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Article

Association Between ‘Weekend Warrior’ and Other Leisure-Time Physical Activity Patterns and Nonalcoholic Fatty Liver Disease: A Cross-Sectional Study Using Data from the Korea National Health and Nutrition Examination Survey (2014–2023)

by
Yun Sung Kim
1,
Seo Yeong An
1,
Justin Y. Jeon
1,2,3 and
Dong Hoon Lee
1,4,*
1
Department of Sport Industry Studies, Yonsei University, Seoul 03722, Republic of Korea
2
Exercise Medicine Center for Diabetes and Cancer Patients, ICONS, Yonsei University, Seoul 03722, Republic of Korea
3
Cancer Prevention Center, Yonsei Cancer Center, Shinchon Severance Hospital, Yonsei University, Seoul 03722, Republic of Korea
4
Department of Nutrition, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA 02115, USA
*
Author to whom correspondence should be addressed.
Appl. Sci. 2025, 15(24), 13172; https://doi.org/10.3390/app152413172
Submission received: 6 October 2025 / Revised: 10 December 2025 / Accepted: 11 December 2025 / Published: 16 December 2025
(This article belongs to the Special Issue Sports Medicine, Exercise, and Health: Latest Advances and Prospects: 2nd Edition)
Browse Figure
Versions Notes

Abstract

Nonalcoholic fatty liver disease (NAFLD) is a major public health concern with a global prevalence of approximately 32%. This study examined the association between the “weekend warrior”, other leisure-time physical activity patterns, and NAFLD in Korean adults. We included 44,264 individuals from the Korea National Health and Nutrition Examination Survey (2014–2023). Physical activity was measured using the Global Physical Activity Questionnaire (GPAQ), a self-reported instrument, and physical activity patterns were classified as inactive, weekend warrior (≥150 min/week of moderate-to-vigorous physical activity [MVPA] performed in 1–2 days), and regularly active. NAFLD was identified using the Hepatic Steatosis Index with a cutoff of >36. Weighted logistic regression was used to examine the association between physical activity patterns and NAFLD. The prevalence of NAFLD was 24%. After adjustment for sociodemographic and metabolic factors, both the weekend warrior (odds ratio [OR] = 0.80, 95% confidence interval [CI]: 0.64–0.99) and regularly active (OR = 0.83, 95% CI: 0.77–0.89) groups had significantly lower odds of NAFLD compared to the inactive group. When stratified by total MVPA level, both the weekend warrior and regularly active patterns with >300 min/week of MVPA showed even lower odds of NAFLD, compared to those with 150–300 min/week of MVPA. Both regularly active and weekend warrior patterns were associated with a lower prevalence of NAFLD, suggesting that the weekend warrior pattern may represent a feasible behavioral pattern associated with lower NAFLD prevalence for individuals with time constraints.

1. Introduction

Nonalcoholic fatty liver disease (NAFLD) has become a significant global health issue, affecting approximately 32% of the worldwide population [1]. NAFLD has been identified as a significant risk factor for several comorbidities, including cardiovascular disease, type 2 diabetes, and osteoporosis [2,3]. According to meta-analyses, individuals with NAFLD have a 64% higher risk of fatal or nonfatal cardiovascular events and more than twice the risk of developing type-2 diabetes than those without NAFLD [4,5]. As the global burden of non-communicable chronic diseases such as cardiovascular diseases, cancer, and diabetes continues to increase, identifying factors related to NAFLD has become increasingly important [6]. Considering the growing burden of these conditions, understanding modifiable factors associated with NAFLD is essential for its prevention and management. Lifestyle modifications, particularly increased physical activity and weight loss have consistently been suggested as some of the most effective strategies for managing NAFLD [7]. To date, no widely approved pharmacological treatment exists for NAFLD; the efficacy of available agents remains uncertain, and pharmacotherapy is generally limited to selected patients with biopsy-proven nonalcoholic steatohepatitis and fibrosis [8].
However, in modern society, participation in physical activity tends to decline due to various barriers, with lack of time being one of the most common reasons [9]. In this context, a physical activity pattern known as the “weekend warrior” has gained attention as a potential alternative approach. The weekend warrior pattern refers to achieving the recommended amount of physical activity through concentrated on one or two days per week, rather than through frequent participation throughout the week [10]. Although growing evidence suggests that the weekend warrior pattern may be associated with favorable health outcomes, including a reduced risk of various chronic diseases [11], to the best of our knowledge, no study has specifically examined its association with NAFLD in Asian populations. Moreover, intermittent high-intensity exercise has been reported to improve insulin sensitivity and enhance lipolysis and fatty acid oxidation, and although direct evidence is limited, similar physiological mechanisms may also partially operate in concentrated exercise patterns [12].
Therefore, this study aimed to examine the association between weekend warrior, other leisure-time physical activity patterns, and NAFLD in Korean adults. By investigating this relationship, we sought to provide evidence for alternative physical activity strategies that may be suitable for individuals facing time constraints, potentially contributing to the effective prevention and management of NAFLD. Although the terminology has recently shifted from NAFLD to metabolic dysfunction-associated steatotic liver disease (MASLD) [13], the Korea National Health and Nutrition Examination Survey (KNHANES) does not include invasive assessment tools required for evaluating MASLD; therefore, we used the term NAFLD in this study. We hypothesized that both the weekend warrior and regularly active patterns would be inversely associated with NAFLD prevalence, independent of boda mass index (BMI) and other metabolic risk factors.

2. Materials and Methods

2.1. Participants

This cross-sectional study analyzed data from the KNHANES conducted between 2014 and 2023 [14]. The KNHANES was implemented in compliance with ethical guidelines, and all participants provided written informed consent. For the 2014–2017 survey cycles, a separate IRB review was not required because these government-operated surveys were exempt under the Bioethics and Safety Act, which permits public-welfare research to forgo additional review. Beginning in 2018, each annual survey protocol received approval from the Institutional Review Board of the Korea Disease Control and Prevention Agency (KDCA) (approval numbers: 2018-01-03-P-A [2018], 2018-01-03-C-A [2019], 2018-01-03-2C-A [2020], 2018-01-03-5C-A [2021], 2018-01-03-4C-A [2022], and 2022-11-16-R-A [2023]). Furthermore, the KDCA provides only de-identified datasets in compliance with the Personal Information Protection Act and the Statistics Act, ensuring that individual participants cannot be personally identified [14]. This study was prepared and presented following the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) recommendations (Supplementary Table S1). The survey provides reliable statistics on health status, health behaviors, and nutritional intake, contributing to the development and evaluation of national health policies.
A total of 62,230 participants of ≥19 years of age were included based on data from the 2014–2023 KNHANES. Individuals with a history of liver cancer, other liver diseases, or high alcohol consumption (defined as consuming seven or more drinks for men and five or more drinks for women on a single occasion at least twice per week, based on KNHANES binge drinking frequency items), and pregnant women were excluded. Other liver diseases were defined based on multiple information items in KNHANES, including self-reported current hepatitis B or C, physician diagnosis, current treatment status, and positivity for viral hepatitis surface antigen. Participants meeting any of these criteria were classified as having viral hepatitis and were excluded. Participants with missing data for NAFLD measurements, physical activity, or liver disease-related variables were excluded (N = 9351). Consequently, 44,264 participants were included in the final analysis. A detailed flowchart of the participant selection process is presented in Supplementary Figure S1.

2.2. Physical Activity Assessment

Physical activity was assessed using the Korean version of the Global Physical Activity Questionnaire (GPAQ), a validated tool that measures physical activity across domains, intensities, frequencies, and durations. The GPAQ has demonstrated moderate validity for assessing moderate-to-vigorous physical activity (MVPA) when compared with accelerometer data, although self-reported measures may overestimate activity levels [15]. In this study, only the leisure-time physical activity domain was analyzed. Following established recommendations for physical activity, we divided participants into two categories: those meeting the guideline of at least 150 min per week of MVPA and those not meeting this threshold. Total MVPA was computed by adding the reported minutes of moderate activity and counting minutes of vigorous activity twice. In accordance with the GPAQ protocol and international physical activity guidelines, only activity bouts lasting at least 10 min were counted toward MVPA. Among those who met the MVPA guideline, physical activity patterns were further categorized according to physical activity frequency: weekend warrior (1–2 days/week) and regularly active (≥3 days/week) group [10,11]. Resistance training was assessed using the GPAQ question asking whether participants engaged in muscle-strengthening activities. Participants reporting ≥2 days per week were classified as meeting the guideline. Because this item measures anaerobic activity not included in MVPA minutes, resistance training was analyzed separately from MVPA.

2.3. NAFLD Assessment

NAFLD was identified as hepatic fat accumulation of at least 5% in the absence of alternative causes of chronic liver disease, including alcohol-related liver conditions or viral hepatitis [16]. Although the diagnostic methods for NAFLD include imaging techniques, liver biopsy, and blood-based indices, the KNHANES dataset provides relevant blood test variables for assessment. NAFLD was identified using the hepatic steatosis index (HSI), calculated as follows:
HSI = 8 × (alanine aminotransferase/aspartate aminotransferase ratio) + BMI (+2 if female; +2 if diabetes mellitus was present) [17].
An HSI score > 36 was used as the cut-off point to indicate the presence of NAFLD, based on its original validation, which reported high diagnostic performance (sensitivity 93.1% for values < 30 and specificity 92.4% for values > 36) [17]. As HSI is a non-invasive surrogate index, some degree of misclassification is possible.

2.4. Covariate Assessment

Information on age, education, marital status, employment status, income, smoking status, and alcohol consumption was assessed using self-reported questionnaires. Age was categorized as 19–44, 45–64, and ≥65 years. Sex was recorded as male or female. Education level was categorized as middle school or below, high school, or college or above. Marital status was grouped as never married, married, or separated/divorced/widowed. Household income was classified as low, mid-low, mid-high, or high. Employment status was defined as employed or unemployed. Smoking status was categorized as non-smoker, former smoker, or current smoker. Alcohol-consumption frequency was grouped as <1 time/month, 1–4 times/month, or ≥2 times/week. Hypertension was defined as an elevated systolic or diastolic blood pressure or the use of antihypertensive medication. Type-2 diabetes was defined based on elevated fasting glucose levels, use of antidiabetic medication or insulin, or a diagnosis by a physician. BMI was calculated from directly measured height and weight and categorized as <23, 23–24.9, and ≥25 kg/m2 based on Asian-Pacific guidelines [18]. To ensure model stability, multicollinearity among covariates was evaluated using variance inflation factors.

2.5. Statistical Analysis

All statistical analyses were performed using SPSS Statistics 29.0.2.0 (IBM Corp., Armonk, NY, USA) and Stata/SE 18.0 (statacorp LLC, College Station, TX, USA). Descriptive statistics were used to compare the sociodemographic and clinical characteristics between participants with and without NAFLD. Categorical variables were compared using chi-squared test. To examine the association between physical activity patterns and NAFLD, weighted logistic regression analyses were conducted to estimate odds ratio (OR) and 95% confidence interval (CI). Three models were applied: model 1 was adjusted for age and sex; model 2 was additionally adjusted for education level, marital status, household income, employment status, smoking status, alcohol-consumption frequency, hypertension and type-2 diabetes; and model 3 further adjusted for BMI. Considering that BMI is a component of the HSI algorithm, Model 2 was designated as the primary etiologic model to avoid structural dependence, while Model 3 was performed as a sensitivity analysis to examine the impact of additional BMI adjustment. Subgroup analyses were conducted within the weekend warrior and regularly active groups to assess whether NAFLD prevalence differed according to physical activity frequency (1, 2, 3–4, and ≥5 days), total MVPA volume (150–300 and >300 min/week), meeting the resistance training guideline (≥2 times/week), and the proportion of vigorous-intensity activity relative to total MVPA (<33%, 33–66%, and >66%). Stratified analyses used the same categorical definitions applied to the covariates described above. Categorizations of MVPA volume and resistance-training adherence were based on current physical activity guidelines [19]. All analyses considered stratification, clustering, and sampling weights to account for the complex survey design of the KNHANES.

3. Results

3.1. Participant Characteristics

A total of 44,264 participants were included in the analysis, of whom 33,531 were classified as non-NAFLD and 10,733 were classified as NAFLD patients. The mean age of the overall sample was 51.9 ± 16.9 years, with a mean age of 51.4 ± 15.9 years and 52.1 ± 17.2 years in the NAFLD and non-NAFLD groups, respectively. The mean BMI was 28.2 ± 3.2 kg/m2 and 22.6 ± 2.5 kg/m2 in the NAFLD and non-NAFLD groups, respectively. The average amount of leisure-time physical activity was 70.1 ± 176.6 min/week and 82.9 ± 194.2 min/week in the NAFLD and non-NAFLD groups, respectively. The prevalence of type-2 diabetes was 26.4% and 8.7%, whereas hypertension was observed in 45.1% and 27.3% of the NAFLD and non-NAFLD groups, respectively (Table 1). Survey-weighted descriptive characteristics are provided separately in Supplementary Table S2.

3.2. Association Between Physical Activity Patterns and NAFLD

Both the weekend warrior and regularly active groups showed an inverse association with NAFLD compared with the inactive group, with similar magnitudes observed between the two active patterns. In the model 2, the weekend warrior group showed 20% lower odds of NAFLD (OR: 0.80, 95% CI: 0.64–0.99), and the regularly active group showed 17% lower odds (OR: 0.83, 95% CI: 0.77–0.89; Table 2). These associations remained consistent even after adjusting for BMI (model 3). Furthermore, in sensitivity analyses excluding participants with a drinking frequency of ≥2 times/week, the ORs for both the weekend warrior and regularly active patterns remained similar to the main results (Supplementary Table S3).

3.3. NAFLD Prevalence According to Specific Physical Activity Patterns

In both the weekend warrior and regularly active groups, higher physical activity frequency and greater total MVPA were associated with lower NAFLD prevalence (Table 3). The weekend warrior group engaging in physical activity twice per week showed 24% lower odds of NAFLD (OR: 0.76, 95% CI: 0.59–0.99), which was the comparable to the 16% reduction observed in the regularly active group with 3–4 days/week (OR: 0.84, 95% CI: 0.74–0.94). In both the weekend warrior and regularly active groups, participants with a total MVPA > 300 min/week demonstrated even lower odds of NAFLD (33% and 19% lower, respectively). When examined according to resistance-training participation, the regularly active group showed a lower prevalence of NAFLD among those who had undergone resistance training. In the weekend warrior group, the odds of prevalent NAFLD were similar regardless of participation in resistance training. Regarding the proportion of vigorous-intensity physical activity, no significant differences were observed in the physical activity intensity in the weekend warrior group. In contrast, the regularly active group showed a clear inverse association, with higher proportions of vigorous-intensity activity being linked to lower NAFLD prevalence.

3.4. Stratified Analyses

Stratified analyses based on relevant covariates indicated that the inverse association between physical activity patterns (weekend warrior and regularly active) and NAFLD remained consistent across the subgroups defined by sex, BMI, alcohol consumption, smoking status, and diabetes. However, variations in the association were observed across age groups (P-interaction < 0.001) and sex (P-interaction < 0.001). For the regularly active group, lower odds of NAFLD were more evident among participants aged ≤64 years. In contrast, the weekend warrior pattern showed lower odds of NAFLD primarily among older adults and among men, while the association was not clearly observed in women. (Figure 1).
Odds ratios (squares) and 95% confidence intervals (horizontal lines) were estimated from the fully adjusted multivariable logistic regression model (Model 2), which included adjustment for age, sex, education level, marital status, household income, employment status, smoking status, alcohol-consumption frequency, hypertension, and type 2 diabetes. The vertical solid line indicates the reference value of 1.0.

4. Discussion

This study evaluated the association of weekend warrior and regularly active physical activity patterns with prevalent NAFLD in a large, population-based sample of Korean adults. Both the weekend warrior and regularly active groups showed significantly lower odds of prevalent NAFLD relative to the inactive group. After adjusting for important confounders, the weekend warrior group showed 20% lower odds of prevalent NAFLD, whereas the regularly active group showed 17% lower odds. Notably, when MVPA was further categorized into 150–300 min/week and >300 min/week, both the weekend warrior and regularly active groups with >300 min/week of MVPA showed an approximately 19–33% lower prevalence of NAFLD. Our findings suggest that achieving a sufficient activity volume, even when concentrated into one or two days per week, may be important for the management of NAFLD.
In line with our results, previous studies have shown that weekend warrior and regularly active patterns showed similar inverse associations with chronic diseases [20]. According to a meta-analysis, the weekend warrior pattern is associated with 17% and 27% lower all-cause and cardiovascular disease mortalities, respectively [11]. However, research exploring the association between weekend warrior and NAFLD. To date, only one study has examined how the weekend warrior pattern relates to the prevalence of MASLD, an updated concept of NAFLD, that incorporates metabolic criteria [21]. In this study of US adults, both the weekend warrior and regularly active groups showed a significantly lower prevalence of MASLD than inactive individuals, with 48% and 37% lower odds, respectively. Moreover, a previous accelerometer-based study found that both the weekend warrior and regularly active exhibited comparable inverse associations with incident NAFLD [22]. They also demonstrated a nonlinear inverse association between MVPA duration and NAFLD, providing additional evidence that longer MVPA duration (≥208 min/week) may offer greater benefits compared to the current recommendation of 150 min/week. Similarly, our study showed that the group with >300 min/week of MVPA had a lower NAFLD prevalence than the 150–300 min/week group. Although existing studies have suggested that the weekend warrior pattern may serve as a viable alternative to regularly active in reducing the risk of NAFLD, only two studies have been conducted to date, both of which were limited to Western populations. Our study strengthens this limited evidence by demonstrating the similar benefits of the weekend warrior pattern in a large Asian population.
In the present study, physical activity patterns were examined in detail. A notable finding was that individuals who engaged in >300 min of MVPA per week, exceeding the recommended threshold of 150 min, showed even lower odds of NAFLD. This finding supports the current physical activity guidelines that suggest that additional health benefits may be gained at higher volumes of activity (>300 min/week of MVPA) [23]. Furthermore, even among those meeting the recommended MVPA level (150 min/week), participation in physical activity twice weekly, rather than once, was associated with a significantly lower prevalence of NAFLD in the weekend warrior group, suggesting that a minimum frequency of two days/week may be important for achieving additional health benefits. Additional analyses were conducted based on adherence to resistance-training guidelines (≥2 days/week) and the proportion of vigorous physical activity. Previous studies have reported that individuals who engage in both aerobic and resistance training [24] or who perform a higher proportion of vigorous-intensity activity [25] tend to show more favorable health outcomes, even when the total MVPA is equivalent. In our findings, the regularly active group demonstrated lower odds of prevalent NAFLD when resistance training was additionally performed or when the proportion of vigorous activity was higher. However, this association was not observed in the weekend warrior group. The results from the regularly active group are consistent with those of previous research, whereas the non-significant findings in the weekend warrior group may be due to the small subgroup size and the resulting insufficient statistical power, rather than the absence of a true association. These findings highlight the need for future research focusing on detailed types and intensities of physical activity within the weekend warrior pattern.
Furthermore, the weekend warrior pattern showed a stronger inverse association with NAFLD among men and older adults compared with women and younger individuals (P-interaction < 0.001; Figure 1). This stronger inverse association in men may be attributed to the higher baseline prevalence and severity of NAFLD generally observed in male populations [26]. Given that men generally lack the protective metabolic effects of estrogen and exhibit higher susceptibility to hepatic steatosis, the inverse association between physical activity and NAFLD may be more clearly observed in men compared with women. Regarding age, the stronger inverse association, particularly in older adults, may be attributed to the physiological characteristics of older adults, such as slower recovery and greater cardiovascular strain, which may make the low-frequency structure of the weekend warrior pattern more feasible for individuals with these characteristics [27]. These findings align with growing evidence suggesting that the health benefits of the weekend warrior pattern may be modified by demographic characteristics. For instance, consistent with our results in older adults, a previous study indicated that the weekend warrior pattern demonstrated a comparable inverse association with hypertension to that of regular activity, especially in participants aged 41–80 years [28]. These observations suggest that the optimal pattern of physical activity may vary depending on individual characteristics such as age and sex. However, evidence regarding the health benefits of the weekend warrior pattern according to specific demographic subgroups remains limited, highlighting the need for further research to explore potential effect modifications. NAFLD develops through multiple pathological pathways and its underlying causes may vary among individuals [29]. It is most commonly associated with insulin resistance and is triggered by states of overnutrition [30]. When overnutrition persists, excess nutrients overwhelm the liver, leading to fat accumulation in the liver and other organs, contributing to liver damage [31,32]. Physical activity mitigates pathological processes by stimulating adiponectin secretion and enhancing insulin sensitivity, which promote anti-inflammatory macrophage polarization in the liver. These responses may mitigate hepatic inflammation and attenuate lipid accumulation [33,34]. Additionally, exercise improves hepatic metabolic function by increasing fatty acid oxidation and autophagy, while suppressing de novo lipogenesis and oxidative stress [35,36]. It also enhances mitochondrial biogenesis and function, further supporting hepatic oxidative metabolism and reducing lipid accumulation in the hepatocytes [33,37]. Although mechanistic evidence specific to weekend warrior patterns is limited, studies of intermittent high-intensity exercise have shown improvements in insulin sensitivity and enhanced fat oxidation, suggesting that similar pathways may partially operate in concentrated activity patterns [12].
This study offers novel insights to inform population-level strategies to promote physical activity in individuals with or at risk of NAFLD. These findings suggest that the weekend warrior pattern may serve as an effective alternative for individuals who face time constraints and are unable to engage in regular weekly physical activity. These results also indicate the importance of considering physical activity patterns, including frequency, total MVPA, resistance-training participation, and physical activity intensity, when developing personalized recommendations for individuals with different NAFLD risk profiles. From a practical public-health perspective, our findings suggest that for individuals adopting a weekend warrior pattern, engaging in at least two days per week and achieving >300 min of MVPA may provide stronger associations with lower NAFLD prevalence. Given the large number of subgroup analyses performed in this study, the possibility of chance findings cannot be fully excluded. Therefore, the subgroup results should be interpreted with caution.
This study has several limitations. First, the cross-sectional design of this study limits the ability to establish causal relationships. Additionally, physical activity levels were assessed using self-reported questionnaires, which may have been subject to recall bias or misclassification. Specifically, occupational and transport physical activities were not included in our analysis. Consequently, some individuals classified as “inactive” during leisure time may engage in high levels of occupational physical activity. This omission likely leads to an underestimation of total physical activity in certain subgroups and may bias the associations toward the null. Moreover, dietary factors including total caloric intake and dietary composition were not controlled for, which may have influenced hepatic fat accumulation. In addition, alternative NAFLD surrogate indices (e.g., the Fatty Liver Index or the NAFLD Liver Fat Score) could not be applied because the variables required to calculate these scores were not consistently available across the 2014–2023 KNHANES cycles. Lastly, NAFLD was identified using the HSI rather than imaging-based diagnosis or liver biopsy, which may limit the diagnostic accuracy. Because BMI is a component of the HSI algorithm, additional adjustment for BMI in the fully adjusted model may introduce partial over-adjustment. For this reason, the associations observed in both the BMI-adjusted (model 3) and non–BMI-adjusted (model 2) should be interpreted in the context of this structural dependence.
Future research should employ longitudinal designs to clarify causal relationships and utilize more precise diagnostic tools to improve the validity and generalizability of the findings. Further studies are needed to explore whether the observed associations differ across subgroups and to determine the optimal physical activity strategies for different populations.

5. Conclusions

Both the weekend warrior and regularly active groups showed lower odds of NAFLD compared with the inactive group, with reductions of 20% and 17%, respectively. These associations remained consistent even after considering physical activity characteristics, such as physical activity frequency, total MVPA volume, and resistance training participation. These findings suggest that engaging in concentrated physical activity may be associated with a lower prevalence of NAFLD, although causality cannot be inferred, and may provide supportive evidence for alternative approaches for individuals who have difficulty engaging in regular physical activity. These results indicate that diverse physical activity patterns should be considered when developing recommendations that reflect varying lifestyle constraints.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/app152413172/s1, Figure S1: Flowchart of participant inclusion and exclusion for the NAFLD analysis using KNHANES 2014–2023; Table S1: STROBE checklist for reporting cross-sectional studies; Table S2: Weighted baseline characteristics of study participants by prevalent nonalcoholic fatty liver disease status; Table S3: Sensitivity analysis of the association between physical activity patterns and NAFLD excluding participants with a drinking frequency of ≥2 times/week.

Author Contributions

Conceptualization, D.H.L.; methodology, Y.S.K. and D.H.L.; investigation, Y.S.K. and S.Y.A.; data curation, Y.S.K. and S.Y.A.; writing—original draft preparation, Y.S.K. and D.H.L.; writing—review and editing, J.Y.J., D.H.L. and S.Y.A.; supervision, D.H.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Yonsei Signature Research Cluster Program of 2021e22-0009 and the Yonsei University Research Fund of 2024-22-0093.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki. The Korea National Health and Nutrition Examination Survey (KNHANES) was conducted in accordance with the principles of the Declaration of Helsinki and approved by the Institutional Review Board (IRB) of the Korea Disease Control and Prevention Agency (KDCA). The KNHANES protocols for 2014–2017 were conducted without separate IRB review in accordance with the Bioethics and Safety Act (Article 2, Paragraph 1) and its Enforcement Rule (Article 2, Paragraph 2, Subparagraph 1), which allow exemptions for government-conducted research performed for public welfare. The protocols for subsequent years were approved by the KDCA IRB (approval numbers: 2018-01-03-P-A [2018], 2018-01-03-C-A [2019], 2018-01-03-2C-A [2020], 2018-01-03-5C-A [2021], 2018-01-03-4C-A [2022], and 2022-11-16-R-A [2023]). The KDCA provides only de-identified data in compliance with the Personal Information Protection Act and the Statistics Act, ensuring that individual participants cannot be personally identified.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study. All participants provided written informed consent prior to participation in the survey.

Data Availability Statement

The data presented in this study are available in the Korea National Health and Nutrition Examination Survey (KNHANES) database at https://knhanes.kdca.go.kr, accessed on 10 December 2025. These data were derived from resources available in the public domain, provided by the Korea Disease Control and Prevention Agency (KDCA).

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
BMIBody mass index
HSIhepatic steatosis index
KNHANESKorea National Health and Nutrition
MASLDmetabolic dysfunction-associated steatotic liver disease
MVPAmoderate-to-vigorous physical activity
NAFLDnonalcoholic fatty liver disease
ORodds ratio

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Applsci 15 13172 g001
Figure 1. Stratified analysis of the association between (A) regular physical activity patterns and (B) weekend warrior with NAFLD.
Figure 1. Stratified analysis of the association between (A) regular physical activity patterns and (B) weekend warrior with NAFLD.
Applsci 15 13172 g001
Table 1. Unweighted baseline characteristics of study participants by prevalent nonalcoholic fatty liver disease status.
Table 1. Unweighted baseline characteristics of study participants by prevalent nonalcoholic fatty liver disease status.
TotalNon-NAFLDNAFLDp Value
Demographic & Anthropometric Indicators
Number of participants44,26433,53110,733
Age <0.001
M ± SD (years)51.9 ± 16.952.1 ± 17.251.4 ± 15.9
19–4415,535 (35.1)11,726 (35.0)3809 (35.5)
45–6416,705 (37.7)12,362 (36.9)4343 (40.5)
≥6512,024 (27.2)9443 (28.2)2581 (24.0)
Sex, n (%) <0.001
Male19,331 (43.7)13,956 (41.6)5375 (50.1)
Female24,933 (56.3)19,575 (58.4)5358 (49.9)
BMI, kg/m2 <0.001
M ± SD 24.0 ± 3.622.6 ± 2.528.2 ± 3.2
<23 18,639 (42.1)18,379 (54.8)260 (2.4)
23–24.9 10,199 (23.0)9050 (27.0)1149 (10.7)
≥25 15,426 (34.8)6102 (18.2)9324 (86.9)
Sociodemographic Indicators
Education, n (%) <0.001
Middle school or below12,840 (29.0)9525 (28.4)3315 (30.9)
High school14,431 (32.6)10,870 (32.4)3561 (33.2)
College or above16,993 (38.4)13,136 (39.2)3857 (35.9)
Household income, n (%) <0.001
Low8148 (18.4)6162 (18.4)1986 (18.5)
Mid-low10,697 (24.2)8019 (23.9)2678 (25.0)
Mid-high12,140 (27.4)9098 (27.1)3042 (28.3)
High13,279 (30.0)10,252 (30.6)3027 (28.2)
Marital status, n (%) 0.007
Never married7934 (17.9)6040 (18.0)1894 (17.6)
Married30,620 (69.2)23,261 (69.4)7359 (68.6)
Divorced or widowed5710 (12.9)4230 (12.6)1480 (13.8)
Lifestyle Indicators
Alcohol intake, n (%) 0.001
<1 time/month22,690 (51.3)17,036 (50.8)5654 (52.7)
1–4 times/month14,894 (33.6)11,350 (33.8)3544 (33.0)
≥2 times/week6680 (15.1)5200 (15.3)1535 (14.3)
Smoking, n (%) <0.001
Non-smoker27,865 (63.0)21,605 (64.4)6260 (58.3)
Ex-smoker9644 (21.8)7194 (21.5)2450 (22.8)
Current-smoker6755 (15.3)4732 (14.1)2023 (18.8)
Type-2 diabetes, n (%) <0.001
Yes5767 (12.9)2934 (8.7)2833 (26.4)
No38,836 (87.1)30,957 (91.3)7879 (73.6)
Hypertension, n (%) <0.001
Yes14,085 (31.6)9253 (27.3)4832 (45.1)
No30,518 (68.4)24,638 (72.7)5880 (54.9)
Physical activity patterns, n (%) <0.001
Inactive36,494 (81.8)27,507 (81.2)8987 (83.9)
Weekend warrior746 (1.7)580 (1.7)166 (1.5)
Regularly active7363 (16.5)5804 (17.1)1559 (14.6)
Total MVPA 0.013
M ± SD (min/week)79.8 ± 190.282.9 ± 194.270.1 ± 176.6
Data are presented as n (%) or mean ± standard deviation (M ± SD). Abbreviations: NAFLD, nonalcoholic fatty liver disease; BMI, body mass index; M ± SD, mean ± standard deviation; PA, physical activity.
Table 2. Association of physical activity patterns with NAFLD.
Table 2. Association of physical activity patterns with NAFLD.
Physical Activity PatternCase/Participants (%) Model 1 aModel 2 bModel 3 c
OR (95% CI)
Inactive8987/36,494 (24.6%)1 [Ref]1 [Ref]1 [Ref]
Weekend warrior167/743 (22.4%)0.69 (0.56–0.85)0.80 (0.64–0.99)0.74 (0.57–0.95)
Regularly active1566/7326 (21.4%)0.75 (0.70–0.81)0.83 (0.77–0.89)0.66 (0.59–0.72)
a Model 1: Adjusted for age and sex. b Model 2: Additionally adjusted for education level, marital status, household income, employment status, smoking status, alcohol-consumption frequency, hypertension, and type 2 diabetes. c Model 3: Further adjusted for body mass index (BMI). Abbreviations: NAFLD, nonalcoholic fatty liver disease; OR, odds ratio; CI, confidence interval.
Table 3. Association of physical activity patterns with NAFLD by frequency, intensity, time (duration) and type of activity.
Table 3. Association of physical activity patterns with NAFLD by frequency, intensity, time (duration) and type of activity.
Inactive (N = 36,394)Weekend Warrior (N = 743)Regularly Active (N = 7326)
OR (95% CI)
Frequency
11 [Ref]0.91 (0.62–1.33)NA
21 [Ref]0.76 (0.59–0.99)NA
3–41 [Ref]NA0.84 (0.74–0.94)
≥51 [Ref]NA0.82 (0.75–0.90)
Intensity a
<33%1 [Ref]0.76 (0.56–1.08)0.83 (0.75–0.92)
33–66%1 [Ref]0.99 (0.40–2.41)0.78 (0.65–0.93)
>66%1 [Ref]0.76 (0.59–0.99)0.76 (0.67–0.85)
Total MVPA
150–300 (min/week)1 [Ref]0.86 (0.67–1.10)0.85 (0.76–0.95)
>300 (min/week)1 [Ref]0.67 (0.45–0.99)0.81 (0.73–0.89)
Resistance training
Yes (≥2 days/week)1 [Ref]0.70 (0.47–1.07)0.72 (0.65–0.80)
No (<2 days/week)1 [Ref]0.82 (0.64–1.05)0.97 (0.88–1.08)
Values represent survey-weighted odds ratios (95% confidence intervals). Group sample sizes (N) are unweighted. Models were adjusted for age, sex, education level, marital status, household income, employment status, smoking status, alcohol-consumption frequency, hypertension, type 2 diabetes, and body mass index. a Proportion of vigorous physical activity out of total moderate-to-vigorous physical activity. Abbreviations: NAFLD, nonalcoholic fatty liver disease; NA, not applicable; MVPA, moderate-to-vigorous physical activity; OR, odds ratio; CI, confidence interval.
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Kim, Y.S.; An, S.Y.; Jeon, J.Y.; Lee, D.H. Association Between ‘Weekend Warrior’ and Other Leisure-Time Physical Activity Patterns and Nonalcoholic Fatty Liver Disease: A Cross-Sectional Study Using Data from the Korea National Health and Nutrition Examination Survey (2014–2023). Appl. Sci. 2025, 15, 13172. https://doi.org/10.3390/app152413172

AMA Style

Kim YS, An SY, Jeon JY, Lee DH. Association Between ‘Weekend Warrior’ and Other Leisure-Time Physical Activity Patterns and Nonalcoholic Fatty Liver Disease: A Cross-Sectional Study Using Data from the Korea National Health and Nutrition Examination Survey (2014–2023). Applied Sciences. 2025; 15(24):13172. https://doi.org/10.3390/app152413172

Chicago/Turabian Style

Kim, Yun Sung, Seo Yeong An, Justin Y. Jeon, and Dong Hoon Lee. 2025. "Association Between ‘Weekend Warrior’ and Other Leisure-Time Physical Activity Patterns and Nonalcoholic Fatty Liver Disease: A Cross-Sectional Study Using Data from the Korea National Health and Nutrition Examination Survey (2014–2023)" Applied Sciences 15, no. 24: 13172. https://doi.org/10.3390/app152413172

APA Style

Kim, Y. S., An, S. Y., Jeon, J. Y., & Lee, D. H. (2025). Association Between ‘Weekend Warrior’ and Other Leisure-Time Physical Activity Patterns and Nonalcoholic Fatty Liver Disease: A Cross-Sectional Study Using Data from the Korea National Health and Nutrition Examination Survey (2014–2023). Applied Sciences, 15(24), 13172. https://doi.org/10.3390/app152413172

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