Access to this full-text is provided by Frontiers.
Content available from Frontiers in Public Health
This content is subject to copyright.
TYPE Original Research
PUBLISHED 17 February 2023
DOI 10.3389/fpubh.2023.1015919
OPEN ACCESS
EDITED BY
Sonu Goel,
Post Graduate Institute of Medical Education
and Research (PGIMER), India
REVIEWED BY
Luca Rinaldi,
University of Campania Luigi Vanvitelli, Italy
Amit Yadav,
The Union South East Asia Oce, India
*CORRESPONDENCE
Sung-In Jang
JANGSI@yuhs.ac
SPECIALTY SECTION
This article was submitted to
Public Health Policy,
a section of the journal
Frontiers in Public Health
RECEIVED 10 August 2022
ACCEPTED 27 January 2023
PUBLISHED 17 February 2023
CITATION
Jang YS, Joo HJ, Park YS, Park E-C and Jang S-I
(2023) Association between smoking cessation
and non-alcoholic fatty liver disease using
NAFLD liver fat score.
Front. Public Health 11:1015919.
doi: 10.3389/fpubh.2023.1015919
COPYRIGHT
©2023 Jang, Joo, Park, Park and Jang. This is
an open-access article distributed under the
terms of the Creative Commons Attribution
License (CC BY). The use, distribution or
reproduction in other forums is permitted,
provided the original author(s) and the
copyright owner(s) are credited and that the
original publication in this journal is cited, in
accordance with accepted academic practice.
No use, distribution or reproduction is
permitted which does not comply with these
terms.
Association between smoking
cessation and non-alcoholic fatty
liver disease using NAFLD liver fat
score
Yun Seo Jang1,2, Hye Jin Joo1,2, Yu Shin Park1,2 , Eun-Cheol Park2,3
and Sung-In Jang2,3*
1Department of Public Health, Graduate School, Yonsei University, Seoul, Republic of Korea, 2Institute of
Health Services Research, Yonsei University, Seoul, Republic of Korea, 3Department of Preventive Medicine,
Yonsei University College of Medicine, Seoul, Republic of Korea
Background: Smoking is well known to be associated with a higher prevalence and
incidence of liver diseases such as advanced fibrosis. However, the impact of smoking
on developing nonalcoholic fatty liver disease remains controversial, and clinical data
on this is limited. Therefore, this study aimed to investigate the association between
smoking history and nonalcoholic fatty liver disease (NAFLD).
Methods: Data from the Korea National Health and Nutrition Examination Survey
2019-2020 were used for the analysis. NAFLD was diagnosed according to an
NAFLD liver fat score of >-0.640. Smoking status was classified as into nonsmokers,
ex-smokers, and current smokers. Multiple logistic regression analysis was conducted
to examine the association between smoking history and NAFLD in the South
Korean population.
Results: In total, 9,603 participants were enrolled in this study. The odds ratio (OR) for
having NAFLD in ex-smokers and current smokers in males was 1.12 (95% confidence
interval [CI]: 0.90–1.41) and 1.38 (95% CI: 1.08–1.76) compared to that in nonsmokers,
respectively. The OR increased in magnitude with smoking status. Ex-smokers who
ceased smoking for <10 years (OR: 1.33, 95% CI: 1.00–1.77) were more likely to have
a strong correlation with NAFLD. Furthermore, NAFLD had a dose-dependent positive
eect on pack-years, which was 10 to 20 (OR: 1.39, 95% CI: 1.04–1.86) and over 20
(OR: 1.51, 95% CI: 1.14–2.00).
Conclusion: This study found that smoking may contribute to NAFLD. Our study
suggests cessation of smoking may help management of NAFLD.
KEYWORDS
smoking, smoking behavior, smoking history, smoking cessation, tobacco, pack-years,
nonalcoholic fatty liver disease
Introduction
Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease. It is a
condition in which neutral fat accumulates excessively in the liver (1,2). Although there are some
differences in its frequency from country to country, it has been reported that 6.3 to 33% and an
average of approximately 20% of patients worldwide have been affected by the disease (3). The
prevalence of NAFLD is rapidly increasing in Asian countries due to the increase in Westernized
eating habits, obesity, and the diabetic population (4,5). In addition, between 10 and 29% of
patients with nonalcoholic fatty hepatitis develop cirrhosis within 10 years and between 4 and
27% of patients develop liver cancer (6,7). Furthermore, patients with NAFLD have a higher
mortality rate than healthy controls, and the mortality rate related to liver disease is also high
(8–11). Therefore, NAFLD must be managed immediately due to its expected serious public
health burden and significant social costs (12,13).
Frontiers in Public Health 01 frontiersin.org
Jang et al. 10.3389/fpubh.2023.1015919
Tobacco smoke contains more than 7,000 chemicals,
of which at least 250 are known to be harmful, such as
ammonia and hydrogen cyanide (14,15). Smoking is closely
related to chronic diseases, such as cardiovascular diseases,
cancer, and type 2 diabetes (16–19), which are also related to
NAFLD (20–22). Previous studies have suggested smoking is
associated with increased prevalence and incidence of liver
diseases (23,24). In particular, it has been reported to be
an independent risk factor for the progression of advanced
fibrosis in patients with primary biliary cirrhosis (23) and chronic
hepatitis C (24).
A positive association between smoking and NAFLD has
been continuously reported (25–27). An experimental study
suggested cigarettes accelerated the progression of NAFLD in
obese mice-fed diets (25). Furthermore, a study conducted in
mice without apolipoprotein E, a condition wherein fatty liver
is easily occurs, found that nicotine in electronic cigarettes
(e-cigarettes) causes genetic mutations and promotes NAFLD
outbreaks (26). Other studies have shown that the activation
of sterol regulatory element-binding proteins (SREBPs), which
stimulate the synthesis of fatty acids in the liver, is associated
with NAFLD (27). These studies provided evidence of the
mechanism of the relationship between smoking and the prevalence
of NAFLD. However, most studies are experimental studies
conducted on animals, and there are not many studies conducted
on humans.
Therefore, this study aimed to examine the association between
smoking history and NAFLD in a representative population and
to explain whether smoking behavior plays a potential role in
developing NAFLD.
FIGURE 1
Flowchart of the study participants showing the inclusion and exclusion.
Materials and methods
Data
The study used cross-sectional data from the 2019–2020
National Health and Nutrition Examination Survey (KNHANES),
conducted by the Korea Centers for Disease Control and
Prevention Agency (KDCA). The KNAHENS is a self-report
survey using a stratified, multistage, cluster sampling design
conducted annually for South Koreans of all ages to evaluate
the health and nutritional status. The survey provides data
for the evaluation and development of health policies and
programs and does not require ethical approval from the ethics
review board, as the KNHANES conforms to the Declaration
of Helsinki.
Study population
Of the 15,469 survey participants, we excluded those under 19
years of age and those who did not participate in a KNHANES
smoking questionnaire survey (n=2,730). Furthermore, participants
who tested positive for serologic markers for liver diseases (hepatitis
B, hepatitis C, and liver cirrhosis) were excluded (n=437).
Participants with missing data were also excluded (n=2,699).
Consequently, a final sample of 9,603 participants was analyzed
in this study (Figure 1). As a study that examined the effects
of smoking on NAFLD, participants with alcohol-related fatty
liver disease were also excluded based on their biochemical and
clinical profiles.
Frontiers in Public Health 02 frontiersin.org
Jang et al. 10.3389/fpubh.2023.1015919
Variables
The main dependent variable was the prevalence of NAFLD.
NAFLD was diagnosed according to the NAFLD liver fat score
developed by the Department of Medicine and the Minerva
Medical Research Institute at Helsinki University (28). The NAFLD
liver fat score formula was derived using a multivariate logistic
regression model using metabolic syndrome, type 2 diabetes, fasting
insulin (fS), serum aspartate aminotransferase (AST) ratio, and
AST to serum alanine aminotransferase (ALT) ratio (28): NAFLD
liver fat score = −0.89 +1.18 ×metabolic syndrome (yes
=1 / no =0) +0.45 ×diabetes (yes =2 / no =0) +
0.15 ×fS-insulin (mu/L) +0.04 ×fS-AST (U/L) – 0.94 ×
AST/ALT. Participants were considered to have NAFLD if their
liver fat score of NAFLD was >−0.640 as the optimal cutoff
point (28).
The primary independent variable was the smoking status
of the participants, which was divided into three groups:
(1) nonsmokers, (2) ex-smokers, and (3) current smokers.
This was defined based on the questions: ’Do you currently
smoke conventional cigarettes?’; “Do you currently smoke e-
cigarettes?”. This classification was the same as that of a previous
study that used the same research tool to investigate smoking
behavior (29).
The covariates included demographic factors (sex, age, marital
status, and educational level), socioeconomic factors (household
income, region, and occupational categories), behavioral health
patterns (current drinking status, physical activity), and health-
related factors (body mass index (BMI), diagnosis of hypertension,
and diagnosis of diabetes).
Statistical analysis
All estimates were calculated using sample weight procedures
to improve representativeness and generalize the data. Clusters
and strata were assigned to the study population. The general
characteristics of the study group, represented by frequencies and
percentages for categorical variables, means and standard deviations
for continuous variables, were based on descriptive analysis. After
adjusting for covariates, a multiple logistic regression analysis was
performed to assess the relationship between smoking and NAFLD.
Subgroup analyzes were also performed according to age, current
drinking status, physical activity, BMI, and diagnosis of hypertension
and diabetes. Furthermore, we also performed a subgroup analysis
for a more complete analysis of smoking behavior, including
smoking cessation status (SCS) and pack years. All statistical analyses
were performed using SAS version 9.4 (SAS Institute Inc., Cary,
NC, USA).
Results
Table 1 shows the characteristics of the study population.
Of the 9,603 participants, 4,063 were men (42.3%) and 5,540
were women (57.7%). Among males, 1,249 (30.7%) were current
smokers, 1,674 (41.2%) were ex-smokers, and 1,140 (28.1%) were
nonsmokers. Among the females, 259 (4.7%) were current smokers,
312 (5.6%) were ex-smokers, and 4,969 (89.7%) were nonsmokers.
In total, 1,433 (35.3%) men and 1,278 (23.1%) women reported
NAFLD.
Table 2 presents the results of the multiple regression analysis
for the relationship between smoking and NAFLD stratified by
sex after adjusting for all covariates. Among male participants,
the odds ratios (OR) for NAFLD among ex-smokers and current
smokers were 1.12 (95% confidence interval [CI]: 0.90–1.41) and
1.38 (95% CI: 1.08–1.76), respectively. In women, the OR for
NAFLD among ex-smokers and current smokers were 1.32 (95%
CI: 0.86–2.01) and 1.18 (95% CI: 0.76–1.83), respectively. Ex-
smokers and current smokers exhibited an increasing trend of OR
for NAFLD compared to that in nonsmokers, although there were
statistically significant associations only in current smokers among
males.
Figure 2 presents the results of the stratified subgroup analysis
of the association between SCS and pack years, indicating the effect
of the number of cigarettes and the smoking period on NAFLD
according to smoking behavior. In general, with nonsmokers as
the reference category, the OR for NAFLD increased linearly as
smoking cessation decreased and pack years increased in males.
Specifically, an ex-smoker with smoking cessation for <10 years
(OR: 1.33, 95% CI: 1.00–1.77) and a current smoker (OR: 1.38, 95%
CI: 1.08–1.76) had the strongest statistically significant association
compared to a nonsmoker, as classified based on the smoking
cessation period. Furthermore, an ex-smoker and current smoker
with 10 to 20 pack years (OR: 1.39, 95% CI: 1.04–1.86) and
over 20 pack years (OR: 1.51, 95% CI: 1.14–2.00), respectively,
was more likely to have a strong relationship with NAFLD
compared to a nonsmoker.
Table 3 shows the results of the independent variable subgroup
analysis, representing the ORs for NAFLD stratified by the smoking
status. Among current male smokers, cases of never or occasional
drinking (OR: 1.78, 95% CI: 1.14–2.78), adequate physical activity
(OR: 1.55, 95% CI: 1.09–2.21), BMI indicating overweight (OR:
2.31, 95% CI: 1.40–3.83), no diagnosis of hypertension (OR: 1.42,
95% CI: 1.07–1.87), and no diagnosis of diabetes (OR: 1.39, 95%
CI: 1.08–1.79) showed the strongest associations with NAFLD
compared to male nonsmokers. In women, drinking 2 to 4 times
per month (current smokers: OR: 1.39, 95% CI: 1.08–1.79), normal
BMI (ex-smokers: OR: 2.74, 95% CI: 1.28–5.88), and BMI indicating
stage 2 and 3 obesity (ex-smokers: OR: 4.36, 95% CI: 1.14–16.71)
showed the strongest associations with NAFLD compared to those
in nonsmokers.
Discussion
The general findings were that there is an association between
smoking and NAFLD, and the risk of having NAFLD has a
dose-dependent negative association with the duration of smoking
cessation and a positive association with pack years. Given
these results, our study suggests that ex-smokers with an SCS
of fewer than 10 years had associations similar to those seen
in current smokers, while ex-smokers whose SCS was more
than 20 years had no association. Furthermore, we found a
strong linear association between the duration of smoking and
the number of cigarettes smoked per day. These findings are
consistent with the results of a previous study (30) and may
provide supporting evidence for an association between smoking
Frontiers in Public Health 03 frontiersin.org
Jang et al. 10.3389/fpubh.2023.1015919
TABLE 1 General characteristics of the study population.
Variables Nonalcoholic fatty liver disease (NAFLD)
Male Female
Total Yes No P-value Total Yes No P-value
N % N % N % N % N % N %
Total (N=9,603) 4,063 100.0 1,433 35.3 2,630 64.7 5,540 100.0 1,278 23.1 4,262 76.9
Smoking Behavior 0.0014 0.5628
Nonsmoker 1,140 28.1 354 31.1 786 68.9 4,969 89.7 1,156 23.3 3,813 76.7
Ex-smoker 1,674 41.2 629 37.6 1,045 62.4 312 5.6 65 20.8 247 79.2
Current smoker 1,249 30.7 450 36.0 799 64.0 259 4.7 57 22.0 202 78.0
Age (Mean, SD) 51.6 17.2 52.2 15.9 51.3 17.9 <0.0001 51.8 16.4 49.8 16.3 58.6 14.9 <0.0001
Marital status 0.0185 0.1441
Married 2,884 71.0 1,043 36.2 1,841 63.8 3,664 66.1 835 22.8 2,829 77.2
Divorced, Separated 166 4.1 67 40.4 99 59.6 343 6.2 94 27.4 249 72.6
Single, widow 1,013 24.9 323 31.9 690 68.1 1,533 27.7 349 22.8 1,184 77.2
Educational level 0.8249 <0.0001
Middle school or below 878 21.6 317 36.1 561 63.9 1,715 31.0 621 36.2 1,094 63.8
High school 1,472 36.2 513 34.9 959 65.1 1,787 32.3 381 21.3 1,406 78.7
College or over 1,713 42.2 603 35.2 1,110 64.8 2,038 36.8 276 13.5 1,762 86.5
Household income 0.6334 <0.0001
Low 651 16.0 224 34.4 427 65.6 1,046 18.9 353 33.7 693 66.3
Mid-low 985 24.2 364 37.0 621 63.0 1,360 24.5 334 24.6 1,026 75.4
Mid-high 1,129 27.8 396 35.1 733 64.9 1,488 26.9 297 20.0 1,191 80.0
High 1,298 31.9 449 34.6 849 65.4 1,646 29.7 294 17.9 1,352 82.1
Region 0.2872 <0.0001
Metropolitan 1,720 42.3 584 34.0 1,136 66.0 2,466 44.5 502 20.4 1,964 79.6
Urban 1,505 37.0 540 35.9 965 64.1 2,034 36.7 459 22.6 1,575 77.4
Rural 838 20.6 309 36.9 529 63.1 1,040 18.8 317 30.5 723 69.5
Occupational categories 0.6403 <0.0001
White 1,155 28.4 422 36.5 733 63.5 1,263 22.8 174 13.8 1,089 86.2
Pink 404 9.9 137 33.9 267 66.1 835 15.1 191 22.9 644 77.1
Blue 1,308 32.2 449 34.3 859 65.7 822 14.8 217 26.4 605 73.6
Inoccupation 1,196 29.4 425 35.5 771 64.5 2,620 47.3 696 26.6 1,924 73.4
Current drinking status 0.0315 <0.0001
Never or occasionally 1,273 31.3 435 34.2 838 65.8 3,310 59.7 892 26.9 2,418 73.1
2–4 times/month 1,478 36.4 498 33.7 980 66.3 1,633 29.5 297 18.2 1,336 81.8
2–4 times/week 1,312 32.3 500 38.1 812 61.9 597 10.8 89 14.9 508 85.1
Physical activity <0.0001 <0.0001
Adequate 1,906 46.9 613 32.2 1,293 67.8 2,216 40.0 425 19.2 1,791 80.8
Inadequate 2,157 53.1 820 38.0 1,337 62.0 3,324 60.0 853 25.7 2,471 74.3
BMI <0.0001 <0.0001
Normal 1,155 28.4 132 11.4 1,023 88.6 2,494 45.0 175 7.0 2,319 93.0
Underweight 92 2.3 3 3.3 89 96.7 272 4.9 6 2.2 266 97.8
Overweight 1,069 26.3 274 25.6 795 74.4 1,116 20.1 268 24.0 848 76.0
(Continued)
Frontiers in Public Health 04 frontiersin.org
Jang et al. 10.3389/fpubh.2023.1015919
TABLE 1 (Continued)
Variables Nonalcoholic fatty liver disease (NAFLD)
Male Female
Total Yes No P-value Total Yes No P-value
N % N % N % N % N % N %
Obesity of stage 1 1,472 36.2 796 54.1 676 45.9 1,351 24.4 597 44.2 754 55.8
Obesity of stages 2&3 275 6.8 228 82.9 47 17.1 307 5.5 232 75.6 75 24.4
Diagnosis of hypertension <0.0001 <0.0001
Yes 1,105 27.2 530 48.0 575 52.0 1,290 23.3 577 44.7 713 55.3
No 2,958 72.8 903 30.5 2,055 69.5 4,250 76.7 701 16.5 3,549 83.5
Diagnosis of diabetes <0.0001 <0.0001
Yes 466 11.5 299 64.2 167 35.8 500 9.0 339 67.8 161 32.2
No 3,597 88.5 1,134 31.5 2,463 68.5 5,040 91.0 939 18.6 4,101 81.4
Year 0.0018 0.1354
2019 2,088 51.4 689 33.0 1,399 67.0 2,932 52.9 653 22.3 1,983 77.7
2020 1,975 48.6 744 37.7 1,231 62.3 2,608 47.1 625 24.0 2,279 76.0
history and NAFLD. Smoking cessation reduces the incidence of
NAFLD. However, due to the low number of female smokers
in Korea, we could not find a relationship between smoking
and NAFLD among females. However, although not statistically
significant, the OR of former smokers and current smokers was
higher than that of nonsmokers. This reflects the recall bias of self-
reported data due to the poor perception of female smokers in
Korea (31).
Smoking has been identified, as an adjunct to obesity, as
a causative factor for NAFLD in animal and clinical studies
(25,32). This study found no association between smoking
behavior and NAFLD in men with stages 1, 2, and 3 obesity;
however, in overweight men and normal women, smoking
behavior was a significant risk factor associated with NAFLD
compared to nonsmoking. This supports the results of a previous
study (33) suggesting that while severe obesity directly affects
NAFLD in BMI groups, smoking may have an independent
relationship in normal or overweight groups. A mechanism
that explains the independent role of BMI in the association
between smoking and NAFLD is that the antiestrogenic effect
of cigarette smoking leads to a change in body fat distribution
(34–36). Therefore, normal and overweight smokers who may
not be evaluated for NAFLD should receive more attention to
prevent NAFLD.
According to the multiple parallel hits hypothesis theory, the
pathophysiological mechanisms of NAFLD indicate the causes of
insulin resistance, genetic and epigenetic factors, mitochondrial
dysfunction, endoplasmic reticulum stress, microbiota, chromatic
low-grade injury, and dysfunction of adipose tissue (37,38).
In insulin-resistant patients, liver fat production can be further
induced by activation of transcription factors such as SREBP-1
(38,39). Many studies have shown that tobacco increases lipid
accumulation in liver cells by regulating the activity of 5′-AMP-
activated protein kinase (AMPK) and SREBP-1, two important
molecules involved in lipid synthesis (27,40–42). It is considered
a mechanism between smoking and NAFLD, especially based on
previous studies that show a decisive role in liver fat accumulation
in SREBP-1, when tobacco smoke is exposed to mice and cultured
hepatocytes (27).
However, the effects of smoking on NAFLD remain
controversial, with inconsistent results (43). One study reported
that active smoking was associated with fibrosis in patients with
NAFLD (25), but another study showed a lack of significant
relationship between active smoking and NAFLD (44). Several
experimental studies in mice have shown that nicotine, a dangerous
substance in cigarettes, promotes the development of NAFLD
or accelerates its progression (25–27). A systematic review and
meta-analysis of 20 observational studies showed that smoking
was significantly associated with NAFLD (43). Furthermore,
second-hand smoking increases the risk of NAFLD around
1.38 times (43). Based on these mechanisms, experimental
studies and cohort studies that consider additional confounders
are needed.
This study had several limitations. First, it was a cross-
sectional study. It may not establish temporal relations and may
have found an inverse causal relationship. Therefore, caution is
warranted when interpreting the results. More research is needed
to clarify the association between smoking and NAFLD. Second,
KNHANES data were collected through self-report surveys. Hence,
data on health-related status, socioeconomic variables, and smoking
status may not be reliable and accurate. In particular, this can
lead to recall bias and is likely to be underestimated in the
case of smoking. Third, although the liver fat score for NAFLD
was demonstrated for the ROC curves for detecting NAFLD
(sensitivity of 86% and specificity of 71%), there were still tiny
errors of false-positive or false-negative results. In addition, due
to the characteristics of the KNHANES called secondary data,
the diagnosis of NAFLD was not measured by the instrument
investigation, so steatosis could not be confirmed by methods such
as CAP, ultrasound, and liver biopsy. Therefore, we calculated
and considered the NAFLD liver fat score instead. Fourth, it
could not differentiate among the various smoking types, such as
Frontiers in Public Health 05 frontiersin.org
Jang et al. 10.3389/fpubh.2023.1015919
TABLE 2 Results of factors associated between smoking and nonalcoholic fatty liver disease.
Variables Nonalcoholic fatty liver disease (NAFLD)
Male Female
OR 95% CI OR 95% CI
Smoking Behavior
Nonsmoker 1.00 1.00
Ex-smoker 1.12 (0.90 – 1.41) 1.32 (0.86 – 2.01)
Current smoker 1.38 (1.08 – 1.76) 1.18 (0.76 – 1.83)
Age 1.00 (1.00 – 1.01) 1.01 (1.00 – 1.83)
Marital status
Married 1.00 1.00
Divorced, Separated 1.29 (0.80 – 2.07) 1.31 (0.93 – 1.84)
Single, widow 0.84 (0.64 – 1.10) 0.91 (0.72 – 1.13)
Educational level
Middle school or below 1.00 1.00
High school 1.07 (0.79 – 1.44) 1.03 (0.78 – 1.36)
College or over 1.06 (0.77 – 1.45) 0.73 (0.53 – 1.01)
Household income
Low 1.04 (0.74 – 1.44) 0.83 (0.60 – 1.16)
Mid-low 1.17 (0.92 – 1.49) 0.73 (0.55 – 0.95)
Mid-high 0.97 (0.78 – 1.21) 0.68 (0.51 – 0.89)
High 1.00 1.00
Region
Metropolitan 1.00 1.00
Urban 1.06 (0.87 – 1.30) 1.12 (0.91 – 1.38)
Rural 1.08 (0.85 – 1.38) 1.34 (1.01 – 1.77)
Occupational categories
White 0.88 (0.65 – 1.19) 0.81 (0.61 – 1.07)
Pink 0.78 (0.55 – 1.09) 0.94 (0.72 – 1.23)
Blue 0.71 (0.55 – 0.92) 0.63 (0.48 – 0.82)
Inoccupation 1.00 1.00
Current drinking status
Never or occasionally 1.00 1.00
2–4 times/month 0.89 (0.72 – 1.09) 0.85 (0.70 – 1.04)
2–4 times/week 1.06 (0.86 – 1.31) 0.60 (0.43 – 0.84)
Physical activity
Adequate 1.00 1.00
Inadequate 1.44 (1.20 – 1.71) 1.33 (1.11 – 1.59)
BMI
Normal 1.00 1.00
Underweight 0.50 (0.14 – 1.78) 0.44 (0.17 – 1.15)
Overweight 2.84 (2.09 – 3.86) 4.21 (3.28 – 5.41)
Obesity of stage 1 10.44 (7.94 – 13.72) 11.48 (8.92 – 14.78)
Obesity of stages 2&3 50.57 (32.58 – 78.48) 62.42 (41.29 – 94.35)
(Continued)
Frontiers in Public Health 06 frontiersin.org
Jang et al. 10.3389/fpubh.2023.1015919
TABLE 2 (Continued)
Variables Nonalcoholic fatty liver disease (NAFLD)
Male Female
OR 95% CI OR 95% CI
Diagnosis of hypertension
No 1.00 1.00
Yes 1.42 (1.14 – 1.77) 1.96 (1.55 – 2.48)
Diagnosis of diabetes
No 1.00 1.00
Yes 4.36 (3.28 – 5.80) 6.06 (4.41 – 8.31)
Year
2019 1.00 1.00
2020 1.06 (0.88 – 1.27) 0.95 (0.79 – 1.15)
FIGURE 2
Results of the subgroup analysis stratified by smoking cessation and pack-years.
conventional cigarette use, electronic cigarette use, or both. Besides,
we could not calculate the pack years for e-cigarettes because the
KNHANES did not include this information. Finally, we cannot
exclude the possibility of unrecognized confounders, although we
adjusted for known confounders in the relationship between smoking
and NAFLD.
Despite these limitations, our study had several notable strengths.
First, the study was based on the KNHANES data, a nationally
representative dataset collected by the KDCA. This is useful for
health-related research because it is updated annually to reflect
the changes in the actual health situation of Koreans. In addition,
it is a statistic that can generalize the study results to the
general population because the survey is performed by reliable
and representative random cluster sampling. Second, we calculated
the SCS and pack years for ex-smokers and current smokers. The
study showed a significant association between current smoking
behavior in men and smoking status considering SCS and pack-
years. Therefore, our results suggest that smoking status has the
opportunity to be considered as a measure of intervention to
reduce the risk of NAFLD when SCS and pack years are taken
into account.
Conclusion
In conclusion, this study found that current smoking was
associated with NAFLD in men in the South Korean population.
In particular, we suggest an association between NAFLD and ex-
smoker and current smoker status with a short smoking cessation
period or many pack years. Given these results, smoking has
a potential effect on NAFLD, and smoking cessation should be
considered in the prevention and management of NAFLD. It is
Frontiers in Public Health 07 frontiersin.org
Jang et al. 10.3389/fpubh.2023.1015919
TABLE 3 Results of subgroup analysis stratified by independent variables.
Nonalcoholic fatty liver disease (NAFLD)
Male Female
Non Ex-smoker Current smoker Non Ex-smoker Current smoker
OR OR 95% CI OR 95% CI OR OR 95% CI OR 95% CI
Age
20–29 1.00 0.53 (0.21 – 1.37) 1.06 (0.54 – 2.09) 1.00 0.82 (0.18 – 3.63) 1.12 (0.32 – 3.92)
30–39 1.00 0.71 (0.33 – 1.51) 1.18 (0.65 – 2.16) 1.00 1.68 (0.41 – 6.84) 0.62 (0.15 – 2.51)
40–49 1.00 1.35 (0.71 – 2.58) 1.47 (0.76 – 2.86) 1.00 1.40 (0.61 – 3.22) 0.74 (0.26 – 2.13)
50–59 1.00 1.14 (0.62 – 2.08) 1.38 (0.72 – 2.62) 1.00 2.67 (1.06 – 6.73) 3.16 (1.12 – 8.86)
60–69 1.00 1.58 (0.94 – 2.67) 1.51 (0.83 – 2.76) 1.00 0.78 (0.33 – 1.86) 1.07 (0.44 – 2.63)
≥70 1.00 0.98 (0.58 – 1.66) 0.99 (0.43 – 2.27) 1.00 0.71 (0.18 – 2.85) 0.38 (0.10 – 1.39)
Current drinking status
Never or occasionally 1.00 0.97 (0.64 – 1.46) 1.78 (1.14 – 2.78) 1.00 1.12 (0.60 – 2.06) 0.61 (0.33 – 1.13)
2–4 times/month 1.00 1.05 (0.74 – 1.50) 1.21 (0.84 – 1.76) 1.00 1.30 (0.59 – 2.87) 2.28 (1.14 – 4.56)
2–4 times/week 1.00 1.52 (0.95 – 2.43) 1.56 (1.01 – 2.42) 1.00 2.56 (0.95 – 6.95) 0.91 (0.36 – 2.31)
Physical activity
Adequate 1.00 1.07 (0.77 – 1.50) 1.55 (1.09 – 2.21) 1.00 1.28 (0.67 – 2.44) 0.99 (0.48 – 2.03)
Inadequate 1.00 1.15 (0.84 – 1.58) 1.28 (0.90 – 1.83) 1.00 1.33 (0.78 – 2.28) 1.27 (0.74 – 2.19)
BMI
Underweight 1.00 – – – – – 1.00 – – – –
Normal 1.00 1.32 (0.74 – 2.34) 1.14 (0.57 – 2.25) 1.00 2.74 (1.28 – 5.88) 2.16 (0.96 – 4.85)
Overweight 1.00 1.63 (0.96 – 2.75) 2.31 (1.40 – 3.83) 1.00 0.79 (0.25 – 2.49) 1.04 (0.41 – 2.65)
Obesity of stage 1 1.00 0.97 (0.71 – 1.33) 1.14 (0.82 – 1.60) 1.00 0.77 (0.38 – 1.57) 1.01 (0.52 – 1.96)
Obesity of stages 2&3 1.00 0.86 (0.28 – 2.60) 1.73 (0.63 – 4.77) 1.00 4.36 (1.14 – 16.71) 1.21 (0.25 – 5.81)
Diagnosis of hypertension
No 1.00 1.07 (0.82 – 1.41) 1.42 (1.07 – 1.87) 1.00 1.33 (0.81 – 2.19) 1.28 (0.79 – 2.07)
Yes 1.00 1.16 (0.74 – 1.82) 1.05 (0.62 – 1.78) 1.00 1.35 (0.61 – 2.99) 0.90 (0.34 – 2.37)
Diagnosis of diabetes
No 1.00 1.06 (0.83 – 1.35) 1.39 (1.08 – 1.79) 1.00 1.29 (0.83 – 2.01) 1.22 (0.76 – 1.95)
Yes 1.00 1.79 (0.85 – 3.80) 0.91 (0.39 – 2.13) 1.00 2.14 (0.24 – 19.16) 1.19 (0.30 – 4.67)
Frontiers in Public Health 08 frontiersin.org
Jang et al. 10.3389/fpubh.2023.1015919
best to stop smoking considering health status and behavior to
avoid serious diseases. More prospective studies and clinical trials
are required to clarify the relationship between smoking history
and NAFLD.
Data availability statement
Publicly available datasets were analyzed in this study. This data
can be found here: https://www.kdca.go.kr/index.es?sid=a2.
Ethics statement
Ethical review and approval was not required for the study
on human participants in accordance with the local legislation
and institutional requirements. Written informed consent for
participation was not required for this study in accordance with the
national legislation and the institutional requirements.
Author contributions
YSJ designed the study, collected data, performed statistical
analysis, and drafted the manuscript. YSJ, HJJ, YSP, E-CP, and S-IJ
contributed to the discussion. S-IJ is the guarantor of this work, has
full access to all the study data, and assumes responsibility for the
integrity of the data and the accuracy of the data analysis. All authors
reviewed and edited the drafts of the manuscript, approved the final
version, and approved the final manuscript.
Funding
This study was supported by the National Research Foundation
of Korea (NRF) grant funded by the Korea Government (MSIT)
(No. 2022R1F1A1062794).
Acknowledgments
The authors express sincere appreciation to our colleagues and
professor from the Department of Public Health, Graduate School
of Yonsei University, for their advice on this manuscript. We thank
KDCA, which provided the KNAHNES.
Conflict of interest
The authors declare that the research was conducted in the
absence of any commercial or financial relationships that could be
construed as a potential conflict of interest.
Publisher’s note
All claims expressed in this article are solely those of the
authors and do not necessarily represent those of their affiliated
organizations, or those of the publisher, the editors and the reviewers.
Any product that may be evaluated in this article, or claim that may
be made by its manufacturer, is not guaranteed or endorsed by the
publisher.
References
1. Cohen JC, Horton JD, Hobbs HH. Human fatty liver disease: old questions and new
insights. Science. (2011) 332:1519–23. doi: 10.1126/science.1204265
2. Armstrong MJ, Houlihan DD, Bentham L, Shaw JC,Cramb R , Olliff S, et al. Presence
and severity of non-alcoholic fatty liver disease in a large prospective primary care cohort.
J Hepatol. (2012) 56:234–40. doi: 10.1016/j.jhep.2011.03.020
3. Chalasani N, Younossi Z, Lavine JE, Diehl AM, Brunt EM, Cusi K, et al. The
diagnosis and management of non-alcoholic fatty liver disease: practice Guideline
by the American Association for the Study of Liver Diseases, American College of
Gastroenterology, and the American Gastroenterological Association. Hepatology. (2012)
55:2005–23. doi: 10.1002/hep.25762
4. Loomba R, Sanyal AJ. The global NAFLD epidemic. Nat Rev Gastroenterol Hepatol.
(2013) 10:686–90. doi: 10.1038/nrgastro.2013.171
5. Lim YS, Kim WR. The global impact of hepatic fibrosis and end-stage liver disease.
Clin Liver Dis. (2008) 12:733–46. doi: 10.1016/j.cld.2008.07.007
6. Argo CK, Caldwell SH. Epidemiology and natural history of non-alcoholic
steatohepatitis. Clin Liver Dis. (2009) 13:511–31. doi: 10.1016/j.cld.2009.07.005
7. Starley BQ, Calcagno CJ, Harrison SA. Nonalcoholic fatty liver disease
and hepatocellular carcinoma: a weighty connection. Hepatology. (2010)
51:1820–32. doi: 10.1002/hep.23594
8. Adams LA, Lymp JF, St Sauver J, Sanderson SO, Lindor KD, Feldstein A, et al.
The natural history of nonalcoholic fatty liver disease: a population-based cohort study.
Gastroenterology. (2005) 129:113–21. doi: 10.1053/j.gastro.2005.04.014
9. Ekstedt M, Franzén LE, Mathiesen UL, Thorelius L, Holmqvist M, Bodemar G, et al.
Long-term follow-up of patients with NAFLD and elevated liver enzymes. Hepatology.
(2006) 44:865–73. doi: 10.1002/hep.21327
10. Rafiq N, Bai C, Fang Y, Srishord M, McCullough A, Gramlich T, et al. Long-term
follow-up of patients with nonalcoholic fatty liver. Clin Gastroenterol Hepatol. (2009)
7:234–8. doi: 10.1016/j.cgh.2008.11.005
11. Stepanova M, Rafiq N, Younossi ZM. Components of metabolic syndrome are
independent predictors of mortality in patients with chronic liver disease: a population-
based study. Gut. (2010) 59:1410–5. doi: 10.1136/gut.2010.213553
12. Lee YH, Kim SU, Song K, Park JY, Kim DY, Ahn SH, et al. Sarcopenia is
associated with significant liver fibrosis independently of obesity and insulin resistance in
nonalcoholic fatty liver disease: Nationwide surveys (KNHANES 2008-2011). Hepatology.
(2016) 63:776–86. doi: 10.1002/hep.28376
13. Younossi Z, Anstee QM, Marietti M, Hardy T, Henry L, Eslam M, et al. Global
burden of NAFLD and NASH: trends, predictions, risk factors and prevention. Nat Rev
Gastroenterol Hepatol. (2018) 15:11–20. doi: 10.1038/nrgastro.2017.109
14. US Department of Health and Human Ser vices. The Health Consequences of
Smoking −50 Years of Progress: A Report of the Surgeon General. Reports of the Surgeon
General (2014).
15. Centers for Disease Control and Prevention (US), National Center for Chronic
Disease Prevention and Health Promotion (US), and Office on Smoking and Health.
How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-
Attributable Disease: A Report of the Surgeon General. Publications and Reports of the
Surgeon General (2010).
16. Jatoi NA, Jerrard-Dunne P, Feely J, Mahmud A. Impact of smoking and smoking
cessation on arterial stiffness and aortic wave reflection in hypertension. Hypertension.
(2007) 49:981–5. doi: 10.1161/hypertensionaha.107.087338
17. Botteri E, Iodice S, Bagnardi V, Raimondi S, Lowenfels AB, Maisonneuve
P. Smoking and colorectal cancer: a meta-analysis. JAMA. (2008) 300:2765–
78. doi: 10.1001/jama.2008.839
18. Willi C, Bodenmann P, Ghali WA, Faris PD, Cornuz J. Active smoking and the
risk of type 2 diabetes: a systematic review and meta-analysis. JAMA. (2007) 298:2654–
64. doi: 10.1001/jama.298.22.2654
19. World Health Organization. WHO Report on the Global Tobacco Epidemic, 2021:
Addressing new and emerging products. (2021).
20. Kasper P, Martin A, Lang S, Kütting F, Goeser T, Demir M, et al. NAFLD
and cardiovascular diseases: a clinical review. Clin Res Cardiol. (2021) 110:921–
37. doi: 10.1007/s00392-020-01709-7
21. Tanase DM, Gosav EM, Costea CF, Ciocoiu M, Lacatusu CM, Maranduca MA,
et al. The Intricate Relationship between Type 2 Diabetes Mellitus (T2DM), Insulin
Frontiers in Public Health 09 frontiersin.org
Jang et al. 10.3389/fpubh.2023.1015919
Resistance (IR), and Nonalcoholic Fatty Liver Disease (NAFLD). J Diabetes Res. (2020)
2020:3920196. doi: 10.1155/2020/3920196
22. Marengo A, Rosso C, Bugianesi E. Liver Cancer: Connections
with obesity, fatty liver, and cirrhosis. Annu Rev Med. (2016) 67:103–
17. doi: 10.1146/annurev-med-090514-013832
23. Zein CO, Beatty K, Post AB, Logan L, Debanne S, McCullough AJ. Smoking
and increased severity of hepatic fibrosis in primary biliary cirrhosis: a cross validated
retrospective assessment. Hepatology. (2006) 44:1564–71. doi: 10.1002/hep.21423
24. Pessione F, Ramond MJ, Njapoum C, Duchatelle V, Degott C, Erlinger S, et al.
Cigarette smoking and hepatic lesions in patients with chronic hepatitis C. Hepatology.
(2001) 34:121–5. doi: 10.1053/jhep.2001.25385
25. Azzalini L, Ferrer E, Ramalho LN, Moreno M, Domínguez M, Colmenero J, et al.
Cigarette smoking exacerbates nonalcoholic fatty liver disease in obese rats. Hepatology.
(2010) 51:1567–76. doi: 10.1002/hep.23516
26. Hasan KM, Friedman TC, Shao X, Parveen M, Sims C, Lee DL, et al. E-cigarettes
and western diet: important metabolic risk factors for hepatic diseases. Hepatology. (2019)
69:2442–54. doi: 10.1002/hep.30512
27. Yuan H, Shyy JY, Martins-Green M. Second-hand smoke stimulates lipid
accumulation in the liver by modulating AMPK and SREBP-1. J Hepatol. (2009) 51:535–
47. doi: 10.1016/j.jhep.2009.03.026
28. Kotronen A, Peltonen M, Hakkarainen A, Sevastianova K, Bergholm R, Johansson
LM, et al. Prediction of non-alcoholic fatty liver disease and liver fat using metabolic and
genetic factors. Gastroenterology. (2009) 137:865–72. doi: 10.1053/j.gastro.2009.06.005
29. Yoon YJ, Lee MS, Jang KW, Ahn JB, Hurh K, Park EC. Association between
smoking cessation and obstructive spirometry pattern among Korean adults aged 40-79
years. Sci Rep. (2021) 11:18667. doi: 10.1038/s41598-021-98156-9
30. Takenaka H, Fujita T, Masuda A, Yano Y, Watanabe A, Kodama Y. Non-
alcoholic fatty liver disease is strongly associated with smoking status and is improved
by smoking cessation in japanese males: a retrospective study. Kobe J Med Sci.
(2020) 66:E102–e12.
31. Kang HG, Kwon KH, Lee IW, Jung B, Park EC, Jang SI. Biochemically-
verified smoking rate trends and factors associated with inaccurate self-reporting
of smoking habits in Korean women. Asian Pac J Cancer Prev. (2013) 14:6807–
12. doi: 10.7314/apjcp.2013.14.11.6807
32. Mallat A, Lotersztajn S. Cigarette smoke exposure: a novel cofactor of NAFLD
progression? J Hepatol. (2009) 51:430–2. doi: 10.1016/j.jhep.2009.05.021
33. Liu Y, Dai M, Bi Y, Xu M, Xu Y, Li M, et al. Active smoking, passive smoking, and
risk of nonalcoholic fatty liver disease (NAFLD): a population-based study in China. J
Epidemiol. (2013) 23:115–21. doi: 10.2188/jea.je20120067
34. Shimokata H, Muller DC, Andres R. Studies in the distribution of body fat. Iii
Effects of cigarette smoking. JAMA. (1989) 261:1169–73.
35. Tankó LB, Christiansen C. An update on the antiestrogenic effect of smoking: a
literature review with implications for researchers and practitioners. Menopause. (2004)
11:104–9. doi: 10.1097/01.Gme.0000079740.18541.Db
36. Windham GC, Mitchell P, Anderson M, Lasley BL. Cigarette smoking and effects on
hormone function in premenopausal women. Environ Health Perspect. (2005) 113:1285–
90. doi: 10.1289/ehp.7899
37. Acierno C, Caturano A, Pafundi P, Nevola R, Adinolfi L, Sasso F. Nonalcoholic fatty
liver disease and type 2 diabetes: pathophysiological mechanisms shared between the two
faces of the same coin. Explor Med. (2020) 1:287–306.
38. Caturano A, Acierno C, Nevola R, Pafundi PC, Galiero R, Rinaldi L, et al. Non-
alcoholic fatty liver disease: From pathogenesis to clinical impact. Processes. (2021) 9:135.
doi: 10.3390/pr9010135
39. George J, Liddle C. Nonalcoholic fatty liver disease: pathogenesis and
potential for nuclear receptors as therapeutic targets. Mol Pharm. (2008)
5:49–59. doi: 10.1021/mp700110z
40. Jung EJ, Kwon SW, Jung BH, Oh SH, Lee BH. Role of the AMPK/SREBP-
1 pathway in the development of orotic acid-induced fatty liver. J Lipid Res. (2011)
52:1617–25. doi: 10.1194/jlr.M015263
41. Kim SP, Nam SH, Friedman M. Mechanism of the antiadipogenic-antiobesity
effects of a rice hull smoke extract in 3T3-L1 preadipocyte cells and in mice on a high-fat
diet. Food Funct. (2015) 6:2939–48. doi: 10.1039/c5fo00469a
42. Ponciano-Rodríguez G, Méndez-Sánchez N. Cigarette smoking and fatty liver. Ann
Hepatol. (2010) 9:215–8.
43. Akhavan Rezayat A, Dadgar Moghadam M, Ghasemi Nour M, Shirazinia
M, Ghodsi H, Rouhbakhsh Zahmatkesh MR, et al. Association between smoking
and non-alcoholic fatty liver disease: a systematic review and meta-analysis.
SAGE Open Med. (2018) 6:2050312117745223. doi: 10.1177/205031211774
5223
44. Chavez-Tapia NC, Lizardi-Cervera J, Perez-Bautista O, Ramos-Ostos MH, Uribe
M. Smoking is not associated with nonalcoholic fatty liver disease. World J Gastroenterol.
(2006) 12:5196–200. doi: 10.3748/wjg.v12.i32.5196
Frontiers in Public Health 10 frontiersin.org
Available via license: CC BY
Content may be subject to copyright.
