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Association between smoking behavior and serum uric acid among the adults: Findings from a national cross-sectional study

  • Yun Seo Jang,

    Roles Conceptualization, Formal analysis, Investigation, Methodology, Validation, Visualization, Writing – original draft

    Affiliations Department of Public Health, Graduate School, Yonsei University, Seoul, Republic of Korea, Institute of Health Services Research, Yonsei University, Seoul, Republic of Korea

  • Nataliya Nerobkova,

    Roles Conceptualization, Formal analysis, Investigation, Methodology, Writing – review & editing

    Affiliations Department of Public Health, Graduate School, Yonsei University, Seoul, Republic of Korea, Institute of Health Services Research, Yonsei University, Seoul, Republic of Korea

  • Il Yun,

    Roles Conceptualization, Formal analysis, Methodology, Visualization, Writing – review & editing

    Affiliations Department of Public Health, Graduate School, Yonsei University, Seoul, Republic of Korea, Institute of Health Services Research, Yonsei University, Seoul, Republic of Korea

  • Hyunkyu Kim,

    Roles Conceptualization, Formal analysis, Investigation, Methodology, Validation, Writing – review & editing

    Affiliations Institute of Health Services Research, Yonsei University, Seoul, Republic of Korea, Department of Preventive Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea

  • Eun-Cheol Park

    Roles Conceptualization, Methodology, Supervision, Validation, Writing – review & editing

    Affiliations Institute of Health Services Research, Yonsei University, Seoul, Republic of Korea, Department of Preventive Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea



Gout incidence is increasing worldwide; appropriate management of serum uric acid levels and a healthy lifestyle may help its prevention. The popularity of electronic cigarettes and the resultant emergence of dual smokers is increasing. Despite many studies on the effects of various health behaviors on serum uric acid levels, the association between smoking and serum uric acid levels remains controversial. This study aimed to investigate the association between smoking and serum uric acid levels.


In this study, total sample of 27,013 participants (11,924 men and 15,089 women) were analyzed. This study used data from the Korea National Health and Nutrition Examination Survey (2016–2020) and grouped adults into dual smokers, single smokers, ex-smokers, and non-smokers. Multiple logistic regression analyses were performed to investigate the association between smoking behavior and serum uric acid levels.


Compared to male non-smokers, male dual smokers had significantly higher serum uric acid level (odds ratio [OR], 1.43; 95% confidence interval [CI], 1.08–1.88). In female, serum uric acid level was higher among single smokers than non-smokers (OR, 1.68; 95% CI, 1.25–2.25). Higher serum uric acid levels were more likely to be present in male dual smokers with a > 20 pack-year smoking habit (OR, 1.84; 95% CI, 1.06–3.18).


Dual smoking may contribute to high serum uric acid levels in adults. Thus, serum uric acid levels should be properly managed through smoking cessation.


Gout is a type of auto-inflammatory arthritis with increasing prevalence and incidence worldwide [1, 2]. Increased incidence and death rate have been reported especially in the United States, Italy, South Korea, Australia, New Zealand, and Taiwan [3, 4]. Serum uric acid (SUA) plays a pivotal role in gout and is an unusual complication of anorexia nervosa [5]. Moreover, SUA is a potential risk factor for the deterioration of kidney function; high SUA levels increase the risk of acute and chronic kidney disease (CKD) [6]. High SUA levels progress to hyperuricemia, which may play a role in the pathogenesis of CKD and damage the vascular lining over time [7]. Additionally, SUA is associated with other health risk factors in daily life, such as hypertension, insulin resistance, and the cardiovascular diseases [810]. Given that elevated SUA causes many diseases in the contemporary world, its management is significant for personal health [11].

Smoking is a leading risk factor for premature death worldwide and is one of the primary causes of chronic diseases such as cancer, cardiovascular diseases, and respiratory diseases [12]. Owing to the adverse health outcomes of smoking, people tend to quit conventional smoking and are increasingly turning to electronic cigarettes (e-cigarettes) as an alternative [13, 14]. E-cigarettes heat a liquid that often contains nicotine to produce aerosol, which is subsequently inhaled. Evidence reveals that dual smoking behavior, which involves smoking both e-cigarettes and conventional cigarettes, is as harmful to health as smoking conventional cigarettes alone [1519]. Although e-cigarette nicotine delivery systems are considered less dangerous than conventional cigarettes, they are associated with a range of complications, including thermal damage, lung damage, cardiovascular outcomes, and psychosocial effects [18]. As of 2020, Korea’s smoking rate is 20.6% (male: 34.0%, female: 6.6%), of which 8.4% for male and 1.9% for female use e-cigarettes. With an increase in the number of dual smokers and decrease in successful smoking cessation observed, dual smoking appears to have the potential to induce tobacco dependence [2023].

Previous SUA level-related studies have found associations with gout, kidney function, alcohol, tea, coffee, milk, and yogurt [7, 8]. Notably, in the United States, patients with gout are advised to limit the consumption of distilled beverages such as beer and wine and are recommended to consume low-fat or non-fat dairy products [10]. Despite studies conducted by various research groups on the association between smoking and SUA, many conflicting opinions still exist [24]. Additionally, unlike the evidence related to smoking, there is insufficient evidence to clarify the association between e-cigarette or dual smoking and SUA.

Therefore, this study aimed to investigate the association between various smoking behaviors, including dual smoking (both e-cigarettes and conventional cigarettes), single smoking (only conventional cigarettes), and past smoking with respect to SUA, in a representative Korean adult population.

Materials and methods

Data and study population

The data used in this study were obtained from the Korea National Health and Nutrition Examination Survey (KNHANES) conducted from 2016 to 2020. The KNHANES is a cross-sectional, nationwide survey conducted annually by the Korea Disease Control and Prevention Agency (KDCA) of the Ministry of Health and Welfare, South Korea, to evaluate the health status, health behavior, and nutritional status of the South Korean population. The respondents answered the questionnaires, and all the obtained data were anonymized. As the KNHANES complies with the Declaration of Helsinki and provides publicly accessible data, ethical approval was not required.

The total number of respondents from the 2016–2020 survey was 39,738. Information from individuals aged 1–18 years was excluded as they had not been asked regarding smoking behavior (N = 7,610). Additionally, data from participants with missing variables were also excluded (N = 5,105). Finally, 27,013 participants (11,924 men and 15,089 women) were analyzed in this study.


The dependent variable, SUA was measured by collecting venous blood from participants who had been fasting for > 8 h. SUA was measured by colorimetry with the enzyme uricase using a Hitachi Automatic Biochemical Analyzer 7600–210 (Hitachi, Tokyo, Japan) from 2016 to 2018 in KNHANES. Uricase was also measured using Labospect 008AS (Hitachi, Tokyo, Japan) from 2019 to 2020 in KNHANES. Furthermore, the common cutoff value for SUA level was 7.0 mg/dL (420 μmol/L) for men and 6.0 mg/dL (357 μmol/L) for women [25].

Based on smoking behavior as the independent variable, the study population was divided into four groups: (1) non-smokers, (2) ex-smokers who had been using conventional cigarettes or e-cigarettes in the past, (3) single smokers who used only conventional cigarettes, and (4) dual smokers who used conventional cigarettes and e-cigarettes. This classification was identical to that of the previous studies that investigated smoking behavior using the same investigative tools [16, 17, 26].

The covariates included demographic factors: age (19–29 / 30–39 / 40–49 / 50–59 / 60–69 / ≥ 70), marital status (married / single or widow / divorced or separated), and educational level (middle school or below / high school / college or over); socioeconomic factors: household income (low / mid-low / mid-high / high), region of residence (metropolitan / urban / rural), and occupation (white / pink / blue / inoccupation); health-related factors: body mass index [BMI] (underweight / normal / overweight), hypertension status (normal / pre-hypertension / hypertension), diabetes status (yes / no), and dyslipidemia status (yes / no); and health-related behavioral patterns of alcohol consumption (yes / no).

Statistical analysis

All estimates were calculated using sample weight procedures, clusters, and strata assigned to the study participants. Descriptive analysis was performed to assess the general characteristics of the study population. Subsequently, a multiple logistic regression analysis was performed to evaluate the effect of smoking behavior on SUA levels and perform a subgroup analysis stratified by independent variables. In addition, we calculated the pack-years by the amount and duration of smoking in the past or current smokers and conducted a subgroup analysis by tying it with the smoking behavior. The main results are expressed as odds ratios (ORs) and 95% confidence intervals (CIs). SAS version 9.4 (SAS Institute Inc.; Cary, NC, USA) was used for all analyses, and a p-value <0.05 was considered statistically significant.


Table 1 highlights the general characteristics of the study population. Of the 27,013 participants, 11,924 were men (44.1%) and 15,089 were women (55.9%). Among the men, 357 (3.0%), 3,629 (30.4%), 5,057 (42.4%), and 2,881 (24.2%) were dual smokers, single smokers, ex-smokers, and non-smokers, respectively. Among the women, 72 (0.5%), 697 (4.6%), 938 (6.2%), and 13,382 (88.7%) were dual smokers, single smokers, ex-smokers, and non-smokers, respectively. The relationship between smoking behavior and SUA levels was statistically significant in men and women. Moreover, differences in demographic, socioeconomic, and health status characteristics were primarily significant (p < .0001).

Table 1. General characteristics of the study population.

Table 2 presents the association between smoking behavior and SUA levels in men and women after adjusting for all covariates. In men, dual smokers (OR, 1.43; 95% CI, 1.08–1.88) were statistically associated with SUA, whereas in women, a statistical association was observed in single smokers (OR, 1.68; 95% CI, 1.25–2.25). Compared with non-smokers, both male and female ex-smokers, single smokers, and dual smokers showed higher ORs for abnormal SUA levels, although some were not statistically significant.

Table 2. Results of factors associated between smoking behavior and serum uric acid.

Table 3 demonstrates a subgroup analysis performed to evaluate the combined effect of smoking behavior, alcohol consumption, and hypertension on SUA levels. For men, alcohol consumption (OR, 1.43; 95% CI, 1.07–1.91) and hypertension (OR, 1.83; 95% CI, 1.01–3.32) among dual smokers had the strongest associations with SUA compared to those of non-smokers. For women, alcohol consumption (single smokers: OR, 1.68; 95% CI, 1.21–2.32), hypertension (dual smokers, OR: 16.99; 95% CI: 2.70–107.16), and dyslipidemia status (single smokers: OR, 1.83; 95% CI, 1.31–2.58) showed the strongest association with serum uric acid compared to those of non-smokers.

Table 3. Results of subgroup analysis stratified by independent variables.

Fig 1 reveals the results of the subgroup analysis depicting changes in ORs according to the pack-years (number of cigarettes smoked and smoking period) smoked. The ORs tended to increase linearly as the pack-years increased. Specifically, male ex-smokers (OR, 1.44; 95% CI, 1.19–1.74) and dual smokers (OR, 1.84; 95% CI, 1.06–3.18) who had > 20 pack-years were more likely to have SUA levels ≥ 7 mg/dL than non-smokers. Female single smokers who had less than 10 pack-years (OR, 1.76; 95% CI, 1.25–2.48) and 10 to 20 pack-years (OR, 1.98; 95% CI, 1.07–3.66) were more likely to have SUA levels ≥ 6 mg/dL than non-smokers.

Fig 1. Results of subgroup analysis stratified by the smoking behavior and pack-year.


The World Health Organization has consistently emphasized the importance of quitting smoking and the dangers of smoking, which kills approximately eight million people every year [12]. However, the mechanism explaining how smoking increases SUA levels remains unclear. A study has revealed that current smokers with a BMI > 24.9 have an increased risk of gout over time [27]. This finding can be applied to single or dual smokers, as indirectly implied by the current results. Hyperuricemia is a major risk factor for metabolic syndrome that leads to the development of cardiovascular and cerebrovascular diseases [9]. Most patients with gout have obesity, hypertension, and hyperlipidemia [9, 25, 27]. Therefore, patients with gout may require proper management through smoking cessation to reduce this risk.

Based on this, the present study aimed to validate the association between SUA and various smoking behaviors, including dual smoking, single smoking, and ex-smoking, in a representative Korean adult population. We also conducted a subgroup analysis according to factors related to smoking and SUA, including BMI, alcohol consumption, hypertension, diabetes, and dyslipidemia status. Furthermore, we stratified smoking behavior according to pack-years smoked.

In this study, elevated SUA levels were observed in dual smokers compared to non-smokers. This relationship was especially strong among men who were dual smokers. A strong connection between elevated SUA levels and women who were single smokers was observed. Among men who had more than 20 pack-years, dual smokers and ex-smokers were more strongly associated with SUA. Among women who had less than 10 pack-years and 10 to 20 pack-years, single smoking was significantly associated with SUA. In general, the SUA level linearly increased with the pack-years. Overall, this study found a significant association among men but not among women, which could be considered a result of a recall bias in self-reported data owing to poor perception of women smoking in Korea [28]. The underreporting of women’s smoking is connected to social stigma, which conceals and masks smoking among women more so than men.

A previous study suggested that SUA was only associated with women, not men [24]. Furthermore, based on a previous study, our study considered dual smokers and found that SUA was related to both women and men. With the increase in the use of e-cigarettes, the risk perception of dual smokers has become important [1, 2]. Additionally, as the prevalence and incidence of gout increase [3, 4], research on the association between smoking and SUA is being actively conducted. The increasing effect of smoking on SUA has been observed globally [24, 2931]. Moreover, one study found that male e-cigarette users have higher levels of SUA than non-smokers and conventional cigarette users [30]. In contrast, some studies suggested that smoking may lower SUA levels [3234], which was explained by the antioxidant effect on ROS and free radicals produced by cigarettes [32]. No effect of reduction was reported to be found in a large study population considering the amount and duration of smoking [35, 36]. Although the association between smoking and SUA is controversial, generally, low SUA levels in smokers are associated with the depletion of antioxidants [24]. Therefore, these results are consistent with our findings on the adverse effects of e-cigarettes and dual smoking in our study population.

This study has certain limitations. First, it was a cross-sectional study. We found an association between smoking behavior and SUA; however, the causal relationship requires careful interpretation. Therefore, further research is needed to clarify the relationship of smoking behavior and SUA levels. Second, KNHANES data were collected as a self-report survey. Data on smoking behavior and health-related and socioeconomic variables might not have been accurately measured and might not be completely reliable. In particular, it may have resulted in recall bias with underestimated smoking behavior. Therefore, smoking behavior was evaluated on its own, and the exact smoking cessation status of ex-smokers was unclear. Future studies need to clear the smoking cessation period through measurement data to compensate for these limitations. Third, we aimed to consider the pack-years of all participants; however, owing to data limitations, we could not sufficiently reflect information on the pack-years of e-cigarettes. This may lead to uncertainty regarding the relationship between dual smokers and SUA. Therefore, further studies reflecting these data are needed. Fourth, e-cigarettes are more recent than conventional cigarettes, and a limited number of respondents smoked only e-cigarettes. Future research should consider each smoking behavior separately because single smokers who smoke only e-cigarettes were not considered. Finally, although we adjusted for many covariates that might have affected the results, residual confounding factors might not have been measured or considered in our analysis.

In contrast with the limitations, our study had several strengths. First, KNHANES conducted by the KDCA is nationally representative survey based on random cluster sampling, which is reliable and representative. Therefore, our results can be generalized to ordinary Korean adults. Second, blood samples were collected using standardized laboratory procedures, and SUA levels were measured to produce reliable and clear data. Third, few studies have evaluated the association between smoking behaviors, including e-cigarette use, dual smoking, and SUA. Therefore, this study is noteworthy in subgroup analysis by calculating pack-years and smoking behavior, such as dual smoking. In addition, the pack-years of ex-smokers and single and dual smokers were calculated and analyzed.


Smoking behavior, particularly dual smoking, in the male population was associated with SUA. In addition, the higher the pack-years, the greater was the risk of high SUA levels. In particular, the risk of increased SUA levels, particularly in those who are dual smokers (> 20 pack-years), has been reported. Given these results, smoking is related to SUA, and dual and single smoking is harmful to health. These findings should provide the direction of research on the adverse effects of e-cigarettes and dual smoking in future studies and educate people regarding the risk. The current study findings may be significant given that many people believe using e-cigarettes to be safe smoking behaviors, and this could lead to dual smoking.


We would like to thank the Korea Centers for Disease Control and Prevention (KDCA) for providing the materials based on the nationwide survey. We would also like to thank our colleagues at the Yonsei University of health research institute for their advice on writing the literature.


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