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. 2023 Jul 4;11(10):6133–6139. doi: 10.1002/fsn3.3549

Relationship between diet quality and nonalcoholic fatty liver disease predictor indices in Iranian patients with metabolic syndrome: A cross‐sectional study

Maryam Taghdir 1,2,✉, Akram Salehi 3, Karim Parastouei 1, Sepideh Abbaszadeh 1
PMCID: PMC10563747  PMID: 37823171

Abstract

The present study aimed to assess the association between diet quality and nonalcoholic fatty liver disease (NAFLD) predictor indices in patients with metabolic syndrome (MetS). This cross‐sectional study was carried out among 344 adult patients with MetS. The diet quality of patients was calculated by Healthy Eating Index‐2015 (HEI‐2015). NAFLD predictor indices (Hepatic Steatosis Index [HSI], Triglyceride‐Glucose Index [TyG], and Fatty Liver Index [FLI]) were calculated and compared according to the HEI‐2015 quartiles. The relationship between the HEI‐2015 score and HSI, FLI, and TyG Index was estimated using multiple linear regression analysis. The findings of the present study revealed that patients with the highest HEI score had the lowest FLI score (p = .003) and HSI score (p = .05). There was an inverse relationship between the HEI‐2015 score and FLI (β = −0.49; p < .001), HSI (β = −0.05; p = .25), and TyG Index (β = −0.002; p = .34). According to our result, after adjusting for possible confounding factors, there was a statistically significant inverse association between HEI‐2015 and FLI.

Keywords: Fatty Liver Index, Healthy Eating Index‐2015, Hepatic Steatosis Index, metabolic syndrome, Triglyceride‐Glucose Index

The findings of the present study revealed that patients with the highest HEI score had the lowest FLI score and HSI score. According to our result, after adjusting for possible confounding factors, there was a statistically significant inverse association between HEI‐2015 and FLI.

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1. INTRODUCTION

A set of metabolic disorders including, increased fasting blood sugar (FBS), blood pressure (BP), triglycerides, and decreased high‐density lipoprotein cholesterol (HDL‐C) along with abdominal obesity constitute the metabolic syndrome (MetS) (Eckel et al., 2005). The prevalence of MetS is increasing globally (Tabatabaei‐Malazy et al., 2021). The overall prevalence of MetS in Iran (based on the criteria of the International Diabetes Federation [IDF]) is estimated at 43.5%. It is also more common in women and urban residents than in men and rural populations (Tabatabaei‐Malazy et al., 2021). MetS is usually accompanied by cardiovascular disease (CVD), diabetes mellitus (type 2), and nonalcoholic fatty liver disease (NAFLD) (Eslam et al., 2020; Katsiki et al., 2018). Recently, it has been suggested that metabolic‐associated fatty liver disease (MAFLD) is a more suitable term for NAFLD associated with metabolic disorders (Eslam et al., 2020). NAFLD may lead to steatohepatitis, fibrosis, and cirrhosis (Matteoni et al., 1999). The gold standard for diagnosing NAFLD is liver biopsy, which is an invasive procedure and has adverse consequences for the patient (Sumida et al., 2014). In recent years, some indices such as Hepatic Steatosis Index (HSI), Fatty Liver Index (FLI), and Triglyceride‐Glucose Index (TyG) have been considered as noninvasive methods to predict liver fat changes (Khamseh et al., 2021; Lee et al., 2010; Motamed et al., 2016).

Lifestyle modifications, including physical activity and adherence to a balanced diet, are recommended to prevent and improve NAFLD (Liver & Diabetes, 2016). Some studies have shown that there is a relationship between diet quality and NAFLD (Chan et al., 2015; Doustmohammadian et al., 2022; Vahid et al., 2019). Diet quality is evaluated using several indices. According to the 2015–2020 Dietary Guidelines for Americans, the Healthy Eating Index‐2015 (HEI‐2015) is a measure for assessing the extent of adherence to dietary recommendations. HEI‐2015 evaluates components such as whole fruits, vegetables, whole grains, plant proteins, and fatty acids (Reedy et al., 2018). A negative correlation between the HEI‐2015 score and CVD and all‐cause mortality has been reported (Hu et al., 2020). To our knowledge, this is the first study on the association between diet quality and NAFLD predictor indices (FLI, HSI, and TyG Index) in patients with MetS.

2. MATERIALS AND METHODS

2.1. Study population

In this cross‐sectional study, a total of 344 patients who which randomly selected from patients with MetS who were referred to a referral clinic (Amiralmomenin clinic) in Mobarakeh, Isfahan province, Iran, between July 2021 and March 2022 were studied.

MetS was diagnosed based on the IDF criteria (a waist circumference (WC) ≥94 cm in men and ≥80 cm in women and having two of the following five criteria: systolic BP: ≥130 mm/Hg, diastolic BP: ≥85 mm/Hg, FBS: ≥100 mg/dL, triglyceride: ≥150 mg/dL, and HDL‐C: <50 mg/dL in women and <40 mg/dL in men) (Alberti et al., 2005). Exclusion criteria were having cancer or a history of chronic liver, kidney, and thyroid diseases, alcohol consumption, and being pregnant or breastfeeding.

Written informed consent was obtained from all participants. The Ethics Committee for Research at Baqiyatallah University of Medical Sciences has approved the protocol of study (IR.BMSU.REC.1400.058).

2.2. Anthropometric and blood pressure measurements

Weight was measured via the Seca scale (Seca) with an accuracy of 100 g, and height was measured, with a precision of 0.5 cm, using the Seca stadiometer (Seca). The BMI was calculated using the formula. WC was measured in the narrowest area between the last rib and the iliac crest with a nonelastic tape measure with an accuracy of 0.1 cm.

BP was measured while sitting and using a digital BP monitor, three times with an interval of at least 5 min, and their average was recorded.

2.3. Laboratory tests

Blood samples, after 12 h of fasting, were taken from all patients, and biochemical parameters were measured. FBS, triglyceride, HDL‐C, alanine aminotransferase (ALT), aspartate aminotransferase (AST), and gamma‐glutamyl‐transferase (GGT) were measured using Pars Azmoon kit (Pars Azmoon Co.) and autoanalyzer BS200 (Mindray).

2.4. Measurement of NAFLD predictor indices

NAFLD predictor indices were calculated through the following formulas:

FLI = (e0.953×Ln (triglycerides)+0.139×BMI+0.718×Ln (GGT)+0.053×WC−15.745)/(1 + e0.953×Ln (triglycerides)+0.139×BMI+0.718×Ln (GGT)+0.053×WC−15.745) × 100 (Bedogni et al., 2006)

TyG Index = Ln (triglycerides [mg/dl] × glucose [mg/dl]/2) (Simental‐Mendía et al., 2008).

HSI = 8 × (ALT/AST) + BMI + 2 (if type 2 diabetes) + 2 (if female) (Fennoun et al., 2020).

The classification of NAFLD predictor indices in terms of the risk of developing NAFLD is as follows:

FLI: <30= (Low risk), 30< to < 60= Indeterminate risk and ≥60= High risk

HSI: < 30= No risk, 30< to <36= Indeterminate Risk, ≥36= High Risk

TyG Index: optimal cut‐off value to predict NAFLD is approximately 8.5 (Correa et al., 2021).

2.5. Diet assessment

Patients' food intake was estimated via a valid semiquantitative food frequency questionnaire (FFQ) (147 food items) (Mirmiran et al., 2010). A trained nutritionist determined the frequency of consumption (daily, weekly, monthly, and yearly) of each food item through an interview. Macro‐ and micronutrients intake, as well as energy intake was calculated based on the modified nutritionist IV for Iranian foods (First Databank Inc.).

HEI‐2015 consists of 13 components (Krebs‐Smith et al., 2018): adequacy components that include (total and whole fruits, total vegetables, greens and beans, total protein foods, whole grains, dairy, seafood and plant proteins, and fatty acids) (polyunsaturated fatty acids [PUFAs] + monounsaturated fatty acids [MUFAs]/saturated fatty acids [SFAs]), and moderation components that include (saturated fats, sodium, added sugars, and refined grains). Added sugars and saturated fats were converted to the percentage of total energy intake, and other components except fatty acids were converted to cups/oz or grams per 1000 kcal intake.

Total fruits, total vegetables, whole fruits, total protein foods, greens and beans, and seafood and plant proteins scored 0 (lowest) and 5 (highest) based on daily intake. The score of daily consumption of fatty acids, whole grains, and dairy was between 0 (lowest) and 10 (highest). Refined grains, added sugars, sodium, and saturated fats scored 0 (highest) and 10 (lowest) based on daily intake. Therefore, the HEI‐2015 total score ranges between 0 and 100.

2.6. Statistical analysis

Data were shown as mean ± standard deviation (SD) and percentages (n [%]) for continuous and categorical variables, respectively. The total HEI‐2015 was classified into quartiles according to their HEI‐2015 score. One‐way analysis of variance (ANOVA) was used to compare the average of the continuous variables across quartiles. A chi‐squared test was used to compare the frequencies between categorical variables. Simple and multiple linear regression were used to assess the adjusted effects of variables affecting the NAFLD predictor indices. In the adjusted model, the following variables were entered as covariates to control for confounding: age, sex, BMI, calorie, carbohydrate, and fat intake. A p value <.05 was considered statistically significant. All analyses were performed using SPSS software version 22 (SPSS Inc.).

3. RESULTS

The total number of participants was 344. There was 92 (26.5%) males. The mean age and BMI of the participants were 61.86 ± 10.21 years and 32.16 ± 4.22 kg/m2, respectively. The patients were divided into quartiles according to their HEI‐2015 scores as follows: Quartile 1: 50–69.25; Quartile 2: 69.26–73.67; Quartile 3: 73.68–77.49; and Quartile 4: ≥77.5. Table 1 shows the patient's characteristics. Patients in the highest quartile of the HEI‐2015 score were younger (p = .04); and had lower BMI (p = .12) and WC (p = .29) compared with those in the lowest quartile. Regarding the NAFLD predictor indices, there were differences in FLI and HSI scores across the HEI‐2015 quartiles, and patients with the highest HEI score had the lowest FLI (p = .003) and HSI scores (p = .05).

TABLE 1.

The characteristics of patients with metabolic syndrome by the lowest (1) and highest (4) quartiles of HEI‐2015 score.

Characteristics Quartile 1 (N = 86) Quartile 2 (N = 86) Quartile 3 (N = 86) Quartile 4 (N = 86) p value*
Age, years 63.51 ± 9.34 61.83 ± 9.81 62.79 ± 11.44 59.36 ± 9.88 .04
Sex (male) 23 (26.7) 21 (24.4) 28 (32.6) 20 (23.3) .52
Marital status (married) 85 (98.8) 84 (97.7) 86 (100.0) 86 (100.0) .29
Educational status
Illiterate 18 (20.9) 25 (29.1) 24 (27.9) 20 (23.3)
Diploma or less 65 (75.6) 54 (62.8) 58 (67.5) 60 (69.7) .64
Bachelor of science 3 (3.5) 5 (5.8) 4 (4.6) 5 (5.8)
Postgraduate 0 (0) 2 (2.3) 0 (0) 1 (1.2)
BMI (kg/m2) 32.4 ± 42.40 31.4 ± 87.15 32.04 ± 93.52 31.03 ± 47.69 .12
WC (cm) 104.8 ± 27.56 104.9 ± 10.29 104.10 ± 63.20 102.9 ± 11.33 .29
FLI 76.2 ± 12.48 69.80 ± 19.35 72.30 ± 18.18 66.71 ± 17.51 .003
TyG Index 4.85 ± 0.31 4.83 ± 0.28 4.80 ± 0.27 4.81 ± 0.26 .63
HSI 43.11 ± 5.14 43.00 ± 5.70 43.97 ± 6.06 41.69 ± 4.79 .05
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Significant results are shown in bold.

Note: Values are provided as mean ± SD or n (%). Quartile 1: 50–69.25; Quartile 2: 69.26–73.67; Quartile 3: 73.68–77.49; and Quartile 4: ≥ 77.5.

Abbreviations: BMI, body mass index; FLI, Fatty Liver Index; HSI, Hepatic Steatosis Index; TyG Index, Triglyceride‐Glucose Index; WC, waist circumference.

*

Statistical significance was set at the level of p < .05.

Table 2 displays the distribution of dietary intakes of macro‐ and micronutrients of participants across the quartiles of the HEI‐2015 scores. According to Table 2, patients in the highest quartile of the HEI‐2015 score intake of more protein, vitamin D, vitamin E, vitamin C, vitamin B6, vitamin B12, calcium, and zinc compared with those in the lowest quartile.

TABLE 2.

The distribution of dietary intakes of macro‐ and micronutrients of participants by the lowest (1) and highest (4) quartiles of HEI‐2015 score.

Characteristics (mean ± SD) Quartile 1 (N = 86) Quartile 2 (N = 86) Quartile 3 (N = 86) Quartile 4 (N = 86) p value*
HEI‐2015 score 64.14 ± 4.24 71.60 ± 1.28 75.70 ± 1.21 80.75 ± 2.78
Energy intake (kcal/days) 2775.03 ± 920.75 2816.24 ± 723.06 3037.9 ± 928.85 2858.18 ± 943.19 .22
Total protein intake (g/days) 95.99 ± 39.18 105.79 ± 33.97 121.92 ± 50.68 121.18 ± 43.58 <.001
Total carbohydrate intake (g/days) 391.84 ± 140.87 396.60 ± 115.47 407.96 ± 120.65 377.90 ± 132.58 .48
Total fat intake (g/days) 97.30 ± 45.19 96.63 ± 36.11 109.90 ± 42.48 104.92 ± 42.91 .11
Vitamin D (μg/days) 1.53 ± 1.65 2.47 ± 2.76 2.84 ± 2.04 3.06 ± 3.03 <.001
Vitamin E (mg/days) 14.40 ± 9.44 13.26 ± 6.01 17.03 ± 8.94 19.43 ± 10.97 <.001
Vitamin C (mg/days) 144.25 ± 93.50 189.62 ± 112.02 223.62 ± 108.09 245.94 ± 117.97 <.001
Vitamin B6 (mg/days) 2.14 ± 0.82 2.46 ± 0.73 2.79 ± 1.08 2.85 ± 1.04 <.001
Vitamin B9 (μg/d) 574.39 ± 220.46 609.35 ± 185.54 644.81 ± 244.11 644.52 ± 221.37 .10
Vitamin B12 (μg/days) 5.69 ± 3.01 6.80 ± 3.35 7.55 ± 4.26 7.18 ± 3.40 .005
Zinc (mg/days) 14.74 ± 5.86 16.54 ± 5.01 18.71 ± 8.19 18.32 ± 7.15 <.001
Calcium (mg /days) 1342.03 ± 697.34 1616.724 ± 706.40 1736.71 ± 772.36 1739.58 ± 717.66 .001
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Significant results are shown in bold.

Note: Quartile 1: 50–69.25; Quartile 2: 69.26–73.67; Quartile 3: 73.68–77.49; and Quartile 4: ≥77.5.

Abbreviation: HEI‐2015, Healthy Eating Index‐2015.

*

Statistical significance was set at the level of p < .05.

Patients in the highest quartile of the HEI‐2015 score intake more total fruits (p < .001), whole fruits (p < .001), total vegetables (p < .001), greens and beans (p < .001), dairy (p < .001), total protein foods (p < .001), seafood and plant proteins (p < .001), and healthy fats (p < .001) as well as less refined grains (p = .006) than patients in the lowest quartile (not shown in the table).

Table 3 indicates the relationship between NAFLD predictor indices and HEI‐2015. According to the crude and adjusted models, there was an inverse relationship between the HEI‐2015 and FLI (β = −0.49; p < .001 and β = −0.44; p < .001, respectively), HSI (β = −0.05; p = .25 and β = −0.02; p = .40, respectively), and TyG Index (β = −0.002; p = .34 and β = −0.002; p = .36, respectively).

TABLE 3.

The crude and adjusted model for the association between HEI‐2015 and NAFLD predictor indices in patients with MetS.

NAFLD predictor indices Crude Model a
β SE p * β SE p *
FLI −0.49 0.14 <.001 −0.44 0.09 <.001
TyG Index −0.002 0.002 .34 −0.002 0.002 .36
HSI −0.05 0.04 .25 −0.02 0.02 .40
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Significant results are shown in bold.

Abbreviations: FLI, Fatty Liver Index; HSI, Hepatic Steatosis Index, TyG Index, Triglyceride‐Glucose Index.

a

Adjusted for age, sex, energy, carbohydrate and fat intake, and BMI.

*

Statistical significance was set at the level of p < .05.

4. DISCUSSION

NAFLD, as a serious complication of MetS, is a main risk factor for chronic liver diseases (Eslam et al., 2020; Matteoni et al., 1999). Various studies have shown that FLI, HSI, and TyG Index are accurate, simple, and valuable tools to predict and diagnose NAFLD (Huang et al., 2015; Khamseh et al., 2021; Sourianarayanane & McCullough, 2022). Identifying the factors influencing the occurrence of NAFLD plays an essential role in preventing disease. The most recommended treatment for NAFLD is lifestyle modification with an emphasis on both physical activity and a healthy diet (Liver & Diabetes, 2016). HEI‐2015 is a well‐known measure of diet quality (Krebs‐Smith et al., 2018). We evaluate the relationship between the HEI‐2015 score and NAFLD predictor indices (FLI, HSI, and TyG Index) in patients with MetS.

Our results showed that there was a negative association between HEI‐2015 and FLI, HSI, and TyG Index; however, it was statistically significant only between HEI‐2015 and FLI. Similar to the finding of the present study, the results of another study showed that the HEI‐2015 score in adults with a higher FLI score was significantly poorer compared with adults with a lower FLI score (Madril et al., 2021). Various studies have shown that there was a negative association between diet quality and NAFLD or fibrosis risk (Kalafati et al., 2019; Ma et al., 2018; Soleimani et al., 2019). A cohort study revealed that a higher HEI‐2015 score was related to a lower risk of NAFLD (Park et al., 2020). In a study with 3589 participants in the United States, a lower risk of NAFLD was reported to be associated with a higher HEI score (Vilar‐Gomez et al., 2022). In another study, a healthy diet (higher HEI‐2015 score) was related to lower all‐cause and cardiovascular mortality in patients with NAFLD (Vilar‐Gomez et al., 2023).

A higher HEI‐2015 score, which indicates a high‐quality diet, shows more intake of vegetables, fruits, seafood, and plant proteins, whole grains, healthier fatty acids, and a lower intake of refined grains, sodium, and added sugars (Krebs‐Smith et al., 2018). In the current study, patients who were in the highest HEI‐2015 quartile consumed more fruits, dairy, vegetables, greens and beans, seafood and plant proteins, and healthy fatty acids, as well as fewer refined grains than patients in the lowest quartile. Furthermore, compared with patients in the first HEI‐2015 quartile, FLI and HSI scores were lower in patients in the highest quartile.

HEI‐2015 components could be related to the reduction of NAFLD risk by different mechanisms. Considering that obesity is one of the causes of NAFLD (Rich et al., 2018), consuming fiber, from whole grains, vegetables, and fruits, by inducing satiety could contribute to weight loss (Nöthlings et al., 2008). In addition, the fermentation process of dietary fibers by intestinal bacteria leads to the production of short‐chain fatty acids (SCFAs). SCFAs may prevent NAFLD by regulating inflammation, appetite, fatty acid oxidation, and insulin resistance (Zhang et al., 2021). Furthermore, oxidative stress is involved in the initiation and progression of NAFLD (Rives et al., 2020), and therefore, vitamins, polyphenols, phytochemicals, and carotenoids in fruits and vegetables could prevent NAFLD due to their antioxidant properties (Ahmadi et al., 2023; Saini et al., 2015; Salomone et al., 2016). A statistically significant inverse relationship between dietary carotenoid intake and the US FLI score was revealed by Christensen et al. (2019).

It has been shown that healthy fatty acids (MUFAs and PUFAs [particularly omega‐3 FAs]) could prevent NAFLD by reducing triglycerides, glucose, oxidative stress, and hepatic steatosis as well as improving insulin sensitivity, anti‐inflammatory effect, and inhibiting hepatic fat accumulation (Berge et al., 2014; Kamari et al., 2023; Spooner & Jump, 2019). The main sources of omega‐3 FAs are seafood, seeds, nuts, and plant derivatives (Calder, 2013). In a cross‐sectional study, nut consumption was associated with a lower risk of NAFLD (calculated by FLI) in older adults (Tan et al., 2021). In another study, it was reported that an omega‐3 PUFA‐rich diet (fish oil diet) reduced the risk of NAFLD by inhibiting acetyl‐CoA carboxylase and sterol regulatory element‐binding protein‐1c (SREBP‐1c) (Zhou et al., 2021). Khan and Jackson (2018) found a significant relationship between pro‐inflammatory omega‐6 FAs intake and FBS, triglyceride, and cholesterol. In this study, the main sources of omega‐6 FAs were red meat, chicken, and dairy products.

Several studies have shown that the Mediterranean diet, which is rich in whole grains, fruits and vegetables, monounsaturated fats, omega‐3 FAs, and plant proteins as well as low in saturated fat is related to lower risk and progression of NAFLD (Baratta et al., 2017; Kastorini & Panagiotakos, 2010; Saeed et al., 2019). On the other hand, it has been determined that Western dietary patterns which are characterized by a high intake of fast foods, refined grains, added sugar, sodium, and saturated fats are associated with high NAFLD risk due to increased insulin resistance, weight gain, oxidative stress, and pro‐inflammatory processes (Kalafati et al., 2019; Soleimani et al., 2019; Trovato et al., 2018). The result of a meta‐analysis showed that higher sodium intake is related to a higher risk of NAFLD (Shojaei‐Zarghani et al., 2022).

The current study has some strengths and limitations. The current research is the first study on the association between the HEI‐2015 score and NAFLD predictor indices (FLI, HSI, and TyG Index) in patients with MetS. According to the study design (cross‐sectional), it was not possible to assess the causality, so it is suggested to conduct prospective cohort studies. While validated FFQ was used, there is the possibility of recall bias. However, the collection of data from the questionnaire by a trained nutritionist reduced recall bias. Despite adjusting for important confounding factors, there may still be other confounders that affect the results of this study.

According to our results, in patients with MetS, HEI‐2015 score and NAFLD predictor indices (FLI, HSI, and TyG Index) were inversely correlated; however, this relationship was statistically significant only in the case of FLI. Adherence to a diet containing whole grains, fruits, vegetables, plant‐based protein foods, and healthy fats could be beneficial in preventing NAFLD in patients with MetS.

AUTHOR CONTRIBUTIONS

Maryam Taghdir: Conceptualization (lead); data curation (equal); formal analysis (equal); investigation (equal); methodology (equal); project administration (lead); supervision (lead); validation (equal); visualization (equal); writing – original draft (lead); writing – review and editing (equal). Akram Salehi: Conceptualization (equal); data curation (equal); formal analysis (equal); investigation (equal); methodology (equal); writing – original draft (equal); writing – review and editing (equal). Karim Parastouei: Conceptualization (equal); data curation (equal); formal analysis (equal); investigation (equal); methodology (equal); project administration (equal); validation (equal); visualization (equal); writing – original draft (equal); writing – review and editing (equal). Sepideh Abbaszadeh: Conceptualization (equal); data curation (equal); formal analysis (equal); investigation (equal); methodology (equal); project administration (equal); validation (equal); visualization (equal); writing – original draft (equal); writing – review and editing (equal).

FUNDING INFORMATION

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

CONFLICT OF INTEREST STATEMENT

No conflicts of interest to declare.

ETHICS APPROVAL

The study was approved by the ethics committee for Research at Baqiyatallah University of Medical Sciences (IR.BMSU.REC.1400.058).

ACKNOWLEDGEMENTS

We acknowledge all patients who contributed to this research.

Taghdir, M. , Salehi, A. , Parastouei, K. , & Abbaszadeh, S. (2023). Relationship between diet quality and nonalcoholic fatty liver disease predictor indices in Iranian patients with metabolic syndrome: A cross‐sectional study. Food Science & Nutrition, 11, 6133–6139. 10.1002/fsn3.3549

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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Associated Data

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

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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