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World J Hepatol. Nov 27, 2025; 17(11): 111995
Published online Nov 27, 2025. doi: 10.4254/wjh.v17.i11.111995
Metabolic associated steatotic liver disease in Qatar: Analysis of dietary patterns and nutrient intake
Joud Alalwani, Reema Tayyem, Maya Bassil, Department of Nutrition Sciences, College of Health Sciences, QU Health, Qatar University, Doha 0000, Qatar
Moutaz Derbala, Division of Gastroenterology, Department of Medicine, Hamad Medical Corporation, Doha 0000, Qatar
ORCID number: Maya Bassil (0000-0001-9996-1300).
Author contributions: Alalwani J and Derbala M performed data collection; Tayyem R and Bassil M were responsible for the study conception and design, and for the development of the methodology; Alalwani J, Tayyem R, and Bassil M analyzed and interpreted the data; Alalwani J, Derbala M, Tayyem R, and Bassil M drafted, critically revised, and approved the final manuscript.
Institutional review board statement: The study protocol was approved by Qatar University and Hamad Medical Center Institutional Review Board Committee, and the study was conducted according to the guidelines of the Declaration of Helsinki. The Institutional Review Board approval was also obtained from Qatar University’s side (No. QU-IRB 007/2024-EA). Our study is part of a large study conducted by Dr. Moutaz Derbala under the study title “Long noncoding RNAs (lncRNA) as non-invasive biomarkers of non-alcoholic fatty liver disease (NAFLD)”, approval No. MRC-01-21-033.
Informed consent statement: All study participants, or their legal guardian, provided informed written consent prior to study enrollment.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
STROBE statement: The authors have read the STROBE Statement-checklist of items, and the manuscript was prepared and revised according to the STROBE Statement-checklist of items.
Data sharing statement: Technical appendix, statistical code, and dataset available from the corresponding author at bassil.maya@qu.edu.qa.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Maya Bassil, MS, PhD, Associate Professor, Head, Department of Nutrition Sciences, College of Health Sciences, QU Health, Qatar University, P.O. Box 2713, Al Tarfa, Doha 0000, Qatar. bassil.maya@qu.edu.qa
Received: July 16, 2025
Revised: August 31, 2025
Accepted: October 24, 2025
Published online: November 27, 2025
Processing time: 134 Days and 16.9 Hours

Abstract
BACKGROUND

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a common and increasingly prevalent condition in the Middle East, but its determinants in the region are underexplored. Diet and lifestyle are known to significantly influence MASLD progression.

AIM

To assess energy and nutrient intake among MASLD patients living in Qatar and evaluate their dietary patterns.

METHODS

Using a cross-sectional design, 94 Arab patients with MASLD, aged ≥ 18 years, living in Qatar were studied. MASLD was diagnosed using ultrasonography, fibro scan, or elastography. Sociodemographic information was collected using a self-administered questionnaire. Dietary intake was assessed through three 24-hour recalls and a qualitative food frequency questionnaire. Energy, macro-, and micronutrient intake were analyzed using Elizabeth Stewart Hands and Associates Food Processor® Nutrition Analysis software. Statistical analyses, including factor loadings were performed using STATA 18.

RESULTS

Compared to recommended dietary allowance, MASLD patients had high intakes of fat, saturated fat, and cholesterol. They also showed reduced intakes of vitamin K in men, and vitamins E and A (retinol), calcium and magnesium in both genders, while selenium and sodium intakes were higher than recommendations. Three dietary patterns were identified: The ‘Traditional Qatari food’ pattern, the ‘Prudent’ pattern, and the ‘Fast-food’ pattern. However, no significant associations were found between these dietary patterns and body mass index or low-density lipoprotein, using adjusted regression models.

CONCLUSION

Findings warrant replication in longitudinal studies and call for dietary interventions to reduce energy density and enhance overall diet quality, including micronutrient intake, for MASLD prevention and management in the region.

Key Words: Metabolic-associated steatotic liver disease; Non-alcoholic fatty liver; Nutrient intakes; Dietary patterns; Body mass index; Low-density lipoprotein

Core Tip: This study investigates the dietary intake and patterns of Arab patients with metabolic dysfunction-associated steatotic liver disease (MASLD) in Qatar, where MASLD is prevalent but under-researched. Results reveal excessive intake of fat, saturated fat, cholesterol, and sodium, alongside inadequate intake of several micronutrients, including vitamins A, E, K, calcium, and magnesium. Three distinct dietary patterns were identified, ‘Traditional’, ‘Prudent’ and ‘Fast-food’ patterns, though none were significantly associated with any health outcome. These findings highlight the need for culturally tailored dietary interventions that improve nutrient quality and reduce energy-dense food consumption, to support MASLD prevention and management in the region.



INTRODUCTION

Metabolic dysfunction-associated steatotic liver disease (MASLD), formerly termed as non-alcoholic fatty liver disease, is a prevalent and potentially serious liver condition characterized by fat accumulation or excess fat in the liver[1-3]. It affects patients with at least one metabolic risk factor (e.g., obesity, diabetes mellitus, dyslipidemia, and hypertension)[4]. MASLD is a broad-spectrum disease, ranging from steatosis (excessive fat accumulation), metabolic-associated steatohepatitis (MASH), fibrosis, cirrhosis, and, in advanced stages, hepatocellular carcinoma[1]. MASLD incidents are rapidly increasing, especially in Western countries, which is estimated to be 70 cases per 1000 person/year[5]. Globally, prevalence of MASLD among adults is estimated to be 32%, with a higher rate among males (40%) compared to females (26%)[6]. Overnutrition and a sedentary lifestyle have a great impact on the development and progression of MASLD. Diets high in calories, saturated fats (SFAs), red/processed meats, refined carbohydrates, added sugars, and poor fiber increase the risk of developing MASLD[7]. On the other hand, diets rich in healthy fats (mono/polyunsaturated fatty acids), fiber, lean proteins, and vitamins are protective and considered a nutritional treatment for patients with MASLD[8]. Healthy dietary patterns like the Mediterranean diet, are associated with a reduced risk of MASLD development, due to the rich content of healthy fats, fruits, vegetables, legumes, and fish[9,10]. Indeed, these diets are rich in fibers found in a variety of vegetables and fruits, whole grains, and legumes, and which help regulate blood sugar[8]. In addition, the antioxidant characteristics of the diets due to their rich content of vitamin E and vitamin C, can help reduce oxidative stress and inflammation[11]. In addition, the lean protein sources like poultry (white flesh), fish, eggs, low-fat dairy, and beans are low in SFA[12]. On the other hand, individuals following Western dietary patterns have a higher risk of developing MASLD due to the high consumption of fast food, juices and sodas, red meat, processed meats, whole-fat dairy products, energy-dense snacks, and sweets[13]. Accordingly, a multidisciplinary panel of 55 international experts issued consensus statements on the dietary management of MASLD, emphasizing the importance of a balanced diet with controlled energy intake and personalized interventions, including calorie restriction, high-protein diets, or low-carbohydrate diets[14]. Recommendations include increasing whole grains, plant-based proteins, fish, seafood, low-fat or fat-free dairy, liquid plant oils, and deeply colored fruits and vegetables, while reducing red and processed meats, saturated and trans fats, ultra-processed foods, added sugars, and alcohol. Following the Mediterranean or Dietary Approaches to Stop Hypertension diets, reducing sedentary behavior, and engaging in regular physical activity are also advised[14].

In the Middle East region, MASLD prevalence is considered one of the highest in the world, affecting 30% of adults[15], with even higher rates among high-risk populations. Indeed, MASLD prevalence is estimated to be 80%-90% in obese adults, 30%-50% in patients with diabetes mellitus (mainly type II), 90% or more in patients with dyslipidemia, and can reach as high as 40%-70% among obese children[16]. In Qatar, this burden is particularly pronounced, with estimated MASLD prevalence reaching 44%, one of the highest rates in the Middle East and North Africa region[17]. Additionally, local dietary habits, including high consumption of fast foods, refined grains, and irregular meal patterns such as frequent snacking, meal skipping, and eating out, contribute significantly to this elevated risk by promoting obesity, insulin resistance, and dyslipidemia[18-20]. These have been directly linked to the widespread obesity and other metabolic disorders[21]. However, no report from the region assessed the dietary intake of people with MASLD, and the associations with disease biomarkers. Thus, this study aims to examine nutrient intake (both macronutrients and micronutrients) and dietary patterns among Arab MASLD patients in Qatar. It addresses a critical gap in current research, offering valuable insights to inform tailored dietary interventions for improved health care for patients with MASLD.

MATERIALS AND METHODS
Study design and population

A cross-sectional study was conducted among 94 adult Arab patients with MASLD, aged 18 years and above, residing in Qatar. The participants were outpatients at a clinic in Hamad Medical Corporation (HMC) in Doha, Qatar. The data was collected between 2022 and 2024. A total of 150 male and female participants visited the outpatient clinics at HMC in the presence of researchers, but due to the strict inclusion and exclusion criteria, the sample size decreased to 94 participants. The diagnosis of MASLD was made based on ultrasonography or elastography. Subjects were considered for the study if they were presented with any mild fatty liver infiltration upon ultrasonography. Ethical approval to conduct this study was obtained from Qatar University (QU-IRB 007/2024-EA) and HMC Institutional Review Board. Our study is part of a larger study titled “Long noncoding RNAs (lncRNA) as non-invasive biomarkers of non-alcoholic fatty liver disease (NAFLD)”, protocol number MRC-01-21-033.

Inclusion and exclusion criteria

The inclusion criteria included being an Arab adult MASLD patient above 18 years old, being followed up at outpatient clinics in HMC. Patients should be able to communicate verbally and were not suffering from diseases requiring special diets. The exclusion criteria included those consuming alcohol (more than 20 g/day for men and 30 g/day for women), having other known liver diseases (like hepatitis viruses A to E, any autoimmune disease and Wilson’s disease), with a history of bariatric surgery or using weight loss medications, as well as those on medications known to induce fatty liver or insulin sensitization, such as estrogens, amiodarone, methotrexate, tamoxifen, and glitazones. In addition, pregnant and lactating women, people suffering from type 1 diabetes, other liver or kidney diseases, or cancer were excluded.

Data collection

Participant consent and demographics: Oral and written consent was obtained from all patients involved in the study. Participants were informed of the study objectives, the questionnaires that would be administered to them, and an estimated time for the interview. Patients were then asked to fill the Personal Information Sheet composed of two forms: One for female participants one for males. Both forms share questions related to age, sex, marital status, education, employment, residency, house condition, smoking status, medication, as well as previous and current health problems.

Dietary assessment: Quantitative dietary assessment was based on a 24-hour recall collected at 3 consecutive days (considering weekdays and weekends). The recall included a detailed dietary intake of a full day from the morning to the end of the day using the 5-step multiple pass method[22]. Portion size estimation sheet, food models and measuring cups were provided to the participant to correctly estimate their intake. In addition, details about meal timings and portion size were also collected from each patient. Elizabeth Stewart Hands and Associates Food Processor® Nutrition Analysis software was used to estimate energy, macronutrient and micronutrient intake for each patient, using the average of 3 days. Additional data on traditional food consumed in Qatar was added using the Bahraini food composition table[23] and analyzed using Elizabeth Stewart Hands and Associates Food Processor®.

Dietary patterns were also identified using a validated food frequency questionnaire (FFQ)[24]. The FFQ included 103 food items that were collected qualitatively from each patient. Data on how frequently, on average, participants had consumed one standard serving of specific food items in nine categories was gathered during face-to-face interviews. Intake of each food items was classified as: Never, < 1 time per month, 2-3 times per month, 1-2 times per week, 3-4 times per week, 5-6 times per week, 1 time per day, 2-3 times a day, 4-5 times a day, 6 or more times a day. If the participants’ dietary pattern did not include a food type, then related questions were marked as ‘Never’. The estimated duration of the interview was about 30 minutes for each participant.

Anthropometric measures: Body weight was measured for each patient using electronic scale (to the nearest 0.5 kg) while the participant was barefoot with light clothes. Standing height was measured for subjects without shoes using a stadiometer with the shoulder in a relaxed position and the arms hanging freely (to the nearest 0.5 cm). Body mass index (BMI) was calculated by dividing weight (kg) by height squared (m2). The following cut-off point ranges were used: Normal weight (BMI: 18.5-24.9 kg/m2), overweight (BMI: 25-29.9 kg/m2), obese I (BMI > 30 kg/m2), obese II (BMI > 35 kg/m2) and obese III (BMI > 40 kg/m2). Waist circumference was measured in cm to the nearest cm using stretchable, tailored measuring tape at the midway level between the lower rib margin and iliac crest in the horizontal plane according to National Institute of Health[25].

Biochemical values: All biochemical analyses were previously carried out in the HMC laboratory by a specialized lab technicians as a routine check-up. The values were obtained from their online medical files. Biochemical values of interest included hemoglobin, ferritin, fasting blood glucose, glycosylated hemoglobin, cholesterol, triglycerides, high density lipoprotein, low-density lipoprotein (LDL), alkaline phosphatase, aspartate transferase, aspartate transferase, vitamin D, vitamin B12, thyroid stimulating hormone, thyroxine free and uric acid. Normal values are based on the HMC laboratory report.

Statistical analysis

Statistical analyses were performed using STATA 18 Statistical software. Continuous variables are presented as means ± SD. Categorical data are presented as the number observed and the percentage of observations. T-test and χ2 were used to test the difference between groups for continues and categorical variables respectively. Principal component analysis was conducted using data from the FFQ, and factor loadings were generated in STATA 18 to identify dietary patterns. Although the FFQ was qualitative in nature, the frequency categories allowed us to apply semi-quantitative methods for data coding and analysis. While thresholds of 0.3-0.4 are commonly used, a lower cut-off of 0.2 was selected in this exploratory analysis to capture broader dietary behaviors and avoid omitting relevant but modestly correlated food groups. Factors were rotated with varimax to improve the interpretability of factors and minimize the correlation between factors. Linear regression analysis was done to describe any associations of the predictor variables on outcomes at significance of P < 0.05. Three models were performed when testing the associations between variables. While model 1 was unadjusted, model 2 was adjusted for age and sex and model 3 was further adjusted for age, sex, education level and energy.

RESULTS
Baseline characteristics of participants

Baseline characteristics stratified by gender are presented in Table 1 (previously published by Eljazzar et al[26]). The mean age of male participants was 47.9 ± 10.4 years, while female participants had a mean age of 50.6 ± 9.6 years. Significant differences were observed in weight, waist circumference, nationality, education and work status between males and females. Males had higher mean weight of 96.5 ± 16.3 kg, and waist circumference of 111.1 ± 13.1 cm, compared to females (85.4 ± 17.2 kg, and 101.7 ± 21.2 cm, respectively). While there were no significant differences in BMI levels between genders, males had a slightly lower mean BMI of 31.6 ± 5.0 kg/m2 compared to females, 33.9 ± 6.5 kg/m2. Males were more likely to be Qatari, working, and of higher education level compared to females (P < 0.05).

Table 1 Sample characteristics of study patients, n (%).
Variable
Males (n = 34)
Females (n = 60)
Total (n = 94)
P value
Age (years)47.9 (10.4)50.6 (9.6)49.6 (9.9)0.216
Waist circumference (cm)111.1 (13.1)101.7 (21.2)105.1 (19.2)0.037a
Weight (kg)96.5 (16.3)85.4 (17.2)89.4 (17.6)0.003a
Body mass index31.6 (5.0)33.9 (6.5)33.1 (6.1)0.077
Body mass index classifications
    Normal3 (8.8)3 (5.0)6 (6.4)0.763
    Overweight9 (26.5)16 (26.7)25 (26.6)
    Obese22 (64.7)41 (68.3)63 (67.0)
Nationality
    Qatari3 (8.8)20 (33.3)23 (24.5)0.008a
    Non-Qatari31 (91.2)40 (66.7)71 (75.5)
Marital status
    Single1 (2.9)3 (5.0)4 (4.3)0.548
    Married32 (94.1)51 (85.0)83 (88.3)
    Divorced1 (2.9)4 (6.7)5 (5.3)
    Widowed0 (0.0)2 (3.3)2 (2.1)
Education level
    High school6 (17.6)22 (36.7)28 (29.8)0.030
    Diploma6 (17.6)16 (26.7)22 (23.4)
    Bachelor or above22 (64.7)22 (36.7)44 (46.8)
Work status
    Work32 (94.1)28 (46.7)60 (63.8)< 0.001a
    Don’t work2 (5.9)32 (53.3)34 (36.2)
Work timings
    Morning shift25 (78.1)23 (82.1)48 (80.0)0.180
    Evening shift0 (0.0)2 (7.1)2 (3.3)
    Split shift7 (21.9)3 (10.7)10 (16.7)
Special diet status
    Yes6 (17.6)11 (18.3)17 (18.1)0.934
    No28 (82.4)49 (81.7)77 (81.9)
Meals consumed
    1 meal3 (8.8)4 (6.7)7 (7.4)0.269
    2 meals23 (67.6)30 (50.0)53 (56.4)
    3 meals8 (23.5)25 (41.7)33 (35.1)
    > 3 meals0 (0.0)1 (1.7)1 (1.1)

The health status of study participants by gender, is outlined in Table 2[26]. Among male participants, 32.4% were smokers compared to only 1.7% of females (P < 0.001). Both genders had normal hemoglobin and ferritin levels, with males showing higher values. No significant gender differences were observed in glycosylated hemoglobin and fasting blood sugar. While lipid profiles were within normal ranges, significant gender differences were found in triglycerides (higher in males; P = 0.002) and high-density lipoprotein (higher in females; P < 0.001). Uric acid levels were significantly higher in males (P < 0.002), though still within the normal range for both genders.

Table 2 Health-related characteristics of the study patients, n (%).
Variable
Male (n = 34)
Female (n = 60)
Total (n = 94)
P value
Health-related variables
Smoking statusYes11 (32.4)1 (1.7)12 (12.8)< 0.001
No16 (47.1)52 (86.7)68 (72.3)
Ex-smoker7 (20.6)7 (11.7)14 (14.9)
Chronic disease statusYes25 (73.5)48 (80.0)73 (77.7)0.469
No9 (26.5)12 (20.0)21 (22.3)
PrediabetesYes32 (94.1)48 (80.0)80 (85.1)0.065
No2 (5.9)12 (20.0)14 (14.9)
T2DMNo17 (50.0)36 (60.0)53 (56.4)0.348
Yes17 (50.0)24 (40.0)41 (43.6)
CVDNo13 (38.2)26 (43.3)39 (41.5)0.630
Yes21 (61.8)34 (56.7)55 (58.5)
HTNNo22 (64.7)41 (68.3)63 (67.0)0.719
Yes12 (35.3)19 (31.7)31 (33.0)
ThyroidNo32 (94.1)50 (83.3)82 (87.2)0.132
Yes2 (5.9)10 (16.7)12 (12.8)
Biochemical values
Hgb (gm/dL)14.6 ± 1.612.7 ± 1.413.3 ± 1.7< 0.001a
Ferritin (μg/L)171.7 ± 212.370.5 ± 66.9104.7 ± 141.70.003a
FBS (mmol/L)7.0 ± 2.76.3 ± 1.76.6 ± 2.10.169
HbA1c (%)6.3 ± 1.36.2 ± 1.16.2 ± 1.20.605
Cholesterol (mmol/L)4.7 ± 1.14.9 ± 1.24.8 ± 1.20.296
TG (mmol/L)2.2 ± 1.11.6 ± 0.71.8 ± 0.90.002a
HDL (mmol/L)1.1 ± 0.41.4 ± 0.31.3 ± 0.4< 0.001a
LDL (mmol/L)2.7 ± 1.12.9 ± 1.12.8 ± 1.10.346
ALK (U/L)84.7 ± 61.986.5 ± 41.085.9 ± 49.20.862
ALT (U/L)35.8 ± 20.229.6 ± 28.031.9 ± 25.50.261
AST (U/L)25.4 ± 10.122.9 ± 16.523.8 ± 14.50.431
Vitamin D (ng/mL)28.5 ± 13.028.1 ± 12.128.2 ± 12.30.886
Vitamin B12 (pml/L)312.1 ± 100.8378.8 ± 252.2356.8 ± 216.00.183
TSH (mIU/L)1.9 ± 1.32.8 ± 5.72.5 ± 4.70.408
FT4 (pmol/L)15.5 ± 1.614.5 ± 2.114.8 ± 2.00.024a
Uric acid (μmol/L)376.6 ± 105.8301.5 ± 69.6326.1 ± 89.60.002a
Energy, macro-, micronutrients intakes and MASLD

Results from 24-hour recalls are shown in Table 3. Energy, macronutrients, micronutrients, and other dietary components are stratified by gender and compared to the recommended dietary allowance (RDA) (Table 3). Among males (n = 34), the mean total calorie intake was 2307.4 ± 519.3 kcal/day, with 914.3 ± 325.3 kcal/day from fat and included 100.3 ± 26.1 g of protein consumed. Males consumed 39.9% of calories from fat, which exceeded the National Institutes of Health recommendations that call for a fat intake lower than 30% of total calories[22]. Cholesterol intake in males also exceeded RDA recommendation with a mean intake of 394.0 ± 226.9 mg. In females (n = 60), the mean total calorie intake was 1897.2 ± 436.0 kcal/day, with 713.4 ± 195.6 kcal/day from fat and 79.2 ± 26.3 g of protein consumed. Similar to males, females surpassed the recommendations of calories from fat with a 37.6% of total calories consumed. Females also exceeded RDA recommendations for SFA with a mean intake of 24.9 ± 8.6 g. Both genders did not meet folate, magnesium (Mg) and zinc RDA recommendations (P < 0.017, P < 0.025 and P < 0.020, respectively). Notably, both genders significantly exceeded the RDA for sodium intake (males: 3234.3 ± 769.6 mg, females: 2687.1 ± 927.6 mg; P < 0.004) and selenium (males: 96.3 ± 48.2 mg, females: 73.3 ± 42.4 mg; P < 0.02). Additionally, the intake of omega-3 (males: 1.5 ± 0.8 g, females: 1.2 ± 0.5 g; P < 0.011) , omega-6 (males: 12.9 ± 5.3 g, females: 9.1 ± 3.8 g; P < 0.001), phosphate (male: 1011.1 ± 321.9 mg, females: 789.9 ± 257.2 mg; P < 0.001), and potassium (males: 2275.5 ± 644.4 mg, females: 1963.8 ± 688.4 mg; P < 0.034), differed significantly between genders.

Table 3 Mean intake of energy, macronutrients and micronutrients and others compared to recommended dietary allowance in patient with metabolic dysfunction-associated steatotic liver disease, mean ± SD.
Nutrients
Males (n = 34)
Recommendations (males)1
Females (n = 60)
Recommendations (females)1
Total (n = 94)
P value
Energy (kcal)
    Total calories2307.4 ± 519.3-1897.2 ± 436.0-2045.5 ± 505.5< 0.001a
    Calories from fat914.3 ± 325.3-713.4 ± 195.6-786.1 ± 266.9< 0.001a
    Calories from saturated fat269.7 ± 150.3-224.4 ± 77.7-240.8 ± 111.00.057
Macronutrients
    Protein (g)100.3 ± 26.1-79.2 ± 26.3-86.8 ± 28.0< 0.001a
    Carbohydrate (g)257.7 ± 63.9-222.5 ± 66.5-235.2 ± 67.40.014a
    Total fiber (g)18.8 ± 7.5-16.5 ± 11.6-17.4 ± 10.30.318
    Soluble fiber (g)0.8 ± 0.8-0.8 ± 0.8-0.8 ± 0.80.909
    Sugar (g)83.4 ± 36.7-79.4 ± 39.5-80.8 ± 38.30.632
    Added sugar (g)29.7 ± 22.7-23.5 ± 17.3-25.7 ± 19.60.138
    Fat (g)102.7 ± 36.7-79.8 ± 22.2-88.1 ± 30.2< 0.001a
    Saturated fat (g)30.0 ± 16.73024.9 ± 8.62026.8 ± 12.30.057
    Mono-unsaturated fatty acids (g)29.5 ± 15.3-21.4 ± 9.4-24.3 ± 12.40.002a
    Poly-unsaturated fatty acids (g)15.0 ± 6.0810.8 ± 4.5612.3 ± 5.5< 0.001a
    Trans fatty acid (g)0.1 ± 0.300.2 ± 0.200.2 ± 0.30.764
    Cholesterol (mg)394.0 ± 226.9300287.5 ± 155.4300326.0 ± 190.30.008a
    Omega-3 (g)1.5 ± 0.81.61.2 ± 0.51.11.3 ± 0.60.011a
    Omega-6 (g)12.9 ± 5.3≤ 50 years: 17; > 50 years: 149.1 ± 3.8≤ 50 years: 12; > 50 years: 1110.5 ± 4.8< 0.001a
Micronutrients
    Vitamins (μg)
        Retinol (μg)487.7 ± 1305.8900228.5 ± 368.0700322.3 ± 840.60.152
        Beta-caroten (μg)1778.0 ± 2215.49002329.9 ± 2796.97002130.3 ± 2602.90.326
        Vitamin B1 (μg)1.1 ± 0.31.20.9 ± 0.31.10.9 ± 0.30.003a
        Vitamin B2 (μg)1.4 ± 0.71.31.1 ± 0.41.11.2 ± 0.60.012a
        Vitamin B3 (μg)22.7 ± 9.31617.2 ± 9.31419.2 ± 9.60.007a
        Vitamin B6 (μg)1.6 ± 0.7≤ 50 years: 1.3; > 50 years: 1.71.3 ± 0.6≤ 50 years: 1.3; > 50 years: 1.51.4 ± 0.60.048a
        Vitamin B12 (μg)4.7 ± 8.22.42.9 ± 4.92.43.5 ± 6.30.189
        Biotin (μg)4.8 ± 7.7302.9 ± 2.3303.5 ± 4.80.098
        Vitamin C (mg)86.3 ± 83.19068.6 ± 44.67575.0 ± 61.50.182
        Vitamin D (μg)3.4 ± 3.8152.9 ± 3.6153.1 ± 3.70.594
        Vitamin E (mg)6.4 ± 2.2155.4 ± 2.6155.8 ± 2.50.073
        Folate (μg)324.2 ± 179.2400251.2 ± 112.0400277.6 ± 143.50.017
        Vitamin K (μg)76.4 ± 96.512089.9 ± 143.69085.0 ± 128.10.628
    Minerals
        Calcium (mg)657.8 ± 222.21000644.5 ± 240.8≤ 50 years: 1000; > 50 years: 1200649.3 ± 233.10.792
        Copper (mg)1.0 ± 0.70.91.1 ± 1.10.91.1 ± 1.00.639
        Chromium (μg)1.3 ± 1.1351.0 ± 0.9251.1 ± 1.00.204
        Iodine (μg)2.5 ± 3.91504.9 ± 6.11504.1 ± 5.50.073
        Iron (mg)12.3 ± 4.289.6 ± 2.88-1810.6 ± 3.6< 0.001a
        Magnesium (mg)220.1 ± 70.4420183.7 ± 76.4320196.9 ± 76.00.025a
        Manganese (mg)0.7 ± 0.52.30.6 ± 0.41.80.7 ± 0.50.328
        Phosphate (mg)1011.1 ± 321.9700789.9 ± 257.2700869.9 ± 300.3< 0.001a
        Potassium (mg)2275.5 ± 644.434001963.8 ± 688.426002076.5 ± 686.00.034a
        Selenium (μg)96.3 ± 48.25573.3 ± 42.45581.7 ± 45.70.018a
        Sodium (mg)3234.3 ± 769.615002687.1 ± 927.615002885.1 ± 908.80.004a
        Zinc (mg)8.0 ± 2.886.5 ± 3.1117.0 ± 3.10.020a
    Other
        Caffeine (mg)65.2 ± 100.440043.3 ± 80.040051.2 ± 88.00.248
Dietary patterns and MASLD

Three dietary patterns were identified using factor analysis (Table 4) and are shown in Table 2. The ‘Traditional Qatari food’ dietary pattern includes high intake of refined grains, sweets and snacks, juice and drinks, sugar and added sugar, Qatari food, pasta, sauces, dressings, fast food, Karak, oils and fats, and starchy vegetables. The second dietary pattern defined as ‘Prudent’ is rich in dairy, meat and poultry, starchy vegetables, non-starchy vegetables, soups, legumes, fish and seafood, tea, and coffee. The last dietary pattern defined as ‘Fast-food’ includes high intakes of fast food, fish and seafood, sauces and dressings, juices and drinks, meat and poultry and sweets and snacks.

Table 4 Factor loadings for three predicted dietary patterns.
Food
Traditional Qatari
Prudent
Fast-foods
Fruits-0.0602-0.0086-0.4032
Legumes0.04110.37671-0.3503
Qatari food0.443310.1427-0.2807
Oils and fats0.1923-0.1697-0.2594
Karak0.27331-0.1567-0.2086
Tea and coffee0.11270.22871-0.1998
Non-starchy vegetables-0.46340.40141-0.1951
Sugar and added sugar0.509210.0671-0.1688
Sweetener-0.2552-0.2798-0.1493
Soups-0.12310.46881-0.1159
Starchy vegetables0.17630.53001-0.0818
Whole grains-0.6551-0.0678-0.0223
Dairy0.06870.653010.0533
Nuts-0.13040.13280.0836
Pasta0.36991-0.09060.0841
Grains0.818610.08220.1096
Sweets and sacks0.626910.02830.1190
Meat and poultry0.03490.608810.20051
Juice and drinks0.57171-0.30410.28511
Sauces and dressings0.337910.00920.57791
Fish and seafood-0.27570.332810.59611
Fast-foods0.29531-0.07530.73741

Supplementary Figure 1 presents the factor loadings for the three identified dietary patterns among MASLD patients: Traditional Qatari food, prudent, and fast-food patterns. Supplementary Figure 2 displays the scree plot of eigenvalues derived from the intake frequency of 22 pre-determined food groups. The X-axis represents the factor components, while the Y-axis shows their corresponding eigenvalues. Each point on the graph indicates a potential factor, and the plot provides a visual continuum of eigenvalues to determine the number of extractable factors. Based on the scree plot, factors with eigenvalues ≥ 1.3 were retained. Accordingly, three factors were extracted through factor analysis.

Association of MASLD biomarkers with dietary patterns

Linear regression analyses were conducted to detect any association between dietary patterns and BMI as a biomarker of MASLD (Table 5). Three models were run; model 1 was unadjusted, model 2 was adjusted for age and sex, and model 3 was adjusted for age, sex, educational level, and energy. There was no significant association between BMI and the dietary patterns in all three models. Regression analyses were also performed to assess the relationship between dietary patterns and LDL (Table 6). No significant association was found between LDL and any dietary pattern in all three models.

Table 5 Associations between body mass index and dietary patterns.
Dietary patternsModel 1
Model 2
Model 3
Coef. (95%)
P value
Coef. (95%)
P value
Coef. (95%)
P value
Traditional Qatari food0.01 (-1.25 to 1.26)0.988-0.02 (-1.31 to 1.26)0.9660.01 (-1.38 to 1.40)0.987
Prudent-0.62 (-1.88 to 0.63)0.326-0.62 (-1.93 to 0.69)0.351-1.01 (-2.42 to 0.39)0.156
Fast-foods-0.77 (-2.03 to 0.48)0.223-0.58 (-1.94 to 0.76)0.389-0.70 (-2.09 to 0.69)0.320
Table 6 Associations between low-density lipoprotein and dietary patterns.
Dietary patternsModel 1
Model 2
Model 3
Coef. (95%)
P value
Coef. (95%)
P value
Coef. (95%)
P value
Traditional Qatari food0.05 (-0.18 to 0.29)0.6430.002 (-0.23 to 0.24)0.9850.03 (-0.23 to 0.27)0.874
Prudent -0.06 (-0.29 to 0.16)0.5950.003 (-0.23 to 0.24)0.9760.01 (-0.24 to 0.26)0.957
Fast foods0.05 (-0.23 to 0.33)0.717-0.03 (-0.33 to 0.27)0.839-0.09 (-0.39 to 0.21)0.546
DISCUSSION

This study assessed energy intake, macronutrient and micronutrient intakes among Arab MASLD patients living in Qatar, identified the common dietary patterns, and explored their potential associations with the disease biomarkers. Arab patients with MASLD living in Qatar were more likely to be older adults, females, obese, married, and having an educational level of bachelor’s degree or more. In addition, they had intakes of fat, SFA, and cholesterol, which exceeded recommendations with gender variations. Micronutrient intakes were either below or above RDAs. Moreover, three dietary patterns were derived from the sample diet: The “Traditional Qatari food” pattern, the “Prudent” pattern, and the “Fast-food” pattern.

Among macronutrients, fat intake (as percentage of total calories) in individuals with MASLD was 39.9% in males and 37.6% in females, which exceeded the recommendations, whereby dietary fat should comprise < 30% of daily calories[27]. Moreover, SFA intake exceeded RDA recommendations in females in our study. This is consistent with the literature that reported higher cholesterol and SFA intake in patients with MASLD[28]. Elevated consumption of total fat, SFA and cholesterol can worsen liver damage and advance disease severity through interconnected mechanisms in individuals with MASLD[28]. SFA from dietary fat directly promote the upregulation of MASLD-associated pathways[28]. Dietary SFA might promote MASLD by influencing intrahepatic triglycerides, insulin resistance, oxidative stress, and the release of pro-inflammatory cytokines[28,29]. One cross-sectional study reported that SFA intake was associated with higher hepatic steatosis, fibrosis, and MASLD prevalence[30]. Moreover, Zhao et al[31] reported that a higher intake of dietary SFA was associated with a higher risk of liver cancer. Similarly, a randomized control trial found that SFA-enriched diets markedly induce liver fat by about 50% relative increase and elevate liver enzymes[32].

Dietary cholesterol in this study also exceeded RDA recommendations in males. As established in the literature, dietary cholesterol has an important role in the progression of MASLD to MASH by inducing inflammation and fibrosis[33-35]. High dietary cholesterol led to the sequential progression of steatosis, steatohepatitis, fibrosis, and eventually hepatocellular carcinoma in mice. This was mediated by insulin resistance, enhanced reactive oxygen species, proinflammatory cytokines and oxidative damage[36]. In another recent rodent study[37], long-term exposure to a high-fat and high-cholesterol diet resulted in the development of MASH in mice. The high-fat and high-cholesterol group had a significantly increased epididymal fat weight and serum levels of both aspartate transferase and aspartate transferase compared with the high-fat group and control group. On the other hand, supplementation with atorvastatin resulted in restored cholesterol-induced gut microbiota dysbiosis and completely prevented MASLD-hepatocellular carcinoma development in mice[38]. Further studies are needed to confirm these mechanisms and findings in human studies.

Vitamins play distinct roles in the pathogenesis and progression of MASLD. In the present study, dietary intakes of vitamins E and A were below the RDAs in both genders, while that of vitamin K was below RDA in males. This is in line with a recent cohort conducted by Nemer et al[39], which reported reduced vitamin K intake in patients with MASLD. Additionally, Wang et al[40] found that patients with diabetes mellitus with higher vitamin K intake have lower risk of MASLD. Vitamin K is involved in blood clotting and bone metabolism, but emerging evidence suggests its potential role in MASLD[41]. One study indicates that vitamin K deficiency is associated with hepatic inflammation and fibrosis[41]. Also, higher vitamin K levels and vitamin K supplementation were associated with reduced insulin resistance and inflammation[42,43]. Similarly, in a hospital-based Korean study vitamin K supplementation helped in lowering the risk of MASLD significantly[44]. Alternatively, vitamin K intake may reflect an overall higher vegetable intake, which is protective of MASLD, through antioxidant pathways[39,45].

As for vitamin E, both males and females had intakes below the RDAs, in line with recent literature[39,46]. While MASLD is a state of oxidative stress and inflammation with increased de-novo lipogenesis and triglyceride hepatic deposition[47], vitamin E is an antioxidant that can inhibit reactive oxygen species and may play a protective role in MASLD pathogenesis[48]. Other potential roles for vitamin E include its anti-apoptotic and anti-inflammatory properties that might be beneficial in patients with MASLD[48]. A systematic review of eight studies suggested that vitamin E supplementation can improve hepatic biochemical (liver enzymes) and histological (liver pathology) characteristics of MASLD patients[49]. In one animal study, obese mice supplementation with α-tocopherol or γ-tocopherol (vitamin E active form) showed protection against lipopolysaccharide-induced liver injury[50]. In another study conducted by Shen et al[51], mice had improved antioxidant activity after supplementation with vitamin E. Still, additional studies are needed to confirm the dosage of vitamin E supplementation that can improve health status in patients with MASLD.

Dietary retinol, a form of vitamin A, was found to be below the RDA in MASLD patients in the present study, in line with a study by Jeon et al[52] where dietary retinol was below RDAs in all four quartiles of retinol intake in MASLD patients. Similarly, a recent study by Liu et al[53] in 2023, reported that retinol intake in females aged > 45 years old was inversely associated with MASLD risk. Conversely, a Japanese study by Kimura et al[54] reported that there were no differences in the daily intake of both retinol and carotenoid between participants with or without MASLD in both genders. Dietary sources of vitamin A are carotenoids, primarily β-carotene found in plant sources such as sweet potatoes, carrots, and dark green leafy vegetables, and retinyl esters found in animal sources like liver, eggs, and fish[55]. The liver plays a central role in vitamin A metabolism, whereby around 80% of vitamin A is stored in hepatic cells in a healthy individual[56]. Although the mechanism underlying the association between carotenoids and MASLD is unclear, one proposed mechanism is the antioxidant properties that carotenoids exert that could prevent liver damage and MASLD by alleviating oxidative stress in hepatocytes[57].

In regard to minerals, many minerals, except for sodium and selenium, were below recommendations. Calcium (Ca) intake was less than the RDA in both males and females. Studies have found that a high Ca diet plays an effective role against MASLD. Ca works by regulating several intracellular events within the hepatocytes, like downregulation of lipogenesis activity, inflammation, oxidative stress, fibrosis, and steatosis[56]. Conversely, one study reported that intake of Ca was not related to the odds of fatty liver disease, prediabetes or both prediabetes and fatty liver disease[58]. Further studies are needed to investigate the role of dietary Ca in patients with MASLD.

Furthermore, Mg intake in both males and females was below RDA in this study. Consistently, Mg intake was associated with approximately 30% reduced odds of fatty liver disease and prediabetes in a previous report[58]. Likewise, the risk of MASLD was 55% lower among individuals in the highest quintile of Mg intake, with a mean of 596 mg/day[59]. Mg modulates insulin secretion and action in liver, adipose tissue, and muscle through interactions with the insulin receptor, and thus prevents insulin resistance and associated liver steatosis and MASLD[59,60]. Animal studies showed that Mg could improve insulin sensitivity and glucose tolerance, by inducing glucose transporter type 4 gene expression and translocation, in addition to the suppression of the gluconeogenesis pathway and glucagon receptor gene expression in the liver and muscle[61]. It is worthy to note that in Qatar, low serum Mg has been positively associated with diabetes, prediabetes, insulin resistance, and poor glycemic control[62]. This is also associated with increased consumption of refined grains that have a low content of Mg due to the refining process[62]. Selenium is the only mineral, besides sodium, with intakes that exceeded RDA in MASLD patients in both genders in our study. Selenium is a trace mineral found in animal proteins, breads and cereals and is known to protect against oxidative stress[39]. Selenium deficiency is rare worldwide in the general population[63]. In line with our findings, Nemer et al[39] reported higher selenium intake in MASLD patients compared to controls, with the highest among MASLD patients with fibrosis compared to MASLD without fibrosis. Moreover, a Chinese study reported that higher dietary selenium intake was associated with a higher prevalence of MASLD in middle-aged and elderly subjects[64]. The mechanism remains unclear, but studies suggest that excessive levels of selenium can exert pro-oxidant effects, leading to oxidative stress, which in turn may activate the NLR family pyrin domain-containing 3 inflammasome, promote insulin resistance, and increase hepatic lipogenesis, a process central to the immunometabolic pathways underlying MASLD[65].

In our study, three dietary patterns were identified in MASLD patients: The “Traditional Qatari food” pattern, the “Prudent” pattern, and the “Fast-food” pattern. Fish and seafood were included in the “Fast-Food” pattern, even though they are commonly reported as components of the healthy and prudent patterns. In Qatar and other Gulf Cooperation Council countries, fish and seafood are frequently consumed in deep-fried forms, rather than grilled or baked as in “Prudent”[17,19]. Thus, this preparation style aligns with the high-fat, energy-dense characteristics of the “fast-food” pattern. A recent systematic review has shown that ‘Western dietary patterns’ increased the risk of MASLD by 56%. The pattern included high levels of processed food, red meat, high-fat dairy, and refined grains, which was similar to our study’s “Traditional Qatari food” and “Fast-food” pattern that are rich in refined grains, starchy vegetables, sweets and snacks, juices, and drinks, pasta, sauces and dressings, fast-food, oils and fats[66]. In another case-control, three dietary patterns, including the “Western” dietary pattern, “Healthy” dietary pattern, and “Traditional” dietary pattern were identified in MASLD patients. The “Western” pattern included high intakes of processed and organ meats, high-fat dairy, soft drinks, refined grains, fast foods, mayonnaise, salty snacks, sugar-sweet desserts, and hydrogenated fats. The “Healthy” pattern included high consumption of fish, skinless poultry, low-fat dairy, fruits (fresh, natural juices, dried fruits, canned fruits), vegetables, nuts, olives, and garlic. The “Traditional” pattern was similar to the “Traditional Qatari food” pattern found in our study and comprised red and organ meats, skinless poultry, eggs, yogurt drinks, tea, legumes, tomato sauce, sugar-sweets-desserts, potatoes, condiments, pickles, salt, and broth[67]. In another study on MASLD patients, two dietary patterns were extracted, vegetables, legumes, fruits, and low-fat dairy products (VLFD) and sweet, hydrogenated fat, red and processed meat, and soft drink (SHMS) patterns. The VLFD dietary pattern was associated with a reduced risk of MASLD, while the SHMS dietary pattern was associated with a higher risk[68]. Additionally, a recent case-control Indian study reported that the “Western dietary pattern” was associated with an increased risk of MASLD[69]. Cases had a significantly higher intake of oils and fats, along with nuts and oilseeds, as compared to controls (P < 0.05)[69]. On the other hand, greater adherence to a “Prudent” dietary pattern, rich in vegetables, fruits, and fish, was associated with a lower risk of MASLD adverse outcomes such as mortality[70]. Similarly, Hassani Zadeh et al[66] reported that adherence to the “Prudent” and “Mediterranean” dietary patterns reduced the risk of MASLD by 22% and 23%, respectively, while Western dietary patterns increased the risk by 56%. Adherence to the “Mediterranean” diet was also linked to reduced liver-related events and mortality in MASLD patients, whereby higher adherence to the “Mediterranean” diet scores were associated with lower risks of liver related events and mortality compared to the lowest scores[71].

Limited studies have explored the association between MASLD biomarkers and dietary patterns in patients with MASLD. In our study, there was no significant association between BMI or LDL with dietary patterns in MASLD patients. This could be due to several factors, including the relatively small sample size, the cross-sectional nature of the study, and potential residual confounding variables, which were not fully accounted for. However, one Chinese study has found that higher BMI and obesity, are associated with poorer dietary patterns in MASLD patients (P < 0.01)[72]. The predominant diet in the study was rich in strawberries, kiwi fruit, persimmon, sweets, candied fruits, and Chinese cakes, and was labeled as “Sugar-rich” dietary pattern[72]. Also, Miryan et al[73] showed that adherence to the Mediterranean diet was associated with reduced LDL (P = 0.002). The discrepancies in findings between these studies and the present one might be related to the distinct cultural and dietary contexts that might influence the observed associations differently. Further longitudinal studies are needed to study the association between MASLD biomarkers and dietary patterns in the Middle East, and to determine whether region-specific dietary and other characteristics may mask or modify such associations.

Strengths and limitations

This is the first study that examined the dietary and nutrient intake in Arab MASLD patients. Another strength is the use of validated FFQ and systematic tools to assess dietary patterns and nutrients intake, which enhances the reliability and comparability of the findings. On the other hand, this study has certain limitations that should be considered. The cross-sectional design limits causal relationships inference and hence warrants future longitudinal studies. Also, dietary data may be associated with recall bias and might not adequately reflect the usual intake. However, an average of three-day dietary recalls was collected by a trained interviewer on separate occasions (2 weekdays and 1 weekend). Moreover, a key limitation of this study is the relatively small sample size. This is partly due to the demographic profile of Qatar, where the number of Arab residents (both Qatari and non-Qatari) is relatively low. According to national statistics, Arabs constitute only a modest proportion of Qatar’s total population of around 2.8 million (Planning and Statistics Authority, Qatar, 2023). Given that MASLD affects only a subset of the Adult Arab population, the pool of eligible participants was inherently limited. Thus, this demographic constraint should be taken into account when interpreting the generalizability of the study’s findings. In addition, while the regression analysis adjusted for total energy intake in model 3, it did not include physical activity due to data being captured in a separate publication. However, additional analyses (not included in the present manuscript) accounting for physical activity in the available subset showed similar results to those of the present study, whereby associations between dietary patterns and MASLD remained statistically non-significant.

CONCLUSION

Findings of the present study on adult Arab MASLD patients living in Qatar showed that calorie intakes from fat, SFA, as well as cholesterol intake exceeded recommendations. Intakes of vitamins E, K, and A (retinol), as well as those of Mg and Ca were less than the RDAs, while selenium and sodium intakes exceeded RDAs. Three dietary patterns were identified: The “Traditional Qatari food” pattern, the “Prudent” pattern, and the “Fast-food” pattern. “Traditional Qatari food” pattern, and “Fast-food” pattern were mainly high in fat and refined grains, while “Prudent” pattern mainly reflected a healthy pattern. No significant association was found between the dietary patterns and BMI and LDL. Further research is warranted in the region to study the associations between dietary intakes, dietary patterns, and risk of MASLD. Based on the identified dietary patterns and the findings of the present study, tailored nutritional interventions are essential to improve diet quality for the prevention and management of MASLD, with a focus on decreasing energy and fat density while increasing overall nutrient density, including micronutrients.

ACKNOWLEDGEMENTS

The authors would like to thank professor Zumin Shi for his support and guidance in the statistical analysis.

Footnotes

Provenance and peer review: Unsolicited article; Externally peer reviewed.

Peer-review model: Single blind

Specialty type: Gastroenterology and hepatology

Country of origin: Qatar

Peer-review report’s classification

Scientific Quality: Grade C

Novelty: Grade C

Creativity or Innovation: Grade C

Scientific Significance: Grade C

P-Reviewer: He J, MD, PhD, Associate Research Scientist, China S-Editor: Hu XY L-Editor: A P-Editor: Lei YY

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