Impact of smoking and physical activity on cardiovascular outcomes in type 2 diabetes across steatotic liver disease categories

So Hyun Cho; Gyuri Kim; Kyu-na Lee; Rosa Oh; Ji Yoon Kim; Myunghwa Jang; You-Bin Lee; Sang-Man Jin; Kyu Yeon Hur; Kyungdo Han; Jae Hyeon Kim

doi:10.1038/s41598-025-16750-7

. 2025 Aug 23;15:31029. doi: 10.1038/s41598-025-16750-7

Impact of smoking and physical activity on cardiovascular outcomes in type 2 diabetes across steatotic liver disease categories

So Hyun Cho ^1,^#, Gyuri Kim ^1,^#, Kyu-na Lee ², Rosa Oh ¹, Ji Yoon Kim ¹, Myunghwa Jang ¹, You-Bin Lee ¹, Sang-Man Jin ¹, Kyu Yeon Hur ¹, Kyungdo Han ^3,^✉, Jae Hyeon Kim ^1,^4,^✉

PMCID: PMC12374968 PMID: 40849338

Abstract

This study investigated the effect of smoking and regular physical activity (PA) on the composite risk of cardiovascular disease (CVD) in patients with type 2 diabetes mellitus (T2DM) across different steatotic liver disease (SLD) categories. We analyzed data for 1,921,310 patients with T2DM aged 20 years and older. The participants were categorized by SLD status, with hepatic steatosis (fatty liver index ≥ 30). Among current smokers, the adjusted hazard ratios (HR) for composite CVD events significantly increased from the no steatosis to metabolic dysfunction-associated steatotic liver disease (MASLD), metabolic dysfunction and alcohol-related steatotic liver disease (MetALD), and alcohol-related liver disease (ALD) groups, with the highest HR observed in the ALD group (aHR, 2.14; 95% confidence interval [CI], 2.04–2.24). The ALD group without regular PA had the highest risk of composite CVD events (aHR, 1.33; 95% CI, 1.28–1.38). The highest risk of composite CVD events was found among current smokers without regular PA, with the aHR increasing in a stepwise manner from no steatosis to MASLD, MetALD, and ALD groups, with the latter showing the highest risk. Smoking and physical inactivity significantly increased the CVD risk in patients with T2DM, with the highest risk in the ALD group.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-025-16750-7.

Keywords: Alcohol drinking, Cardiovascular diseases, Diabetes mellitus, Exercise, Fatty liver, Smoking

Subject terms: Endocrinology, Health care, Risk factors

Introduction

Cardiovascular disease (CVD) is the leading cause of death in patients with non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH)^1–3with NAFLD conferring a cardiovascular (CV) risk greater than the sum of its individual comorbidities⁴. Recent terminology updates have led to the introduction of the term metabolic dysfunction-associated steatotic liver disease (MASLD), which encompasses NAFLD and highlights its role in driving insulin resistance, hepatic inflammation, and atherogenic dyslipidemia, all of which increase the risk of CVD^5–7. NAFLD is associated with a 2.2-fold increased risk of incident diabetes mellitus (DM), and its risk is correlated with its severity⁸. In a previous meta-analysis, patients with NAFLD and type 2 diabetes mellitus (T2DM) were found to have twice the risk of CVD compared to those with T2DM alone⁹. A recent cohort study found that current smoking significantly increased the risk of T2DM in patients with NAFLD (hazard ratio [HR], 2.05; 95% confidence interval [CI], 1.43–2.94)¹⁰while smoking cessation was associated with decreased CVD incidence among T2DM patients¹¹. A recent study indicated that many participants with MASLD did not recognize the role of exercise as an effective treatment option¹². Recent evidence suggests that regular physical activity (PA) improves histological outcomes pertaining to the liver in patients with MASLD even in the absence of significant weight loss, reinforcing the importance of exercise in managing metabolic and CV risks¹³. Furthermore, Balogun et al. demonstrated that the combined effect of smoking and T2DM was associated with an increased prevalence of hepatic fibrosis in MASLD patients¹⁴. However, despite established links between modifiable lifestyle factors such as smoking, PA, and CVD, their impact on CVD risk in T2DM patients across different steatotic liver disease (SLD) categories remains underexplored. Given the increasing global prevalence of NAFLD/MASLD among patients with T2DM¹⁵this study aimed to address this gap by investigating how smoking and PA affect CVD outcomes, including composite CVD events (myocardial infarction [MI], ischemic stroke, and CV mortality), in these populations.

Results

Baseline characteristics

A total of 1,921,310 individuals were categorized into four groups: group 1 (never or former smokers with regular PA, n = 335,222), group 2 (never or former smokers with irregular PA, n = 1,120,489), group 3 (current smokers with regular PA, n = 85,793), and group 4 (current smokers with irregular PA, n = 379,806). Table 1 presents the baseline characteristics of the participants. The median age of the total population was 58 years, with 61.4% being men, and the median follow-up duration was 6.0 years.

Table 1.

Baseline characteristics of the study participants.

	Never or former smoker	Never or former smoker	Current smoker	Current smoker	p-value
	Regular exercise	Irregular exercise	Regular exercise	Irregular exercise
	Group 1 (N = 335222)	Group 2 (N = 1120489)	Group 3 (N = 85793)	Group 4 (N = 379806)
Age, years	60.14 ± 10.61	59.74 ± 11.85	53.12 ± 10.80	51.81 ± 10.63	< 0.001
Age groups					< 0.001
< 40	10,168 (3.03)	50,374 (4.50)	8868 (10.34)	44,719 (11.77)
40–64	208,368 (62.16)	684,597 (61.10)	64,820 (75.55)	293,442 (77.26)
≥ 65	116,686 (34.81)	385,518 (34.41)	12,105 (14.11)	41,645 (10.96)
Sex					< 0.001
Male	200,415 (59.79)	540,588 (48.25)	82,081 (95.67)	356,820 (93.95)
Female	134,807 (40.21)	579,901 (51.75)	3712 (4.33)	22,986 (6.05)
BMI, kg/m²	25.11 ± 3.27	25.49 ± 3.60	25.18 ± 3.48	25.35 ± 3.69	< 0.001
BMI					< 0.001
< 18.5	3221 (0.96)	13,832 (1.23)	1113 (1.30)	6436 (1.69)
18.5–22.9	81,882 (24.43)	250,266 (22.34)	21,157 (24.66)	90,540 (23.84)
23.0-24.9	87,476 (26.09)	264,770 (23.63)	21,644 (25.23)	88,660 (23.34)
25.0-29.9	138,194 (41.22)	475,922 (42.47)	34,556 (40.28)	155,071 (40.83)
≥ 30.0	24,449 (7.29)	115,699 (10.33)	7323 (8.54)	39,099 (10.29)
Waist circumference, cm	85.06 ± 8.58	85.85 ± 9.14	86.60 ± 8.48	87.37 ± 8.93	< 0.001
SBP, mmHg	128.52 ± 14.75	128.60 ± 15.09	127.46 ± 14.48	127.48 ± 14.73	< 0.001
DBP, mmHg	77.80 ± 9.70	78.15 ± 9.91	78.89 ± 9.97	79.40 ± 10.15	< 0.001
Fasting glucose, mg/dL	141.14 ± 40.23	144.65 ± 45.05	150.03 ± 48.20	155.09 ± 51.44	< 0.001
Total cholesterol, mg/dL	184.72 ± 42.04	188.52 ± 43.78	189.45 ± 43.13	193.35 ± 44.36	< 0.001
HDL-C, mg/dL	52.63 ± 15.10	51.71 ± 14.74	50.19 ± 14.57	49.09 ± 14.91	< 0.001
LDL-C, mg/dL	103.73 ± 37.21	106.21 ± 38.69	104.36 ± 38.42	106.63 ± 39.34	< 0.001
eGFR, mL/min/1.73 m²	89.14 ± 52.48	89.12 ± 48.60	95.51 ± 64.82	96.60 ± 64.94	< 0.001
Triglyceride, mg/dL	124.38 (124.15-124.61)	135.28 (135.14-135.42)	156.30 (155.67-156.92)	170.97 (170.64-171.29)	< 0.001
Low income	66,938 (19.97)	245,621 (21.92)	16,879 (19.67)	79,926 (21.04)	< 0.001
Hypertension	186,513 (55.64)	632,457 (56.44)	40,560 (47.28)	175,333 (46.16)	< 0.001
Dyslipidemia	187,469 (55.92)	635,591 (56.72)	40,330 (47.01)	180,794 (47.60)	< 0.001
CKD	27,628 (8.24)	103,676 (9.25)	3663 (4.27)	15,501 (4.08)	< 0.001
Smoking					< 0.001
Never	214,627 (64.03)	812,517 (72.51)	–	–
Former	120,595 (35.97)	307,972 (27.49)	–	–
Current	–	–	85,793 (100)	379,806 (100)
Alcohol consumption					< 0.001
None	192,969 (57.56)	722,972 (64.52)	22,558 (26.29)	101,661 (26.77)
Mild	117,003 (34.90)	320,738 (28.62)	46,720 (54.46)	198,024 (52.14)
Heavy	20,344 (6.07)	60,942 (5.44)	13,005 (15.16)	62,157 (16.37)
Excessive	4906 (1.46)	15,837 (1.41)	3510 (4.09)	17,964 (4.73)
Regular exercise	335,222 (100)	–	85,793 (100)	-	< 0.001
CCI score, ≥5	53,406 (15.93)	179,801 (6.05)	8576 (10.00)	35,190 (9.27)	< 0.001
CCI score	2.55 ± 2.00	2.52 ± 2.04	1.96 ± 1.86	1.84 ± 1.84	< 0.001
DM duration					< 0.001
New onset	94,278 (28.12)	336,855 (30.06)	34,551 (40.27)	167,361 (44.06)
< 5 years	88,972 (26.54)	314,931 (28.11)	21,985 (25.63)	99,779 (26.27)
5–9 years	66,867 (19.95)	217,006 (19.37)	14,449 (16.84)	59,086 (15.56)
≥ 10 years	85,105 (25.39)	251,697 (22.46)	14,808 (17.26)	53,580 (14.11)
OHA, ≥3	73,001 (21.78)	251,144 (22.41)	17,536 (20.44)	77,412 (20.38)	< 0.001
Metformin	217,739 (64.95)	711,870 (63.53)	47,229 (55.05)	197,526 (52.01)	< 0.001
Sulfonylurea	109,122 (32.55)	368,810 (32.92)	25,019 (29.16)	105,976 (27.90)	< 0.001
TZD	24,145 (7.20)	82,116 (7.33)	5684 (6.63)	24,313 (6.40)	< 0.001
DPP-4 inhibitor	134,201 (40.03)	438,013 (39.09)	30,219 (35.22)	128,744 (33.90)	< 0.001
Meglitinide	1498 (0.45)	4765 (0.43)	257 (0.30)	980 (0.26)	< 0.001
SGLT-2 inhibitor	8282 (2.47)	30,173 (2.69)	1847 (2.15)	8649 (2.28)	< 0.001
GLP-1 RA	116 (0.03)	466 (0.04)	25 (0.03)	95 (0.03)	< 0.001
Insulin use	22,908 (6.83)	81,450 (7.27)	4984 (5.81)	21,281 (5.60)	< 0.001
SLD group					< 0.001
No Steatosis	155,140 (46.28)	455,780 (40.68)	25,509 (29.73)	95,551 (25.16)
MASLD	154,380 (46.05)	581,741 (51.92)	44,450 (51.81)	206,230 (54.30)
MetALD	14,686 (4.38)	47,063 (4.20)	9594 (11.18)	48,086 (12.66)
ALD	11,016 (3.29)	35,905 (3.20)	6240 (7.27)	29,939 (7.88)

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Values are presented as mean ± standard deviation (SD) or number (%).

ALD, alcohol-related liver disease; BMI, body mass index; CCI, Charlson Comorbidity Index; CKD, chronic kidney disease; DBP, diastolic blood pressure; DM, diabetes mellitus; DPP-4, dipeptidyl peptidase-4; eGFR, estimated glomerular filtration rate; GLP-1 RA, glucagon-like peptide-1 receptor agonist; HDL, high-density lipoprotein; LDL, low-density lipoprotein; MASLD, metabolic dysfunction-associated steatotic liver disease; MetALD, metabolic dysfunction and alcohol-related steatotic liver disease; OHA, oral hypoglycemic agent; SBP, systolic blood pressure; SD, standard deviation; SGLT, sodium glucose co-transporter; SLD, steatotic liver disease; TZD, thiazolidinedione.

The average body mass index (BMI) was approximately 25. In groups 3 and 4, which consisted primarily of current smokers and individuals with new-onset diabetes, most participants were male, with group 4 having a younger average age than the other groups. The waist circumference (WC), fasting glucose, total cholesterol, and triglyceride (TG) levels increased from group 1 to group 4, whereas high density lipoprotein (HDL) cholesterol levels decreased.

Risk of CVD incidence according to smoking status

Table 2 presents the association between CVD outcomes (composite CVD events, MI, ischemic stroke, and CV mortality) and smoking status, stratified by SLD subtype. Overall, current smoking significantly increased the CVD outcomes across all SLD subtypes. For current smokers, the HRs for composite CVD event, MI, stroke, and CV mortality significantly increased from the no steatosis group to the MASLD, metabolic dysfunction and alcohol-related steatotic liver disease (MetALD), and alcohol-related liver disease (ALD) groups. With the never smoker and no steatosis group as the reference, the current smokers in the ALD group demonstrated the highest HRs: composite CVD event (aHR, 2.14; 95% CI, 2.04–2.24), MI (aHR, 2.14; 95% CI, 1.99–2.30), stroke (aHR, 1.99; 95% CI, 1.86–2.13), and CV mortality (aHR, 2.91; 95% CI, 2.57–3.30). Former smokers generally showed increased aHRs for CVD risk compared to never smokers without steatosis. However, when referenced to never smokers within each SLD subtype, the aHRs for former smokers were reduced or neutral, suggesting the potential benefit of smoking cessation. Additionally, when never smoker status was used as the reference within each SLD group, the effect of smoking on CVD risk was more pronounced in individuals with ALD and no steatosis. Significant interactions were observed between smoking and SLD subtypes for composite CVD events, MI, and stroke (P for interaction < 0.001, 0.028, and < 0.001, respectively), indicating that the effect of smoking on these outcomes differed across SLD groups. In contrast, no significant interaction was observed for CV mortality.

Table 2.

Hazard ratios for CVD risk based on smoking status, stratified by steatotic liver disease group.

SLD group	Smoking	N	Event	Follow-up duration	Incidence rates	Composite		Subgroup
SLD group	Smoking	N	Event	Follow-up duration	Incidence rates	Adjusted		Adjusted
Composite CVD event (myocardial infarction or ischemic stroke or cardiovascular mortality)
No Steatosis	Never	480,981	28,984	2,740,453.6	10.58	1 (Ref.)	1 (Ref.)	1 (Ref.)	1 (Ref.)
	Former	129,939	7841	735,691.4	10.66	1.01 (0.98, 1.03)	0.97 (0.94, 0.99)	1.01 (0.98, 1.03)	0.97 (0.94, 0.99)
	Current	121,060	8530	674,728.4	12.64	1.20 (1.17, 1.23)	1.60 (1.56, 1.64)	1.20 (1.17, 1.23)	1.60 (1.56, 1.64)
MASLD	Never	503,517	31,266	2,863,373.0	10.92	1.03 (1.02, 1.05)	1.20 (1.18, 1.22)	1 (Ref.)	1 (Ref.)
	Former	232,604	12,528	1,327,851.5	9.43	0.89 (0.88, 0.91)	1.12 (1.09, 1.15)	0.86 (0.85, 0.88)	0.93 (0.91, 0.95)
	Current	250,680	14,560	1,418,031.4	10.27	0.97 (0.96, 0.99)	1.80 (1.76, 1.84)	0.94 (0.92, 0.96)	1.50 (1.47, 1.53)
MetALD	Never	21,582	1087	123,356.0	8.81	0.83 (0.79, 0.89)	1.28 (1.20, 1.36)	1 (Ref.)	1 (Ref.)
	Former	40,167	1667	231,288.3	7.21	0.68 (0.65, 0.72)	1.12 (1.06, 1.18)	0.82 (0.76, 0.88)	0.88 (0.81, 0.95)
	Current	57,680	2886	327,093.1	8.82	0.84 (0.81, 0.87)	1.80 (1.73, 1.89)	1.00 (0.94, 1.08)	1.41 (1.32, 1.51)
ALD	Never	21,064	1403	118,593.4	11.83	1.12 (1.06, 1.18)	1.32 (1.25, 1.40)	1 (Ref.)	1 (Ref.)
	Former	25,857	1396	147,165.5	9.49	0.90 (0.85, 0.95)	1.26 (1.19, 1.34)	0.80 (0.74, 0.86)	0.95 (0.89, 1.03)
	Current	36,179	2459	200,658.6	12.25	1.16 (1.12, 1.21)	2.14 (2.04, 2.24)	1.04 (0.97, 1.11)	1.61 (1.51, 1.73)
p-value						< 0.001	< 0.001	–	–
p for interaction						–	–	< 0.001	< 0.001
Myocardial infarction
No steatosis	Never	480,981	12,464	2,772,805.6	4.50	1 (Ref.)	1 (Ref.)	1 (Ref.)	1 (Ref.)
	Former	129,939	3430	743,875.8	4.61	1.03 (0.99, 1.07)	1.01 (0.97, 1.05)	1.03 (0.99, 1.07)	1.01 (0.97, 1.05)
	Current	121,060	3715	684,625.8	5.43	1.21 (1.17, 1.26)	1.56 (1.50, 1.63)	1.21 (1.17, 1.26)	1.56 (1.50, 1.63)
MASLD	Never	503,517	13,895	2,900,464.6	4.79	1.07 (1.04, 1.09)	1.19 (1.15, 1.22)	1 (Ref.)	1 (Ref.)
	Former	232,604	5775	1,341,912.7	4.30	0.96 (0.93, 0.99)	1.16 (1.11, 1.20)	0.90 (0.87, 0.93)	0.98 (0.94, 1.01)
	Current	250,680	7061	1,434,657.1	4.92	1.10 (1.07, 1.13)	1.81 (1.74, 1.88)	1.03 (1.00, 1.06)	1.53 (1.48, 1.58)
MetALD	Never	21,582	481	124,699.4	3.86	0.86 (0.79, 0.94)	1.37 (1.25, 1.51)	1 (Ref.)	1 (Ref.)
	Former	40,167	727	233,310.4	3.12	0.70 (0.65, 0.75)	1.17 (1.08, 1.27)	0.81 (0.72, 0.91)	0.85 (0.76, 0.95)
	Current	57,680	1315	330,520.6	3.98	0.89 (0.84, 0.94)	1.84 (1.72, 1.97)	1.03 (0.93, 1.15)	1.34 (1.21, 1.49)
ALD	Never	21,064	573	120,329.7	4.76	1.06 (0.98, 1.15)	1.26 (1.16, 1.37)	1 (Ref.)	1 (Ref.)
	Former	25,857	601	148,836.8	4.04	0.90 (0.83, 0.98)	1.30 (1.19, 1.42)	0.85 (0.76, 0.95)	1.03 (0.92, 1.15)
	Current	36,179	1085	203,452.6	5.33	1.19 (1.12, 1.27)	2.14 (1.99, 2.30)	1.12 (1.02, 1.24)	1.70 (1.53, 1.88)
p-value						< 0.001	< 0.001	–	–
p for interaction						–	–	< 0.001	0.028
Ischemic stroke
No steatosis	Never	480,981	14,825	2,766,634.4	5.36	1 (Ref.)	1 (Ref.)	1 (Ref.)	1 (Ref.)
	Former	129,939	3948	742,712.3	5.32	0.99 (0.96, 1.03)	0.94 (0.91, 0.98)	0.99 (0.96, 1.03)	0.94 (0.91, 0.98)
	Current	121,060	4417	682,800.3	6.47	1.21 (1.17, 1.25)	1.63 (1.57, 1.69)	1.21 (1.17, 1.25)	1.63 (1.57, 1.69)
MASLD	Never	503,517	16,234	2,894,419.1	5.61	1.05 (1.03, 1.07)	1.23 (1.20, 1.26)	1 (Ref.)	1 (Ref.)
	Former	232,604	6271	1,341,052.4	4.68	0.87 (0.85, 0.90)	1.11 (1.07, 1.15)	0.83 (0.81, 0.86)	0.90 (0.87, 0.93)
	Current	250,680	6995	1,434,892.1	4.87	0.91 (0.89, 0.94)	1.76 (1.70, 1.82)	0.87 (0.85, 0.90)	1.43 (1.38, 1.47)
MetALD	Never	21,582	571	124,432.6	4.59	0.86 (0.79, 0.93)	1.24 (1.14, 1.36)	1 (Ref.)	1 (Ref.)
	Former	40,167	894	232,894.9	3.84	0.72 (0.67, 0.77)	1.13 (1.05, 1.21)	0.84 (0.75, 0.93)	0.91 (0.82, 1.01)
	Current	57,680	1485	330,141.7	4.50	0.84 (0.80, 0.89)	1.78 (1.67, 1.89)	0.98 (0.89, 1.08)	1.43 (1.30, 1.58)
ALD	Never	21,064	773	119,858.2	6.45	1.21 (1.12, 1.30)	1.38 (1.28, 1.49)	1 (Ref.)	1 (Ref.)
	Former	25,857	715	148,482.2	4.82	0.90 (0.83, 0.97)	1.20 (1.11, 1.31)	0.75 (0.67, 0.83)	0.87 (0.79, 0.97)
	Current	36,179	1220	203,178.9	6.00	1.12 (1.06, 1.19)	1.99 (1.86, 2.13)	0.93 (0.85, 1.02)	1.44 (1.31, 1.58)
p-value						< 0.001	< 0.001	–	–
p for interaction						–	–	< 0.001	< 0.001
Cardiovascular mortality
No steatosis	Never	480,981	5164	2,801,538.0	1.84	1 (Ref.)	1 (Ref.)	1 (Ref.)	1 (Ref.)
	Former	129,939	1386	751,520.4	1.84	1.00 (0.94, 1.06)	0.94 (0.88, 1.00)	1.00 (0.94, 1.06)	0.94 (0.88, 1.00)
	Current	121,060	1415	693,440.9	2.04	1.12 (1.05, 1.18)	1.78 (1.67, 1.90)	1.12 (1.05, 1.18)	1.78 (1.67, 1.90)
MASLD	Never	503,517	4583	2,934,332.4	1.56	0.85 (0.82, 0.88)	1.20 (1.14, 1.25)	1 (Ref.)	1 (Ref.)
	Former	232,604	1679	1,356,071.3	1.24	0.67 (0.64, 0.71)	1.05 (0.98, 1.12)	0.79 (0.75, 0.84)	0.87 (0.82, 0.93)
	Current	250,680	1855	1,452,795.0	1.28	0.70 (0.66, 0.74)	2.08 (1.95, 2.22)	0.82 (0.78, 0.87)	1.74 (1.64, 1.85)
MetALD	Never	21,582	141	125,890.9	1.12	0.61 (0.52, 0.72)	1.26 (1.05, 1.50)	1 (Ref.)	1 (Ref.)
	Former	40,167	192	235,026.7	0.82	0.44 (0.39, 0.51)	1.10 (0.94, 1.29)	0.73 (0.59, 0.91)	0.88 (0.70, 1.09)
	Current	57,680	343	333,850.2	1.03	0.56 (0.50, 0.63)	2.19 (1.94, 2.48)	0.92 (0.76, 1.12)	1.74 (1.43, 2.12)
ALD	Never	21,064	212	121,716.7	1.74	0.95 (0.83, 1.09)	1.42 (1.23, 1.64)	1 (Ref.)	1 (Ref.)
	Former	25,857	200	150,265.5	1.33	0.72 (0.63, 0.83)	1.44 (1.24, 1.68)	0.76 (0.63, 0.93)	1.02 (0.84, 1.24)
	Current	36,179	349	206,132.2	1.69	0.93 (0.83, 1.03)	2.91 (2.57, 3.30)	0.98 (0.83, 1.16)	2.05 (1.73, 2.44)
p-value						< 0.001	< 0.001	–	–
p for interaction						–	–	< 0.001	0.433

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The results were obtained using Cox proportional hazards analysis and presented as HR with 95% CI. The follow-up duration is presented as person-years.

Incidence rates are presented per 1000 person-years.

Adjusted model: Adjusted for age, sex, income, regular physical activity, CCI score, fasting glucose level, DM duration, insulin use, OHA use, CKD, BMI, alcohol consumption, HTN, and dyslipidemia.

ALD, alcohol-related liver disease; BMI, body mass index; CCI, Charlson Comorbidity Index; CI, confidence interval; CKD, chronic kidney disease; CVD, cardiovascular disease; DM, diabetes mellitus; HR, hazard ratio; HTN, hypertension; MASLD, metabolic dysfunction-associated steatotic liver disease; MetALD, metabolic dysfunction and alcohol-related steatotic liver disease; OHA, oral hypoglycemic agent; SLD, steatotic liver disease.

Risk of CVD incidence according to regular PA and intensity

Table 3 presents the associations between regular PA and CVD outcomes stratified by the SLD subtype. As shown in Table 3, compared to the no steatosis group without regular PA (reference group), the ALD group without regular PA had the highest risk of composite CVD event (aHR, 1.33; 95% CI, 1.28–1.38), MI (aHR, 1.32; 95% CI, 1.24–1.39), stroke (aHR, 1.29; 95% CI, 1.23–1.36), and CV mortality (aHR, 1.55; 95% CI, 1.41–1.70). Additionally, when irregular PA was used as the reference within each SLD group, overall regular PA was associated with a reduced risk of composite CVD events, MI, ischemic stroke, and CV mortality across all SLD groups. This association was consistent across MI, ischemic stroke, and CV mortality (P for interaction = 0.161, 0.103, and 0.387, respectively). However, we observed an interaction between the PA and SLD subtypes for composite CVD event (P for interaction = 0.005). Furthermore, we stratified patients into three categories according to energy expenditure: <500, 500–1499, ≥1500 metabolic equivalent of task (MET)-minutes/week (Supplementary Table 1). The association between CVD outcomes and intensity of regular PA, measured in MET-minutes per week, is shown in Supplementary Table 1. Across all SLD groups, higher PA levels were significantly associated with reduced risks of composite CVD events, MI, ischemic stroke, and CV mortality. When <500 MET-min/week was used as the reference within each SLD group, increased PA intensity (500–1499 and ≥1500 MET-min/week) consistently reduced the CVD risk in a dose-dependent manner. Notably, the highest PA group (≥1500 MET-min/week) showed the highest risk reduction for composite CVD events evidenced by aHRs of 0.84 (95% CI, 0.81–0.87), 0.84 (95% CI, 0.76–0.94), and 0.79 (95% CI, 0.70–0.88) in the MASLD, MetALD, and ALD groups, respectively, with the most prominent reduction observed in the ALD group. Significant interactions were observed between PA levels and SLD subtypes with regard to the risk of composite CVD events and CV mortality (P for interaction < 0.001 and 0.048, respectively), suggesting that the protective effect of PA intensity varied across the SLD groups.

Table 3.

Hazard ratios for CVD risk based on regular PA, stratified by steatotic liver disease group.

SLD group	Physical activity	N	Event	Follow-up duration	Incidence rates	Composite		Subgroup
SLD group	Physical activity	N	Event	Follow-up duration	Incidence rates	Adjusted		Adjusted
Composite CVD event (myocardial infarction or ischemic stroke or cardiovascular mortality)
No steatosis	Irregular	551,331	35,961	3,114,269.7	11.55	1 (Ref.)	1 (Ref.)	1 (Ref.)	1 (Ref.)
No steatosis	Regular	180,649	9394	1,036,603.8	9.06	0.78 (0.77, 0.80)	0.82 (0.80, 0.84)	0.78 (0.77, 0.80)	0.82 (0.80, 0.84)
MASLD	Irregular	787,971	47,510	4,472,721.9	10.62	0.92 (0.91, 0.93)	1.16 (1.14, 1.18)	1 (Ref.)	1 (Ref.)
MASLD	Regular	198,830	10,844	1,136,534.0	9.54	0.83 (0.81, 0.84)	1.01 (0.98, 1.03)	0.90 (0.88, 0.92)	0.87 (0.85, 0.89)
MetALD	Irregular	95,149	4559	542,349.4	8.41	0.73 (0.71, 0.75)	1.17 (1.13, 1.21)	1 (Ref.)	1 (Ref.)
MetALD	Regular	24,280	1081	139,387.9	7.76	0.67 (0.63, 0.71)	1.00 (0.94, 1.06)	0.92 (0.86, 0.99)	0.85 (0.80, 0.91)
ALD	Irregular	65,844	4258	368,725.5	11.55	1.00 (0.97, 1.03)	1.33 (1.28, 1.38)	1 (Ref.)	1 (Ref.)
ALD	Regular	17,256	1000	97,692.0	10.24	0.89 (0.83, 0.94)	1.12 (1.05, 1.20)	0.89 (0.83, 0.95)	0.85 (0.79, 0.91)
p-value						< 0.001	< 0.001	–	-
p for interaction						–	–	< 0.001	0.005
Myocardial infarction
No steatosis	Irregular	551,331	15,423	3,154,108.5	4.89	1 (Ref.)	1 (Ref.)	1 (Ref.)	1 (Ref.)
No steatosis	Regular	180,649	4186	1,047,198.7	4.00	0.82 (0.79, 0.85)	0.84 (0.81, 0.87)	0.82 (0.79, 0.85)	0.84 (0.81, 0.87)
MASLD	Irregular	787,971	21,731	4,527,950.5	4.80	0.98 (0.96, 1.00)	1.16 (1.13, 1.19)	1 (Ref.)	1 (Ref.)
MASLD	Regular	198,830	5000	1,149,083.9	4.35	0.89 (0.86, 0.92)	1.03 (0.99, 1.06)	0.91 (0.88, 0.93)	0.89 (0.86, 0.91)
MetALD	Irregular	95,149	2058	547,788.5	3.76	0.77 (0.74, 0.81)	1.21 (1.15, 1.28)	1 (Ref.)	1 (Ref.)
MetALD	Regular	24,280	465	140,741.9	3.30	0.68 (0.62, 0.74)	1.01 (0.91, 1.11)	0.88 (0.80, 0.97)	0.83 (0.75, 0.92)
ALD	Irregular	65,844	1830	373,671.4	4.90	1.00 (0.96, 1.05)	1.32 (1.24, 1.39)	1 (Ref.)	1 (Ref.)
ALD	Regular	17,256	429	98,947.8	4.34	0.89 (0.81, 0.98)	1.12 (1.01, 1.24)	0.88 (0.80, 0.98)	0.85 (0.77, 0.95)
p-value						< 0.001	< 0.001	–	-
p for interaction						–	–	< 0.001	0.161
Ischemic stroke
No steatosis	Irregular	551,331	18,374	3,146,590.7	5.84	1 (Ref.)	1 (Ref.)	1 (Ref.)	1 (Ref.)
No steatosis	Regular	180,649	4816	1,045,556.3	4.61	0.79 (0.76, 0.81)	0.83 (0.81, 0.86)	0.79 (0.76, 0.81)	0.83 (0.81, 0.86)
MASLD	Irregular	787,971	23,992	4,522,191.9	5.31	0.91 (0.89, 0.93)	1.18 (1.15, 1.20)	1 (Ref.)	1 (Ref.)
MASLD	Regular	198,830	5508	1,148,171.8	4.80	0.82 (0.80, 0.85)	1.03 (0.99, 1.06)	0.90 (0.88, 0.93)	0.87 (0.85, 0.90)
MetALD	Irregular	95,149	2355	547,080.2	4.30	0.74 (0.71, 0.77)	1.16 (1.11, 1.22)	1 (Ref.)	1 (Ref.)
MetALD	Regular	24,280	595	140,389.0	4.24	0.73 (0.67, 0.79)	1.05 (0.96, 1.14)	0.98 (0.90, 1.08)	0.90 (0.82, 0.99)
ALD	Irregular	65,844	2180	372,849.1	5.85	1.00 (0.96, 1.05)	1.29 (1.23, 1.36)	1 (Ref.)	1 (Ref.)
ALD	Regular	17,256	528	98,670.2	5.35	0.92 (0.84, 1.00)	1.13 (1.03, 1.24)	0.91 (0.83, 1.01)	0.87 (0.79, 0.96)
p-value						< 0.001	< 0.001	-	–
p for interaction						–	–	< 0.001	0.103
Cardiovascular mortality
No steatosis	Irregular	551,331	6587	3,189,572.6	2.07	1 (Ref.)	1 (Ref.)	1 (Ref.)	1 (Ref.)
No steatosis	Regular	180,649	1378	1,056,926.6	1.30	0.63 (0.60, 0.67)	0.72 (0.68, 0.76)	0.63 (0.60, 0.67)	0.72 (0.68, 0.76)
MASLD	Irregular	787,971	6758	4,581,578.5	1.48	0.72 (0.69, 0.74)	1.16 (1.11, 1.21)	1 (Ref.)	1 (Ref.)
MASLD	Regular	198,830	1359	1,161,620.3	1.17	0.57 (0.54, 0.60)	0.89 (0.84, 0.95)	0.79 (0.75, 0.84)	0.77 (0.73, 0.82)
MetALD	Irregular	95,149	560	552,945.9	1.01	0.49 (0.45, 0.54)	1.22 (1.11, 1.35)	1 (Ref.)	1 (Ref.)
MetALD	Regular	24,280	116	141,821.9	0.82	0.40 (0.33, 0.48)	0.87 (0.72, 1.05)	0.81 (0.66, 0.98)	0.71 (0.58, 0.87)
ALD	Irregular	65,844	633	378,103.8	1.67	0.81 (0.75, 0.88)	1.55 (1.41, 1.70)	1 (Ref.)	1 (Ref.)
ALD	Regular	17,256	128	100,010.7	1.28	0.62 (0.52, 0.74)	1.10 (0.92, 1.32)	0.76 (0.63, 0.92)	0.72 (0.59, 0.86)
p-value						< 0.001	< 0.001	–	-
p for interaction						–	–	< 0.001	0.387

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The results were obtained using Cox proportional hazards analysis and presented as HR with 95% CI. The follow-up duration is presented as person-years.

Incidence rates are presented per 1000 person-years.

Adjusted model: adjusted for age, sex, income, regular physical activity, CCI score, fasting glucose level, DM duration, insulin use, OHA, CKD, BMI, alcohol consumption, HTN, and dyslipidemia.

Risk of CVD incidence according to regular PA and smoking status

We categorized the participants into four subgroups based on smoking status and regular PA to explore the joint impact on CVD outcomes (Table 4). The risk of composite CVD events, MI, stroke, and CV mortality increased in a stepwise manner from group 1 (never or former smokers with regular PA) to group 4 (current smokers without regular PA) and from no steatosis to MASLD, MetALD, and ALD, with the latter (ALD, group 4) showing the highest risk: composite CVD event (aHR, 2.67; 95% CI, 2.53–2.82), MI (aHR, 2.53; 95% CI, 2.34–2.75), stroke (aHR, 2.47; 95% CI, 2.29–2.66), and CV mortality (aHR, 4.36; 95% CI, 3.79–5.01). Furthermore, with group 1 as reference, the aHRs for CVD risk were consistently higher in group 3 (current smokers with regular PA) than in group 2 (never or former smokers without regular PA) across all SLD groups. On assessing the interactions among smoking, regular PA, and the risk of composite CVD events and stroke, significant differences were observed across the SLD groups (P for interaction = 0.002 and < 0.001, respectively).

Table 4.

Hazard ratios for CVD risk based on regular PA and smoking status, stratified by steatotic liver disease group.

SLD group	Group	N	Event	Follow-up duration	Incidence rates	Composite		Subgroup
SLD group	Group	N	Event	Follow-up duration	Incidence rates	Adjusted		Adjusted
Composite CVD event (myocardial infarction or ischemic stroke or cardiovascular mortality)
No steatosis	Group 1	155,140	7735	893,072.6	8.66	1 (Ref.)	1 (Ref.)	1 (Ref.)	1 (Ref.)
	Group 2	455,780	29,090	2,583,072.4	11.26	1.30 (1.27, 1.34)	1.23 (1.20, 1.26)	1.30 (1.27, 1.34)	1.23 (1.20, 1.26)
	Group 3	25,509	1659	143,531.2	11.56	1.34 (1.27, 1.41)	1.71 (1.63, 1.81)	1.34 (1.27, 1.41)	1.71 (1.63, 1.81)
	Group 4	95,551	6871	531,197.3	12.93	1.50 (1.45, 1.55)	1.99 (1.92, 2.05)	1.50 (1.45, 1.55)	1.99 (1.92, 2.05)
MASLD	Group 1	154,380	8286	884,086.8	9.37	1.08 (1.05, 1.12)	1.24 (1.20, 1.28)	1 (Ref.)	1 (Ref.)
	Group 2	581,741	35,508	3,307,137.7	10.74	1.24 (1.21, 1.27)	1.45 (1.41, 1.48)	1.15 (1.12, 1.17)	1.17 (1.14, 1.20)
	Group 3	44,450	2558	252,447.2	10.13	1.17 (1.12, 1.23)	2.01 (1.92, 2.10)	1.08 (1.04, 1.13)	1.62 (1.55, 1.70)
	Group 4	206,230	12,002	1,165,584.3	10.30	1.19 (1.16, 1.23)	2.22 (2.15, 2.29)	1.10 (1.07, 1.13)	1.79 (1.74, 1.85)
MetALD	Group 1	14,686	624	84,786.6	7.36	0.85 (0.79, 0.92)	1.24 (1.14, 1.35)	1 (Ref.)	1 (Ref.)
	Group 2	47,063	2,130	269,857.6	7.89	0.91 (0.87, 0.96)	1.47 (1.40, 1.55)	1.07 (0.98, 1.17)	1.19 (1.09, 1.30)
	Group 3	9594	457	54,601.4	8.37	0.97 (0.88, 1.07)	1.92 (1.75, 2.12)	1.14 (1.01, 1.29)	1.55 (1.37, 1.75)
	Group 4	48,086	2,429	272,491.8	8.91	1.03 (0.99, 1.08)	2.25 (2.15, 2.37)	1.21 (1.11, 1.33)	1.82 (1.66, 1.98)
ALD	Group 1	11,016	595	62,832.2	9.47	1.09 (1.01, 1.19)	1.35 (1.24, 1.47)	1 (Ref.)	1 (Ref.)
	Group 2	35,905	2204	202,926.6	10.86	1.26 (1.20, 1.32)	1.61 (1.54, 1.70)	1.15 (1.05, 1.26)	1.19 (1.09, 1.31)
	Group 3	6240	405	34,859.8	11.62	1.35 (1.22, 1.49)	2.29 (2.07, 2.54)	1.23 (1.08, 1.40)	1.70 (1.50, 1.93)
	Group 4	29,939	2054	165,798.9	12.39	1.44 (1.37, 1.51)	2.67 (2.53, 2.82)	1.31 (1.20, 1.44)	1.97 (1.80, 2.16)
p-value						< 0.001	< 0.001	–	–
p for interaction						–	–	< 0.001	0.002
Myocardial infarction
No steatosis	Group 1	155,140	3,467	901,764.2	3.84	1 (Ref.)	1 (Ref.)	1 (Ref.)	1 (Ref.)
	Group 2	455,780	12,427	2,614,917.2	4.75	1.24 (1.19, 1.29)	1.19 (1.15, 1.24)	1.24 (1.19, 1.29)	1.19 (1.15, 1.24)
	Group 3	25,509	719	145,434.5	4.94	1.29 (1.19, 1.40)	1.60 (1.48, 1.73)	1.29 (1.19, 1.40)	1.60 (1.48, 1.73)
	Group 4	95,551	2996	539,191.4	5.56	1.45 (1.38, 1.52)	1.86 (1.77, 1.95)	1.45 (1.38, 1.52)	1.86 (1.77, 1.95)
MASLD	Group 1	154,380	3781	893,727.7	4.23	1.10 (1.05, 1.15)	1.22 (1.16, 1.28)	1 (Ref.)	1 (Ref.)
	Group 2	581,741	15,889	3,348,649.6	4.74	1.24 (1.19, 1.28)	1.39 (1.34, 1.44)	1.12 (1.08, 1.16)	1.14 (1.10, 1.18)
	Group 3	44,450	1219	255,356.2	4.77	1.25 (1.17, 1.33)	1.93 (1.80, 2.06)	1.13 (1.06, 1.21)	1.58 (1.48, 1.69)
	Group 4	206,230	5842	1,179,300.9	4.95	1.29 (1.24, 1.35)	2.13 (2.03, 2.22)	1.18 (1.13, 1.22)	1.75 (1.67, 1.82)
MetALD	Group 1	14,686	251	85,594.6	2.93	0.77 (0.67, 0.87)	1.16 (1.02, 1.32)	1 (Ref.)	1 (Ref.)
	Group 2	47,063	957	272,415.2	3.51	0.92 (0.85, 0.98)	1.51 (1.40, 1.63)	1.20 (1.04, 1.37)	1.30 (1.13, 1.50)
	Group 3	9594	214	55,147.4	3.88	1.01 (0.88, 1.16)	1.96 (1.70, 2.26)	1.32 (1.10, 1.59)	1.69 (1.41, 2.03)
	Group 4	48,086	1101	275,373.2	4.00	1.05 (0.98, 1.12)	2.17 (2.01, 2.34)	1.36 (1.19, 1.56)	1.87 (1.63, 2.15)
ALD	Group 1	11,016	249	63,569.6	3.92	1.02 (0.90, 1.16)	1.28 (1.13, 1.46)	1 (Ref.)	1 (Ref.)
	Group 2	35,905	925	205,597.0	4.50	1.17 (1.09, 1.26)	1.52 (1.41, 1.64)	1.15 (1.00, 1.32)	1.19 (1.03, 1.36)
	Group 3	6240	180	35,378.3	5.09	1.33 (1.14, 1.54)	2.21 (1.90, 2.58)	1.30 (1.08, 1.58)	1.72 (1.42, 2.09)
	Group 4	29,939	905	168,074.4	5.38	1.41 (1.31, 1.51)	2.53 (2.34, 2.75)	1.38 (1.20, 1.59)	1.98 (1.72, 2.27)
p-value						< 0.001	< 0.001	–	–
p for interaction						–	–	< 0.001	0.237
Ischemic stroke
No steatosis	Group 1	155,140	3961	900,436.8	4.40	1 (Ref.)	1 (Ref.)	1 (Ref.)	1 (Ref.)
	Group 2	455,780	14,812	2,608,910.0	5.68	1.29 (1.25, 1.34)	1.21 (1.17, 1.25)	1.29 (1.25, 1.34)	1.21 (1.17, 1.25)
	Group 3	25,509	855	145,119.6	5.89	1.34 (1.25, 1.45)	1.74 (1.61, 1.87)	1.34 (1.25, 1.45)	1.74 (1.61, 1.87)
	Group 4	95,551	3562	537,680.7	6.62	1.51 (1.45, 1.58)	2.02 (1.93, 2.11)	1.51 (1.45, 1.58)	2.02 (1.93, 2.11)
MASLD	Group 1	154,380	4265	892,801.3	4.78	1.09 (1.04, 1.14)	1.25 (1.20, 1.31)	1 (Ref.)	1 (Ref.)
	Group 2	581,741	18,240	3,342,670.3	5.46	1.24 (1.20, 1.29)	1.46 (1.40, 1.51)	1.14 (1.11, 1.18)	1.16 (1.13, 1.20)
	Group 3	44,450	1243	255,370.5	4.87	1.11 (1.04, 1.18)	1.97 (1.84, 2.10)	1.02 (0.96, 1.09)	1.57 (1.47, 1.67)
	Group 4	206,230	5752	1,179,521.7	4.88	1.11 (1.07, 1.16)	2.16 (2.07, 2.25)	1.02 (0.98, 1.07)	1.72 (1.66, 1.79)
MetALD	Group 1	14,686	358	85,283.8	4.20	0.96 (0.86, 1.06)	1.33 (1.19, 1.48)	1 (Ref.)	1 (Ref.)
	Group 2	47,063	1107	272,043.8	4.07	0.93 (0.87, 0.99)	1.43 (1.33, 1.53)	0.97 (0.86, 1.09)	1.08 (0.96, 1.21)
	Group 3	9594	237	55,105.2	4.30	0.98 (0.86, 1.12)	1.90 (1.66, 2.17)	1.03 (0.87, 1.21)	1.43 (1.22, 1.69)
	Group 4	48,086	1248	275,036.5	4.54	1.04 (0.97, 1.10)	2.22 (2.07, 2.38)	1.08 (0.96, 1.22)	1.67 (1.49, 1.88)
ALD	Group 1	11,016	321	63,423.3	5.06	1.15 (1.03, 1.29)	1.37 (1.22, 1.54)	1 (Ref.)	1 (Ref.)
	Group 2	35,905	1167	204,917.1	5.69	1.30 (1.21, 1.38)	1.60 (1.50, 1.72)	1.13 (1.00, 1.27)	1.17 (1.04, 1.33)
	Group 3	6240	207	35,246.9	5.87	1.34 (1.16, 1.54)	2.21 (1.92, 2.55)	1.16 (0.98, 1.39)	1.62 (1.36, 1.93)
	Group 4	29,939	1013	167,932.0	6.03	1.38 (1.29, 1.48)	2.47 (2.29, 2.66)	1.20 (1.06, 1.36)	1.80 (1.59, 2.05)
p-value						< 0.001	< 0.001	–	–
p for interaction						–	–	< 0.001	< 0.001
Cardiovascular mortality
No steatosis	Group 1	155,140	1108	909,786.7	1.22	1 (Ref.)	1 (Ref.)	1 (Ref.)	1 (Ref.)
	Group 2	455,780	5442	2,643,271.6	2.06	1.69 (1.59, 1.81)	1.45 (1.36, 1.55)	1.69 (1.59, 1.81)	1.45 (1.36, 1.55)
	Group 3	25,509	270	147,139.9	1.83	1.52 (1.33, 1.73)	2.21 (1.93, 2.52)	1.52 (1.33, 1.73)	2.21 (1.93, 2.52)
	Group 4	95,551	1145	546,301.0	2.10	1.74 (1.60, 1.89)	2.57 (2.37, 2.80)	1.74 (1.60, 1.89)	2.57 (2.37, 2.80)
MASLD	Group 1	154,380	1034	903,132.6	1.14	0.94 (0.87, 1.03)	1.25 (1.14, 1.36)	1 (Ref.)	1 (Ref.)
	Group 2	581,741	5228	3,387,271.2	1.54	1.27 (1.19, 1.36)	1.68 (1.57, 1.80)	1.35 (1.26, 1.44)	1.35 (1.26, 1.44)
	Group 3	44,450	325	258,487.7	1.26	1.04 (0.92, 1.18)	2.59 (2.28, 2.94)	1.10 (0.97, 1.25)	2.08 (1.83, 2.36)
	Group 4	206,230	1530	1,194,307.3	1.28	1.06 (0.98, 1.15)	3.01 (2.77, 3.26)	1.13 (1.04, 1.22)	2.42 (2.23, 2.62)
MetALD	Group 1	14,686	67	86,132.5	0.78	0.64 (0.50, 0.82)	1.23 (0.95, 1.58)	1 (Ref.)	1 (Ref.)
	Group 2	47,063	266	274,785.2	0.97	0.80 (0.70, 0.91)	1.75 (1.51, 2.02)	1.25 (0.95, 1.63)	1.42 (1.09, 1.86)
	Group 3	9594	49	55,689.4	0.88	0.73 (0.55, 0.97)	2.35 (1.75, 3.14)	1.14 (0.79, 1.64)	1.91 (1.32, 2.76)
	Group 4	48,086	294	278,160.7	1.06	0.88 (0.77, 1.00)	3.29 (2.86, 3.78)	1.37 (1.05, 1.78)	2.68 (2.05, 3.49)
ALD	Group 1	11,016	77	64,206.5	1.20	0.99 (0.78, 1.24)	1.52 (1.21, 1.93)	1 (Ref.)	1 (Ref.)
	Group 2	35,905	335	207,775.8	1.61	1.33 (1.17, 1.50)	2.13 (1.88, 2.43)	1.35 (1.05, 1.72)	1.40 (1.09, 1.79)
	Group 3	6240	51	35,804.2	1.42	1.18 (0.89, 1.56)	3.13 (2.36, 4.17)	1.19 (0.84, 1.70)	2.06 (1.44, 2.93)
	Group 4	29,939	298	170,328.0	1.75	1.45 (1.28, 1.65)	4.36 (3.79, 5.01)	1.47 (1.14, 1.89)	2.86 (2.22, 3.68)
p-value						< 0.001	< 0.001	–	–
p for interaction						–	–	< 0.001	0.639

Open in a new tab

The results were obtained using Cox proportional hazards analysis and presented as HR with 95% CI. The follow-up duration is presented as person-years.

Incidence rates are presented per 1000 person-years.

Group 1: never smoker or former smoker with regular PA; Group 2: never smoker or former smoker without regular PA; Group 3: current smoker with regular PA; Group 4: current smoker without regular PA.

Adjusted model: adjusted for age, sex, income, regular physical activity, CCI score, fasting glucose level, DM duration, insulin use, OHA, CKD, BMI, alcohol consumption, HTN, and dyslipidemia.

Discussion

This population-based retrospective study investigated the associations among smoking, regular PA, and composite CVD outcomes in patients with T2DM across different SLD categories. Both current smoking and lack of regular PA were independently and significantly associated with an increased CVD risk across all SLD groups. Notably, current smokers without regular PA, particularly those with ALD, exhibited the highest risk.

In a previous study, the combination of T2DM and tobacco use was found to be associated with a higher prevalence of fibrosis (adjusted odds ratio [OR], 3.04; 95% CI, 1.62–5.76) in patients with MASLD than T2DM alone (aOR, 2.28; 95% CI, 1.37–3.85)¹⁴. In one Korean study, smoking was linked to a high risk of NAFLD (OR, 1.38; 95% CI, 1.08–1.76), with the risk decreasing as the smoking cessation duration increased and increasing as the pack years increased, suggesting that smoking cessation can help manage NAFLD¹⁶. Furthermore, a meta-analysis demonstrated a significant association between smoking and NAFLD, with passive smoking increasing the risk approximately 1.38 times, highlighting a public health concern that warrants attention¹⁷. Smoking is associated with an increased risk of CVD in individuals with NAFLD¹⁸. Consistent with these findings, our study suggests that current smoking significantly increases the risks of composite CVD events, MI, stroke, and CV mortality across all SLD subtypes, with the highest risk observed among current smokers in the ALD group. In addition, although former smokers showed a higher CVD risk than never smokers without steatosis, this risk was attenuated or neutral when referenced within each SLD subtype, suggesting the potential benefits of smoking cessation. Therefore, smoking cessation should be emphasized as part of CV risk management, especially for individuals with varying degrees of liver disease and T2DM. According to previous studies, regular PA has been associated with reduced CV mortality and has been shown to improve the fatty liver index (FLI) in patients with MASLD in a randomized controlled trial^19,20. Similarly, in our study, regular PA was associated with a significant reduction in CVD risk across all SLD groups, with increasing benefits observed as the PA intensity increased. Notably, achieving ≥1500 MET-min/week was linked to the lowest risk of composite CVD events and CV mortality, even in high-risk groups such as MASLD and ALD.

In our study, both current smoking and physical inactivity independently increased the risks of composite CVD events, MI, ischemic stroke, and CV mortality across all SLD groups, with the highest risk observed in the ALD group. A recent study suggested that alcohol contributes to an increased risk of significant fibrosis through a dose-dependent supra-additive interaction with cardiometabolic risk factors²¹. Previous studies have shown that patients with advanced liver fibrosis have a high risk of developing CVD^22,23. In a recent Korean cohort study, individuals with ALD exhibited a significantly increased risk of CVD compared to those without SLD (HR, 1.95; 95% CI, 1.01–3.77)²⁴and among those with MASLD, the risk of CVD was markedly higher in participants with DM than in those with prediabetes (HR, 1.69; 95% CI, 1.32–2.15). A recent study reported that individuals with both MASLD and T2DM had significantly high CVD mortality²⁵. Therefore, in individuals with high-risk fibrosis, stringent management of metabolic conditions and adherence to alcohol abstinence should be prioritized to mitigate the elevated CVD risk. Previous studies have shown that exercise reduces liver fat and enzyme levels and improves insulin sensitivity^26–28whereas smoking, through nicotine, contributes to insulin resistance both directly and indirectly by promoting abdominal obesity and impairing cell-mediated immunity^29,30. Recent research has emphasized that the mechanisms underlying MASLD involve lipotoxicity; therefore, the interaction between exercise and smoking could play a significant role in managing the condition^31–34.

A key strength of our nationwide study in an Asian population is its focus on the effects of smoking and regular PA on CVD outcomes in patients with T2DM across different SLD subtypes, which, to our knowledge, has not been previously explored. However, this study had several limitations. First, owing to the lack of biopsy or imaging data in routine health screenings, the FLI was used as a simple, cost-effective tool used for noninvasive diagnosis in clinical settings^35,36. Nonetheless, its limited sensitivity and specificity compared to imaging modalities including ultrasonography and magnetic resonance imaging (MRI) may have led to misclassification of hepatic steatosis, and the findings should be interpreted carefully. Second, self-reported questionnaires may introduce recall bias, and the study design may not fully capture long-term behavioral changes, potentially missing shifts in SLD subtypes over time. Third, the unavailability of glycated hemoglobin (HbA1c) data from the National Health Insurance Service (NHIS) database may have led to an underestimation of T2DM incidence, and the lack of platelet count data limited the calculation of liver fibrosis biomarker scores such as Fibrosis-4 index and aspartate aminotransferase (AST)-to-platelet ratio index. Finally, because the study included only Korean participants, our findings should be applied to the general population with caution, taking genetic and environmental differences into consideration³⁷.

In conclusion, current smoking and physical inactivity significantly increased the risks of composite CVD events, MI, ischemic stroke, and CV mortality in all SLD subtypes among T2DM patients, with the highest risk noted in the ALD group. This result highlights the need for targeted lifestyle changes, particularly smoking cessation, regular exercise, and alcohol abstinence, to reduce the CVD risk in this vulnerable population, where no established therapies for MASLD currently exist.

Methods

Study population and design

We obtained data from the comprehensive Korean NHIS database, which includes the entire Korean population from January 2015 to December 2022. In the NHIS, the National Health Insurance covers approximately 97% of the population, whereas Medical Aid supports the remaining 3% with the lowest income, providing comprehensive health coverage. This government-operated database comprises a claims dataset with patient demographics, health check-up records, diagnoses coded according to the International Classification of Diseases, 10th revision (ICD-10), and prescription details. The health examination dataset included responses to health-related behavior questionnaires, comprehensive medical histories, anthropometric data, and laboratory results. Mortality records from the Korean National Statistical Office including death dates and causes were coded according to the revised 10th International Statistical Classification of Diseases. This study was approved by the Institutional Review Board of Samsung Medical Center (approval no. SMC 2024-03-104), Seoul, Republic of Korea. The requirement for informed consent was waived because all data provided to the researchers were de-identified.

The study included patients with T2DM aged 20 years and older who underwent general health examinations between 2015 and 2016 (N = 2,616,828). The exclusion criteria were age under 20 years (n = 323), missing data (n = 88,559), prior diagnosis of liver cancer before the index date (n = 10,438), history of liver transplantation (n = 946), previous diagnosis of concomitant liver disease (n = 174,667), MI (n = 132,121), stroke (n = 264,506), and individuals who died or were diagnosed with MI or stroke within 1 year of screening (n = 23,958). The final cohort consisted of 1,921,310 individuals (Supplementary Fig. 1).

Measurements and definitions

Height, body weight, and WC were recorded during health examinations. BMI was calculated by dividing the body weight (kg) by the square of height (m²). Chronic kidney disease (CKD) was defined as an estimated glomerular filtration rate (eGFR) ≤ 60 mL/min/1.73 m². T2DM was defined as fasting blood glucose level ≥ 126 mg/dL; the use of specific drugs (oral hypoglycemic agents (OHAs), glucagon-like peptide-1 receptor agonist (GLP-1 RA), and insulin; or at least one claim using codes E11-14. OHAs include metformin, sulfonylureas, thiazolidinediones, dipeptidyl peptidase-4 (DPP-4) inhibitors, meglitinides, alpha-glucosidase inhibitors, and sodium-glucose co-transporter (SGLT)-2 inhibitors. Insulin use was defined as one or more insulin prescriptions per year or three or more prescriptions per year in an outpatient setting. New-onset DM was defined as fasting blood glucose level of 126 mg/dL or higher at the time of health screening, with no prior DM medication prescriptions before the health check-up, and with HbA1c data not provided in the screening records. Hypertension (HTN) was defined by systolic blood pressure (SBP) ≥ 140 mmHg, diastolic blood pressure (DBP) ≥ 90 mmHg, use of antihypertensive medication, or at least one claim with codes I10-13 and I15. Dyslipidemia was defined as at least one claim per year with code E78, at least one claim per year for the prescription of a lipid-lowering agent, or total cholesterol level of ≥ 240 mg/dL. Alcohol abuse/misuse or ALD was defined by ICD-10 codes E24.4, F10, G31.2, G62.1, G72.1, I42.6, K29.2, K70, K86.0, Q35.4, R78.0, T51.0, T51.8, T51.9, X65, Y15, Y57.3, Y90, Y91, Z50.2, and Z71.4. Concomitant liver diseases were also defined using ICD-10 codes, including viral hepatitis (B15–B19), drug-induced (toxic) liver disease (K71), hepatic veno-occlusive disease (I82), liver abscess (K75.0, A06.4), hemochromatosis (E83.1), Wilson’s disease (E83.0), alpha-1 antitrypsin deficiency (E88.0), autoimmune hepatitis (K75.4), primary biliary cholangitis (K74.3, K74.4), other cholangitis (K83), and glycogen storage disease (E74). Liver cancer was defined using codes C22 and V193, and liver transplantation was defined using code Z94.4.

A composite CVD event was defined as hospitalization for MI, diagnosed using ICD-10 codes I21 or I22; hospitalization for ischemic stroke, diagnosed using I63 or I64, accompanied by claims for brain computed tomography (CT) or MRI; or CV mortality, diagnosed using ICD-10 codes I00–99.

The Charlson Comorbidity Index (CCI) comprises 12 conditions. Low income was defined as the lowest quartile of income distribution within the study population. PA was evaluated using a questionnaire and defined according to the following criteria: (i) light-intensity PA (i.e., slow walking) for > 30 min, (ii) moderate-intensity PA (i.e., brisk-pace walking or bicycling leisurely) for > 30 min, and (iii) vigorous-intensity PA (i.e., running or climbing) for > 20 min during a recent week. In this study, participants were classified as engaging in regular PA if they performed vigorous-intensity PA for > 20 min or moderate-intensity PA for > 30 min at least once a week. Conversely, participants were classified as having ‘no regular PA’ if they did not participate in any moderate- or vigorous-intensity PA, irrespective of the duration of light-intensity PA. Energy expenditure (MET-minutes/week) was calculated as: 7.0 × (average daily minutes of vigorous-intensity PA × number of days) + 4.0 × (average daily minutes of moderate-intensity PA × number of days) + 2.7 × (average daily minutes of light-intensity PA × number of days). Since the exact duration of activity in minutes was not available from the questionnaire, we assumed 20 min for vigorous-intensity PA and 30 min for moderate- and light-intensity PA, based on the response categories in the survey. Based on these calculations, patients were stratified into <500, 500 to <1500, and ≥1500 MET-min/week groups. Smoking status was categorized as never smoked, former smoker, and current smoker. Alcohol consumption was assessed using questionnaires in which participants reported their average frequency (days per week) and amount consumed (in standard glasses). Standard glass was defined as a glass containing 8 g of pure alcohol, and the reported consumption was converted into daily pure alcohol intake (g).

Definition of hepatic steatosis and MASLD

Hepatic steatosis was assessed using the FLI, calculated using the following equation:

(e^{0.953 × loge (TG) + 0.139 × BMI + 0.718 × loge (gamma-glutamyl transferase (GGT)) + 0.053 × WC − 15.745})/(1 + e^{0.953 × loge (TG) + 0.139 × BMI + 0.718 × loge (GGT) + 0.053 × WC − 15.745}).

Participants with hepatic steatosis (FLI ≥ 30)²² were diagnosed with MASLD if they also presented with at least one of the following cardiometabolic risk factors: (1) BMI ≥ 23 kg/m² or WC ≥ 90 cm in men and ≥ 80 cm in women; (2) fasting blood glucose levels ≥ 100 mg/dL or T2DM or specific drug treatment; (3) blood pressure (BP) ≥ 130/85 mmHg or specific drug treatment; (4) TG ≥ 150 mg/dL or specific drug treatment; and (5) HDL cholesterol < 40 mg/dL for men and < 50 mg/dL for women or specific drug treatment.

We classified the participants into four groups: (1) no steatosis (FLI < 30); (2) MASLD, defined as FLI ≥ 30 with alcohol consumption < 30 g/d for men and < 20 g/d for women and at least one cardiometabolic risk factor; (3) MetALD, characterized by alcohol consumption (≥ 30 g/d but < 60 g/d for men and ≥ 20 g/d but < 50 g/d for women) with FLI ≥ 30 and at least one cardiometabolic risk factor; and (4) ALD, defined as FLI ≥ 30 and at least one cardiometabolic risk factor with alcohol consumption (≥ 60 g/d for men and ≥ 50 g/d for women) or any ICD code related to ALD.

Outcomes

The primary outcome was the occurrence of a composite CVD event—MI, ischemic stroke, and CV mortality. The participants were monitored from the initial health examination until the incidence of one of these primary outcomes. The baseline period was defined as the period between 2015 and 2016, and the date of the last examination was used as the reference point. The study cohort was followed from baseline until death or December 31, 2022, whichever was earlier.

Statistical analysis

Continuous variables are presented as mean ± standard deviation (SD), and categorical variables as counts and percentages (%). One-way ANOVA was used to compare continuous variables, and the chi-squared test was used for categorical variables. The incidence rates were calculated by dividing the number of incident cases by the total follow-up duration (person-years). We evaluated the risks of incident composite CVD events (MI, ischemic stroke, and CV mortality) by incorporating a 1-year lag period in our analysis.

We used Cox proportional hazards models to assess the HRs and 95% CIs for incidence. The final model was adjusted for age, sex, income, regular PA, CCI score, fasting glucose levels, DM duration, insulin use, OHA use, CKD, BMI, alcohol consumption, HTN, and dyslipidemia. Covariates were selected based on clinical relevance and evidence from previous studies in T2DM populations^38,39. Statistical significance was defined as P < 0.05, and all analyses were conducted using the SAS software, version 9.3 (SAS Institute, Cary, NC, USA).

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary Material 1.^{(41.2KB, docx)}

Abbreviations

ALD: Alcohol-related liver disease
AST: Aspartate aminotransferase
BMI: Body mass index
BP: Blood pressure
CCI: Charlson Comorbidity Index
CI: Confidence interval
CKD: Chronic kidney disease
CT: Computed tomography
CV: Cardiovascular
CVD: Cardiovascular disease
DBP: Diastolic blood pressure
DM: Diabetes mellitus
DPP-4: Dipeptidyl peptidase-4
eGFR: Estimated glomerular filtration rate
FLI: Fatty liver index
GGT: Gamma-glutamyl transferase
GLP-1 RA: Glucagon-like peptide-1 receptor agonist
HbA1c: Glycated hemoglobin
HDL: High density lipoprotein
HR: Hazard ratio
HTN: Hypertension
ICD-10: International classification of diseases 10th revision
LDL: Low density lipoprotein
MASLD: Metabolic dysfunction-associated steatotic liver disease
MET: Metabolic equivalent of task
MetALD: Metabolic dysfunction and alcohol-related steatotic liver disease
MI: Myocardial infarction
MRI: Magnetic resonance imaging
NAFLD: Non-alcoholic fatty liver disease
NASH: Non-alcoholic steatohepatitis
NHIS: National health insurance service
OHA: Oral hypoglycemic agent
OR: Odds ratio
PA: Physical activity
SBP: Systolic blood pressure
SD: Standard deviation
SGLT: Sodium glucose co-transporter
SLD: Steatotic liver disease
TG: Triglyceride
TZD: Thiazolidinedione
T2DM: Type 2 diabetes mellitus
WC: Waist circumference

Author contributions

G.K., K.H., and J.H.K. conceived and designed the study. S.H.C. and K.L. collected and analyzed the data. S.H.C. interpreted the results and wrote the manuscript. G.K., K.H., and J.H.K. edited the manuscript and contributed to discussion. All authors contributed to the discussion and reviewed the manuscript.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Data availability

The data used in this study are available from the Korean NHIS, but restrictions apply to the availability of these data, which were provided for research purposes during a limited access period. Data are therefore not publicly available. However, data may be available from the authors upon reasonable request and with permission from the NHIS. Please contact the corresponding author for inquiries.

Declarations

Competing interests

The authors declare no competing interests.

Ethical approval and consent to participate

All procedures involving human participants were conducted in accordance with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. The requirement for informed consent was waived because the data were publicly available and de-identified.

Footnotes

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

So Hyun Cho and Gyuri Kim contributed equally to this work.

Contributor Information

Kyungdo Han, Email: hkd@ssu.ac.kr.

Jae Hyeon Kim, Email: jaehyeon@skku.edu.

References

1.Lonardo, A., Ballestri, S., Targher, G. & Loria, P. Diagnosis and management of cardiovascular risk in nonalcoholic fatty liver disease. Expert Rev. Gastroenterol. Hepatol.9, 629–650. 10.1586/17474124.2015.965143 (2015). [DOI] [PubMed] [Google Scholar]
2.Mantovani, A. et al. Non-alcoholic fatty liver disease and risk of fatal and non-fatal cardiovascular events: An updated systematic review and meta-analysis. Lancet Gastroenterol. Hepatol.6, 903–913. 10.1016/s2468-1253(21)00308-3 (2021). [DOI] [PubMed] [Google Scholar]
3.Oh, R. et al. Metabolic dysfunction-associated steatotic liver disease and all-cause and cause-specific mortality. Diabetes Metab. J.10.4093/dmj.2024.0042 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
4.Allen, A. M. et al. Nonalcoholic fatty liver disease incidence and impact on metabolic burden and death: A 20 year-community study. Hepatology67, 1726–1736. 10.1002/hep.29546 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]
5.Targher, G., Day, C. P. & Bonora, E. Risk of cardiovascular disease in patients with nonalcoholic fatty liver disease. N Engl. J. Med.363, 1341–1350. 10.1056/NEJMra0912063 (2010). [DOI] [PubMed] [Google Scholar]
6.Targher, G., Byrne, C. D. & Tilg, H. NAFLD and increased risk of cardiovascular disease: clinical associations, pathophysiological mechanisms and pharmacological implications. Gut69, 1691–1705. 10.1136/gutjnl-2020-320622 (2020). [DOI] [PubMed] [Google Scholar]
7.Driessen, S. et al. Metabolic dysfunction-associated steatotic liver disease and the heart. Hepatology10.1097/hep.0000000000000735 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
8.Mantovani, A. et al. Non-alcoholic fatty liver disease and risk of incident diabetes mellitus: an updated meta-analysis of 501 022 adult individuals. Gut70, 962–969. 10.1136/gutjnl-2020-322572 (2021). [DOI] [PubMed] [Google Scholar]
9.Zhou, Y. Y. et al. Synergistic increase in cardiovascular risk in diabetes mellitus with nonalcoholic fatty liver disease: A meta-analysis. Eur. J. Gastroenterol. Hepatol.30, 631–636. 10.1097/meg.0000000000001075 (2018). [DOI] [PubMed] [Google Scholar]
10.Liu, C., Wu, Y., Duan, W. & Xu, W. Cigarette smoking increases the risk of type 2 diabetes mellitus in patients with non-alcoholic fatty liver disease: A population-based cohort study. Exp. Clin. Endocrinol. Diabetes. 130, 793–800. 10.1055/a-1813-7435 (2022). [DOI] [PubMed] [Google Scholar]
11.Jeong, S. M. et al. Smoking behavior change and risk of cardiovascular disease incidence and mortality in patients with type 2 diabetes mellitus. Cardiovasc. Diabetol.22, 193. 10.1186/s12933-023-01930-4 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
12.Deshpande, K., Olynyk, J., Ayonrinde, O. & Nosaka, K. Barriers to exercise in patients with metabolic dysfunction-associated steatotic liver disease: A patient survey. J. Clin. Med. Res.16, 94–105. 10.14740/jocmr5113 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
13.Cuthbertson, D. J. et al. Exercise improves surrogate measures of liver histological response in metabolic dysfunction-associated steatotic liver disease. Liver Int.44, 2368–2381. 10.1111/liv.15947 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
14.Balogun, O. et al. Effect of combined tobacco use and type 2 diabetes mellitus on prevalent fibrosis in patients with MASLD. Hepatol. Commun.710.1097/hc9.0000000000000300 (2023). [DOI] [PMC free article] [PubMed]
15.Younossi, Z. M. et al. The global epidemiology of nonalcoholic fatty liver disease and nonalcoholic steatohepatitis among patients with type 2 diabetes. Clin. Gastroenterol. Hepatol.10.1016/j.cgh.2024.03.006 (2024). [DOI] [PubMed] [Google Scholar]
16.Jang, Y. S., Joo, H. J., Park, Y. S., Park, E. C. & Jang, S. I. Association between smoking cessation and non-alcoholic fatty liver disease using NAFLD liver fat score. Front. Public. Health. 11, 1015919. 10.3389/fpubh.2023.1015919 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
17.Akhavan Rezayat, A. et al. Association between smoking and non-alcoholic fatty liver disease: A systematic review and meta-analysis. SAGE Open. Med.6, 2050312117745223. 10.1177/2050312117745223 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]
18.Åberg, F. & Färkkilä, M. Drinking and obesity: alcoholic liver disease/nonalcoholic fatty liver disease interactions. Semin Liver Dis.40, 154–162. 10.1055/s-0040-1701443 (2020). [DOI] [PubMed] [Google Scholar]
19.Kim, D., Wijarnpreecha, K., Dennis, B. B., Cholankeril, G. & Ahmed, A. Types of physical activity in nonalcoholic fatty liver disease and All-Cause and cardiovascular mortality. J. Clin. Med.1210.3390/jcm12051923 (2023). [DOI] [PMC free article] [PubMed]
20.Couret, A. et al. Effect of different modalities of exercise on fatty liver index in patients with metabolic syndrome: The RESOLVE randomized trial. Clin. Res. Hepatol. Gastroenterol.48, 102461. 10.1016/j.clinre.2024.102461 (2024). [DOI] [PubMed] [Google Scholar]
21.Marti-Aguado, D. et al. Low-to-moderate alcohol consumption is associated with increased fibrosis in individuals with metabolic dysfunction-associated steatotic liver disease. J. Hepatol.81, 930–940. 10.1016/j.jhep.2024.06.036 (2024). [DOI] [PubMed] [Google Scholar]
22.Lee, H. H. et al. Metabolic dysfunction-associated steatotic liver disease and risk of cardiovascular disease. Gut73, 533–540. 10.1136/gutjnl-2023-331003 (2024). [DOI] [PubMed] [Google Scholar]
23.Vilar-Gomez, E. et al. Fibrosis severity as a determinant of cause-specific mortality in patients with advanced nonalcoholic fatty liver disease: A multi-national cohort study. Gastroenterology155, 443–457e417. 10.1053/j.gastro.2018.04.034 (2018). [DOI] [PubMed] [Google Scholar]
24.Choe, H. J., Moon, J. H., Kim, W., Koo, B. K. & Cho, N. H. Steatotic liver disease predicts cardiovascular disease and advanced liver fibrosis: A community-dwelling cohort study with 20-year follow-up. Metabolism153, 155800. 10.1016/j.metabol.2024.155800 (2024). [DOI] [PubMed] [Google Scholar]
25.Riley, D. R. et al. The synergistic impact of type 2 diabetes and MASLD on cardiovascular, liver, diabetes-related and cancer outcomes. Liver Int.44, 2538–2550. 10.1111/liv.16016 (2024). [DOI] [PubMed] [Google Scholar]
26.Smart, N. A., King, N., McFarlane, J. R., Graham, P. L. & Dieberg, G. Effect of exercise training on liver function in adults who are overweight or exhibit fatty liver disease: A systematic review and meta-analysis. Br. J. Sports Med.52, 834–843. 10.1136/bjsports-2016-096197 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]
27.Zou, T. T. et al. Lifestyle interventions for patients with nonalcoholic fatty liver disease: A network meta-analysis. Eur. J. Gastroenterol. Hepatol.30, 747–755. 10.1097/meg.0000000000001135 (2018). [DOI] [PubMed] [Google Scholar]
28.Sabag, A. et al. The effect of high-intensity interval training vs moderate-intensity continuous training on liver fat: A systematic review and meta-analysis. J. Clin. Endocrinol. Metab.107, 862–881. 10.1210/clinem/dgab795 (2022). [DOI] [PubMed] [Google Scholar]
29.Artese, A., Stamford, B. A. & Moffatt, R. J. Cigarette smoking: an accessory to the development of insulin resistance. Am. J. Lifestyle Med.13, 602–605. 10.1177/1559827617726516 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]
30.Moszczyński, P. et al. Immunological findings in cigarette smokers. Toxicol. Lett.118, 121–127. 10.1016/s0378-4274(00)00270-8 (2001). [DOI] [PubMed] [Google Scholar]
31.Hejazi, K. & Hackett, D. Effect of exercise on liver function and insulin resistance markers in patients with non-alcoholic fatty liver disease: A systematic review and meta-analysis of randomized controlled trials. J. Clin. Med.12. 10.3390/jcm12083011 (2023). [DOI] [PMC free article] [PubMed]
32.Li, Y. et al. Updated mechanisms of MASLD pathogenesis. Lipids Health Dis.23, 117. 10.1186/s12944-024-02108-x (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
33.Gastaldelli, A., Folli, F. & Maffei, S. Impact of tobacco smoking on lipid metabolism, body weight and cardiometabolic risk. Curr. Pharm. Des.16, 2526–2530. 10.2174/138161210792062858 (2010). [DOI] [PubMed] [Google Scholar]
34.Lee, Y. et al. The effects of PPAR agonists on atherosclerosis and nonalcoholic fatty liver disease in ApoE-/-FXR-/- mice. Endocrinol. Metab. (Seoul)36, 1243–1253. 10.3803/EnM.2021.1100 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
35.Cho, E. J. et al. Fatty liver index for predicting nonalcoholic fatty liver disease in an asymptomatic Korean population. Diagnostics (Basel)11. 10.3390/diagnostics11122233 (2021). [DOI] [PMC free article] [PubMed]
36.Lee, H., Lee, Y. H., Kim, S. U. & Kim, H. C. Metabolic Dysfunction-Associated fatty liver disease and incident cardiovascular disease risk: A nationwide cohort study. Clin. Gastroenterol. Hepatol.19, 2138–2147e2110. 10.1016/j.cgh.2020.12.022 (2021). [DOI] [PubMed] [Google Scholar]
37.Liu, X. R., Yin, S. C., Chen, Y. T. & Lee, M. H. Metabolic dysfunction-associated steatotic liver disease and its associated health risks. J. Chin. Med. Assoc.88, 343–351. 10.1097/jcma.0000000000001230 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]
38.Moon, J. H., Jeong, S., Jang, H., Koo, B. K. & Kim, W. Metabolic dysfunction-associated steatotic liver disease increases the risk of incident cardiovascular disease: A nationwide cohort study. EClinicalMedicine65, 102292. 10.1016/j.eclinm.2023.102292 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
39.Cho, S. H. et al. Impact of steatotic liver disease categories on atrial fibrillation in type 2 diabetes: A nationwide study. Sci. Rep.15, 11430. 10.1038/s41598-025-94783-8 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Material 1.^{(41.2KB, docx)}

Data Availability Statement

[CR1] 1.Lonardo, A., Ballestri, S., Targher, G. & Loria, P. Diagnosis and management of cardiovascular risk in nonalcoholic fatty liver disease. Expert Rev. Gastroenterol. Hepatol.9, 629–650. 10.1586/17474124.2015.965143 (2015). [DOI] [PubMed] [Google Scholar]

[CR2] 2.Mantovani, A. et al. Non-alcoholic fatty liver disease and risk of fatal and non-fatal cardiovascular events: An updated systematic review and meta-analysis. Lancet Gastroenterol. Hepatol.6, 903–913. 10.1016/s2468-1253(21)00308-3 (2021). [DOI] [PubMed] [Google Scholar]

[CR3] 3.Oh, R. et al. Metabolic dysfunction-associated steatotic liver disease and all-cause and cause-specific mortality. Diabetes Metab. J.10.4093/dmj.2024.0042 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR4] 4.Allen, A. M. et al. Nonalcoholic fatty liver disease incidence and impact on metabolic burden and death: A 20 year-community study. Hepatology67, 1726–1736. 10.1002/hep.29546 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR5] 5.Targher, G., Day, C. P. & Bonora, E. Risk of cardiovascular disease in patients with nonalcoholic fatty liver disease. N Engl. J. Med.363, 1341–1350. 10.1056/NEJMra0912063 (2010). [DOI] [PubMed] [Google Scholar]

[CR6] 6.Targher, G., Byrne, C. D. & Tilg, H. NAFLD and increased risk of cardiovascular disease: clinical associations, pathophysiological mechanisms and pharmacological implications. Gut69, 1691–1705. 10.1136/gutjnl-2020-320622 (2020). [DOI] [PubMed] [Google Scholar]

[CR7] 7.Driessen, S. et al. Metabolic dysfunction-associated steatotic liver disease and the heart. Hepatology10.1097/hep.0000000000000735 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR8] 8.Mantovani, A. et al. Non-alcoholic fatty liver disease and risk of incident diabetes mellitus: an updated meta-analysis of 501 022 adult individuals. Gut70, 962–969. 10.1136/gutjnl-2020-322572 (2021). [DOI] [PubMed] [Google Scholar]

[CR9] 9.Zhou, Y. Y. et al. Synergistic increase in cardiovascular risk in diabetes mellitus with nonalcoholic fatty liver disease: A meta-analysis. Eur. J. Gastroenterol. Hepatol.30, 631–636. 10.1097/meg.0000000000001075 (2018). [DOI] [PubMed] [Google Scholar]

[CR10] 10.Liu, C., Wu, Y., Duan, W. & Xu, W. Cigarette smoking increases the risk of type 2 diabetes mellitus in patients with non-alcoholic fatty liver disease: A population-based cohort study. Exp. Clin. Endocrinol. Diabetes. 130, 793–800. 10.1055/a-1813-7435 (2022). [DOI] [PubMed] [Google Scholar]

[CR11] 11.Jeong, S. M. et al. Smoking behavior change and risk of cardiovascular disease incidence and mortality in patients with type 2 diabetes mellitus. Cardiovasc. Diabetol.22, 193. 10.1186/s12933-023-01930-4 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR12] 12.Deshpande, K., Olynyk, J., Ayonrinde, O. & Nosaka, K. Barriers to exercise in patients with metabolic dysfunction-associated steatotic liver disease: A patient survey. J. Clin. Med. Res.16, 94–105. 10.14740/jocmr5113 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR13] 13.Cuthbertson, D. J. et al. Exercise improves surrogate measures of liver histological response in metabolic dysfunction-associated steatotic liver disease. Liver Int.44, 2368–2381. 10.1111/liv.15947 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR14] 14.Balogun, O. et al. Effect of combined tobacco use and type 2 diabetes mellitus on prevalent fibrosis in patients with MASLD. Hepatol. Commun.710.1097/hc9.0000000000000300 (2023). [DOI] [PMC free article] [PubMed]

[CR15] 15.Younossi, Z. M. et al. The global epidemiology of nonalcoholic fatty liver disease and nonalcoholic steatohepatitis among patients with type 2 diabetes. Clin. Gastroenterol. Hepatol.10.1016/j.cgh.2024.03.006 (2024). [DOI] [PubMed] [Google Scholar]

[CR16] 16.Jang, Y. S., Joo, H. J., Park, Y. S., Park, E. C. & Jang, S. I. Association between smoking cessation and non-alcoholic fatty liver disease using NAFLD liver fat score. Front. Public. Health. 11, 1015919. 10.3389/fpubh.2023.1015919 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR17] 17.Akhavan Rezayat, A. et al. Association between smoking and non-alcoholic fatty liver disease: A systematic review and meta-analysis. SAGE Open. Med.6, 2050312117745223. 10.1177/2050312117745223 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR18] 18.Åberg, F. & Färkkilä, M. Drinking and obesity: alcoholic liver disease/nonalcoholic fatty liver disease interactions. Semin Liver Dis.40, 154–162. 10.1055/s-0040-1701443 (2020). [DOI] [PubMed] [Google Scholar]

[CR19] 19.Kim, D., Wijarnpreecha, K., Dennis, B. B., Cholankeril, G. & Ahmed, A. Types of physical activity in nonalcoholic fatty liver disease and All-Cause and cardiovascular mortality. J. Clin. Med.1210.3390/jcm12051923 (2023). [DOI] [PMC free article] [PubMed]

[CR20] 20.Couret, A. et al. Effect of different modalities of exercise on fatty liver index in patients with metabolic syndrome: The RESOLVE randomized trial. Clin. Res. Hepatol. Gastroenterol.48, 102461. 10.1016/j.clinre.2024.102461 (2024). [DOI] [PubMed] [Google Scholar]

[CR21] 21.Marti-Aguado, D. et al. Low-to-moderate alcohol consumption is associated with increased fibrosis in individuals with metabolic dysfunction-associated steatotic liver disease. J. Hepatol.81, 930–940. 10.1016/j.jhep.2024.06.036 (2024). [DOI] [PubMed] [Google Scholar]

[CR22] 22.Lee, H. H. et al. Metabolic dysfunction-associated steatotic liver disease and risk of cardiovascular disease. Gut73, 533–540. 10.1136/gutjnl-2023-331003 (2024). [DOI] [PubMed] [Google Scholar]

[CR23] 23.Vilar-Gomez, E. et al. Fibrosis severity as a determinant of cause-specific mortality in patients with advanced nonalcoholic fatty liver disease: A multi-national cohort study. Gastroenterology155, 443–457e417. 10.1053/j.gastro.2018.04.034 (2018). [DOI] [PubMed] [Google Scholar]

[CR24] 24.Choe, H. J., Moon, J. H., Kim, W., Koo, B. K. & Cho, N. H. Steatotic liver disease predicts cardiovascular disease and advanced liver fibrosis: A community-dwelling cohort study with 20-year follow-up. Metabolism153, 155800. 10.1016/j.metabol.2024.155800 (2024). [DOI] [PubMed] [Google Scholar]

[CR25] 25.Riley, D. R. et al. The synergistic impact of type 2 diabetes and MASLD on cardiovascular, liver, diabetes-related and cancer outcomes. Liver Int.44, 2538–2550. 10.1111/liv.16016 (2024). [DOI] [PubMed] [Google Scholar]

[CR26] 26.Smart, N. A., King, N., McFarlane, J. R., Graham, P. L. & Dieberg, G. Effect of exercise training on liver function in adults who are overweight or exhibit fatty liver disease: A systematic review and meta-analysis. Br. J. Sports Med.52, 834–843. 10.1136/bjsports-2016-096197 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR27] 27.Zou, T. T. et al. Lifestyle interventions for patients with nonalcoholic fatty liver disease: A network meta-analysis. Eur. J. Gastroenterol. Hepatol.30, 747–755. 10.1097/meg.0000000000001135 (2018). [DOI] [PubMed] [Google Scholar]

[CR28] 28.Sabag, A. et al. The effect of high-intensity interval training vs moderate-intensity continuous training on liver fat: A systematic review and meta-analysis. J. Clin. Endocrinol. Metab.107, 862–881. 10.1210/clinem/dgab795 (2022). [DOI] [PubMed] [Google Scholar]

[CR29] 29.Artese, A., Stamford, B. A. & Moffatt, R. J. Cigarette smoking: an accessory to the development of insulin resistance. Am. J. Lifestyle Med.13, 602–605. 10.1177/1559827617726516 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR30] 30.Moszczyński, P. et al. Immunological findings in cigarette smokers. Toxicol. Lett.118, 121–127. 10.1016/s0378-4274(00)00270-8 (2001). [DOI] [PubMed] [Google Scholar]

[CR31] 31.Hejazi, K. & Hackett, D. Effect of exercise on liver function and insulin resistance markers in patients with non-alcoholic fatty liver disease: A systematic review and meta-analysis of randomized controlled trials. J. Clin. Med.12. 10.3390/jcm12083011 (2023). [DOI] [PMC free article] [PubMed]

[CR32] 32.Li, Y. et al. Updated mechanisms of MASLD pathogenesis. Lipids Health Dis.23, 117. 10.1186/s12944-024-02108-x (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR33] 33.Gastaldelli, A., Folli, F. & Maffei, S. Impact of tobacco smoking on lipid metabolism, body weight and cardiometabolic risk. Curr. Pharm. Des.16, 2526–2530. 10.2174/138161210792062858 (2010). [DOI] [PubMed] [Google Scholar]

[CR34] 34.Lee, Y. et al. The effects of PPAR agonists on atherosclerosis and nonalcoholic fatty liver disease in ApoE-/-FXR-/- mice. Endocrinol. Metab. (Seoul)36, 1243–1253. 10.3803/EnM.2021.1100 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR35] 35.Cho, E. J. et al. Fatty liver index for predicting nonalcoholic fatty liver disease in an asymptomatic Korean population. Diagnostics (Basel)11. 10.3390/diagnostics11122233 (2021). [DOI] [PMC free article] [PubMed]

[CR36] 36.Lee, H., Lee, Y. H., Kim, S. U. & Kim, H. C. Metabolic Dysfunction-Associated fatty liver disease and incident cardiovascular disease risk: A nationwide cohort study. Clin. Gastroenterol. Hepatol.19, 2138–2147e2110. 10.1016/j.cgh.2020.12.022 (2021). [DOI] [PubMed] [Google Scholar]

[CR37] 37.Liu, X. R., Yin, S. C., Chen, Y. T. & Lee, M. H. Metabolic dysfunction-associated steatotic liver disease and its associated health risks. J. Chin. Med. Assoc.88, 343–351. 10.1097/jcma.0000000000001230 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR38] 38.Moon, J. H., Jeong, S., Jang, H., Koo, B. K. & Kim, W. Metabolic dysfunction-associated steatotic liver disease increases the risk of incident cardiovascular disease: A nationwide cohort study. EClinicalMedicine65, 102292. 10.1016/j.eclinm.2023.102292 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR39] 39.Cho, S. H. et al. Impact of steatotic liver disease categories on atrial fibrillation in type 2 diabetes: A nationwide study. Sci. Rep.15, 11430. 10.1038/s41598-025-94783-8 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

Impact of smoking and physical activity on cardiovascular outcomes in type 2 diabetes across steatotic liver disease categories

So Hyun Cho

Gyuri Kim

Kyu-na Lee

Rosa Oh

Ji Yoon Kim

Myunghwa Jang

You-Bin Lee

Sang-Man Jin

Kyu Yeon Hur

Kyungdo Han

Jae Hyeon Kim

Abstract

Supplementary Information

Introduction

Results

Baseline characteristics

Table 1.

Risk of CVD incidence according to smoking status

Table 2.

Risk of CVD incidence according to regular PA and intensity

Table 3.

Risk of CVD incidence according to regular PA and smoking status

Table 4.

Discussion

Methods

Study population and design

Measurements and definitions

Definition of hepatic steatosis and MASLD

Outcomes

Statistical analysis

Supplementary Information

Abbreviations

Author contributions

Funding

Data availability

Declarations

Competing interests

Ethical approval and consent to participate

Footnotes

Contributor Information

References

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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