Short sleep duration and its Determinants in MASLD and Non-MASLD: A Population-Based Cohort Study from Iran

Short sleep duration and its Determinants in MASLD and Non-MASLD: A Population-Based Cohort Study from Iran | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Short sleep duration and its Determinants in MASLD and Non-MASLD: A Population-Based Cohort Study from Iran Alireza Gharebaghi, Hadi Raeisi Shahraki, Reza Homayounfar, Behnam Honarvar, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8331697/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Metabolic dysfunction–associated steatotic liver disease (MASLD) affects about 25–30% of adults and is linked to obesity, diabetes, and metabolic syndrome. Sleep disturbance, especially short sleep duration, is common in this population. This study examined the association between MASLD and short sleep. Methods: We analyzed 10,019 adults (35–70 years) from the Fasa Adult Cohort Study, part of the PERSIAN cohort. MASLD was identified by the Fatty Liver Index (FLI). Sleep duration was self-reported, with short sleep defined as <6 hours per night. Logistic regression identified factors associated with short sleep. Results: Among 10,019 participants, 2,601 (25.9%) had MASLD. Compared with non-MASLD individuals, they had higher BMI, blood pressure, metabolic markers, and more diabetes and hypertension. In non-MASLD, short sleep was associated with age, SGPT, lupus, headache, dizziness, and back pain, while higher HDL and WSI were protective. In MASLD, short sleep was linked to age and osteoporosis, whereas higher HDL and food regurgitation were protective. Conclusion: Short sleep was common in both MASLD and non-MASLD adults. Age and low HDL consistently contributed, while other factors differed between groups, highlighting the multifactorial nature of sleep disturbance in MASLD. MASLD NAFLD non alcoholic fatty liver disease Short sleep duration Sleep disturbance Introduction Metabolic dysfunction–associated steatotic liver disease (MASLD), previously termed non-alcoholic fatty liver disease (NAFLD), is now recognized as a distinct clinical entity within the spectrum of steatotic liver diseases. It is defined as hepatic steatosis in the presence of at least one cardiometabolic risk factor, in the absence of harmful alcohol consumption. MASLD has emerged as one of the most prevalent liver disorders worldwide, with rates increasing in parallel with obesity and type 2 diabetes mellitus. [ 1 , 2 ] The liver plays a pivotal role in lipid metabolism, converting carbohydrates into triglycerides and cholesterol for energy storage and use. When this balance is disrupted, conditions such as fatty liver, hyperlipidemia, and diabetes may develop. With the global decline of viral hepatitis due to vaccination programs and effective antiviral therapies, MASLD has emerged as a leading cause of chronic liver disease and its end-stage complications, including cirrhosis and hepatocellular carcinoma (HCC). MASLD often begins as simple steatosis and may progress to metabolic dysfunction–associated steatohepatitis (MASH). Approximately one-quarter of patients eventually advance to more severe stages marked by inflammation and fibrosis.[ 1 , 3 – 5 ] The pathogenesis of MASLD is multifactorial, with strong links to obesity, insulin resistance, and metabolic syndrome, while genetic and environmental influences add further complexity to its management. Although lifestyle interventions, particularly dietary modification and regular physical activity, remain the cornerstone of treatment, the growing global burden of MASLD highlights the pressing need for novel therapeutic strategies[ 6 , 7 ]. Sleep disturbances, particularly short sleep duration, are closely associated with insulin resistance, glucose dysregulation, obesity, type 2 diabetes, and metabolic syndrome, all of which contribute to an increased risk of MASLD. Short sleep, which affects an estimated 20–40% of adults, is frequently linked to chronic health conditions .[ 7 – 9 ] The Fatty Liver Index (FLI) is a simple and useful tool for estimating the likelihood of fatty liver. It is calculated using BMI, waist circumference, triglycerides, and GGT. An FLI of 60 or higher suggests a high chance of having hepatic steatosis, based on the original validation work. [ 10 ] Jeong et al. also showed that FLI performs very well as a diagnostic marker, with an AUC of 0.870.[ 11 ] Growing evidence suggests a strong association between MASLD and sleep disturbances. Short sleep duration is commonly reported among MASLD patients, likely mediated by shared mechanisms such as obesity, metabolic dysregulation, and systemic inflammation. [ 9 , 12 ] With its growing prevalence and widespread systemic effects, MASLD has become a significant global health challenge. To improve outcomes and develop effective targeted interventions, it is essential to better understand its complex interactions with lifestyle, metabolic, and behavioral factors. In this context, the present study evaluated sleep duration by comparing the amount of sleep between individuals with and without MASLD, aiming to clarify the potential contribution of reduced sleep to the disease. Methods The Fasa Adult Cohort Study This cross-sectional study draws on data from the Fasa Adult Cohort Study (FACS), a branch of the Prospective Epidemiological Research Studies in Iran (PERSIAN). Initiated in 2014 in the Sheshdeh and Qarabolagh districts of Fasa, Fars Province, the study enrolled 10,115 participants aged 35–70 years, with a planned 20-year follow-up. Fasa, a city of around 205,000 residents representing Persian, Arab, and Turkish ethnic groups, is located in a temperate semi-arid region. The cohort includes both urban and rural populations across two towns and 22 villages. By 2021, four follow-ups had been completed, with the latest reassessment launched in September 2021. The study protocols were reviewed and approved by the Ethics Committee of Fasa University of Medical Sciences (enrollment: IR.FUMS.REC.1394.3; follow-up: IR.FUMS.REC.1395.177) [ 13 ]. Study sample Participants were excluded if they: (1) did not provide consent for examinations, diagnostic procedures, or use of their data in the study; or (2) had missing essential information, such as key variables including body mass index (BMI), blood pressure, fasting plasma glucose, liver function tests, or blood lipid levels.or (3)History of excessive alcohol consumption, viral hepatitis, or chronic liver disease.or (4) Pregnant or breastfeeding women. After applying these exclusion criteria, a total of 10,019 participants remained for further analysis. Sociodemographic and lifestyle variables Sociodemographic data, including ethnicity and the Wealth Score Index (WSI), were obtained through the FACS general questionnaire. Lifestyle factors such as smoking status and drug use were collected using medical questionnaires. Anthropometric and clinical variables Anthropometric measurements included height (measured with a wall stadiometer), weight (using an analog scale), and waist, hip, and wrist circumferences (using a standard tape). Blood pressure was measured twice in both arms at 15-minute intervals with a standard sphygmomanometer, and the average of the two readings was recorded. Biochemical analyses were performed on blood serum samples using a Pars Azmoon kit to assess fasting blood glucose, total cholesterol, high-density lipoprotein (HDL), low-density lipoprotein (LDL), alanine aminotransferase (ALT), aspartate aminotransferase (AST), and triglycerides (TG). MASLD Diagnosis MASLD status was assessed using the Fatty Liver Index (FLI), a validated algorithm incorporating body mass index (BMI), waist circumference, triglyceride levels, and gamma-glutamyl transferase (GGT). Participants with an FLI score ≥ 60 were classified as having MASLD, whereas those with a score < 30 were considered free of the condition. Individuals with intermediate values (FLI 30–59) were classified into the non-MASLD group. Sleep Duration Sleep duration was assessed by self-report. Participants reporting an average sleep duration of less than six hours per night were classified as having short sleep duration. Statistical Analysis variables were summarized as means with standard deviations (SD), and categorical variables as frequencies and percentages. In univariate analyses, variables with a p-value < 0.1 were selected as candidates for further modeling. These variables were then entered into multivariable logistic regression models with a backward elimination approach to identify independent factors associated with short sleep duration in each study group .Adjusted odds ratios (ORs) with 95% confidence intervals (CIs) were reported, and a two-sided p -value < 0.05 was considered statistically significant. All analyses were conducted using IBM SPSS Statistics 29.0. Results Baseline characteristics of participants Among the 10,019 participants, 4,528 (45.1%) were men, and 2,601 individuals (949 men and 1,652 women) were diagnosed with MASLD. The prevalence of short sleep duration was 18.1% among non-MASLD individuals and 21.1% among participants with MASLD. Compared with their non-MASLD counterparts, participants with MASLD had a markedly higher fatty liver index (77.5 vs. 25.6) and, on average, higher BMI (mean ± SD: 31.01 ± 3.81), systolic blood pressure (117.28 ± 19.16), and diastolic blood pressure (78.55 ± 12.27) (Table 1 ). They also showed elevated metabolic markers, including total cholesterol (189.9 ± 60.0), triglycerides (180.5 ± 119.2), SGOT (22.62 ± 11.14), and SGPT (27.53 ± 18.12) (Table 2 ). In addition, the prevalence of type 2 diabetes (19.4%) and hypertension (31.8%) was considerably higher in the MASLD group compared with the healthy group (9.7% and 15.7%, respectively) . Table 1 Anthropometric and Clinical Characteristics of Participants With and Without MASLD (Mean ± SD, p-values) group Sleep. disorder N Mean Std. Deviation P-value Non-MASLD Age (years) No 6015 48.0690 9.72622 < 0.001 Yes 1404 50.0926 9.44263 Height (cm) No 6015 161.5851 12.03827 0.84 Yes 1404 161.5098 14.59982 Weight (kg) No 6015 61.9979 10.49221 0.61 Yes 1404 62.1573 11.29472 Waist circumference (cm) No 6015 88.2247 9.85515 0.93 Yes 1404 88.1994 11.17138 Hip circumference (cm) No 6015 96.2222 8.18386 0.39 Yes 1404 96.0076 9.47773 Wrist circumference (cm) No 6015 16.3442 1.40148 0.92 Yes 1404 16.3400 1.70204 Body mass index (BMI, kg/m²) No 6015 23.6434 3.68243 0.63 Yes 1404 23.5909 3.82806 Diastolic blood pressure (mmHg) No 6015 73.2663 11.75583 0.29 Yes 1404 72.8989 11.41586 Systolic blood pressure (mmHg) No 6015 109.1912 18.04882 0.68 Yes 1404 108.9715 17.61772 Pulse rate (beats/min) No 6015 73.4331 10.95001 0.01 Yes 1404 72.5734 10.45165 MASLD Age (years) No 2049 48.5052 9.11406 < 0.001 Yes 552 51.3596 9.00491 Height (cm) No 2049 160.8630 8.75251 0.72 Yes 552 161.0104 9.29456 Weight (kg) No 2049 80.2017 11.61976 0.49 Yes 552 80.5804 11.52625 Waist circumference (cm) No 2049 105.7955 8.81202 0.11 Yes 552 106.4581 8.24239 Hip circumference (cm) No 2049 108.1947 8.23875 0.98 Yes 552 108.2061 8.02888 Wrist circumference (cm) No 2049 17.6381 1.35978 0.21 Yes 552 17.7198 1.39368 Body mass index (BMI, kg/m²) No 2049 31.0000 3.86450 0.67 Yes 552 31.0759 3.61568 Diastolic blood pressure ( mmHg( No 2049 78.5611 12.45879 0.95 Yes 552 78.5246 11.58996 Systolic blood pressure (mmHg( No 2049 117.1971 19.28289 0.40 Yes 552 117.9544 18.67448 Pulse rate (PR, beats/min) No 2049 76.1482 10.69606 0.80 Yes 552 76.0211 10.66668 Table 2 Lipid Profile, Liver Enzymes, and Fatty Liver Index in MASLD and Non-MASLD Groups (Mean ± SD, p-values) group Sleep. disorder N Mean Std. Deviation P-value Non-MASLD Triglycerides (TG, mg/dL) No 6015 104.4079 57.53569 0.29 Yes 1404 102.5929 57.98691 Total cholesterol (CHOL, mg/dL) No 6015 170.2276 55.61068 0.02 Yes 1404 166.2865 57.50080 Serum glutamic-oxaloacetic transaminase (SGOT, U/L) No 6015 20.6822 9.01758 0.88 Yes 1404 20.7244 9.15624 Serum glutamic-pyruvic transaminase (SGPT, U/L No 6015 19.8056 12.41205 0.08 Yes 1404 20.4823 14.37105 Alkaline phosphatase (ALP, U/L) No 6015 193.2314 80.71790 0.76 Yes 1404 193.9687 79.09456 High-density lipoprotein cholesterol (HDL, mg/dL) No 6015 49.8995 20.55815 < 0.001 Yes 1404 46.3093 17.84005 Low-density lipoprotein cholesterol (LDL, mg/dL) No 6015 99.3996 39.48142 0.96 Yes 1404 99.4586 40.56633 Gamma-glutamyl transferase (GGT, U/L) No 6015 18.1007 16.22681 0.27 Yes 1404 18.6258 16.23210 Fatty Liver Index (FLI) No 6015 25.5651 16.96695 0.22 Yes 1404 26.1851 17.28459 Metabolic equivalent of task (MET, final score) No 6015 42.0217 11.59085 Yes 1404 43.3803 12.87333 Wealth Score Index (total No 6015 − .9255 .88017 Yes 1404 − .8427 .87633 Wealth Score Index (by center) No 6015 − .0579 1.00295 Yes 1404 .0030 1.00437 MASLD Triglycerides (TG, mg/dL) No 2049 181.0429 117.54526 0.61 Yes 552 178.1454 125.12739 Total cholesterol (CHOL, mg/dL) No 2049 191.0882 59.24353 0.05 Yes 552 185.6165 62.23671 Serum glutamic-oxaloacetic transaminase (SGOT, U/L) No 2049 22.6783 10.99795 0.60 Yes 552 22.4009 11.74413 Serum glutamic-pyruvic transaminase (SGPT, U/LT No 2049 27.6956 18.23192 0.18 Yes 552 26.5598 17.63529 Alkaline phosphatase (ALP, U/L) No 2049 210.5635 79.69420 0.93 Yes 552 210.1630 124.72348 High-density lipoprotein cholesterol (HDL, mg/dL) No 2049 47.2728 18.85035 < 0.001 Yes 552 42.8175 16.03805 Low-density lipoprotein cholesterol (LDL, mg/dL) No 2049 107.5681 42.78271 0.84 Yes 552 107.1695 43.54445 Gamma-glutamyl transferase (GGT, U/L) No 2049 30.1759 26.25463 0.56 Yes 552 30.9425 34.39023 Fatty Liver Index (FLI) No 2049 77.2994 10.94110 0.02 Yes 552 78.5077 10.94236 Metabolic equivalent of task (MET, final score) No 2049 39.1290 9.70706 Yes 552 39.3631 8.58557 Wealth Score Index (total No 2049 − .7587 .84681 Yes 552 − .6971 .86329 Wealth Score Index (by center) No 2049 .1171 .96892 Yes 552 .1614 1.00666 Multivariable Logistic Regression Analysis of Factors Associated with sleep duration In the multivariable logistic regression analysis, variables with a univariate p-value below 0.1 were entered into the model. Using a backward elimination approach, we identified several factors that were independently associated with short sleep duration. the following demographic, clinical, and lifestyle factors met the inclusion criteria and were entered into the multivariable model: Demographics ethnicity, gender. Cardiometabolic conditions diabetes, hypertension, cardiac disease, myocardial infarction (MI), stroke, renal failure, chronic lung disease, thyroid disease, kidney stones, gallstones, rheumatic disease. Cancer history skin, breast, stomach, colorectal, bladder, esophageal, prostate, lung, brain ,and CNS cancers, as well as laryngeal, tongue, uterine, and ovarian cancers. Neurological and psychiatric disorders epilepsy, chronic headaches, depression, psychiatric disorders, learning disabilities, amnesia, multiple sclerosis (MS), history of cardiovascular disease, thought disorders. Autoimmune and inflammatory diseases lupus, rheumatoid arthritis. Symptoms and physical conditions sternum irritation, swelling, urinary changes, abnormal urine tests, gastrointestinal symptoms (heartburn, food regurgitation, gastroesophageal reflux disease, bloating, changes in bowel movement interval, blood in stool, weight loss, jaundice), respiratory symptoms (cough, shortness of breath), gait problems, fainting, visual impairment, muscle weakness, movement disorders, numbness, head trauma, recurring headaches, dizziness, tinnitus. Musculoskeletal issues fracture history (including hip femoral fracture), osteoporosis, back pain, joint pain, with or without stiffness. Other health conditions aphthous ulcers (oral and genital). Lifestyle and medication use smoking (cigarette and non-cigarette forms, including exposure at home, workplace, and childhood), drug use, and use of antihypertensive drugs, oral diabetes medications, insulin, statins, and anti-triglyceride drugs. Multivariable Logistic Regression Results In the Non-MASLD group, logistic regression analysis showed that increasing age (OR = 1.02; 95% CI: 1.01–1.03; p < 0.001), higher SGPT levels (OR = 1.007; 95% CI: 1.00–1.01; p = 0.003), lupus (OR = 9.00; 95% CI: 2.07–39.12; p = 0.003), recurring headaches (OR = 1.34; 95% CI: 1.15–1.56; p < 0.001), dizziness (OR = 1.25; 95% CI: 1.07–1.45; p = 0.05), back pain/stiffness (OR = 1.23; 95% CI: 1.09–1.40; p = 0.01), and higher total WSI scores (OR = 2.91; 95% CI: 2.07–4.10; p < 0.001) were independently associated with a greater likelihood of short sleep duration. In contrast, higher HDL (OR = 0.98; 95% CI: 0.98–0.99; p < 0.001) and WSI by center (OR = 0.45; 95% CI: 0.33–0.60; p 0.05) (Table 3 ). Table 3 Variables included in the multivariable logistic regression model in individuals without MASLD Variable P-value OR 95% C.I. for OR Lower Upper Age < 0.001 1.022 1.014 1.03 Metabolic equivalent of task Score < 0.001 1.012 1.007 1.017 Number of Missing Teeth 0.001 1.011 1.005 1.018 Total WSI < 0.001 2.916 2.072 4.104 Center-specific WSI < 0.001 0.45 0.334 0.606 Granulocyte count 0.09 0.996 0.992 1.001 BUN (Blood Urea Nitrogen) 0.007 1.02 1.005 1.035 ALT (SGPT) 0.003 1.007 1.003 1.012 HDL < 0.001 0.988 0.984 0.992 History of HSC 0.016 17.395 1.702 177.825 Depression (Yes/No) 0.052 1.264 0.998 1.601 Lupus (Yes/No) 0.003 9.009 2.074 39.129 Food Regurgitation (Yes/No) 0.079 0.802 0.626 1.026 Recurring Headaches (Yes/No) < 0.001 1.343 1.152 1.565 Dizziness (Yes/No) 0.005 1.25 1.071 1.459 Back Pain with Stiffness (Yes/No) 0.001 1.238 1.093 1.403 Mouth Aphthous Ulcers (Yes/No) 0.022 1.434 1.054 1.951 Alcohol Use (Yes/No) 0.042 1.301 1.009 1.678 Among MASLD patients, increasing age (OR = 1.02; 95% CI: 1.01–1.03; p < 0.001) and osteoporosis (OR = 1.65; 95% CI: 1.25–2.19; p < 0.001) were significantly associated with short sleep duration. Conversely, higher HDL (OR = 0.98; 95% CI: 0.97–0.98; p < 0.001) and food regurgitation (OR = 0.41; 95% CI: 0.25–0.66; p 0.05) (Table 4 ). Table 4 .Variables included in the multivariable logistic regression model in individuals with MASLD Variable P-value OR 95% C.I. for OR Lower Upper Age < 0.001 1.027 1.015 1.039 Total Cholesterol (CHOL) 0.047 1.002 1 1.004 HDL < 0.001 0.981 0.974 0.989 History of Breast Cancer 0.044 4.529 1.043 19.665 History of Depression 0.026 1.463 1.047 2.047 Learning Disability 0.038 0.671 0.461 0.978 Food Regurgitation < 0.001 0.416 0.259 0.666 GERD 0.08 1.239 0.975 1.574 Head Trauma History 0.034 1.487 1.03 2.147 Recurring Headaches 0.025 1.314 1.035 1.668 Osteoporosis < 0.001 1.658 1.252 2.197 Joint Pain 0.061 1.216 0.991 1.492 Cigarette Smoking (Type) 0.039 0.772 0.604 0.988 Childhood Smoking Exposure 0.087 0.842 0.692 1.025 Use of Non-Cigarette Tobacco 0.032 1.52 1.037 2.229 Antihypertensive Drug Use 0.031 1.299 1.024 1.649 Insulin Therapy 0.027 2.772 1.12 6.819 Discussion Our study investigated the factors associated with short sleep duration in both non-MASLD individuals and patients with MASLD. In the non-MASLD group, short sleep duration was independently linked to increasing age, higher SGPT levels, lupus, recurring headache, dizziness, and back pain stiffness, while higher HDL levels and WSI by center appeared protective. Among MASLD patients, increasing age and osteoporosis were also significantly associated with short sleep duration, whereas higher HDL levels showed protective effect. These findings suggest that while age and low HDL consistently influence short sleep duration across populations, other risk and protective factors vary between non-MASLD individuals and those with MASLD. In our study, sleep duration was assessed using a self-reported questionnaire that has been widely applied in PERSIAN cohort studies.[ 13 ]. As with all self-reported measures, relying on participants’ subjective responses may have introduced some degree of measurement error. Such error typically biases associations toward the null, potentially underestimating the true strength of the relationships observed. Our findings are partly consistent with the results of recent crosssectional study . Recent studies have demonstrated that patients with MASLD often experience sleep disturbances .Even simple sleep hygiene interventions have not been sufficient to meaningfully improve their sleep, reinforcing the need for comprehensive strategies that integrate metabolic, behavioral, and circadian approaches. Therefore, short sleep duration should be recognized as a clinically relevant feature of MASLD that contributes to disease progression and deserves attention in prevention and treatment strategies.[ 14 ] There is growing recognition that disrupted sleep influences key metabolic pathways, including glucose control and weight gain, both well-established drivers of MASLD. [ 15 ] In our cohort, similar patterns emerged. Insulin resistance can serve as an important biological link between reduced sleep and MASLD pathophysiology. Additionally, sleep disruption has been associated with increased levels of inflammatory mediators and advancing disease severity.[ 16 ] genetic studies further strengthen the idea that sleep disturbance is not simply a consequence of liver dysfunction but may contribute directly to MASLD development. The work by Zijin Sun and colleagues highlights the potential of screening tools such as the Pittsburgh Sleep Quality Index (PSQI) for individuals at risk and suggests that improving sleep may serve as a simple, non-invasive strategy to reduce disease burden [ 17 ] Similar relationships have been observed in other health conditions. Yu et al. identified strong links between sleep-disordered breathing and metabolic syndrome risk. [ 18 ] Meanwhile, studies such as Hu et al. have found poor sleep quality in patients with infective endocarditis, where reduced sleep efficiency correlated negatively with ALT levels ,suggesting hepatic involvement in the relationship [ 19 ] Overall, the sleep MASLD link appears modest but consistent across studies. Different reference groups and evaluation tools make direct comparisons difficult, but recent research increasingly favors global PSQI evaluations to more fully capture sleep health. The associations we observed parallel findings in various patient populations. For instance, Abdallah et al. showed markedly poorer sleep in women with systemic lupus erythematosus, particularly under financial stress [ 20 ]. Martini et al. demonstrated strong associations between migraine and sleep impairment[ 21 ]. Konukseven et al. confirmed that sleep disturbances correlate with dizziness severity and emotional burden[ 22 ]. Awad et al. connected low back pain to poorer sleep and unhealthy habits, positioning sleep as an independent factor in symptom intensity.[ 23 ] In cancer patients, Maroufi et al. found high rates of poor sleep linked with chronic disease and socioeconomic disadvantage [ 24 ]. Finally, Jia et al. emphasized that cardiometabolic status can predict sleep problems, providing a potential clinical tool to guide prevention[ 25 ] . The strengths of our study include: i) a direct comparison between two distinct populations (non-MASLD individuals and patients with MASLD), ii) the consideration of a broad spectrum of clinical and lifestyle factors, iii) the identification of both risk and protective factors for poor sleep quality, and iv) the use of a large, population-based cohort of 10,019 participants, providing robust statistical power. Our study has several limitations. First, MASLD was identified using the Fatty Liver Index (FLI). While this tool is practical for large, population-based studies, it may lead to some degree of misclassification. More accurate methods such as liver biopsy were not an option due to their risks (including bleeding and, rarely, death), as well as concerns about safety, feasibility, and cost-effectiveness in such a large cohort. Second, we did not use liver ultrasonography, the most common non-invasive imaging technique for diagnosing fatty liver. With a sample size of more than 10,000 participants, conducting ultrasounds for everyone was simply not feasible in terms of cost, logistics, and time. Third, the cross-sectional design limits our ability to infer causality between MASLD and short sleep duration. Finally, short sleep duration was assessed using self-reported questionnaires, which may be subject to recall bias and potential misclassification. Future research should adopt longitudinal designs and use objective sleep assessments. Examining lifestyle, metabolic, and psychosocial factors may help clarify causal relationships and identify effective interventions to improve sleep quality in MASLD patients. Conclusions Short sleep duration is a common issue in both healthy individuals and patients with MASLD. Increasing age and lower HDL levels were consistently associated with short sleep duration across both groups. In healthy participants, additional contributors included elevated SGPT, lupus, recurring headaches, dizziness, and back pain stiffness, whereas higher HDL levels and a higher Wealth Score Index (WSI) appeared protective. Modifier factors such as age and HDL influenced how other risk factors impacted sleep duration, highlighting shared mechanisms. These findings underscore the complex, multifactorial nature of short sleep and highlight associations between MASLD and short sleep duration, suggesting that future longitudinal studies are needed to explore potential causal relationships. Abbreviations Abbreviation Definition MASLD Metabolic dysfunction–associated steatotic liver disease FACS Fasa Adult Cohort Study WSI Wealth Score Index HDL High‑density lipoprotein LDL Low‑density lipoprotein ALT Alanine aminotransferase AST Aspartate aminotransferase TG Tiglycerides MET Metabolic equivalent of task OR odds ratio CI Confidence intervals SD Standard deviation Declarations Funding: No funding was received ACKNOWLEDGEMENTS: This article is based on the Master of Public Health (MPH) thesis of Alireza Gharebaghi at Shiraz University of Medical Sciences (Email: [email protected] ). The data used in this thesis were obtained from the Fasa Cohort Study, which was funded by Fasa University of Medical Sciences and supported by the Deputy for Research at the Iranian Ministry of Health. CONFLICT OF INTEREST: None declared. Consent for publication: Not applicable. Ethics approval and consent to participate: The study adhered to the Declaration of Helsinki and Iran’s National Ethical Guidelines in Biomedical Research. It was approved by the Ethics Committee of Fasa University of Medical Sciences (enrollment: IR.FUMS.REC.1394.3; follow‑up: IR.FUMS.REC.1395.177). Written informed consent was obtained from all participants; for illiterate individuals, forms were read aloud and confirmed with fingerprints and a family member’s signature. Participants could withdraw at any time. Data were anonymized and securely stored to ensure confidentiality and ethical compliance. Availability of data and materials: The datasets used and analyzed during this study are available from the corresponding author upon reasonable request and with permission from the Fasa Cohort Study team. Further details on the study design and data collection procedures are described in the cohort profile publication by Homayounfar et al. [13]. 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Poor Sleep Quality and Its Influencing Factors Among Iranian Patients with Esophageal and Gastric Cancer. Middle East J Dig Dis. 2024;16(1):39–46. Jia M, Li M. Association of cardiometabolic index with sleep quality in adults: a population–based study. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8331697","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":561794831,"identity":"63152a85-e71c-42a2-98ad-bbd0fc28fa23","order_by":0,"name":"Alireza Gharebaghi","email":"","orcid":"","institution":"Shiraz University of Medical Sciences, Shiraz, Iran.","correspondingAuthor":false,"prefix":"","firstName":"Alireza","middleName":"","lastName":"Gharebaghi","suffix":""},{"id":561794833,"identity":"2c09f917-6cb3-46ec-8810-99cb85023fdb","order_by":1,"name":"Hadi Raeisi Shahraki","email":"","orcid":"","institution":"Shahrekord University of Medical Sciences, Shahrekord, Iran","correspondingAuthor":false,"prefix":"","firstName":"Hadi","middleName":"Raeisi","lastName":"Shahraki","suffix":""},{"id":561794836,"identity":"34acda20-de8f-4cfc-88e2-929903985f90","order_by":2,"name":"Reza Homayounfar","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4UlEQVRIiWNgGAWjYFACHhiD8QEDQwUDgwEJWpiBis+QrIWxjQgt5g28Bx/dqDksZ3C7mfFz5bzD8ubszQcYflRsw6lF5gBfsnHOscPGBncOM0ue3XbYcGfPsQTGnjO3cWqRYOAxk85hO5y44Ub+AcnGbYcZN9zIMWBmbCOk5R9ISzLzz8Y5h+2J05LbBtbCJtnYAGIQ1mJsnNuXbiwJ1GLZcCw9ecOZYwkHCfjF8HHON2s5PqDDbjbUWNtuON588MGPCtxaGOQfgMhmGBfCOIBbPRzUYTBGwSgYBaNgFMABADeIWO6GKXmmAAAAAElFTkSuQmCC","orcid":"","institution":"Shahid Beheshti University of Medical Sciences, Tehran, Iran","correspondingAuthor":true,"prefix":"","firstName":"Reza","middleName":"","lastName":"Homayounfar","suffix":""},{"id":561794841,"identity":"f6e62977-a302-4212-ac9a-efbec310849d","order_by":3,"name":"Behnam Honarvar","email":"","orcid":"","institution":"Shiraz University of Medical Sciences, Shiraz, Iran.","correspondingAuthor":false,"prefix":"","firstName":"Behnam","middleName":"","lastName":"Honarvar","suffix":""},{"id":561794847,"identity":"82d13087-e23d-4bfd-92bc-86f609a207d9","order_by":4,"name":"Fatemeh Rostamian","email":"","orcid":"","institution":"Fasa University of Medical Sciences, Fasa, Iran","correspondingAuthor":false,"prefix":"","firstName":"Fatemeh","middleName":"","lastName":"Rostamian","suffix":""},{"id":561794849,"identity":"5c9810c0-bd21-4308-9955-38b0ff3e73ef","order_by":5,"name":"Sayed Reza Hojati","email":"","orcid":"","institution":"Fasa University of Medical Sciences, Fasa, 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16:27:34","extension":"html","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":192262,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8331697/v1/6f8efdc2bdcee8fbcb867964.html"},{"id":99311727,"identity":"d9acb458-dc8f-447e-b89a-2561ae57d795","added_by":"auto","created_at":"2025-12-31 16:16:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1298568,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8331697/v1/e5c21a19-0083-41de-9855-b28f9e579ae8.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Short sleep duration and its Determinants in MASLD and Non-MASLD: A Population-Based Cohort Study from Iran","fulltext":[{"header":"Introduction ","content":"\u003cp\u003eMetabolic dysfunction\u0026ndash;associated steatotic liver disease (MASLD), previously termed non-alcoholic fatty liver disease (NAFLD), is now recognized as a distinct clinical entity within the spectrum of steatotic liver diseases. It is defined as hepatic steatosis in the presence of at least one cardiometabolic risk factor, in the absence of harmful alcohol consumption. MASLD has emerged as one of the most prevalent liver disorders worldwide, with rates increasing in parallel with obesity and type 2 diabetes mellitus. [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eThe liver plays a pivotal role in lipid metabolism, converting carbohydrates into triglycerides and cholesterol for energy storage and use. When this balance is disrupted, conditions such as fatty liver, hyperlipidemia, and diabetes may develop. With the global decline of viral hepatitis due to vaccination programs and effective antiviral therapies, MASLD has emerged as a leading cause of chronic liver disease and its end-stage complications, including cirrhosis and hepatocellular carcinoma (HCC). MASLD often begins as simple steatosis and may progress to metabolic dysfunction\u0026ndash;associated steatohepatitis (MASH). Approximately one-quarter of patients eventually advance to more severe stages marked by inflammation and fibrosis.[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eThe pathogenesis of MASLD is multifactorial, with strong links to obesity, insulin resistance, and metabolic syndrome, while genetic and environmental influences add further complexity to its management. Although lifestyle interventions, particularly dietary modification and regular physical activity, remain the cornerstone of treatment, the growing global burden of MASLD highlights the pressing need for novel therapeutic strategies[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSleep disturbances, particularly short sleep duration, are closely associated with insulin resistance, glucose dysregulation, obesity, type 2 diabetes, and metabolic syndrome, all of which contribute to an increased risk of MASLD. Short sleep, which affects an estimated 20\u0026ndash;40% of adults, is frequently linked to chronic health conditions .[\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eThe Fatty Liver Index (FLI) is a simple and useful tool for estimating the likelihood of fatty liver. It is calculated using BMI, waist circumference, triglycerides, and GGT. An FLI of 60 or higher suggests a high chance of having hepatic steatosis, based on the original validation work. [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] Jeong et al. also showed that FLI performs very well as a diagnostic marker, with an AUC of 0.870.[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eGrowing evidence suggests a strong association between MASLD and sleep disturbances. Short sleep duration is commonly reported among MASLD patients, likely mediated by shared mechanisms such as obesity, metabolic dysregulation, and systemic inflammation. [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eWith its growing prevalence and widespread systemic effects, MASLD has become a significant global health challenge. To improve outcomes and develop effective targeted interventions, it is essential to better understand its complex interactions with lifestyle, metabolic, and behavioral factors. In this context, the present study evaluated sleep duration by comparing the amount of sleep between individuals with and without MASLD, aiming to clarify the potential contribution of reduced sleep to the disease.\u003c/p\u003e"},{"header":"Methods ","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eThe Fasa Adult Cohort Study\u003c/h2\u003e \u003cp\u003eThis cross-sectional study draws on data from the Fasa Adult Cohort Study (FACS), a branch of the Prospective Epidemiological Research Studies in Iran (PERSIAN). Initiated in 2014 in the Sheshdeh and Qarabolagh districts of Fasa, Fars Province, the study enrolled 10,115 participants aged 35\u0026ndash;70 years, with a planned 20-year follow-up. Fasa, a city of around 205,000 residents representing Persian, Arab, and Turkish ethnic groups, is located in a temperate semi-arid region. The cohort includes both urban and rural populations across two towns and 22 villages. By 2021, four follow-ups had been completed, with the latest reassessment launched in September 2021. The study protocols were reviewed and approved by the Ethics Committee of Fasa University of Medical Sciences (enrollment: IR.FUMS.REC.1394.3; follow-up: IR.FUMS.REC.1395.177) [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy sample\u003c/h3\u003e\n\u003cp\u003eParticipants were excluded if they: (1) did not provide consent for examinations, diagnostic procedures, or use of their data in the study; or (2) had missing essential information, such as key variables including body mass index (BMI), blood pressure, fasting plasma glucose, liver function tests, or blood lipid levels.or (3)History of excessive alcohol consumption, viral hepatitis, or chronic liver disease.or (4) Pregnant or breastfeeding women.\u003c/p\u003e \u003cp\u003eAfter applying these exclusion criteria, a total of 10,019 participants remained for further analysis.\u003c/p\u003e\n\u003ch3\u003eSociodemographic and lifestyle variables\u003c/h3\u003e\n\u003cp\u003eSociodemographic data, including ethnicity and the Wealth Score Index (WSI), were obtained through the FACS general questionnaire. Lifestyle factors such as smoking status and drug use were collected using medical questionnaires.\u003c/p\u003e\n\u003ch3\u003eAnthropometric and clinical variables\u003c/h3\u003e\n\u003cp\u003eAnthropometric measurements included height (measured with a wall stadiometer), weight (using an analog scale), and waist, hip, and wrist circumferences (using a standard tape). Blood pressure was measured twice in both arms at 15-minute intervals with a standard sphygmomanometer, and the average of the two readings was recorded. Biochemical analyses were performed on blood serum samples using a Pars Azmoon kit to assess fasting blood glucose, total cholesterol, high-density lipoprotein (HDL), low-density lipoprotein (LDL), alanine aminotransferase (ALT), aspartate aminotransferase (AST), and triglycerides (TG).\u003c/p\u003e\n\u003ch3\u003eMASLD Diagnosis\u003c/h3\u003e\n\u003cp\u003eMASLD status was assessed using the Fatty Liver Index (FLI), a validated algorithm incorporating body mass index (BMI), waist circumference, triglyceride levels, and gamma-glutamyl transferase (GGT). Participants with an FLI score\u0026thinsp;\u0026ge;\u0026thinsp;60 were classified as having MASLD, whereas those with a score\u0026thinsp;\u0026lt;\u0026thinsp;30 were considered free of the condition. Individuals with intermediate values (FLI 30\u0026ndash;59) were classified into the non-MASLD group.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSleep Duration\u003c/h2\u003e \u003cp\u003eSleep duration was assessed by self-report. Participants reporting an average sleep duration of less than six hours per night were classified as having short sleep duration.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003evariables were summarized as means with standard deviations (SD), and categorical variables as frequencies and percentages. In univariate analyses, variables with a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.1 were selected as candidates for further modeling. These variables were then entered into multivariable logistic regression models with a backward elimination approach to identify independent factors associated with short sleep duration in each study group .Adjusted odds ratios (ORs) with 95% confidence intervals (CIs) were reported, and a two-sided \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. All analyses were conducted using IBM SPSS Statistics 29.0.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eBaseline characteristics of participants\u003c/h2\u003e \u003cp\u003eAmong the 10,019 participants, 4,528 (45.1%) were men, and 2,601 individuals (949 men and 1,652 women) were diagnosed with MASLD. The prevalence of short sleep duration was 18.1% among non-MASLD individuals and 21.1% among participants with MASLD. Compared with their non-MASLD counterparts, participants with MASLD had a markedly higher fatty liver index (77.5 vs. 25.6) and, on average, higher BMI (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD: 31.01\u0026thinsp;\u0026plusmn;\u0026thinsp;3.81), systolic blood pressure (117.28\u0026thinsp;\u0026plusmn;\u0026thinsp;19.16), and diastolic blood pressure (78.55\u0026thinsp;\u0026plusmn;\u0026thinsp;12.27) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). They also showed elevated metabolic markers, including total cholesterol (189.9\u0026thinsp;\u0026plusmn;\u0026thinsp;60.0), triglycerides (180.5\u0026thinsp;\u0026plusmn;\u0026thinsp;119.2), SGOT (22.62\u0026thinsp;\u0026plusmn;\u0026thinsp;11.14), and SGPT (27.53\u0026thinsp;\u0026plusmn;\u0026thinsp;18.12) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In addition, the prevalence of type 2 diabetes (19.4%) and hypertension (31.8%) was considerably higher in the MASLD group compared with the healthy group (9.7% and 15.7%, respectively) .\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAnthropometric and Clinical Characteristics of Participants With and Without MASLD (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, p-values)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003egroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSleep.\u003c/p\u003e \u003cp\u003edisorder\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eStd. Deviation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"19\" rowspan=\"20\"\u003e \u003cp\u003eNon-MASLD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e48.0690\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.72622\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e50.0926\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.44263\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHeight (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e161.5851\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e12.03827\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e161.5098\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e14.59982\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWeight (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e61.9979\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10.49221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e62.1573\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11.29472\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWaist circumference (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e88.2247\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.85515\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e88.1994\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11.17138\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHip circumference (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e96.2222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.18386\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e96.0076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.47773\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWrist circumference (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e16.3442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.40148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e16.3400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.70204\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBody mass index (BMI, kg/m\u0026sup2;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23.6434\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.68243\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23.5909\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.82806\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDiastolic blood pressure\u003c/p\u003e \u003cp\u003e(mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e73.2663\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11.75583\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e72.8989\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11.41586\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSystolic blood pressure\u003c/p\u003e \u003cp\u003e(mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e109.1912\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e18.04882\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e108.9715\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e17.61772\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePulse rate\u003c/p\u003e \u003cp\u003e(beats/min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e73.4331\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10.95001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e72.5734\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10.45165\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"19\" rowspan=\"20\"\u003e \u003cp\u003eMASLD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e48.5052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.11406\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e51.3596\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.00491\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHeight (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e160.8630\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.75251\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e161.0104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.29456\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWeight (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e80.2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11.61976\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e80.5804\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11.52625\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWaist circumference (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e105.7955\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.81202\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e106.4581\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.24239\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHip circumference (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e108.1947\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.23875\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e108.2061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.02888\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWrist circumference (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17.6381\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.35978\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17.7198\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.39368\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBody mass index (BMI, kg/m\u0026sup2;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e31.0000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.86450\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e31.0759\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.61568\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDiastolic blood pressure\u003c/p\u003e \u003cp\u003e( mmHg(\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e78.5611\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e12.45879\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e78.5246\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11.58996\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSystolic blood pressure (mmHg(\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e117.1971\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e19.28289\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e117.9544\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e18.67448\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePulse rate (PR, beats/min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e76.1482\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10.69606\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e76.0211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10.66668\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLipid Profile, Liver Enzymes, and Fatty Liver Index in MASLD and Non-MASLD Groups (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, p-values)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003egroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSleep.\u003c/p\u003e \u003cp\u003edisorder\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eStd. Deviation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"23\" rowspan=\"24\"\u003e \u003cp\u003eNon-MASLD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTriglycerides (TG, mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e104.4079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e57.53569\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e102.5929\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e57.98691\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal cholesterol (CHOL, mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e170.2276\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e55.61068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e166.2865\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e57.50080\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSerum glutamic-oxaloacetic transaminase (SGOT, U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e20.6822\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.01758\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e20.7244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.15624\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSerum glutamic-pyruvic transaminase (SGPT, U/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e19.8056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e12.41205\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e20.4823\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e14.37105\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAlkaline phosphatase (ALP, U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e193.2314\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e80.71790\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e193.9687\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e79.09456\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHigh-density lipoprotein cholesterol (HDL, mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e49.8995\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e20.55815\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e46.3093\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e17.84005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLow-density lipoprotein cholesterol (LDL, mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e99.3996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e39.48142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e99.4586\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e40.56633\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGamma-glutamyl transferase (GGT, U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e18.1007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e16.22681\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e18.6258\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e16.23210\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFatty Liver Index (FLI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e25.5651\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e16.96695\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26.1851\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e17.28459\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMetabolic equivalent of task (MET, final score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e42.0217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11.59085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e43.3803\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e12.87333\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWealth Score Index (total\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.9255\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.88017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.8427\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.87633\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWealth Score Index (by center)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.0579\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.00295\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.0030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.00437\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"23\" rowspan=\"24\"\u003e \u003cp\u003eMASLD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTriglycerides (TG, mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e181.0429\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e117.54526\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e178.1454\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e125.12739\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal cholesterol (CHOL, mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e191.0882\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e59.24353\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e185.6165\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e62.23671\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSerum glutamic-oxaloacetic transaminase (SGOT, U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e22.6783\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10.99795\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e22.4009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11.74413\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSerum glutamic-pyruvic transaminase (SGPT, U/LT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e27.6956\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e18.23192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26.5598\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e17.63529\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAlkaline phosphatase (ALP, U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e210.5635\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e79.69420\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e210.1630\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e124.72348\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHigh-density lipoprotein cholesterol (HDL, mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e47.2728\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e18.85035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e42.8175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e16.03805\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLow-density lipoprotein cholesterol (LDL, mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e107.5681\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e42.78271\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e107.1695\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e43.54445\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGamma-glutamyl transferase (GGT, U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e30.1759\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e26.25463\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e30.9425\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e34.39023\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFatty Liver Index (FLI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e77.2994\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10.94110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e78.5077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10.94236\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMetabolic equivalent of task (MET, final score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e39.1290\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.70706\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e39.3631\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.58557\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWealth Score Index (total\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.7587\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.84681\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.6971\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.86329\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWealth Score Index (by center)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.1171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.96892\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.1614\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.00666\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eMultivariable Logistic Regression Analysis of Factors Associated with sleep duration\u003c/h2\u003e \u003cp\u003eIn the multivariable logistic regression analysis, variables with a univariate p-value below 0.1 were entered into the model. Using a backward elimination approach, we identified several factors that were independently associated with short sleep duration.\u003c/p\u003e \u003cp\u003ethe following demographic, clinical, and lifestyle factors met the inclusion criteria and were entered into the multivariable model:\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eDemographics\u003c/strong\u003e \u003cp\u003eethnicity, gender.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCardiometabolic conditions\u003c/strong\u003e \u003cp\u003ediabetes, hypertension, cardiac disease, myocardial infarction (MI), stroke, renal failure, chronic lung disease, thyroid disease, kidney stones, gallstones, rheumatic disease.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCancer history\u003c/strong\u003e \u003cp\u003eskin, breast, stomach, colorectal, bladder, esophageal, prostate, lung, brain ,and CNS cancers, as well as laryngeal, tongue, uterine, and ovarian cancers.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eNeurological and psychiatric disorders\u003c/strong\u003e \u003cp\u003eepilepsy, chronic headaches, depression, psychiatric disorders, learning disabilities, amnesia, multiple sclerosis (MS), history of cardiovascular disease, thought disorders.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eAutoimmune and inflammatory diseases\u003c/strong\u003e \u003cp\u003elupus, rheumatoid arthritis.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eSymptoms and physical conditions\u003c/strong\u003e \u003cp\u003esternum irritation, swelling, urinary changes, abnormal urine tests, gastrointestinal symptoms (heartburn, food regurgitation, gastroesophageal reflux disease, bloating, changes in bowel movement interval, blood in stool, weight loss, jaundice), respiratory symptoms (cough, shortness of breath), gait problems, fainting, visual impairment, muscle weakness, movement disorders, numbness, head trauma, recurring headaches, dizziness, tinnitus.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eMusculoskeletal issues\u003c/strong\u003e \u003cp\u003efracture history (including hip femoral fracture), osteoporosis, back pain, joint pain, with or without stiffness.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eOther health conditions\u003c/strong\u003e \u003cp\u003eaphthous ulcers (oral and genital).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eLifestyle and medication use\u003c/strong\u003e \u003cp\u003esmoking (cigarette and non-cigarette forms, including exposure at home, workplace, and childhood), drug use, and use of antihypertensive drugs, oral diabetes medications, insulin, statins, and anti-triglyceride drugs.\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eMultivariable Logistic Regression Results\u003c/h2\u003e \u003cp\u003eIn the Non-MASLD group, logistic regression analysis showed that increasing age (OR\u0026thinsp;=\u0026thinsp;1.02; 95% CI: 1.01\u0026ndash;1.03; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), higher SGPT levels (OR\u0026thinsp;=\u0026thinsp;1.007; 95% CI: 1.00\u0026ndash;1.01; p\u0026thinsp;=\u0026thinsp;0.003), lupus (OR\u0026thinsp;=\u0026thinsp;9.00; 95% CI: 2.07\u0026ndash;39.12; p\u0026thinsp;=\u0026thinsp;0.003), recurring headaches (OR\u0026thinsp;=\u0026thinsp;1.34; 95% CI: 1.15\u0026ndash;1.56; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), dizziness (OR\u0026thinsp;=\u0026thinsp;1.25; 95% CI: 1.07\u0026ndash;1.45; p\u0026thinsp;=\u0026thinsp;0.05), back pain/stiffness (OR\u0026thinsp;=\u0026thinsp;1.23; 95% CI: 1.09\u0026ndash;1.40; p\u0026thinsp;=\u0026thinsp;0.01), and higher total WSI scores (OR\u0026thinsp;=\u0026thinsp;2.91; 95% CI: 2.07\u0026ndash;4.10; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were independently associated with a greater likelihood of short sleep duration. In contrast, higher HDL (OR\u0026thinsp;=\u0026thinsp;0.98; 95% CI: 0.98\u0026ndash;0.99; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and WSI by center (OR\u0026thinsp;=\u0026thinsp;0.45; 95% CI: 0.33\u0026ndash;0.60; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were linked to a reduced likelihood of short sleep duration. Other factors were not statistically significant (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eVariables included in the multivariable logistic regression model in individuals without MASLD\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e95% C.I. for OR\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLower\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUpper\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetabolic equivalent of task Score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of Missing Teeth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal WSI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.916\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCenter-specific WSI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.334\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.606\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGranulocyte count\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.992\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBUN (Blood Urea Nitrogen)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALT (SGPT)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.988\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.984\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.992\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of HSC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.395\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.702\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e177.825\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepression (Yes/No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.998\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.601\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLupus (Yes/No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e39.129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFood Regurgitation (Yes/No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.802\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.626\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRecurring Headaches (Yes/No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.343\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.565\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDizziness (Yes/No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.071\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.459\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBack Pain with Stiffness (Yes/No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.238\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.093\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.403\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMouth Aphthous Ulcers (Yes/No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.434\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.951\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcohol Use (Yes/No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.301\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.678\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAmong MASLD patients, increasing age (OR\u0026thinsp;=\u0026thinsp;1.02; 95% CI: 1.01\u0026ndash;1.03; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and osteoporosis (OR\u0026thinsp;=\u0026thinsp;1.65; 95% CI: 1.25\u0026ndash;2.19; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were significantly associated with short sleep duration. Conversely, higher HDL (OR\u0026thinsp;=\u0026thinsp;0.98; 95% CI: 0.97\u0026ndash;0.98; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and food regurgitation (OR\u0026thinsp;=\u0026thinsp;0.41; 95% CI: 0.25\u0026ndash;0.66; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were protective factors. Other variables were not statistically significant (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e.Variables included in the multivariable logistic regression model in individuals with MASLD\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e95% C.I. for OR\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLower\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUpper\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.039\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal Cholesterol (CHOL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.981\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.974\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.989\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of Breast Cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.529\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e19.665\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of Depression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.463\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.047\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLearning Disability\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.671\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.461\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.978\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFood Regurgitation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.416\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.259\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.666\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGERD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.239\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.975\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.574\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHead Trauma History\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.487\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.147\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRecurring Headaches\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.314\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.668\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOsteoporosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.658\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.252\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.197\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJoint Pain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.991\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.492\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCigarette Smoking (Type)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.772\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.604\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.988\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChildhood Smoking Exposure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.087\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.842\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.692\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.025\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUse of Non-Cigarette Tobacco\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.229\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntihypertensive Drug Use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.649\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInsulin Therapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.772\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.819\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur study investigated the factors associated with short sleep duration in both non-MASLD individuals and patients with MASLD. In the non-MASLD group, short sleep duration was independently linked to increasing age, higher SGPT levels, lupus, recurring headache, dizziness, and back pain stiffness, while higher HDL levels and WSI by center appeared protective. Among MASLD patients, increasing age and osteoporosis were also significantly associated with short sleep duration, whereas higher HDL levels showed protective effect. These findings suggest that while age and low HDL consistently influence short sleep duration across populations, other risk and protective factors vary between non-MASLD individuals and those with MASLD.\u003c/p\u003e \u003cp\u003eIn our study, sleep duration was assessed using a self-reported questionnaire that has been widely applied in PERSIAN cohort studies.[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. As with all self-reported measures, relying on participants\u0026rsquo; subjective responses may have introduced some degree of measurement error. Such error typically biases associations toward the null, potentially underestimating the true strength of the relationships observed. Our findings are partly consistent with the results of recent crosssectional study .\u003c/p\u003e \u003cp\u003eRecent studies have demonstrated that patients with MASLD often experience sleep disturbances .Even simple sleep hygiene interventions have not been sufficient to meaningfully improve their sleep, reinforcing the need for comprehensive strategies that integrate metabolic, behavioral, and circadian approaches. Therefore, short sleep duration should be recognized as a clinically relevant feature of MASLD that contributes to disease progression and deserves attention in prevention and treatment strategies.[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] There is growing recognition that disrupted sleep influences key metabolic pathways, including glucose control and weight gain, both well-established drivers of MASLD. [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] In our cohort, similar patterns emerged. Insulin resistance can serve as an important biological link between reduced sleep and MASLD pathophysiology. Additionally, sleep disruption has been associated with increased levels of inflammatory mediators and advancing disease severity.[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] genetic studies further strengthen the idea that sleep disturbance is not simply a consequence of liver dysfunction but may contribute directly to MASLD development. The work by Zijin Sun and colleagues highlights the potential of screening tools such as the Pittsburgh Sleep Quality Index (PSQI) for individuals at risk and suggests that improving sleep may serve as a simple, non-invasive strategy to reduce disease burden [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eSimilar relationships have been observed in other health conditions. Yu et al. identified strong links between sleep-disordered breathing and metabolic syndrome risk. [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] Meanwhile, studies such as Hu et al. have found poor sleep quality in patients with infective endocarditis, where reduced sleep efficiency correlated negatively with ALT levels ,suggesting hepatic involvement in the relationship [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] Overall, the sleep MASLD link appears modest but consistent across studies. Different reference groups and evaluation tools make direct comparisons difficult, but recent research increasingly favors global PSQI evaluations to more fully capture sleep health. The associations we observed parallel findings in various patient populations. For instance, Abdallah et al. showed markedly poorer sleep in women with systemic lupus erythematosus, particularly under financial stress [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMartini et al. demonstrated strong associations between migraine and sleep impairment[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eKonukseven et al. confirmed that sleep disturbances correlate with dizziness severity and emotional burden[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAwad et al. connected low back pain to poorer sleep and unhealthy habits, positioning sleep as an independent factor in symptom intensity.[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] In cancer patients, Maroufi et al. found high rates of poor sleep linked with chronic disease and socioeconomic disadvantage [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Finally, Jia et al. emphasized that cardiometabolic status can predict sleep problems, providing a potential clinical tool to guide prevention[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] .\u003c/p\u003e \u003cp\u003eThe strengths of our study include: i) a direct comparison between two distinct populations (non-MASLD individuals and patients with MASLD), ii) the consideration of a broad spectrum of clinical and lifestyle factors, iii) the identification of both risk and protective factors for poor sleep quality, and iv) the use of a large, population-based cohort of 10,019 participants, providing robust statistical power. Our study has several limitations. First, MASLD was identified using the Fatty Liver Index (FLI). While this tool is practical for large, population-based studies, it may lead to some degree of misclassification. More accurate methods such as liver biopsy were not an option due to their risks (including bleeding and, rarely, death), as well as concerns about safety, feasibility, and cost-effectiveness in such a large cohort. Second, we did not use liver ultrasonography, the most common non-invasive imaging technique for diagnosing fatty liver. With a sample size of more than 10,000 participants, conducting ultrasounds for everyone was simply not feasible in terms of cost, logistics, and time. Third, the cross-sectional design limits our ability to infer causality between MASLD and short sleep duration. Finally, short sleep duration was assessed using self-reported questionnaires, which may be subject to recall bias and potential misclassification.\u003c/p\u003e \u003cp\u003eFuture research should adopt longitudinal designs and use objective sleep assessments. Examining lifestyle, metabolic, and psychosocial factors may help clarify causal relationships and identify effective interventions to improve sleep quality in MASLD patients.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eShort sleep duration is a common issue in both healthy individuals and patients with MASLD. Increasing age and lower HDL levels were consistently associated with short sleep duration across both groups. In healthy participants, additional contributors included elevated SGPT, lupus, recurring headaches, dizziness, and back pain stiffness, whereas higher HDL levels and a higher Wealth Score Index (WSI) appeared protective. Modifier factors such as age and HDL influenced how other risk factors impacted sleep duration, highlighting shared mechanisms. These findings underscore the complex, multifactorial nature of short sleep and highlight associations between MASLD and short sleep duration, suggesting that future longitudinal studies are needed to explore potential causal relationships.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"638\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 253px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAbbreviation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 385px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDefinition\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 253px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMASLD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 385px;\"\u003e\n \u003cp\u003eMetabolic dysfunction\u0026ndash;associated steatotic liver disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 253px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFACS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 385px;\"\u003e\n \u003cp\u003eFasa Adult Cohort Study\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 253px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWSI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 385px;\"\u003e\n \u003cp\u003eWealth Score Index\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 253px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHDL\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 385px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHigh‑density lipoprotein\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 253px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLDL\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 385px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLow‑density lipoprotein\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 253px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eALT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 385px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAlanine aminotransferase\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 253px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAST\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 385px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAspartate aminotransferase\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 253px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 385px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTiglycerides\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 253px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMET\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 385px;\"\u003e\n \u003cp\u003eMetabolic equivalent of task\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 253px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 385px;\"\u003e\n \u003cp\u003eodds ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 253px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 385px;\"\u003e\n \u003cp\u003eConfidence intervals\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 253px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 385px;\"\u003e\n \u003cp\u003eStandard deviation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding was received\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eACKNOWLEDGEMENTS:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis article is based on the Master of Public Health (MPH) thesis of \u003cem\u003eAlireza Gharebaghi\u003c/em\u003e at Shiraz University of Medical Sciences (Email: [email protected]). The data used in this thesis were obtained from the Fasa Cohort Study, which was funded by Fasa University of Medical Sciences and supported by the Deputy for Research at the Iranian Ministry of Health.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCONFLICT OF INTEREST: \u003c/strong\u003eNone declared.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e\u0026nbsp;Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study adhered to the Declaration of Helsinki and Iran\u0026rsquo;s National Ethical Guidelines in Biomedical Research. It was approved by the Ethics Committee of Fasa University of Medical Sciences (enrollment: IR.FUMS.REC.1394.3; follow‑up: IR.FUMS.REC.1395.177). Written informed consent was obtained from all participants; for illiterate individuals, forms were read aloud and confirmed with fingerprints and a family member\u0026rsquo;s signature. Participants could withdraw at any time. Data were anonymized and securely stored to ensure confidentiality and ethical compliance.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and analyzed during this study are available from the corresponding author upon reasonable request and with permission from the Fasa Cohort Study team. Further details on the study design and data collection procedures are described in the cohort profile publication by Homayounfar et al. \u0026nbsp;[13]. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eR. H. and B. H. conceived the research topic, explored that idea, supervised the project, analyzed the data and drafted the manuscript.\u003c/p\u003e\n\u003cp\u003eR.H. , B. H. , A. GH., H. R.SH. , F. R. and S. R. H. provided critical review and participated in data analysis and writing. All authors reviewed the manuscript.\u003cbr\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSeo Y, et al. Weekend catch-up sleep is associated with the alleviation of non-alcoholic fatty liver disease. Ann Hepatol. 2022;27(3):100690.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLuong TV, et al. Integrating liver and heart health: Cardiovascular risk reduction in patients with metabolic-associated steatotic liver disease. World J Cardiol. 2025;17(7):107751.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBu LF, et al. Non-alcoholic fatty liver disease and sleep disorders. World J Hepatol. 2024;16(3):304\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang M et al. MASLD: insights on the role of folate in hepatic lipid metabolism. Front Nutr, 2025. Volume 12\u0026ndash;2025.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSyed-Abdul MM. Lipid Metabolism in Metabolic-Associated Steatotic Liver Disease (MASLD). Metabolites, 2023. 14(1).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi Y et al. \u003cem\u003eUpdated mechanisms of MASLD pathogenesis.\u003c/em\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim Y et al.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFan H, et al. Investigating the Association Between Seven Sleep Traits and Nonalcoholic Fatty Liver Disease: Observational and Mendelian Randomization Study. Frontiers in Genetics; 2022. pp. 13\u0026ndash;2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eG\u0026uuml;ray C. \u003cem\u003eNon-alcoholic fatty liver disease and sleep quality: a single center cross-sectional survey study.\u003c/em\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGonzalez C, Uribe M, Chavez-Tapia NC. \u003cem\u003eClinical and molecular implications of antipsychotics in MASLD.\u003c/em\u003e Annals of Hepatology, 2025: p. 102158.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJeong S, et al. Development of a simple nonalcoholic fatty liver disease scoring system indicative of metabolic risks and insulin resistance. Annals Translational Med. 2020;8(21):1414.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLu C et al. Adverse events of pharmacological interventions for insomnia disorder in adults: a systematic review and network meta-analysis. Front Psychiatry, 2025. Volume 16\u0026ndash;2025.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHomayounfar R, et al. Cohort Profile: The Fasa Adults Cohort Study (FACS): a prospective study of non-communicable diseases risks. Int J Epidemiol. 2023;52(3):e172\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchaeffer S et al. Significant nocturnal wakefulness after sleep onset in metabolic dysfunction\u0026ndash;associated steatotic liver disease. Front Netw Physiol, 2024. Volume 4\u0026ndash;2024.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStenvers DJ, et al. Circadian clocks and insulin resistance. Nat Rev Endocrinol. 2019;15(2):75\u0026ndash;89.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarjot T, et al. Sleep and liver disease: a bidirectional relationship. Lancet Gastroenterol Hepatol. 2021;6(10):850\u0026ndash;63.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSun Z et al. Causal relationship between nonalcoholic fatty liver disease and different sleep traits: a bidirectional Mendelian randomized study. Front Endocrinol, 2023. Volume 14\u0026ndash;2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYu T, et al. Association Between Obstructive Sleep Apnea and Non-Alcoholic Fatty Liver Disease: Epidemiological Cross-Sectional Study and Mendelian Randomization Analysis. Nat Sci Sleep. 2025;17:1361\u0026ndash;76.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHu XM, et al. The Assessment of Sleep Quality in Patients Following Valve Repair and Valve Replacement for Infective Endocarditis: A Retrospective Study at a Single Center. Med Sci Monit. 2021;27:e930596.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbdallah K, et al. Financial Hardship and Sleep Quality Among Black American Women With and Without Systemic Lupus Erythematosus. Psychosom Med. 2024;86(4):315\u0026ndash;23.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMartini N et al. \u003cem\u003eExploring the symptoms and sleep disorders associated with migraines in women of Syria: A cross-sectional observational study.\u003c/em\u003e Health Sci Rep, 2024. 7(4): p. e2070.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKonukseven \u0026Ouml;, Sa\u0026ccedil;lı Y, K\u0026uuml;\u0026ccedil;\u0026uuml;k A, Ceyhan. Can Dizziness Be Related to Insomnia Severity and Sleep Quality in Young Adults? Turk Arch Otorhinolaryngol. 2025;63(2):80\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAwad MYH, et al. Prevalence of lower back pain and its associations with lifestyle behaviors among university students in the West Bank, Palestine: a cross-sectional study. Ann Med. 2025;57(1):2522974.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMaroufi N, et al. Poor Sleep Quality and Its Influencing Factors Among Iranian Patients with Esophageal and Gastric Cancer. Middle East J Dig Dis. 2024;16(1):39\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJia M, Li M. \u003cem\u003eAssociation of cardiometabolic index with sleep quality in adults: a population\u0026ndash;based study.\u003c/em\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"MASLD, NAFLD, non alcoholic fatty liver disease, Short sleep duration, Sleep disturbance","lastPublishedDoi":"10.21203/rs.3.rs-8331697/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8331697/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e\u003cbr\u003e\nMetabolic dysfunction–associated steatotic liver disease (MASLD) affects about 25–30% of adults and is linked to obesity, diabetes, and metabolic syndrome. Sleep disturbance, especially short sleep duration, is common in this population. This study examined the association between MASLD and short sleep.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e\u003cbr\u003e\nWe analyzed 10,019 adults (35–70 years) from the Fasa Adult Cohort Study, part of the PERSIAN cohort. MASLD was identified by the Fatty Liver Index (FLI). Sleep duration was self-reported, with short sleep defined as \u0026lt;6 hours per night. Logistic regression identified factors associated with short sleep.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e\u003cbr\u003e\nAmong 10,019 participants, 2,601 (25.9%) had MASLD. Compared with non-MASLD individuals, they had higher BMI, blood pressure, metabolic markers, and more diabetes and hypertension. In non-MASLD, short sleep was associated with age, SGPT, lupus, headache, dizziness, and back pain, while higher HDL and WSI were protective. In MASLD, short sleep was linked to age and osteoporosis, whereas higher HDL and food regurgitation were protective.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e\u003cbr\u003e\nShort sleep was common in both MASLD and non-MASLD adults. Age and low HDL consistently contributed, while other factors differed between groups, highlighting the multifactorial nature of sleep disturbance in MASLD.\u003c/p\u003e","manuscriptTitle":"Short sleep duration and its Determinants in MASLD and Non-MASLD: A Population-Based Cohort Study from Iran","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-18 16:27:29","doi":"10.21203/rs.3.rs-8331697/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"48992879-0944-4374-8e58-2dc393cb15d5","owner":[],"postedDate":"December 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-12-24T14:53:58+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-18 16:27:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8331697","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8331697","identity":"rs-8331697","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}