Association between E-Cigarette Smoking and Insulin Resistance Using the Triglyceride-Glucose Index in Korean Adults: Korea National Health and Nutrition Examination Survey
Article information
Abstract
Background
Insulin resistance contributes to the development of cardiovascular disease and type 2 diabetes mellitus. Smoking leads to an increase in triglyceride levels, which, in turn, increases insulin resistance. Although the number of e-cigarette users has increased in recent years, few studies have investigated the association between e-cigarette use and insulin resistance. Therefore, this study aimed to determine the association between e-cigarette use and insulin resistance using the triglyceride-glucose (TyG) index in Korean adults.
Methods
This study included 4,404 healthy adults aged ≥20 years who participated in the Korea National Health and Nutrition Examination Survey between 2019 and 2020. Participants were categorized as never-smokers or ecigarette users, and the TyG index was categorized into low- and high-TyG index groups according to the median value (9.22). A logistic regression analysis was performed to determine the association between e-cigarette smoking and insulin resistance.
Results
E-cigarette users had a higher TyG index than never smokers (e-cigarette: mean=3.95; never: mean=9.18; P<0.001). The e-cigarette users had a higher risk of being in the high TyG index group than never-smokers (odds ratio [OR], 1.38; 95% confidence interval [CI], 1.03–1.84). In the subgroup analysis stratified by sex, age, and body mass index, a higher OR for a high TyG index was observed in men (OR, 1.46; 95% CI, 1.03–2.08) and individuals aged 60 years or older (OR, 3.74; 95% CI, 1.14–12.30).
Conclusion
Our findings suggest that e-cigarette use is significantly associated with insulin resistance.
INTRODUCTION
Smoking is a major cause of cardiovascular, cerebrovascular and respiratory diseases, and various types of cancer [1]. Cigarette smoking has also been linked to increased plasma triglyceride levels and decreased plasma high-density lipoprotein cholesterol levels. Increased triglyceride levels not only reduce insulin sensitivity by interfering with glucose absorption by insulin stimulation but also increase insulin resistance by causing hyperinsulinemia [2]. Insulin resistance results in the development of cardiovascular disease [3] and type 2 diabetes [4].
According to the Korea National Health and Nutrition Examination Survey (KNHANES), the traditional cigarette smoking rate among Korean adults steadily decreased from 35.1% in 1998 to 20.6% in 2020, while e-cigarette use increased (2.0% to 5.2% in men and 0.3% to 1.1% in women from 2013 to 2020) [5]. A previous study found that many smokers use e-cigarettes to decrease the frequency of smoking or because they perceive them to be less harmful than traditional cigarettes; additionally, 71.1% of e-cigarette users do so for smoking cessation and harm reduction [6]. However, the World Health Organization reported that e-cigarettes not only contain toxic substances that can cause various diseases but also have insufficient evidence for their effect on smoking cessation [7].
Studies on the association between e-cigarette use and insulin resistance are limited, and their results are inconsistent [8-10]. Previous studies have shown that e-cigarette use is not associated with insulin resistance [8]. In contrast, a cross-sectional study in humans found that current e-cigarette users were more likely to be diagnosed with prediabetes [9]. A recent human study showed that dual smokers (both cigarette and e-cigarette) had a higher triglyceride-glucose (TyG) index, a measure of insulin resistance, than nonsmokers [10].
The TyG index is a recently developed and useful indirect method for assessing insulin resistance based on triglyceride and fasting blood glucose levels [11,12]. Mounting evidence has revealed the detrimental effects of e-cigarette use and its correlation with insulin resistance, which steadily increases over time [13]. Therefore, this study aimed to determine the association between e-cigarette use and insulin resistance using the TyG index, an indirect indicator of insulin resistance, based on the 8th KNHANES (2019–2020).
METHODS
1. Data and Study Population
This study used data from the 8th KNHANES (2019–2020) and was approved by the Research Ethics Advisory Committee of the Agency for Disease Control. This study was approved by the Institutional Review Board (IRB) of Pusan National University Yangsan Hospital (IRB approval no., 05-2023-119). Informed consent was obtained from all individual participants.
Of the 15,469 people who participated in the questionnaire survey from 2019 to 2020, 12,614 people aged ≥20 years were selected. Patients with hypertension, diabetes, dyslipidemia, renal failure, liver cirrhosis, stroke, myocardial infarction, angina pectoris, or cancer were excluded (N=5,914). Additionally, those with missing data on the variables were excluded (N=149). Finally, a total of 4,404 individuals were included in this study.
2. Variables
The independent variable was categorized into two groups: “never-smokers” and “e-cigarette users.” “Never-smokers” comprised participants who had never smoked either traditional cigarettes or e-cigarettes in their lifetime (N=4,108). “E-cigarette users” included participants who had smoked traditional cigarettes in the past but were currently not using them and were currently using e-cigarettes, either pod-based, liquid-based, or both (N=296). The dependent variable was the TyG index, which was calculated as ln [fasting triglyceride (mg/dL)×fasting plasma glucose (mg/dL)/2] [12]. The TyG index was categorized into low TyG index (<9.22) and high TyG index (≥9.22) based on the median value (9.22) [14].
Sex, age, systolic blood pressure (SBP), diastolic blood pressure (DBP), body mass index (BMI), total cholesterol level, alcohol consumption, and physical activity were considered as potential confounding variables that may influence insulin resistance and were adjusted for in the analysis. Sex was classified as either “male” or “female,” and alcohol consumption was dichotomized as “yes” or “no” based on lifetime drinking history.
Physical activity was categorized into two groups: “sufficient” and “insufficient” physical activity. “sufficient” was defined as engaging in moderate-to-vigorous sports, exercise, and leisure activities for at least 30 minutes a day, 3 or more times a week. “Insufficient” was defined as not meeting these criteria.
Final SBP and DBP were defined as the secondary and tertiary averages of the measured blood pressures. BMI was defined as body weight (kg) divided by height squared (m). Fasting glucose, total cholesterol, triglyceride, and high-density lipoprotein levels were determined using a LaboSpect 008AS instrument (Hitachi, Tokyo, Japan).
3. Statistical Analysis
A weighted composite sample analysis was performed to obtain a nationally representative sample. The study participants were categorized as e-cigarette users or never-smokers. The general characteristics of the two groups were compared using Student t-test or chi-square test. Multiple logistic regression was conducted to calculate odds ratios (OR) and 95% confidence intervals (CIs) to assess the risk of having a high TyG index among e-cigarette users. The regression models were categorized into two groups. Model 1 was adjusted for sex and age, and model 2 was adjusted for sex, age, SBP, DBP, BMI, total cholesterol, alcohol consumption, and physical activity. After adjusting for covariates, a subgroup analysis of the OR for a high TyG index stratified by independent variables (sex, age, and BMI) was performed using multiple regression analysis. General linear analysis was conducted to examine the association between e-cigarette variables (type and quantity) and the TyG index. Statistical analysis was performed using IBM SPSS Statistics ver. 27.0 (IBM Corp., Armonk, NY, USA), with a statistical significance level of less than 0.05.
RESULTS
Table 1 shows the general characteristics of the study population. Of the 4,404 participants, 4,108 (91.6%) were never smokers, and 296 (8.4%) were e-cigarette users. E-cigarette use was more prevalent among men (79.3%) than among women (20.7%). The average age in e-cigarette users was found to be 38.53±0.74 years, while among never-smokers it was 45.24±0.37 years. Mean SBP, DBP, total cholesterol, HDL cholesterol, and fasting blood glucose levels were not significantly different between the two groups. E-cigarette users exhibited a higher body mass index and triglyceride levels, a greater history of alcohol consumption, and a higher rate of sufficient physical activity than never-smokers. The TyG index was significantly higher in e-cigarette users (mean=9.35) than in never smokers (mean=9.18) (P<0.001).
Comparison of general characteristics of the study population
Table 2 presents the correlations between the type and quantity of e-cigarettes and the TyG index. No significant differences in the TyG index were observed between the different types of e-cigarettes, indicating that no specific type of e-cigarette was notably worse in terms of its impact on the TyG index. A significant positive correlation was observed between the quantity of e-cigarettes and the TyG index, indicating that as the quantity of e-cigarettes increased, the TyG index also increased (r=0.288, P<0.001).
Association between types and quantity of e-cigarettes and the TyG index
Multiple logistic regression analysis was conducted to evaluate the risk of individuals using e-cigarettes with a high TyG index compared with never-smokers (Table 3). After adjusting for sex, age, SBP, DBP, BMI, total cholesterol, alcohol consumption, and physical activity, e-cigarette users demonstrated higher ORs for a high TyG index, compared to never-smokers (OR, 1.38; 95% CI, 1.03–1.84).
OR (95% CI) of a high TyG index between never-smokers and e-cigarette users
Subgroup analyses were stratified according to sex, age, and BMI (Table 4). Using never-smokers as a reference, we observed that male (OR, 1.46; 95% CI, 1.03–2.08) and individuals aged 60 years and older (OR, 3.74; 95% CI, 1.14–12.30) had higher ORs for a high TyG index.
Subgroup analysis stratified by sex, age, and BMI
DISCUSSION
This study was based on data from the 8th KNHANES (2019–2020), and aimed to determine the relationship between e-cigarette use and insulin resistance in adults aged ≥20 years. E-cigarette use significantly increased the risk of TyG index even after adjusting for sex, age, SBP, DBP, BMI, total cholesterol level, alcohol consumption, and physical activity. In the subgroup analysis based on sex, age, and BMI, e-cigarette users who were older than 60 years and male had a higher risk of having a high TyG index than non-smokers. However, no significant differences were observed in the BMI.
Previous animal studies have demonstrated that e-cigarettes reduce insulin sensitivity and increase the risk of diabetes, similar to traditional cigarette smoking [15,16]. In a cross-sectional study conducted in the United States involving a total of 154,404 participants, it was found that e-cigarette users had a higher risk of being diagnosed with prediabetes compared to never smokers (OR, 1.97; 95% CI, 1.25–3.10) [9]. In a Korean human study, both dual (using both cigarettes and e-cigarettes) and single smokers exhibited higher insulin resistance compared to never smokers (dual OR, 2.19; 95% CI, 1.39–3.44; single OR, 1.78; 95% CI, 1.43–2.22) [10]. They indirectly assessed e-cigarette use in the form of dual smoking, because the number of participants who used only e-cigarettes was too small. In contrast, our study evaluated the association with insulin resistance, specifically in a population that used only e-cigarettes.
However, the precise mechanism underlying the association between e-cigarette use and insulin resistance remains unclear. Nonetheless, it has been proposed that nicotine, present in e-cigarettes, may contribute to insulin resistance [16-19]. Several studies have demonstrated that nicotine leads to reduced tissue sensitivity to insulin, thereby elevating the risk of developing type 2 diabetes mellitus [2,17]. Nicotine contributes to elevated levels of insulin-antagonistic hormones, such as catecholamines and cortisol [18]. Studies conducted in animals have revealed a direct influence of nicotine on the activation of AMP-dependent protein kinases in the adipose tissue. It also accelerates lipolysis and promotes insulin resistance [20]. In another animal study, both nicotine-free and nicotine-containing e-liquids induced hyperglycemia [16].
This study had several limitations. First, because this was a cross-sectional study, it was difficult to establish a causal relationship between e-cigarette use and insulin resistance. Second, owing to the self-report survey method used, there may be limitations in the accuracy or reliability of information regarding smoking, drinking, physical activity, and e-cigarette use. Third, due to data limitations, information regarding the frequency, duration, quantity, and type of traditional cigarette and e-cigarette use was not controlled. Fourth, the dose-response relationship between e-cigarette use and insulin resistance was not analyzed. In future studies, it’s important to consider analyzing the smoking behavior, particularly usage duration and intensity, among individuals who exclusively use e-cigarettes without a history of traditional cigarette smoking.
Despite these limitations, this study is meaningful because it confirms the association between e-cigarette use and the TyG index. Moreover, e-cigarette use alone is associated with insulin resistance, with a similar effect observed with traditional cigarette use. Thus, the results of this study may provide evidence for future studies investigating the association between e-cigarette use and insulin resistance.
In conclusion, we found a significant positive correlation between e-cigarette use and the TyG index in healthy adults, confirming its association with insulin resistance. This study is significant from a public health perspective as it can contribute to preventing e-cigarettes from being promoted and marketed as less harmful tobacco products. Large prospective studies are needed to clarify the causal relationship between e-cigarette use and TyG index.
Notes
CONFLICT OF INTEREST
Sang Yeoup Lee serves as an Editorial Board member of the Korean Journal of Family Medicine but had no role in the decision to publish this article. Except for that, no potential conflict of interest relevant to this article was reported.
FUNDING
This study was supported by a 2024 research grant from Pusan National University Yangsan Hospital.