Impact of Smoking on Muscle Biomarkers and Function: A Systematic Review and Meta-Analysis

Abstract

Research Project Description: Impact of Smoking on Muscle Biomarkers and Function Purpose and Rationale This systematic review and meta-analysis was undertaken to address a critical gap in the understanding of how cigarette smoking affects skeletal muscle health. While the detrimental effects of smoking on the cardiovascular and respiratory systems are well established, the impact on skeletal muscle—the body's largest organ system, comprising approximately 40% of body mass—has remained incompletely characterized. Skeletal muscle is essential not only for locomotion and mechanical function but also for metabolic regulation, glucose disposal, lipid oxidation, and protein storage, making it a key determinant of metabolic health and functional independence across the lifespan. The primary purpose of this research was to quantitatively synthesize the available evidence on the association between cigarette smoking and both biochemical markers of muscle integrity (serum creatine kinase [CK], CK-MB, and lactate dehydrogenase [LDH]) and functional parameters of muscle performance (fatigue index and grip strength). Individual studies examining these associations have produced inconsistent findings—some reporting elevated muscle biomarkers in smokers, others finding no significant differences—due to variations in study design, population characteristics, smoking intensity and duration, and small sample sizes. No comprehensive quantitative synthesis had previously been conducted to establish a clear consensus on the magnitude and consistency of smoking-related effects on muscle health. To our knowledge, this is the first meta-analysis to simultaneously examine biochemical and functional indices of muscle health in relation to smoking status. The specific aims of the project were threefold: (1) to quantify the pooled effect of smoking on each muscle biomarker and functional parameter; (2) to assess consistency across studies and identify sources of heterogeneity; and (3) to evaluate methodological quality and potential biases in the included literature. Methods and Approach The research employed a systematic review and meta-analysis design conducted in accordance with PRISMA guidelines. A comprehensive search strategy was implemented across PubMed, Scopus, Web of Science, and MagIran databases, using terms related to smoking (smoking, smoker, cigarette, tobacco) combined with terms related to muscle biomarkers and function (creatine kinase, CK, CK-MB, lactate dehydrogenase, LDH, fatigue index, grip strength, muscle biomarkers, muscle function). Studies were eligible for inclusion if they: (a) included both control (non-smokers) and case (smokers) groups; (b) investigated cigarette smoking in relation to serum muscle biomarkers or muscle function parameters; (c) were published in English or Persian; (d) measured at least one of the specified parameters (serum CK, CK-MB, LDH, fatigue index, or grip strength); and (e) evaluated muscle parameters in healthy individuals or general populations. Studies were excluded if they were reviews, case reports, or conference abstracts; lacked sufficient data to calculate mean differences; included participants with conditions significantly affecting muscle metabolism without separate analysis; measured biomarkers in other biological fluids; or did not clearly define smoking status. Two authors independently performed screening in two stages (title/abstract and full text), with disagreements resolved by discussion or consultation with a third reviewer. Reference lists of included studies and review articles were manually examined to identify additional eligible papers. The Newcastle-Ottawa Scale was adapted to assess risk of bias across six domains: consecutive enrollment, inclusion of both genders, control by matching on ≥2 factors, results adjusted for ≥2 factors, blind outcome assessment, and ≥95% reported data. Statistical analysis involved calculating unstandardized mean differences with 95% confidence intervals. All outcome data were converted to uniform units before pooling, and studies reporting standard error of the mean (SEM) were converted to standard deviation (SD) using the formula SD = SEM × √n. A random-effects model was applied to account for expected heterogeneity. Variability among studies was assessed using Cochran's Q test and the I² statistic, with I² values interpreted as low (25%), moderate (50%), or high (75%) heterogeneity. Sensitivity analysis was performed by sequentially omitting individual studies, and publication bias was evaluated using Begg & Mazumdar adjusted rank correlation test, Egger's regression asymmetry test, and funnel plots. All analyses were performed using Stata version 11.2, with statistical significance set at P < 0.05. Expected Outcomes and Findings The meta-analysis included 22 studies comprising 2,808 participants (1,120 non-smokers and 1,688 cigarette smokers) from diverse countries including Nigeria, Kuwait, Spain, Netherlands, Israel, Iraq, Turkey, India, Taiwan, UK, Switzerland, Egypt, France, and Saudi Arabia, with participant ages ranging from 18 to 87 years. The random-effects model revealed several significant findings: CK-MB: Smoking was associated with a significant increase in CK-MB (effect size: 5.80, 95% CI: 2.4 to 9.2, P < 0.001), with moderate heterogeneity (I² = 72.9%). This finding suggests potential subclinical muscle damage in smokers, as CK-MB—while primarily used as a cardiac marker—is also expressed in skeletal muscle, particularly during regeneration and in response to injury. Fatigue Index: A significant increase in fatigue index was observed among smokers (effect size: 7.84, 95% CI: 3.4 to 12.3, P < 0.001), with very high heterogeneity (I² = 96.3%). This indicates that smokers experience greater muscle fatigability, consistent with smoking-induced impairment of muscle oxidative capacity, reduced capillary density, and altered muscle fiber type composition. Grip Strength: Smoking was associated with a significant decrease in grip strength (effect size: −4.07, 95% CI: −7.3 to −0.8, P = 0.015), with high heterogeneity (I² = 85.2%). Given that grip strength is a validated indicator of overall muscle strength predicting disability, morbidity, and mortality, this finding has important clinical implications. LDH: A non-significant trend toward increased LDH was observed (effect size: 35.48, 95% CI: −13.1 to 84.1, P = 0.152), with high heterogeneity (I² = 97.0%). While not statistically significant, the direction of effect is consistent with the observed increase in CK-MB, suggesting a generalized pattern of muscle damage in smokers. CK: Total CK levels remained unchanged (effect size: −1.30, 95% CI: −11.1 to 8.5, P = 0.796), with low heterogeneity (I² = 0.0%). This finding may reflect that total CK is less specific for muscle damage than CK-MB and may be influenced by other factors including physical activity, medication use, and genetic variation. Publication bias assessment using Egger's and Begg's tests showed no statistically significant asymmetry for any outcome, and visual inspection of funnel plots indicated no clear evidence of publication bias. However, these tests have limited power when the number of data points is small, so publication bias cannot be entirely excluded. Quality Assessment Findings The risk of bias assessment using the adapted Newcastle-Ottawa Scale revealed variable methodological quality across included studies. While all 22 studies (100%) demonstrated low risk of bias for control by matching on ≥2 factors and ≥95% reported data, only 4 out of 22 studies (18.2%) demonstrated low risk of bias for consecutive enrollment, 7 out of 22 (31.8%) for inclusion of both genders, and 7 out of 22 (31.8%) for blind outcome assessment. Results adjusted for ≥2 factors showed low risk of bias in 19 out of 22 studies (86.4%). These limitations, together with the observational nature of the included studies, preclude causal inference. Conclusions and Implications This meta-analysis provides quantitative evidence that smoking is associated with significant increases in serum CK-MB and fatigue index and a significant decrease in grip strength, with a non-significant trend toward increased LDH. These findings suggest that smoking may induce subclinical muscle damage and impair muscle function, even in healthy individuals. The results support smoking cessation as a strategy for preserving muscle health and highlight the need for further prospective studies with detailed smoking histories, comprehensive confounding assessment, and inclusion of additional muscle biomarkers to further elucidate the relationships between smoking, muscle biomarkers, and muscle function. The substantial heterogeneity observed across most analyses (I² = 72.9–97.0%) indicates that the effects of smoking on muscle biomarkers and function are not uniform, likely reflecting differences in smoking intensity, duration, cumulative exposure, participant ages, baseline physical activity levels, and geographic/ethnic variations in muscle metabolism and body composition. These factors should be carefully considered in future research and clinical interpretations. Limitations and Future Directions Several limitations warrant acknowledgment. The predominance of male participants limits generalizability to women. The restriction to serum biomarkers and functional parameters limits assessment of the full spectrum of smoking effects on muscle metabolism. Residual confounding by body mass index, physical activity, alcohol consumption, dietary intake, and medication use remains a concern given the observational nature of the included studies. Additionally, the small number of contributing data points for some outcomes limited statistical power and the ability to detect publication bias. Future well-designed prospective studies with detailed smoking histories, comprehensive confounding assessment, inclusion of additional muscl