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. 2021 Jul 23;16(7):e0255118. doi: 10.1371/journal.pone.0255118

Long working hours are associated with a higher risk of non-alcoholic fatty liver disease: A large population-based Korean cohort study

Yesung Lee 1, Eunchan Mun 1, Soyoung Park 1, Woncheol Lee 1,*
Editor: Jee-Fu Huang2
PMCID: PMC8301658  PMID: 34297733

Abstract

Background

Non-alcoholic fatty liver disease (NAFLD), a common chronic liver disease, may progress to fibrosis, cirrhosis, hepatocellular carcinoma, and liver failure. But only a few cross-sectional studies have reported an association of NAFLD with working hours. This cohort study further examined the association between working hours and the development of NAFLD.

Methods

We included 79,048 Korean adults without NAFLD at baseline who underwent a comprehensive health examination and categorized weekly working hours into 35–40, 41–52, 53–60, and >60 hours. NAFLD was defined as the presence of fatty liver, in the absence of excessive alcohol use, as observed by ultrasound.

Results

During a median follow-up of 6.6 years, 15,095 participants developed new-onset NAFLD (incidence rate, 5.55 per 100 person-years). After adjustment for confounders, the hazard ratios (95% confidence interval) for the development of NAFLD in 41–52, 53–60, and >60 working hours compared with that in 35–40 working hours were 1.07 (1.02–1.13), 1.06 (1.00–1.13), and 1.13 (1.05–1.23), respectively. Furthermore, the association remained significant after confounders were treated as time-varying covariates.

Conclusion

In this large-scale cohort, long working hours, especially >60 working hours a week, were independently associated with incident NAFLD. Our findings indicate that long working hours are a risk factor for NAFLD.

Introduction

Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease, and its incidence has increased rapidly, with a global prevalence of 34–46% [1–3]. NAFLD, which ranges from simple benign steatosis to non‐alcoholic steatohepatitis, may progress to fibrosis, cirrhosis, portal hypertension, hepatocellular carcinoma and, liver failure [4]. Given the increasing prevalence and hepatic and extrahepatic complications, it is important to identify modifiable risk factors and develop preventive strategies for NAFLD [5].

Overwork is an emerging issue that not only reduces work efficiency but also threatens the health of workers. According to recent statistics from the Organization for Economic Cooperation and Development, South Korea was one of the countries with the highest annual working hours per worker in 2018 [6]. Studies have demonstrated that long working hours affect general health [7] and probably lead to coronary heart disease [8], stroke [9], obesity [10, 11], hypertension [12], diabetes mellitus (DM) [13], and metabolic syndrome [14, 15], which can cause NAFLD.

Generally, NAFLD is recognized as a hepatic component of metabolic syndrome [16], and NAFLD patients tend to be obese and often have increased risk factors of cardiovascular diseases such as hypertension, DM, and dyslipidemia [17]. These findings suggest that overwork might be associated with the pathogenesis of NAFLD. However, studies regarding the relationship between actual working hours and NAFLD are scarce. A few cross-sectional studies have shown an association of NAFLD with long working hours and shift work [18, 19].

The present cohort study aimed to further examine the direct relationship between long working hours and NAFLD. We evaluated the effects of weekly working hours on the incidence of NAFLD in a large-scale cohort of young and middle-aged individuals who participated in a health screening program.

Materials and methods

Study population

The Kangbuk Samsung Health Study is a cohort study of South Korean adults aged 18 years and older who underwent a comprehensive annual or biennial health examination at Kangbuk Samsung Hospital Total Healthcare Center in Seoul and Suwon, South Korea [20]. More than 80% of participants were employees of various companies and local governmental organizations and their spouses. In South Korea, the Industrial Safety and Health Law requires annual or biennial health screening examinations of all employees, free of charge. Other examinees voluntarily underwent health checkups at the health care center [21].

The present study included a total of 217,654 participants who underwent the comprehensive health examinations from January 1, 2012, to December 31, 2017, and had undergone at least one other screening exam before December 31, 2018 [22]. During this period, the baseline data were collected at the time of the first health examination visit. We excluded 138,606 participants based on the following criteria (Fig 1): missing data on abdominal ultrasound findings or average working hours per week at baseline; presence of fatty liver or liver cirrhosis on ultrasound; history of malignancy; known liver disease or current use of medications for liver disease; alcohol intake of ≥30 g/day for men or ≥20 g/day for women; positive serologic markers for hepatitis B or C virus; use of steatogenic medications within the past year such as valproate, amiodarone, methotrexate, tamoxifen, or corticosteroids; aged >65 years or <19 years; and working <35 hours per week [5]. Some participants met more than one exclusion criterion. Finally, a total of 79,048 participants were eligible for this study at baseline. We followed the 79,048 Korean adults without NAFLD at baseline annually or biennially. This study was approved by the Institutional Review Board of Kangbuk Samsung Hospital, which exempted the requirement for informed consent because we accessed only de-identified data routinely collected as part of health screening examinations (IRB No: KBSMC2020-06-001). All methods were performed in accordance with relevant guidelines and regulations (the Declaration of Helsinki and comparable ethical principles).

Fig 1. Flowchart of study participants.

Fig 1

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Measurements

All examinations were completed at the Kangbuk Samsung Hospital Total Healthcare Center in Seoul and Suwon. Data on demographic characteristics; working hours; smoking status; alcohol consumption; physical activity; education level; medication use; and medical history of hypertension, diabetes, and liver disease were collected by standardized, self-administered questionnaires at each visit [20]. On the day of the health examination, a trained nurse checked the questionnaire for blanks, and during the final stage of the health examination, a trained doctor double-checked whether there were any incorrect or blank marks on the questionnaire while conducting a face-to-face interview with the examinee. Smoking status was categorized as never, former, or current smokers. Alcohol consumption was categorized as ≥10 g/day and <10 g/day. The weekly frequency of moderate- or vigorous-intensity physical activity was also assessed and categorized as <3 or ≥3 times per week, respectively. Education level was categorized as less than college graduate or college graduate or more [23].

Working hours were identified using the following question: “How many hours did you work in a week on average in your job for the past year, including overtime?” According to the International Labour Organization, working >48 hours per week is considered a major job stress, and working >60 hours per week is associated with occurrence of cerebro-cardiovascular diseases [24, 25]. In addition, the Labor Standards Act of Korea states that working hours of adults should not exceed 40 hours per week excluding recess hours (12 additional hours per week are allowed with workers’ permission) and working hours of adolescents should not exceed 35 hours per week (5 additional hours per week are allowed with workers’ permission) [26]. Based on this information, the weekly working hours on average in the past year were categorized as 35–40, 41–52, 53–60, and >60 hours per week.

Blood pressure, height, and weight were measured by trained nurses. Obesity was defined as body mass index (BMI) ≥25 kg/m2. Hypertension was defined as a systolic blood pressure ≥140 mmHg, a diastolic blood pressure ≥90 mmHg, a self-reported history of hypertension, or current use of anti-hypertensive medications. Fasting blood measurements included glucose, total cholesterol, low-density lipoprotein cholesterol (LDL-C), triglycerides, high-density lipoprotein cholesterol (HDL-C), aspartate aminotransferase (AST), alanine aminotransferase (ALT), gamma-glutamyltransferase (GGT), and high-sensitivity C-reactive protein (hsCRP). DM was defined as a fasting serum glucose level of ≥126 mg/dL, a hemoglobin A1c level ≥6.5%, a self-reported history of DM, or current use of anti-diabetic medications. Insulin resistance was assessed with the homeostatic model assessment-insulin resistance (HOMA-IR) equation as follows: fasting insulin (μU/mL) × fasting glucose (mg/dL)/405 [5, 27].

Abdominal ultrasounds were performed using a Logic Q700 MR 3.5-MHz transducer (GE, Milwaukee, WI) by experienced radiologists who were unaware of the study aims. Images were obtained in a standard fashion with patients in the supine position with their right arm raised above their head [28]. An ultrasonographic diagnosis of fatty liver was defined as the presence of a diffuse increase of fine echoes in the liver parenchyma compared with the kidney or spleen parenchyma [29]. The inter- and intra-observer reliability in the diagnosis of fatty liver was very high (kappa statistics of 0.74 and 0.94, respectively) [30]. NAFLD was defined as the presence of fatty liver in the absence of excessive alcohol use (≥20 g/day for women and ≥30 g/day for men) or other identifiable cause, as described in the exclusion criteria [16]. Because we had already excluded participants with excessive alcohol use, as well as other identifiable causes of fatty liver at baseline as described in the exclusion criteria, incident cases of fatty liver were considered NAFLD.

Statistical analysis

The chi-square test and one-way ANOVA were used to compare characteristics of study participants stratified by working hours at baseline. The primary endpoint was the development of incident NAFLD. Participants were followed from the baseline visit to the NAFLD diagnosis visit or to the last available visit before December 31, 2018, whichever came first. Incidence rates were calculated as the number of incident cases divided by person-years of follow-up.

Hazard ratios (HRs) and 95% confidence intervals (CIs) for incident NAFLD were estimated using Cox proportional hazards regression analyses. We initially adjusted for age, sex, center (Seoul and Suwon), and year of screening exam (Model 1). Model 2 was further adjusted for smoking status, alcohol intake, education level, history of diabetes, medication for diabetes, history of hypertension, medication for hypertension and medication for dyslipidemia. To explore the mechanism underlying the observed associations between working hours and NAFLD risk, Model 3 was further adjusted for BMI, hsCRP, and HOMA-IR. We assessed the proportional hazards assumption by examining graphs of estimated log (-log) survival; no violation of the assumption was found. To determine the linear trend of incidence, the number of categories was used as a continuous variable and tested in each model. To evaluate the effects of changes in covariates during follow-up, we conducted additional analyses using covariates as time-varying covariates in the models.

In addition, stratified analyses in predefined subgroups were performed by BMI (<25 versus ≥25 kg/m2), hsCRP (<1.0 versus ≥1.0 mg/L), HOMA-IR (<2.5 versus ≥2.5), and shift work (daytime work versus shift work). Interactions between working hours categories and subgroup characteristics were tested using likelihood ratio tests, which compared models with and without multiplicative interaction terms.

Statistical analyses were performed using STATA version 16.1 (StataCorp LP, College Station, TX). All reported P values were two-tailed. A P value <0.05 was considered statistically significant.

Results

At baseline, the mean (standard deviation) age and BMI of 79,048 participants were 36.3 (7.0) years and 22.2 (2.6) kg/m2, respectively (Table 1). Weekly working hours were positively associated with male sex, current smoking status, alcohol intake, regular exercise, education level, obesity, BMI, systolic and diastolic BP, total cholesterol, LDL-C, triglycerides, AST, ALT, and GGT, whereas they were inversely associated with age, diabetes, and HDL-C.

Table 1. Baseline characteristics of study participants stratified by weekly working hours.

Weekly working hours P-value for trend
Characteristics Overall 35–40 41–52 53–60 >60
Number 79,048 18,558 41,480 13,620 5,390
Age (years)* 36.3 (7.0) 38.1 (7.7) 35.7 (6.8) 35.8 (6.4) 35.8 (6.7) <0.001
Male (%) 58.8 37.9 62.3 71.1 73.0 <0.001
Current smoker (%) 17.5 11.9 17.3 22.3 25.7 <0.001
Alcohol intake (%)a 87.4 82.2 88.2 90.5 90.8 <0.001
Regular exercise (%)b 12.2 13.0 12.3 11.3 11.2 <0.001
High education level (%)c 87.7 82.4 88.5 91.5 89.9 <0.001
Hypertension (%) 5.6 5.9 5.3 5.9 5.6 0.646
Diabetes (%) 1.06 1.37 0.97 0.97 0.89 <0.001
Medication for dyslipidemia (%) 1.23 1.44 1.13 1.20 1.34 0.226
Obesity (%)d 14.5 12.5 14.5 16.2 16.9 <0.001
BMI (kg/m2)* 22.2 (2.6) 21.9 (2.6) 22.3 (2.6) 22.5 (2.6) 22.6 (2.6) <0.001
Systolic BP (mmHg)* 105.4 (11.6) 103.6 (11.9) 105.7 (11.5) 106.5 (11.3) 106.8 (11.2) <0.001
Diastolic BP (mmHg)* 67.9 (9.1) 67.0 (9.3) 68.0 (9.0) 68.6 (8.9) 68.8 (8.7) <0.001
Glucose (mg/dL)* 92.0 (9.8) 91.9 (10.7) 92.0 (9.6) 92.1 (9.8) 92.2 (8.6) 0.055
Total cholesterol (mg/dL)* 188.4 (31.5) 187.6 (32.0) 188.3 (31.4) 189.4 (31.0) 189.7 (31.2) <0.001
LDL-C (mg/dL)* 115.6 (29.5) 113.7 (29.7) 115.7 (29.5) 117.2 (29.3) 117.3 (29.2) <0.001
HDL-C (mg/dL)* 61.1 (14.7) 63.0 (15.0) 60.8 (14.6) 59.8 (14.2) 59.8 (14.2) <0.001
Triglycerides (md/dL)# 79 (59–109) 75 (56–104) 79 (59–109) 81 (60–112) 82 (61–113) <0.001
AST (U/L)# 18 (16–22) 18 (15–21) 18 (16–22) 18 (16–22) 19 (16–22) <0.001
ALT (U/L)# 16 (12–21) 14 (11–19) 16 (12–22) 17 (12–23) 17 (13–23) <0.001
GGT (U/L)# 17 (12–26) 15 (11–23) 18 (13–26) 19 (14–27) 19 (14–28) <0.001
hsCRP (mg/L)# 0.03 (0.02–0.07) 0.03 (0.02–0.07) 0.03 (0.02–0.07) 0.04 (0.02–0.07) 0.04 (0.02–0.07) 0.029
HOMA-IR# 1.08 (0.73–1.52) 1.06 (0.72–1.52) 1.08 (0.74–1.53) 1.07 (0.73–1.51) 1.08 (0.75–1.53) 0.86
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Data are expressed as

*mean (standard deviation)

#median (interquartile range), or percentage.

a≥ 10g/day

b≥ 3 times/week

c≥ College graduate

dBMI ≥ 25kg/m2.

Table 2 shows the relationship between weekly working hours and the incidence of NAFLD. Over 271,968.3 person-years of follow-up (median follow-up, 6.6 years; interquartile range, 4.9–6.9 years), 15,095 participants developed NAFLD (incidence density, 5.55 per 100 person-years). Participants with longer working hours had a higher incidence of NAFLD. Across all models, working >60 hours were associated with a significantly higher risk of incident NAFLD than working 35–40 hours. Especially, in Model 3, multivariable-adjusted HRs (95% CI) of incident NAFLD for working 41–52 hours, 53–60 hours and, >60 hours to compared with working 35–40 hours were 1.07 (1.02–1.13), 1.06 (1.00–1.13), and 1.13 (1.05–1.23), respectively. Even after introducing confounders (alcohol intake, smoking status, regular exercise, BMI, hsCRP, and HOMA-IR) as time-varying covariates, the association between working hours and NAFLD was still observed in the time-dependent model.

Table 2. Development of NAFLD according to weekly working hours.

Weekly working hours Person-years (PY) Incident cases Incidence density (per 102 PY) (95% CI) Multivariable-adjusted HR (95% CI)a HR (95% CI)b in model using time-dependent variables
Model 1* Model 2** Model 3***
35–40 61,646.0 2,691 4.37 (4.20–4.53) 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference)
41–52 143,813.3 8,150 5.67 (5.55–5.79) 1.02 (0.98–1.07) 1.03 (0.98–1.08) 1.07 (1.02–1.13) 1.06 (1.01–1.12)
53–60 47,977.8 3,016 6.29 (6.07–6.51) 1.04 (0.99–1.10) 1.05 (0.99–1.11) 1.06 (1.00–1.13) 1.05 (0.99–1.12)
>60 18,531.2 1,238 6.68 (6.32–7.06) 1.09 (1.02–1.17) 1.09 (1.01–1.17) 1.13 (1.05–1.23) 1.14 (1.06–1.23)
P for trend 0.012 0.013 0.009 0.006
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a Estimated from Cox proportional hazard models.

b Estimated from Cox proportional hazard models with alcohol intake, smoking status, regular exercise, BMI, hsCRP, and HOMA-IR as time-dependent variables and baseline age, sex, center, year of screening exam, education level, weekly working hours, history of diabetes, medication for diabetes, history of hypertension, medication for hypertension, and medication for dyslipidemia as time-fixed variables.

* Model 1 was adjusted for age, sex, center, and year of screening examination.

** Model 2: model 1 plus adjustment for smoking status, alcohol intake, regular exercise, education level, history of diabetes, medication for diabetes, history of hypertension, medication for hypertension, and medication for dyslipidemia.

*** Model 3: model 2 plus adjustment for BMI, hsCRP, and HOMA-IR.

In subgroup analyses (Table 3), the association between working hours and incident NAFLD was consistently observed in those with hsCRP <1.0 mg/L (versus ≥1.0 mg/L) and daytime work (versus shift work). The association was similar across subgroups stratified by BMI (<25 versus ≥25 kg/m2) and HOMA-IR (<2.5 versus ≥2.5). There was no significant interaction with predetermined subgroups.

Table 3. Hazard ratiosa (95% CI) for NAFLD by weekly working hours in clinically relevant subgroups.

Weekly working hours
Subgroups 35–40 41–52 53–60 >60 P for trend P for interaction
BMI 0.423
<25 kg/m2 (n = 67,466) 1.00 (reference) 1.08 (1.01–1.15) 1.06 (0.98–1.14) 1.12 (1.02–1.23) 0.076
≥25 kg/m2 (n = 11,481) 1.00 (reference) 1.08 (0.98–1.19) 1.09 (0.98–1.22) 1.20 (1.04–1.37) 0.021
hsCRP 0.83
<1.0 mg/L (n = 64,779) 1.00 (reference) 1.08 (1.02–1.14) 1.07 (1.00–1.14) 1.14 (1.05–1.23) 0.008
≥1.0 mg/L (n = 667) 1.00 (reference) 0.88 (0.52–1.48) 0.81 (0.45–1.46) 1.11 (0.53–2.33) 0.959
HOMA-IR 0.182
<2.5 (n = 75,028) 1.00 (reference) 1.07 (1.02–1.14) 1.06 (0.99–1.13) 1.12 (1.03–1.21) 0.034
≥2.5 (n = 3,739) 1.00 (reference) 1.09 (0.92–1.29) 1.28 (1.05–1.56) 1.45 (1.12–1.87) 0.001
Shift workb 0.414
Daytime work (n = 71,303) 1.00 (reference) 1.08 (1.02–1.14) 1.07 (1.00–1.14) 1.15 (1.06–1.25) 0.006
Shift work (n = 7,117) 1.00 (reference) 1.09 (0.93–1.28) 1.04 (0.85–1.28) 1.01 (0.78–1.29) 0.971
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a Estimated from Cox proportional hazard models adjusted for age, sex, center, year of screening examination, smoking status, alcohol intake, regular exercise, education level, history of diabetes, medication for diabetes, history of hypertension, medication for hypertension, medication for dyslipidemia, BMI, hsCRP, and HOMA-IR.

b In the question "In the past year, during which time of the day did you work the most?", daytime work was defined as participants who answered that "I worked mostly during the day (between 6 AM and 6 PM)," and shift work was defined as participants who answered that "I worked during other hours."

Discussion

A previous cross-sectional study of 194,625 Koreans showed that the prevalence of NAFLD tended to increase with increasing working hours, especially in participants with over 52 hours per week; the prevalence of NALFD differed according to sleep duration as well as working hours, suggesting that increased working hours would lead to decreased sleeping hours, reduced physical activity, and increased obesity incidence [18]. In addition, two Chinese cross-sectional studies found an association between rotating night shift work and the prevalence of NAFLD, which might be due to circadian disruption [19, 31]. However, several other studies showed no association between shift work and NAFLD. Therefore, the relationship between shift work and NAFLD is still controversial [32, 33].

To our knowledge, most of the existing studies on the relationship between work-related factors and NAFLD are only cross-sectional studies; thus, we conducted a longitudinal cohort study to elucidate the causal relationship. Our large-scale cohort study, in which participants had no fatty liver at baseline, is the largest study to analyze the causality between working hours and NAFLD. Working >60 hours based on self-reports was significantly associated with an increased risk of incident NAFLD compared with working 35–40 hours. Increased baseline working hours had a dose-response relationship with the incidence of NAFLD. Moreover, the association was consistently observed when changes in potential confounders during follow-up were treated as time-varying covariates.

The mechanisms by which working hours affects the development of NAFLD are not fully understood. A previous cohort study showed that metabolically healthy individuals with no metabolic abnormalities had a higher risk of NAFLD when they were overweight or obese [20]. Consistently, in order to explore whether the increased risk of NAFLD associated with long working hours was mediated by BMI, we performed a stratified analysis adjusted for obesity (BMI <25 versus ≥25 kg/m2) and found that the association of long working hours with development of NAFLD remained significant in both subgroups with no interaction. In addition, another cohort study showed that relatively higher hsCRP levels increased the risk of developing NAFLD [34]. Such association can be explained by chronic low-grade inflammation due to oxidative stress, which is one of the major mechanisms of NAFLD. Therefore, we also performed a stratified analysis in subgroups by hsCRP (<1.0 versus ≥1.0 mg/L) and found that the association still remained significant in those with hsCRP <1.0 mg/L. Because of the exceedingly small number of participants with hsCRP ≥1.0 mg/L and possible healthy worker effects, HRs became insignificant even though the HRs in working >60 hours were similar in both subgroups of hsCRP. Moreover, long working hours were significantly related to psychosocial stress [35], and stress activates the hypothalamic-pituitary-adrenal axis, which contribute to insulin resistance by affecting the release of cortisol [36]. From the point of view of such a relationship, long working hours may be associated with insulin resistance. Notably, insulin resistance is closely related to NAFLD and is known as one of the main mechanisms of the progression of NAFLD [37]. Therefore, we performed a stratified analysis in subgroups by HOMA-IR (<2.5 versus ≥2.5). The association still remained significant in both subgroups with no interaction and was even higher in those with HOMA-IR ≥2.5 than in those with HOMA-IR <2.5. Taken together, these findings suggest that long working hours affect the development of NAFLD through various underlying mechanisms. Still, the effect of long working hours on the liver is not yet clear, and further studies are needed to elucidate the mechanisms underlying these direct associations.

Some limitations should be noted in the present study. First, NAFLD was diagnosed with abdominal ultrasound rather than more accurate methods such as liver biopsy. However, liver biopsy is an invasive procedure that can be accompanied by complications. In large-scale epidemiological studies, ultrasound is widely used due to its accuracy for detecting fatty liver [38]. Second, the work-related variables and lifestyle variables were collected through a self-administered structured questionnaire. Therefore, measurement errors from those variables could not be excluded. However, since there was no reason for the examinee to underreport or overreport out of self-interest, it was considered that the results would not be significantly affected by differential misclassification. Third, working hours might change during the follow-up period, which could affect the study results. During the entire follow-up period, the percentage of participants whose group of working hours moved only once or less to one adjacent group was approximately 70% of the total population (data not shown). Consequently, if all participants with small fluctuations in working hours were excluded, selection bias could occur. Furthermore, if the same analysis is performed on 30,311 participants without changes in working hours, the risk is much stronger when it exceeds 60 hours (HR = 2.90, 95% CI 2.47–3.41, S1 Table), suggesting that our study results could be underestimated. Fourth, we could not adjust for sleep duration and diet, which could be risk factors for NAFLD. Therefore, further research is needed to explicate the exact mechanism. Lastly, our study participants were young and middle-aged Korean with relatively good health status and high educational level. Thus, our findings may not be generalized to other populations.

Despite the limitations, our study has several notable strengths. This longitudinal study conducted in a large sample size with a relatively large time of follow-up is the first to investigate the temporal association of long working hours with the risk of incident NAFLD. Our findings obtained in the relatively healthy young and middle-aged population are less likely to be affected by survivor bias from comorbidities or the use of multiple medications.

In conclusion, our large-scale cohort study of young and middle-aged individuals demonstrated a causal relationship between long working hours and the incidence of NAFLD. Our findings suggest that long working hours are a risk factor for NAFLD. Further studies are needed to elucidate the potential mechanisms underlying this association.

Supporting information

S1 Table. Development of NAFLD according to weekly working hours among participants with no changes of working hours (n = 30,311).

(DOCX)

Click here for additional data file. (18.9KB, docx)

Acknowledgments

This study was conducted based on the data provided by Kangbuk Samsung Health Study. The authors thank all study participants and the study personnel for their dedication and continuing support.

Data Availability

The data are not available to be shared publicly because of ethical restrictions imposed by the Institutional Review Board of Kangbuk Samsung Hospital. For additional information to request the data, please contact the Institutional Review Board of Kangbuk Samsung Hospital (IRB, Tel. +82-2001-1943; e-mail: irb.kbsmc@samsung.com).

Funding Statement

The author(s) received no specific funding for this work.

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Decision Letter 0

Jee-Fu Huang

20 May 2021

PONE-D-21-10560

Long working hours are associated with a higher risk of non-alcoholic fatty liver disease: a large population-based Korean cohort study

PLOS ONE

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Reviewer #1: This study aims to evaluate the association between working hours and the development of NAFLD. 79,048 Korean adults without NAFLD at baseline were included in the retrospective study and weekly working hours were categorized into 35–40, 41–52, 53–60, and >60 hours. The median follow-up period was 6.6 years and 15,095 participants developed new-onset NAFLD. After adjustment for confounders, the hazard ratios for the development of NAFLD in 41–52, 53–60, and >60 working hours compared with that in 35–40 working hours were 1.07 (1.02–1.13), 1.06 (1.00–1.13), and 1.13 (1.05–1.23), respectively. They concluded that long working hours are a risk factor for NAFLD.

Comments are as follows:

1. Patients were categorized into four groups according to working hours at baseline. Since the median follow-up was 6.6 years, working hours might change during follow-up period. Will the change of working hours affect the outcome and how to prevent this bias?

2. The authors categorized weekly working hours as 35–40, 41–52, 53–60, and >60 hours based on the policy of Labor Standards Act of Korea.

There are questions about this classification.

a. Why were subjects with weekly working hours <35 excluded from this study?

b. The group of working hours between 35 and 40 was based on the policy for adolescents. Because subjects with age <19 years were excluded from this study, why did the authors include the group of working hours between 35 and 40?

c. Is it more reasonable to simply adapt the suggestion of International Labour Organization (48 hours and 60 hours) as mentioned by the authors in the Measurements section?

3. In MATERIALS AND METHODS section, alcohol consumption was divided into ≥10 g/day and <10 g/day. Since alcohol intake of ≥30 g/day for men or ≥20 g/day for women has been excluded from this study. What is the clinical significance of this classification?

Reviewer #2: Non-alcoholic fatty liver disease (NAFLD) is an increasingly cause of chronic liver disease. Several factors are associated with the development of NAFLD, such as obesity, type 2 diabetes mellitus. In this study, Lee et al. investigated the association between working hours and the development of NAFLD. They found that long working hours, were independently associated with incident NAFLD. Although the results were clinically interesting, several points need be critically addressed.

1. The time of baseline data collection is not clear. The authors should describe when the baseline data was collected in this study.

2. In this study, alcohol consumption was categorized as ≥10 g/day and <10 g/day. Please describe the reason for this category.

3. In this study, obesity was defined as body mass index (BMI) ≥25 kg/m2. However, the cutoff for obesity is 23.0 kg/m2 in Asia-Pacific countries, including Korea. The authors may perform subgroups analysis by BMI <23 versus ≥23 kg/m2.

4. The association between the change in body weight or BMI during the follow-up period and development of NAFLD should be taken into consideration.

5. The authors should describe how to evaluate the reliability and validity of the self-administered questionnaires.

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PLoS One. 2021 Jul 23;16(7):e0255118. doi: 10.1371/journal.pone.0255118.r002

Author response to Decision Letter 0

25 Jun 2021

Reviewer #1: This study aims to evaluate the association between working hours and the development of NAFLD. 79,048 Korean adults without NAFLD at baseline were included in the retrospective study and weekly working hours were categorized into 35–40, 41–52, 53–60, and >60 hours. The median follow-up period was 6.6 years and 15,095 participants developed new-onset NAFLD. After adjustment for confounders, the hazard ratios for the development of NAFLD in 41–52, 53–60, and >60 working hours compared with that in 35–40 working hours were 1.07 (1.02–1.13), 1.06 (1.00–1.13), and 1.13 (1.05–1.23), respectively. They concluded that long working hours are a risk factor for NAFLD.

Comments are as follows:

1. Patients were categorized into four groups according to working hours at baseline. Since the median follow-up was 6.6 years, working hours might change during follow-up period. Will the change of working hours affect the outcome and how to prevent this bias?

Response: We thank the reviewer for the opportunity to clarify this issue. During the entire follow-up period, the percentage of participants with unchanged working hours was 38.35%, and the percentage of participants whose group of working hours moved only once or less to one adjacent group was about 70% of the total population. Therefore, we can assume that there is little variation in working hours between the participants of this study. Furthermore, when the same analysis is performed on 30,311 people who have no change in working hours, the risk is much stronger when it exceeds 60 hours (HR = 2.90, 95% CI 2.47–3.41, S1 Table). However, if all the people with small fluctuations in working hours are excluded, selection bias may occur. Therefore, the current method seems reasonable, and the results are considered to be underestimations. Besides pointing out that the change in working hours is a limitation of our study, we added that the results could be underestimated in the limitation paragraph of the DISCUSSION (Lines 205–211) along with S1 Table.

S1 Table. Development of NAFLD according to weekly working hours among participants with no changes in working hours (n=30,311)

Weekly working hours Person-years (PY) Incident cases Incidence density

(per 102 PY)

(95% CI) Multivariable-adjusted HR (95% CI)a HR (95% CI)b in model using time-dependent variables

Model 1* Model 2** Model 3***

35-40 33185.3 1532 4.62 (4.39-4.85) 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference)

41-52 50238.2 3792 7.55 (7.31-7.79) 1.20 (1.12-1.28) 1.20 (1.12-1.28) 1.21 (1.12-1.31) 1.19 (1.10-1.29)

53-60 3604.2 552 15.32 (14.09-16.65) 2.54 (2.30-2.82) 2.47 (2.23-2.74) 2.54 (2.26-2.85) 2.57 (2.29-2.89)

>60 1499.3 237 15.80 (13.92-17.95) 2.73 (2.38-3.15) 2.69 (2.33-3.11) 2.90 (2.47-3.41) 3.00 (2.56-3.52)

P for trend <0.001 <0.001 <0.001 <0.001

a Estimated from Cox proportional hazard models.

b Estimated from Cox proportional hazard models with alcohol intake, smoking status, regular exercise, BMI, hsCRP and HOMA-IR as time-dependent variables and baseline age, sex, center, year of screening exam, education level, weekly working hours, history of diabetes, medication for diabetes, history of hypertension, medication for hypertension and medication for dyslipidemia as time-fixed variables

* Model 1 was adjusted for age, sex, center, and year of screening examination.

** Model 2: model 1 plus adjustment for smoking status, alcohol intake, regular exercise, education level, history of diabetes, medication for diabetes, history of hypertension, medication for hypertension and medication for dyslipidemia.

*** Model 3: model 2 plus adjustment for BMI, hsCRP and HOMA-IR

2. The authors categorized weekly working hours as 35–40, 41–52, 53–60, and >60 hours based on the policy of Labor Standards Act of Korea.

There are questions about this classification.

a. Why were subjects with weekly working hours <35 excluded from this study?

Response: We thank the reviewer for this comment. In our study, part-time and full-time workers were not classified separately. However, to completely understand the effect of long working hours, only participants who thought they were full-time workers were included in the analysis. According to the ILO report, a person working less than 35 hours was defined as a part-time worker (Lee SH, et al. Working Time Around the World: Trends in Working Hours, Laws and Policies in a Global Comparative Perspective. Oxford: Routledge; 2007.).

b. The group of working hours between 35 and 40 was based on the policy for adolescents. Because subjects with age <19 years were excluded from this study, why did the authors include the group of working hours between 35 and 40?

Response: We thank the reviewer for the pertinent comment. There were fewer than 10 participants aged under 19 years in the entire population of our study, and we wanted to exclude the effects of adolescents. The reason for using weekly working 35-40 hours as a reference was to understand the health effects of long working hours among full-time workers. Since this study is conducted among Korean workers, the legal maximum working hours for adolescents in Korean law was used as a reference. In addition, several previous studies of long working hours have used 35–40 hours as the standard working hours for workers who worked more than 35 hours (Kim W, et al. Effect of working hours and precarious employment on depressive symptoms in South Korean employees: a longitudinal study. Occup Environ Med. 2016;73(12):816-22; Kivimäki M, et al. Long working hours, socioeconomic status, and the risk of incident type 2 diabetes: a meta-analysis of published and unpublished data from 222 120 individuals. The Lancet Diabetes & Endocrinology. 2015;3(1):27-34.).

c. Is it more reasonable to simply adapt the suggestion of International Labour Organization (48 hours and 60 hours) as mentioned by the authors in the Measurements section?

Response: We thank the reviewer for this important comment. We defined the classification of working hours based on the fact that Korea has one of the countries with the highest annual working hours per worker among OECD countries and that the participants of this study were all Koreans who are legally allowed to work up to 52 hours (except for some occupations such as medical personnel or transporter). However, when the sensitivity analysis was performed according to the ILO classification, the risk of NAFLD still significantly increased with respect to long working hours (>60 hours: HR = 1.13, 95% CI 1.05–1.23, Table 1 not shown in the manuscript), showing no difference from our results.

Table 1. Development of NAFLD according to weekly working hours in the ILO classification

Weekly working hours Person-years (PY) Incident cases Incidense density

(per 102 PY)

(95% CI) Multivariable-adjusted HR (95% CI)a HR (95% CI)b in model using time-dependent variables

Model 1* Model 2** Model 3***

35-40 61646.0 2691 4.37 (4.20-4.53) 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference)

41-48 64951.5 3369 5.19 (5.01-5.37) 1.03 (0.98-1.09) 1.03 (0.98-1.09) 1.08 (1.01-1.14) 1.06 (1.00-1.13)

49-60 126839.6 7797 6.15 (6.01-6.29) 1.02 (0.98-1.07) 1.04 (0.99-1.09) 1.07 (1.01-1.13) 1.06 (1.00-1.11)

>60 18531.2 1238 6.68 (6.32-7.06) 1.09 (1.02-1.17) 1.09 (1.02-1.17) 1.13 (1.05-1.23) 1.14 (1.06-1.23)

P for trend 0.093 0.035 0.005 0.008

a Estimated from Cox proportional hazard models.

b Estimated from Cox proportional hazard models with alcohol intake, smoking status, regular exercise, BMI, hsCRP and HOMA-IR as time-dependent variables and baseline age, sex, center, year of screening exam, education level, weekly working hours, history of diabetes, medication for diabetes, history of hypertension, medication for hypertension and medication for dyslipidemia as time-fixed variables

* Model 1 was adjusted for age, sex, center, and year of screening examination.

** Model 2: model 1 plus adjustment for smoking status, alcohol intake, regular exercise, education level, history of diabetes, medication for diabetes, history of hypertension, medication for hypertension and medication for dyslipidemia.

*** Model 3: model 2 plus adjustment for BMI, hsCRP and HOMA-IR

3. In MATERIALS AND METHODS section, alcohol consumption was divided into ≥10 g/day and <10 g/day. Since alcohol intake of ≥30 g/day for men or ≥20 g/day for women has been excluded from this study. What is the clinical significance of this classification?

Response: We thank the reviewer for this thoughtful comment. This classification was defined considering the cultural aspects of drinking in Korea, where alcohol consumption is high and it is difficult to completely avoid alcohol. The group that consumed relatively high amounts of alcohol and the group that did not consume alcohol were classified by one standard drink used in Korea (10 grams of pure alcohol based on the WHO definition). We referred to previous studies on NAFLD, which set one standard drink as the criteria for alcohol consumption (Jung HS, et al. Smoking and the Risk of Non-Alcoholic Fatty Liver Disease: A Cohort Study. Am J Gastroenterol. 2019;114(3):453-63.) (Kim Y, et al. Metabolically healthy versus unhealthy obesity and risk of fibrosis progression in non-alcoholic fatty liver disease. Liver Int. 2019;39(10):1884-94.).

 

Reviewer #2: Non-alcoholic fatty liver disease (NAFLD) is an increasingly cause of chronic liver disease. Several factors are associated with the development of NAFLD, such as obesity, type 2 diabetes mellitus. In this study, Lee et al. investigated the association between working hours and the development of NAFLD. They found that long working hours, were independently associated with incident NAFLD. Although the results were clinically interesting, several points need be critically addressed.

1. The time of baseline data collection is not clear. The authors should describe when the baseline data was collected in this study.

Response: We thank the reviewer for this comment. We described that the study included the participants who underwent health examinations from January 1, 2012, to December 31, 2017 in Lines 64–65. To avoid misunderstanding, we added the following explanation to the Study population section (Lines 66–67): “During this period, the baseline data were collected at the time of the first health examination visit.”

2. In this study, alcohol consumption was categorized as ≥10 g/day and <10 g/day. Please describe the reason for this category

Response: We thank the reviewer for the pertinent comment. The group that consumed relatively high amounts of alcohol and the group that did not consume alcohol were classified by one standard drink used in Korea (10 grams of pure alcohol based on the WHO definition). We referred to previous studies on NAFLD, which set one standard drink as the criteria for alcohol consumption (Jung HS, et al. Smoking and the Risk of Non-Alcoholic Fatty Liver Disease: A Cohort Study. Am J Gastroenterol. 2019;114(3):453-63.) (Kim Y, et al. Metabolically healthy versus unhealthy obesity and risk of fibrosis progression in non-alcoholic fatty liver disease. Liver Int. 2019;39(10):1884-94.).

3. In this study, obesity was defined as body mass index (BMI) ≥25 kg/m2. However, the cutoff for obesity is 23.0 kg/m2 in Asia-Pacific countries, including Korea. The authors may perform subgroups analysis by BMI <23 versus ≥23 kg/m2.

Response: We thank the reviewer for the in-depth comment. In Korea, the cut-off value for obesity is 25 kg/m2, as recommended by the Korean Society for the Study of Obesity. This is derived from the Asia-Pacific classification of obesity established in 2000 by the WHO, where 23 kg/m2 is the cut-off value for being overweight (WHO. The Asia-Pacific perspective: Redefining obesity and its treatment. Sydney: Health Communications Australia; 2000). The Korean Society for the Study of Obesity has defined the cut-off value for obesity as 25 kg/m2 because the prevalence and mortality of obesity-related diseases increase when the BMI exceeds 25 kg/m2 in Asians (Korean Society for the Study of Obesity. Guideline for the management of obesity 2020. Seoul: Korean Society for the Study of Obesity; 2020). Furthermore, many Korean studies on NAFLD have set the criteria for obesity as 25 kg/m2 (Chang Y, et al. Nonheavy Drinking and Worsening of Noninvasive Fibrosis Markers in Nonalcoholic Fatty Liver Disease: A Cohort Study. Hepatology. 2019;69(1):64-75.). When subgroup analysis was performed based on overweight status, the HR increased in long working hours with no significance (HR = 1.14, 95% CI 1.00–1.30, Table 2 not shown in the manuscript), but no interaction was observed. The hypothesis for this result is that people who maintain BMI at less than 23 kg/m2 did not show a high risk of NAFLD in long working hours because they are generally interested in health care and diet control. The limitation of our study is that there are no data on diet, which was mentioned in the limitation paragraph of the DISCUSSION. (Lines 211–213)

Table 2. Hazard ratiosa (95% CI) for NAFLD by weekly working hours subgrouped by overweight

　 Weekly working hours 　 　

Subgroup 35-40 41-52 53-60 >60 P for trend P for interaction

BMI 0.062

<23 kg/m2 (n=49,208) 1.00 (reference) 1.07 (0.98-1.17) 1.07 (0.96-1.19) 1.14 (1.00-1.30) 0.097

≥23 kg/m2 (n=29,739) 1.00 (reference) 1.09 (1.02-1.16) 1.08 (1.00-1.17) 1.16 (1.05-1.28) 0.01

a Estimated from Cox proportional hazard models adjusted for age, sex, center, year of screening examination, smoking status, alcohol intake, regular exercise, education level, history of diabetes, medication for diabetes, history of hypertension, medication for hypertension, medication for dyslipidemia, BMI, hsCRP and HOMA-IR

4. The association between the change in body weight or BMI during the follow-up period and development of NAFLD should be taken into consideration.

Response: We thank the reviewer for this important comment. During the entire follow-up period, the percentage of participants in the unchanged category of obesity was 87.82%, and the percentage of participants whose obesity status changed less than once was 97% of the total population. Therefore, it can be considered that there was almost no variation in obesity in participants of this study. When subgroup analysis was performed based on changes of obesity status, the HR of the changed group increased in long working hours with no significance (HR = 1.13, 95% CI 0.95–1.33, Table 3 not shown in the manuscript), but no interaction was observed.

 

Table 3. Hazard ratiosa (95% CI) for NAFLD by weekly working hours subgrouped by changes of obesity

　 Weekly working hours 　 　

Subgroup 35-40 41-52 53-60 >60 P for trend P for interaction

changes of obesity 0.779

change (n=9,626) 1.00 (reference) 1.05 (0.94-1.17) 1.11 (0.97-1.26) 1.13 (0.95-1.33) 0.074

no change (n=69,422) 1.00 (reference) 1.07 (1.01-1.14) 1.05 (0.98-1.13) 1.13 (1.03-1.23) 0.044

a Estimated from Cox proportional hazard models adjusted for age, sex, center, year of screening examination, smoking status, alcohol intake, regular exercise, education level, history of diabetes, medication for diabetes, history of hypertension, medication for hypertension, medication for dyslipidemia, BMI, hsCRP and HOMA-IR

5. The authors should describe how to evaluate the reliability and validity of the self-administered questionnaires.

Response: We thank the reviewer for this thoughtful comment. We secured the reliability of the self-questionnaire by adding the following explanation to the measurements paragraph of MATERIALS AND METHODS in Lines 86–89: “On the day of the health examination, a trained nurse checked the questionnaire for blanks, and during the final stage of the health examination, a trained doctor double-checked whether there were any incorrect or blank marks on the questionnaire while conducting a face-to-face interview with the examinee.” In addition, when filling out a questionnaire of the examinee's medical history or working hours, there was no apparent benefit to the examinee. Therefore, since there was no reason for the examinee to underreport or overreport, we considered that the results would not be significantly affected by differential misclassification. This description was added to the limitation paragraph of the DISCUSSION (Lines 204–205).

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Decision Letter 1

Jee-Fu Huang

12 Jul 2021

Long working hours are associated with a higher risk of non-alcoholic fatty liver disease: a large population-based Korean cohort study

PONE-D-21-10560R1

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Acceptance letter

Jee-Fu Huang

14 Jul 2021

PONE-D-21-10560R1

Long working hours are associated with a higher risk of non-alcoholic fatty liver disease: a large population-based Korean cohort study

Dear Dr. Lee:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

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Associated Data

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

    Supplementary Materials

    S1 Table. Development of NAFLD according to weekly working hours among participants with no changes of working hours (n = 30,311).

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    Data Availability Statement

    The data are not available to be shared publicly because of ethical restrictions imposed by the Institutional Review Board of Kangbuk Samsung Hospital. For additional information to request the data, please contact the Institutional Review Board of Kangbuk Samsung Hospital (IRB, Tel. +82-2001-1943; e-mail: irb.kbsmc@samsung.com).

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