Associations between dietary inflammatory index (DII) scores and attention deficit hyperactivity disorder (ADHD) in children

Abstract

Attention deficit hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders, yet its underlying mechanisms remain unclear. Genetic, family history, nutritional, lifestyle, and inflammatory factors are considered as contributing factors of ADHD. The dietary inflammatory index (DII) could be used to determine whether a diet has an inflammatory potential. Therefore, the purpose of this study was to find out if DII scores and ADHD were related. This study included 500 Iranian children aged 4–12 (200 ADHD cases and 300 healthy controls). Food frequency questionnaires (FFQs) consisting of 168 items were used to determine dietary intake. DII scores were calculated using data from D-FFQ. Energy-adjusted DII (E-DII) scores were calculated using standardized z-scores for each food item, following established protocols. Analysis of covariance (ANCOVA) assessed energy-adjusted dietary intake across DII tertiles. Multivariable logistic regression estimated ADHD odds ratios (ORs) and 95% confidence intervals (CIs) through two hierarchical models: Model 1 (adjusted for age, gender, income) and Model 2 (Model 1 + BMI). Statistical significance was set at p < 0.05, with analyses performed in SPSS version 21. Overall, 200 ADHD and 300 healthy children participated in this study. Energy-adjusted dietary inflammatory index (E-DII) was directly associated with ADHD risk in the crude model (OR = 1.104; 95% CI: 1.009, 1.208; p = 0.031). This result also remained significant in Model 1 (OR = 1.162; 95% CI: 1.050, 1.285; p = 0.004) and Model 2 (OR = 1.133; 95% CI: 1.021, 1.258; p = 0.019). We found that E-DII had a significant association with the risk of ADHD in Iranian children. Limitations include the case-control design, which precludes causal inference, and potential residual confounding from unmeasured factors. It will be necessary to conduct further studies to confirm these findings.

Introduction

Attention deficit hyperactivity disorder (ADHD), a prevalent neurodevelopmental disorder characterized by impulsivity, inattention, and hyperactivity, profoundly impacts behavioral, social, and academic functioning across the lifespan^1–4. The global prevalence of ADHD in children and adolescents aged 3–12 years was 7.6%⁵. The prevalence of ADHD is nearly twice as high in Western countries (15.5%) as in Iran (9.7%), according to epidemiological studies of primary school populations⁶.

ADHD, a multifactorial disorder with unclear mechanisms, involves genetic, environmental, and lifestyle factors, with emerging evidence highlighting inflammatory pathways in its pathophysiology. High dietary inflammatory index (DII) scores, reflecting diets rich in inflammatory agents (e.g., processed fats, sugars), correlate with elevated levels of inflammatory markers^7–9. These processes disrupt neurodevelopment by impairing BDNF synthesis, altering neuronal migration via glial dysfunction, and modifying synaptic plasticity—mechanisms central to ADHD’s cognitive and behavioral symptoms^10,11. By linking dietary patterns to neuroinflammatory cascades, DII provides critical insights into how nutrition modulates ADHD pathophysiology, positioning dietary anti-inflammatory strategies as potential therapeutic avenues.

Emerging evidence underscores a link between pro-inflammatory diets and heightened ADHD risk in children. Meta-analytic data reveal that unhealthy dietary patterns (e.g., high processed foods, low fruit/vegetable intake) correlate with increased ADHD diagnosis and symptom severity¹², while adherence to nutrient-rich diets may mitigate attentional deficits¹³. Cross-sectional studies highlight associations between ADHD and Western-style diets or excessive sweet-food consumption¹⁴, though maternal pro-inflammatory diets during pregnancy paradoxically linked to reduced ADHD symptoms in boys¹⁵. While prior research predominantly isolates micronutrients (e.g., vitamins A, D, B-complex; iron, zinc) as neuroprotective agents^16–18, these studies neglect the systemic inflammatory impact of diet as a whole. The Dietary Inflammatory Index (DII) bridges this gap by quantifying how pro-inflammatory diets disrupt neurodevelopment through chronic inflammation, offering a holistic lens to evaluate dietary contributions to ADHD pathophysiology.

To date, limited research has directly investigated DII and ADHD, with no studies focusing on pediatric populations in the Middle East, particularly Iran. Given this country’s high ADHD prevalence and the modifiable nature of dietary habits, understanding the role of diet-driven inflammation in ADHD is critical. This study is the first to examine the association between DII scores and ADHD in Iranian children, addressing a significant regional and methodological gap in the literature. Our findings could inform culturally tailored dietary interventions to mitigate the ADHD burden in this population.

Materials and methods

Study design and participants

This case-control study was performed in Isfahan, Iran. 500 children aged 4–12 years were enrolled: 105 preschoolers and 395 schoolchildren. Age and sex were matched between cases and controls. ADHD children were recruited from psychotherapy clinics, while the control group was selected from preschools and elementary schools. Participants were recruited through a multistage stratified cluster sampling method to ensure geographic diversity and minimize selection bias. There was no history of chronic diseases, psychiatric disorders, special diets, dietary restrictions, or medication use among subjects in the control group. Moreover, they were tested for ADHD. A meeting was held with children and their parents to explain the procedure for the study, and informed consent from a parent and/or legal guardian was obtained before the commencement of the study. Ethics committee approval was received from Isfahan University of Medical Sciences (IR.MUI.REC.1395.3529). All methods were performed according to the relevant guidelines and regulations.

Sample size calculation

Since no prior studies have assessed the association between the “Dietary Inflammatory Index” and ADHD, we derived estimates for sample size calculation from a study examining a conceptually similar dietary pattern, the Mediterranean diet, which was previously linked to reduced ADHD risk in Iranian children (OR = 0.49)¹⁹. Key assumptions for sample size estimation were, Confidence level: 95% (α = 0.05), Power: 80% (β = 0.20), Control-to-case ratio: 1.5 (to enhance statistical efficiency). Based on the above assumptions and calculations, the minimum required sample size was determined to be 105 cases (ADHD group) and 158 controls (non-ADHD group).

ADHD diagnosis

This study used the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-V) to diagnose ADHD. The DSM-V specifies that someone suffering from ADHD has six or more symptoms of hyperactivity-impulsivity or inattention for at least six months²⁰. In a previous study, it was demonstrated that this questionnaire was reliable and valid²⁰. ADHD diagnosis was made by a psychiatrist in this study.

Dietary assessment

A semi-quantitative food frequency questionnaire (FFQ) consisting of 168 food items was administered by an interviewer to evaluate dietary intake. Each food item was provided with a standard portion size. This questionnaire investigated the usual food intake over the last year. While seasonal variations were minimized by assessing both groups during similar times of the year, residual effects of seasonality on food availability (e.g., seasonal fruits or festive diets) could still introduce variability. However, seasonality was not included as a covariate in statistical models due to overlapping assessment periods. To contextualize the analysis, food items were categorized into pro-inflammatory (e.g., refined carbohydrates, saturated fats, trans fats) and anti-inflammatory (e.g., fruits, vegetables, whole grains, omega-3-rich foods) groups based on their established effects on inflammatory biomarkers. The validation and reliability of this FFQ were published elsewhere²¹. The questionnaire was completed by parents. To minimize seasonal variations in food consumption, the nutritional intakes of subjects in both groups were assessed at similar times of the year. To report the mean intake, parents could select from the following frequency options: every day, 5–6 times per week, 2–4 times per week, once a week, 2–3 times per month, and never. Parents completed the FFQ, which may introduce recall bias, particularly for children with irregular eating patterns or discretionary snack consumption. To mitigate this, interviewers provided visual aids (e.g., household measurement tools) to improve portion size accuracy, and dietary intakes were converted to grams/day using standardized protocols. Nutritionist IV software (version 7.0; N-Squared Computing, Salem, OR, USA) was used to calculate nutrient intake.

Calculation of energy-adjusted dietary inflammatory index (E-DII)

DII scores for all subjects were estimated based on dietary data derived from D-FFQ. The DII was designed [12] and validated [30,31] in earlier studies. Shivappa et al. [12] determined that inflammatory markers such as CRP, Tumor Necrosis Factor-a (TNF-a), Interleukin-1b (IL-1b), IL-6, or anti-inflammatory factors such as IL-4 and IL-10 were related to 45 different foods and nutrients. Then, for each food item, the researchers evaluated whether it reduced anti-inflammatory or elevated inflammatory factors (þ1), reduced inflammatory or elevated anti-inflammatory factors¹, or did not alter anti-inflammatory and inflammatory factors (0).

The world means and standard deviations of 45 food items were calculated using 11 data sets from 11 countries. However, 16 food items (e.g., polyphenols, specific spices) were excluded due to their unavailability in the Iranian nutrient database or irrelevance to local dietary habits, reducing the final DII calculation to 29 items. We used the following food items: Anti-inflammatory factors consist of vitamin D, B6, fiber, riboflavin, folic acid, thiamin, niacin, polyunsaturated fatty acids (PUFA), mono-unsaturated fatty acids (MUFA), beta carotene, vitamin C, A, E, pepper, onion, caffeine, tea, zinc, magnesium, and selenium and pro-inflammatory factors included iron, vitamin B12, fat, carbohydrate, trans fat, protein, saturated fat, energy, and cholesterol. The energy density method was used to adjust dietary intake for calories (dietary intake per 1000 calories). The DII was calculated using the approved method²². The z-score for each food item was calculated by following the formula:

Z-score = (individual mean intake – global mean intake) / global SD.

As the distribution of the z-score is right-skewed, we estimated a centered percentile score for all food items. Then, these scores were multiplied by the overall inflammatory effect scores reported in a previous study²². The DII scores of all items were summed and reported as the total DII score. The DII assumes that the inflammatory effects of foods and nutrients are consistent across populations, despite potential regional variations in food preparation (e.g., spice use in Iranian cuisine) or consumption patterns (e.g., tea brewing methods). These differences may alter the actual inflammatory impact of certain items, potentially limiting the generalizability of DII scores to culturally distinct diets.

Anthropometric measurements

Digital scales were used to measure the weight of participants while they wore light clothing and no shoes. According to WHO protocols²³, a tape measure was used to measure height. Body mass index (BMI) was estimated as follows: weight (kg) × height² (m).

Other variables

General characteristics including age and sex as well as family income of the participants were collected via a self-reported questionnaire.

Statistical analysis

Means and standard deviations (SD), and percentages were reported for continuous and categorical variables, respectively. Using an independent t-test and the chi-square test, the scale and categorical variables were compared between two groups. Comparing energy-adjusted dietary intake across tertiles of DII was done using analysis of covariance (ANCOVA). The odds ratio (OR) and 95% confidence interval of ADHD were estimated using logistic regression. The results of Model 1 were adjusted for age, gender, and income status. Model 2 was adjusted based on the variables of Model 1 and BMI. In the analysis, P ˂0.05 was considered significant, and SPSS version 21 was used for data analysis.

Results

Overall, 200 ADHD and 300 healthy children in the age range of 4–12 years and mean age of 6.98 participated in this study. Table 1 shows the general characteristics of ADHD children and the control group. Age (P = 0.354) and sex (P = 0.455) did not differ significantly between the two groups. ADHD subjects had lower weight (P < 0.001), BMI (P = 0.001), and height (P = 0.003) than control subjects. Income status was higher among healthy than ADHD children (< 0.001).

Table 1.

General characteristics of children with attention deficit hyperactivity disorder and healthy controls.

Variable	ADHD (n = 200)	Healthy Controls (n = 300)	P
Gender (%)
Male	79.5	76.7	0.455
Female	20.5	23.3
Age (year)	7.07 ± 1.71	6.92 ± 1.66	0.354
Weight (kg)	20.50 ± 6.43	23.02 ± 8.80	< 0.001
Height (cm)	120.86 ± 9.77	123.60 ± 10.49	0.003
BMI (kg/m2)	13.71 ± 2.49	14.60 ± 3.15	0.001
Income status (%)
Low	54	29.3	< 0.001
Middle	30	32.7
High	16	38

Data are presented as mean ± SD for continuous and percent for categorical variables.

P-value obtained from chi-square analysis for categorical variables and independent t-test for continuous variables.

ADHD: Attention deficit hyperactivity disorder.

BMI: Body mass index.

Table 2 indicates dietary intakes of participants across tertiles of E-DII scores. Healthy children consistently demonstrated higher consumption of protein, vitamins A, B1, and C, as well as zinc, potassium, magnesium, phosphorus, calcium, and dietary fiber compared to children with ADHD, with differences remaining significant across all E-DII tertiles (P < 0.001). Conversely, children with ADHD exhibited greater intake of total fat and saturated fatty acids (SFAs) than their healthy counterparts (P < 0.001).

Table 2.

Dietary intakes across tertiles of energy-adjusted dietary inflammatory index.

Nutrient	Tertiles of energy-adjusted dietary inflammatory index
	T1 (n = 166)	T2 (n = 167)	T3 (n = 167)
Carbohydrate (gr/day)
ADHD Control	219.1 ± 15.2 228.7 ± 19.3	217.6 ± 16.7 223.1 ± 13.2	216.7 ± 21.9 217.1 ± 18.0
P value	< 0.001	0.003	0.893
Protein (gr/day)
ADHD Control	42.3 ± 20.5 71.8 ± 18.1	47.3 ± 21.9 75.3 ± 15.4	50.6 ± 21.9 82.3 ± 18.0
P value	< 0.001	< 0.001	< 0.001
Fat (gr/day)
ADHD Control	77.3 ± 6.1 61.7 ± 8.6	75.9 ± 7.7 62.8 ± 6.4	70.1 ± 10.8 57.6 ± 9.0
P value	< 0.001	< 0.001	< 0.001
SFA (gr/day)
ADHD Control	21.6 ± 2.5 17.2 ± 2.5	21.1 ± 3.2 17.0 ± 1.6	19.2 ± 2.5 15.2 ± 2.5
P value	< 0.001	< 0.001	< 0.001
Vitamin A (RAE)
ADHD Control	748.1 ± 468.2 1182.2 ± 383.8	845.7 ± 579.8 1263.2 ± 438.0	999.5 ± 592.6 1200.6 ± 489.5
P value	< 0.001	< 0.001	0.005
Vitamin B1(mg/day)
ADHD Control	1.0 ± 0.12 1.2 ± 0.12	1.0 ± 0.1 1.2 ± 0.1	1.0 ± 0.1 1.3 ± 0.1
P value	< 0.001	< 0.001	< 0.001
Vitamin C (mg/day)
ADHD Control	84.2 ± 16.24 163.2 ± 58.50	91.3 ± 60.5 162.3 ± 45.1	109.1 ± 61.8 178.2 ± 50.2
P value	< 0.001	< 0.001	< 0.001
Zn (mg/day)
ADHD Control	5.0 ± 0.1.3 7.6 ± 1.3	5.4 ± 1.6 8.0 ± 1.6	5.6 ± 1.3 8.2 ± 1.3
P value	< 0.001	< 0.001	< 0.001
Potassium (mg/day)
ADHD Control	1959.9 ± 772.8 3036.7 ± 631.1	2116.6 ± 876.1 3208.2 ± 657.0	2318.3 ± 721.5 3335.3 ± 582.7
P value	< 0.001	< 0.001	< 0.001
Magnesium (mg/day)
ADHD Control	152.9 ± 56.6 242.5 ± 46.4	162.4 ± 64.5 250.6 ± 47.7	175.1 ± 50.2 263.5 ± 41.2
P value	< 0.001	< 0.001	< 0.001
Phosphorus (mg/day)
ADHD Control	738.0 ± 235.1 1141.2 ± 193.3	785.2 ± 283.4 1198.1 ± 219.8	837.6 ± 243.5 1255.6 ± 199.7
P value	< 0.001	< 0.001	< 0.001
Calcium (mg/day)
ADHD Control	525.9 ± 253.8 818.7 ± 176.5	549.8 ± 248.6 847.6 ± 185.5	578.8 ± 213.9 881.5 ± 175.2
P value	< 0.001	< 0.001	< 0.001
Fiber (gr/day)
ADHD Control	8.1 ± 5.1 17.7 ± 3.8	9.0 ± 5.1 18.4 ± 3.8	10.9 ± 5.1 19.3 ± 3.8
P value	< 0.001	< 0.001	< 0.001

Data are presented as mean ± SD.

P-value obtained from analysis of variance (ANOVA).

Carbohydrate intakes differed notably across E-DII tertiles: while consumption was significantly higher in the lowest (P < 0.001) and middle (P = 0.03) tertiles, no significant difference was observed between ADHD and healthy children within the highest E-DII tertile (P = 0.893). Consistent with our hypotheses, the findings of this study revealed a higher intake of pro-inflammatory nutrients (e.g., fat and SFAs) in the ADHD group, whereas the healthy group exhibited a dietary profile enriched with anti-inflammatory components. Notably, for certain nutrients such as carbohydrates, phosphorus, and protein, the dietary source, rather than the absolute intake level, appears to critically determine their inflammatory or anti-inflammatory potential. For instance, while phosphorus intake from legumes and red meat may be comparable, their inflammatory effects differ significantly, with red meat-derived phosphorus demonstrating a stronger pro-inflammatory impact compared to plant-based sources. These findings highlight a critical dietary dichotomy, with nutrient sources, not just quantities, exerting a pivotal influence on inflammatory profiles, urging tailored nutritional interventions for ADHD management.

Table 3 illustrates the risk of ADHD per one-unit increase in the E-DII. E-DII and ADHD are directly associated (OR = 1.104; 95% CI: 1.009, 1.208; p = 0.031) in the crude model. This result remained significant in Model 1 (OR = 1.162; 95% CI: 1.050, 1.285; p = 0.004) and Model 2 (OR = 1.133; 95% CI: 1.021, 1.258; p = 0.019) after adjustments for potential cofactors.

Table 3.

Risk of attention deficit hyperactivity disorder per one-unit increase in energy-adjusted dietary inflammatory index.

Model	Odds ratio	95% CI	P
Crude	1.104	1.009, 1.208	0.031
Model 1	1.162	1.050, 1.285	0.004
Model 2	1.133	1.021, 1.258	0.019

P-value obtained from logistic regression.

Model 1: Adjusted for sex, age, and income status.

Model 2: adjusted for sex, age, income status and body mass index.

Discussion

This study investigated the possible association of E-DII with the risk of ADHD in Iranian children and indicated that higher E-DII scores could increase the risk for ADHD. As far as we are aware, this study is the first to examine the relationship between E-DII scores and ADHD in children.

ADHD significantly impacts the quality of life of children and their families and causes financial hardship for families and societies²³. Previous research has suggested that dietary patterns may contribute to the etiology of ADHD. A meta-analysis revealed that ADHD was associated with unhealthy dietary patterns, which included a higher intake of processed foods and sweets. Conversely, the odds of ADHD were reduced by a diet that was well-balanced and abundant in fruits and vegetables²⁴. Furthermore, lower systemic inflammation had an association with higher consumption of vegetables and fruits, as demonstrated by lower DII scores²⁵.

Research on the link between diet and ADHD reveals divergent findings, with certain studies indicating that nutrient-dense diets may lower ADHD risk²⁶, while others report no significant association²⁷. A comprehensive meta-analysis highlights that dietary choices substantially modulate ADHD susceptibility¹². Specifically, diets emphasizing fruits, vegetables, fatty fish, polyunsaturated fats (PUFAs), and micronutrients like magnesium and zinc correlate with a 37% reduction in ADHD risk. Conversely, Western-style diets—high in processed meats, refined carbohydrates, sugary drinks, and trans fats—are associated with a 92% higher ADHD likelihood. Similarly, diets dominated by ultra-processed foods laden with artificial additives and refined sugars elevate ADHD risk by 51%. These findings underscore the critical role of dietary quality in ADHD prevention and management.

Recent research has revealed an association between dietary inflammatory potential and neuropsychiatric disorders. A higher DII score was related to higher odds of anxiety and depression^28–30. A study conducted in Iran demonstrated that diets that promote inflammation strongly correlated with mental illnesses³¹. Another meta-analysis suggested that an anti-inflammatory diet may reduce depression symptoms³². Elevated levels of inflammatory biomarkers have adverse effects on childhood neurodevelopment³³.

Diets high in pro-inflammatory compounds might elevate the risk of ADHD and other psychological disorders through some mechanisms. Pro-inflammatory diets, rich in processed foods and saturated fats, disrupt gut microbiota composition, fostering dysbiosis characterized by reduced beneficial taxa (e.g., Bifidobacteria, Lactobacillus) and overgrowth of pathogenic species³⁴. This imbalance compromises intestinal barrier integrity, increasing permeability (“leaky gut”) and allowing translocation of lipopolysaccharides (LPS) into systemic circulation³⁵. LPS triggers Toll-like receptor 4 (TLR4) signaling, activating NF-κB and stimulating pro-inflammatory cytokine release (e.g., IL-6, TNF-α)³⁴. These cytokines perpetuate systemic inflammation and may cross the blood-brain barrier (BBB) or activate vagal afferents, directly influencing central nervous system (CNS) function^36,37. Chronic gut-derived inflammation, driven by systemic inflammation and oxidative stress, has been implicated in neurodevelopmental disruptions, particularly in regions governing attention and impulse control^38–40. Furthermore, inflammatory cytokines enter the brain and may interact with the metabolism and function of neurotransmitters like dopamine, serotonin, and norepinephrine⁴¹. Additionally, oxidative stress caused by inflammation also increases dopamine, a very important neurotransmitter in the symptoms of ADHD⁴². Dietary nutrients with potent antioxidant and anti-inflammatory properties play a pivotal role in maintaining cellular redox homeostasis and mitigating neuropsychiatric disorders. These nutrients regulate antioxidant defenses by activating pathways such as nuclear factor erythroid 2-related factor 2 (Nrf2), which enhances phase II detoxification processes through enzymes like heme oxygenase-1 (HO-1), glutathione peroxidase (GPx), superoxide dismutase (SOD), and catalase (CAT). Concurrently, they modulate neuroprotective agents, including heat shock protein 70 (Hsp70) and sirtuin-1 (Sirt1), to counteract oxidative stress (OS) and neurotoxic damage implicated in the development and progression of neuropsychiatric disorders, such as ADHD. By mitigating oxidative and inflammatory cascades, these mechanisms support neuronal integrity and function, highlighting the therapeutic potential of anti-inflammatory diets in ADHD pathophysiology^43–45.

There were some limitations regarding this study that should be considered. First, the case-control design and reliance on retrospective dietary assessment via the Food Frequency Questionnaire (FFQ) introduce potential biases that limit causal inference. Another potential limitation of this study was that only 38 dietary items were used to calculate the DII score, and 16 dietary items were missed. Although we tried to control the impact of confounders, it is not possible to exclude residual confounding. While adjustments were made for age, sex, income, and BMI, unmeasured confounders such as physical activity, sleep quality, environmental exposures, or genetic factors were not accounted for, which may influence the observed associations between DII and ADHD. Despite these limitations, this study had several strengths. The inclusion of a relatively large sample size improves statistical power, while rigorous ADHD diagnosis by a psychiatrist using DSM-V criteria ensures diagnostic accuracy. Furthermore, dietary intake was assessed using a validated 168-item FFQ, which captures detailed nutritional data and accounts for seasonal variations, strengthening the reliability of dietary exposure estimates. Importantly, while this study provides novel insights into the relationship between E-DII and ADHD in Iranian children, the cultural and dietary context of Iran, characterized by unique dietary patterns, food availability, and culinary traditions, may limit the generalizability of findings to other populations. Future research should prioritize replicating these findings in diverse geographic locations and ethnic populations to determine whether the observed association between dietary inflammation and ADHD is consistent across varying cultural, socioeconomic, and environmental contexts.

In conclusion, this study demonstrates a significant association between higher Dietary Inflammatory Index (DII) scores and increased ADHD risk in Iranian children, suggesting that pro-inflammatory diets may influence neurodevelopmental health. Consequently, dietary modification has gained traction as a promising adjunctive therapeutic strategy for ADHD. However, further rigorous scientific validation through large-scale randomized controlled trials and longitudinal studies is imperative to establish causal efficacy, optimize dietary protocols, and integrate these interventions into standardized ADHD treatment guidelines.

Author contributions

Fatemeh Navab: Writing original draft – review & editingKhadijeh Abbasi: Writing original draftHajar Heidari: Writing original draftReza Ghiasvand: Writing – review & editingCain C. T. Clark: review & editingMohammad Bagherniya: Writing – review & editingShirin Hassanizadeh: Writing – review & editingMohammad Hossein Rouhani: Writing – review & editing, Supervision, Formal analysis, Conceptualization, Validation, Software, Project administration.

Funding

The study was funded by Isfahan University of Medical Science. However, the funder was not involved in designing, collecting, analyzing, interpreting data, writing the report, or deciding whether it should be submitted. Grant/Award Number: 395529.

Data availability

Data will be provided upon request. The lead author, Mohammed Hossein Rouhani, should be contacted regarding data requirements.

Declarations

Competing interests

The authors declare no competing interests.

Consent to participate and ethical approval

The Research Council and Ethical Committee of Isfahan University of Medical Sciences, Isfahan, Iran, gave ethical approval to this study (Code IR.MUI.REC.1395.3529). Every participant filled out an informed consent form as well. As the lead author, Mohammed Hossein Rouhani confirms the report is honest, accurate, and transparent; no significant study components have been omitted; and any deviations from the original plan have been explained.