity and mortality [3]. Many modeling and database studies have quantified the country-specific and global economic burden of smoking, underscoring its far-reaching financial impact on health care systems and economies. However, despite this growing body of research, a notable gap in studies that directly compare the economic burden between smokers and non-smokers remains. This lack of comparison limits our understanding of the full extent of smoking’s economic toll, particularly for direct health care expenditures. In this systematic literature review, we aimed to fill this gap by critically analyzing the direct health care costs incurred by smokers versus non-smokers, with the goal of estimating the incremental costs associated with smoking. By doing so, we sought to provide valuable insights to inform tobacco control policies and enhance strategies aimed at reducing the economic burden of smoking on both individuals and society.

Methods

This systematic literature review (SLR) was conducted and reported in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines [4]. The SLR aimed to investigate whether direct health care costs differ substantially and statistically significantly between smokers and non-smokers. In addition, it sought to estimate the mean annual incremental health care costs associated with smoking, comparing smokers with non-smokers.

Study Eligibility Criteria

Studies were selected for inclusion based on the pre-defined PICO (Population, Intervention, Comparison, and Outcome) framework (Table 1). The focus was on observational studies, both prospective and retrospective, as well as non-randomized comparative studies. If available, randomized controlled trials were also considered for synthesis. Individual case reports were excluded because of their low degree of evidence value in the hierarchy of scientific research [5]. Studies that included former smokers were excluded unless ex-smokers were explicitly grouped with either current smokers or non-smokers by the original study designs.

Table 1.

PICO^a criteria for inclusion of studies

Parameter	Study selection criteria
Population	Current smokers and non-smokers, both sexes, aged ≥18 years
Intervention	Smoking
Comparator	Non-smokers
Outcome measures	Primary outcome: Mean difference in direct health care costs between smokers and non-smokers Secondary outcome: mean annual incremental health care costs associated with smokers and non-smokers

^aPICO population, intervention, comparison, and outcome

Search Strategy

The following literature indexing databases were searched using English key words: Medline PubMed, Embase, PubMed Central, and Scopus for studies published between January 1, 2000, and April 15, 2025. The bibliographies of included articles were also searched to identify further relevant studies. The search term strategy is provided in the online Appendix.

Study Selection Process and Data Extraction

The citations of studies identified through a search of each database were exported and uploaded to Covidence [6], software that helps in the automatic de-duplication of records and facilitates double-anonymized title/abstract screening, full-text review, and data extraction. The titles and abstracts were screened by two of the authors, and disagreements were resolved through collaborative discussions and consensus. The full texts of the records that were marked as potentially eligible were sought for retrieval. The retrieved full-text articles were further screened for eligibility by two non-author reviewers, and disagreements were again resolved via collaborative discussions and consensus. The selection process of the studies is described through a PRISMA flow chart in Fig. 1. The following data were extracted from individual studies: first author and publication year, study place, study period, study design, study population, and data source used in the conduct of the study. Additional data extracted were the numbers of participants in smoking and non-smoking groups, mean ages (± SD) for each group, and mean annual health care costs (± SD) in either group. One author extracted the data, and a second author confirmed the correctness of the extracted data by the first author.

Fig. 1.

PRISMA flow chart summarizing the study selection and disposition process. PRISMA: Preferred Reporting Items for Systematic Reviews and Meta-Analyses

Risk of Bias (Quality) Assessment

The risk of bias (quality) of each included study was assessed using an updated Newcastle-Ottawa Scale modified for cohort studies [7, 8]. The Newcastle-Ottawa scale is a 10-point star system that assesses study quality against via three domains: selection, comparability, and the outcome along with statistical analysis. The studies were categorized as “very good quality” if they scored 9 or 10 (of 10 points), “good quality” (score 7–8 points), “satisfactory” (score 5–6), and “unsatisfactory” (score 0–4 points) [8]. The quality assessment was performed by two reviewers, and disagreements were resolved through consensus.

Data Analysis

Data analysis was conducted using R statistical software (version 4.1.0, The R Foundation, Vienna, Austria) with the “Metafor” package [9]. The primary outcome of the meta-analysis was the mean difference (MD) in annual health care costs between smokers and non-smokers, expressed in 2025 US dollars. This MD was interpreted as the incremental annual healthcare costs incurred by smokers compared with non-smokers. To convert the mean annual health care costs to 2025 US dollars, the reported currency in the included studies was first converted to US dollars using appropriate exchange rates. Subsequently, costs were adjusted for a 12-month period and inflated to 2025 using consumer price indices, ensuring consistency across all studies.

The meta-analysis was conducted using a random-effects model with restricted maximum likelihood estimation (restricted maximum likelihood, REML) approach, and forest plots were generated [10]. The existence of statistical heterogeneity between studies was evaluated using I² statistics, for which values >50% were considered to represent moderate to considerable heterogeneity. To assess heterogeneity in a multivariate analysis, a Cochran’s Q was used. A p-value ≤ 0.05 was considered statistically significant [11]. When heterogeneity was present, sources of heterogeneity were investigated by assessing forest plots and identifying outlying studies. In addition, the full texts of the included studies were re-read to further investigate the sources of heterogeneity.

This article is based on previously conducted studies and does not include any new studies with human participants or animals performed by any of the authors.

Results

Study Selection Outcomes

In total, 880 studies were identified from all source databases: Scopus (n = 26) and Embase and Medline PubMed (n = 196), PubMed Central (n = 651), and bibliography search (n = 7). Fifteen duplicates were eliminated. Therefore, 865 studies were eligible for title and abstract review, of which 828 articles were excluded for non-relevance to the analysis at hand. The full texts of the remaining 37 records were read in full, and one of the full texts was not available online. Only 11 studies were included in the quantitative synthesis (Fig. 1).

Characteristics of Included Studies

Following the systematic literature search, a total of 11 clinically relevant studies were included in this review. The included studies were conducted in the US, Finland, Germany, Japan, Canada, Jordan, Belgium, Iran, and Spain. Our review included eight retrospective studies and three prospective studies. Of the included studies, seven were population-based, and four were conducted in a hospital setting. A total of 19,759,529 participants in the smoker group and 206,913,108 in the non-smoker group were analyzed. The mean age of the participants ranged from 34.5–60.6 years in the smoker group and 34.3–65.1 years in the non-smoker group. The patient characteristics of the 11 included studies are presented in Table 2.

Table 2.

Patient characteristics of 11 included studies

						Smokers			Non-smokers
Author/year	Study place	Study design	Data source	Study population	Study year	Sample analyzed	Mean age (± SD)	Mean annual medical costs ($, ± SD)	Sample analyzed	Mean age (± SD)	Mean annual medical costs ($, ± SD)	Currency, year
Tiihonen et al. 2012 [12]	Finland	Prospective cohort	Kuopio Ischemic Heart Disease study (KIHD)	Random sample of people residing in and around Kuopio city	1984–2011	493	55.54 (2.38)	5040 (10,650)	1483	55.72 (2.50)	3420 (9,870)	Euros, 2009
Izumi et al. 2001 [13]	Japan	Prospective cohort	Ohsaki cohort study	National Health Insurance beneficiaries living in Ohsaki	1995–1997	21,098	NA	2012 (1,194.5)	22,310	NA	1710 (1,032.2)	British pounds, 2000
Isaranuwatchai et al. 2018 [14]a	Canada	Retrospective cohort	Admin-istrative databases of Cancer Care Ontario (CCO) and the Institute for Clinical Evaluative Sciences (ICES)	Newly diagnosed adult cancer patients from 14 Regional Cancer Centers (RCCs) in Ontario	2016	3606	60.6 (12.1)	5649 (7,169)	14,911	65.1 (13.6)	4704 (6,737)	Canadian dollars, 2016
Alefan et al. 2019 [15]	Jordan	Retrospective cohort	King Abdullah University Hospital database	Patients with chronic diseases visiting outpatient clinics	2015–2016	187	56 (10.7)	2001 (3,005.9)	469	61 (10.2)	2249 (7,901.2)	Jordanian dinars, 2015
Vynckier et al. 2025 [16]	Belgium	Retrospective	Belgian Health Interview Survey	Nationally representative population	2020	1131	49.4 (19.8)	2407	4171	47.5 (15.4)	2279	Euros, 2018
Cowan et al. 2011 [17]	US	Retrospective	National Longitudinal Survey of Youth	Nationally representative youth population	2000–2005	15,397	34.53 (4.75)	28,54.37 (7125.96)	5355	34.31 (4.81)	2373.87 (6521.43)	US dollars, 2002
Swedler et al. 2019 [18]	US	Retrospective	National Health Interview Survey (NHIS) and Medical Expenditure Panel Survey (MEPS)	Nationally representative US population	2011–2015	19 716 719	NA	4647 (4186.9–5107.0)	206,862,703	NA	4499 (4219.6–4778.9)	US dollars, 2015
Sari et al. 2016 [19]	Iran	Retrospective	Patient medical records	Patients admitted with lung cancer in government and private hospitals of Iran	2014–2015	180	NA	52,470,550 (43,329,550)	178	NA	26,523,890 (19,519,710)	Iranian rials, 2015
Fishman et al. 2003 [20]	US	Retrospective	HMO cohort	General population of western Washington state	1990–1994	342	42.4 (10.5)	2746.72	489	43.5 (11.4)	1686.15	US dollars, 2000
Suárez-Bonel et al. 2015 [21]	Spain	Prospective cohort	Primary data	Patients attending a health care district	2010–2011	250	56.3 (8.2)	848.6 (477.9)	250	56.4 (8.9)	474.7 (325.4)	Euros, 2010
Wacker et al. 2013 [22]	Germany	Retrospective	German KORA F4 study	General population of Southern Germany	2006–2008	468	57.5 (13.5)	1931 (837.1)	1278	49.7 (10.5)	2075 (676.8)	Euros, 2008

^aMean monthly costs; NA, not available; SD, standard deviation

The mean annual health care costs in the included studies ranged from $65,640 and $54,564 (2025 US dollars) [14] to $1297.1 and $724.4 (2025 US dollars) [21] in the smoking and non-smoking groups, respectively. The annual incremental direct health care costs for smokers compared with non-smokers ranged from –$458 (95% CI: –2011.0 to 1095.0) to $11,076 (95% CI: 10,211.9 to 11,940.1) in 2025 US dollars, in the individual studies. A comparison of mean annual health care costs between smokers and non-smokers in the included studies is presented in Table 3.

Table 3.

Mean annual health care costs in smokers vs. non-smokers, 2025 US dollars

	Smokers		Non-smokers
Author/year	Sample analyzed	Mean annual medical costs (SD), in 2025 US dollars	Sample analyzed	Mean annual medical costs (SD), in 2025 US dollars
Tiihonen et al. 2012 [12]	493	10,368 (21,909)	1,483	7,040 (20,318)
Izumi et al. 2001 [13]	21,098	6,211 (3,687)	22,310	5,284 (3,189)
Isaranuwatchai et al. 2018 [14]a	3,606	5,470 (6,936)	14,911	4,547 (6,519)
Alefan et al. 2019 [15]	187	3,726 (5,594)	469	4,184 (14,696)
Vynckier et al. 2025 [16]	1,131	3,520	4,171	3,332
Cowan et al. 2011[17]	15,397	4,885 (12,186)	5,355	4,060 (11,154)
Swedler et al. 2019 [18]	19,716,719	5,969 (1,338,485)	206,862,703	5,781 (2,651,830)
Sari et al. 2016 [19]	180	2,323 (1,920)	178	1,176 (865)
Suárez-Bonel et al. 2015 [20]	250	1,297.1 (730.3)	250	724.41 (496.6)
Wacker et al. 2013 [21]	468	3,052 (1,322)	1,278	3,279.6 (1,069.7)

^aMean monthly costs

Meta-Analysis of Outcome Measures

The differences in health care costs between smokers and non-smokers were assessed in meta-analysis using the mean difference in average annual costs between the two groups. Of the 11 included studies, 9 were meta-analyzed, because 2 did not have report standard deviations of the mean annual costs.

The meta-analysis indicated that, generally, smoking incurred greater health care costs compared with non-smokers. The mean annual incremental cost of smoking was $1916.50 (95% CI: –439.9 to 4272.9) in 2025 US dollars. However, a statistically non-significant difference was observed (MD = 1916.5; p = 0.111). The forest plot is presented in Fig. 2.

Fig. 2.

Direct health care costs between smokers and non-smokers

A substantial heterogeneity was observed (I² = 99.9%). A sensitivity analysis was performed to address heterogeneity by removing studies [14, 15, 19] conducted of patients with chronic, debilitating diseases and cancer to limit the high costs of medical costs incurred by these groups of patients. When a meta-analysis was conducted by only including the general population, the incremental costs of smoking were substantially decreased. A mean annual incremental health care cost of $583.9 (95% CI: 92.3–1075.6) in 2025 US dollars was estimated. The meta-analysis demonstrated a statistically significant difference in health care costs between smokers and non-smokers (MD = 583.9, p = 0.02). However, the heterogeneity did not improve (I² = 98.0%).

Risk of Bias Assessment

Studies were evaluated using the Newcastle-Ottawa quality assessment tool. Three studies were categorized as “very good quality,” “good quality,” and “satisfactory.”

The studies in Table 4 were categorized as “very good quality” if they scored 9 or 10 (of 10 points), “good quality” (scores of 7–8 points), “satisfactory” (score of 5–6), and “unsatisfactory” with scores of 0–4 points (Fig. 3).

Table 4.

Newcastle-Ottawa Quality assessment

Studies	Selection bias assessment				Comparability assessment	Outcome assessment			Total score
Tiihonen et al. 2012 [12]	*	*	*	*	*	*	–	*	8
Izumi et al. 2001 [13]	*	*	*	–	*	–	*	*	6
Isaranuwatchai et al. 2018 [14]	–	–	*	*	*	*	*	**	7
Alefan et al. 2019 [15]	*	*	*	*	*	–	–	*	6
Cowan et al. 2011 [17]	*	*	*	*	*	*	*	**	9
Swedler et al. 2019 [18]	*	*	*	*	**	*	*	*	9
Sari et al. 2016 [19]	*	*	*	*	*	**	*	*	9
Suárez-Bonel et al. 2015 [20]	*	*	*	*	*	*	*	*	8
Wacker et al. 2013 [21]	*	*	*	*	*	*	–	–	6

Fig. 3.

Differences in health care costs between smokers and non-smokers in a general population

Discussion

Smoking remains a major public health concern, with well-documented impacts on morbidity and mortality. Beyond its undeniable and well-established health consequences, smoking also places a significant economic burden on health care systems and economics [23]. By focusing exclusively on direct health care costs, the present meta-analysis examined direct health care costs for smokers compared with non-smokers. The findings reveal that smokers consistently incur greater mean annual health care expenses. Considering both hospitalized and non-hospitalized individuals in the general population, the average annual cost attributed to smoking was $1,916.5 (2025 US dollars). Of the general non-diseased population, this cost was lower, but still substantial, at $583.9 annually. The quality of studies on risk of bias analysis was generally considered “very good” to “good,” especially across performance bias. These results underscore the economic toll of smoking and highlight the potential health care savings that could be associated with effective tobacco control interventions.

This review synthesized evidence from studies conducted during the past 25 years that examined direct health care costs for smokers and non-smokers. By including both general population studies and those focusing on individuals with chronic diseases, the analysis allowed for a broader understanding of how smoking-related costs vary across different health contexts. Notably, the financial burden of smoking was consistently greater for populations with existing morbidity. For example, the study by Isaranuwatchai et al. [14], which focused on cancer patients, reported markedly greater mean health care expenditures compared with population-based studies—a pattern indicating that comorbid conditions amplify the economic impact of smoking. Furthermore, the annual incremental cost attributed to smoking reached $11,076 (2025 US dollars) in these clinical populations significantly exceeded the average incremental costs observed in the general population. This finding demonstrates the compounding effect of smoking in individuals with chronic disease and underscores the importance of targeted smoking cessation efforts in high-risk groups.

In contrast to the findings of Isaranuwatchai et al. [14] and Tiihonen et al. [12], both Wacker et al. [22] and Alefan et al. [15] did not report significant incremental health care costs associated with smoking. Interestingly, in these studies, smokers exhibited lower mean health care expenditures versus non-smokers. This discrepancy could be attributed to differences in health care-seeking behaviors, as smokers may be less likely to engage with health care services because of factors such as perceived health resilience or under-reporting of conditions. However, despite these lower observed health care expenditures, both studies still found that the total direct and indirect costs—considering broader economic factors—were generally greater for smokers than for non-smokers. (Again, indirect costs of smoking were beyond the scope of our present analysis.) This suggests that, while immediate health care costs might be lower, the long-term economic burden of smoking could still outweigh short-term differences. This points to the need for a more nuanced understanding of the full cost implications of smoking.

The synthesis of studies in this review revealed considerable study heterogeneity, which can be attributed to several key factors. First, the review encompassed studies from both non-diseased general populations and hospitalized patient groups, introducing variability in health care costs as a result of differences in the severity of health conditions. Second, the studies were conducted in different countries, each with distinct health care systems and varying degrees of health care expenditure, further contributing to the observed heterogeneity. While this diversity in study design and contextual factors may have complicated direct comparisons, the findings nonetheless carry important implications for tobacco control policy. They underscore the need to strengthen smoking cessation programs, highlighting the potential for significant reductions in both health care costs and broader economic burdens across different population groups.

On the other hand, the considerable heterogeneity of studies, attributable to differences in study populations (non-diseased vs. hospitalized patients), country-specific health systems, and baseline degrees of health care expenditure, also strengthened the relevance of the findings across various contexts. Notably, a sensitivity analysis excluding studies focused on patients with chronic diseases yielded somewhat lower incremental costs, but still demonstrated a significant excess economic burden for smokers. This supports the generalizability of our conclusions beyond specialized clinical populations to broader community settings.

While a few studies have reported greater health care costs for former smokers compared with both current smokers and non-smokers [20, 22], these findings were not addressed in the current review, which did not analyze the health care expenditures associated with former smokers. This omission represents a gap in our understanding of the full breadth and depth of the economic burden of smoking, as former smokers may exhibit different patterns of health care utilization and associated costs because of lingering health effects. This approach ensured consistency but also represents a limitation, given evidence that former smokers can experience distinct patterns of health care utilization and costs. We recommend that future research explore the economic burden across all three groups—smokers, non-smokers, and former smokers—to provide a complete assessment of the long-term health care costs of smoking cessation.

In addition, a key limitation of this review was its exclusive focus on direct health care expenditures, without accounting for the indirect costs—such as lost productivity or reduced health-related quality of life. These are integral to the overall economic impact of smoking. This study deliberately concentrated on direct health care costs to maintain a clear scope aligned with payer interests. Expanding future studies to include these indirect costs would offer a more complete picture of the financial burden of smoking.

Conclusion

This systematic review and meta-analysis provides robust evidence that smokers incur significantly greater direct health care costs compared with non-smokers, with the economic burden further exacerbated for individuals with chronic diseases. Despite observed heterogeneity in the studies included, the findings consistently highlight the substantial health care expenditures associated with smoking and reinforce the need for comprehensive tobacco control policies. However, limitations such as the exclusion of former smokers and the focus solely on direct health care costs suggest that future research should expand to include a broader range of economic factors, including indirect costs and the health care expenditures of former smokers. Ultimately, strengthening smoking cessation programs and promoting policies that reduce smoking prevalence could lead to substantial long-term savings and improve public health outcomes.

Supplementary Information

Below is the link to the electronic supplementary material.

Author Contributions

Nadia J. Sweis: Dr. Sweis conceptualized and designed the study, led the systematic literature review, developed the search strategy, supervised the data extraction and risk of bias assessment, conducted the meta-analysis, interpreted the findings, and wrote the first and final drafts of the manuscript. She also coordinated communication and ensured adherence to PRISMA guidelines. Zane Z. Elfessi: Dr. Elfessi contributed to the screening of articles, extraction and validation of data, statistical consultation on the meta-analysis methodology, and critical revision of the manuscript for important intellectual content. Israel Rubinstein: Dr. Rubinstein contributed to reference verification and formatting, and assisted in manuscript formatting and figure preparation for submission. Rachel Caskey: Dr. Caskey participated in the quality assessment of included studies, contributed to the interpretation of results in the context of public health policy, and reviewed and edited the final manuscript draft for clarity and clinical relevance.

Funding

This study was supported by the University of Illinois College of Medicine in Chicago, IL, USA. This material is also the result of work supported with resources and the use of facilities at the Jesse Brown VA Medical Center, Chicago, Illinois, USA. No funding or sponsorship was received for the publication of this article. The Rapid Service Fee was funded by the authors. The Rapid Service and Open Access fees were funded by the University of Illinois Chicago.

Data Availability

This article is based on previously conducted studies. All source data are contained in cited articles in the References section.

Declarations

Conflicts of Interest

The authors (Nadia J. Sweis, Zane Z. Elfessi, Israel Rubinstein, and Rachel Caskey) report no conflicts of interest relevant to this work.

Ethics Statement

This article is based on previously conducted studies and does not include any new studies with human participants or animals performed by any of the authors.