Skip to main content
Download PDF

Association of healthy eating index and self-rated health in adults living in Tehran: a cross-sectional study

BMC Public Health volume 24, Article number: 1106 (2024) Cite this article

Abstract

Background

Self-rated health (SRH) has been identified in many studies as a valid predictor of mortality and healthcare utilization. There is limited research on SRH and dietary intake. This study aimed to investigate the association between healthy eating index (HEI) and SRH in adults living in Tehran.

Methods

This cross-sectional study was carried out among 850 adult men and women aged 20–59 years who visited health centers in Tehran from 2021 to 2022. Dietary intake was assessed using a validated and reliable semiquantitative food frequency questionnaire with 168 food items, and SRH was assessed with one question: “In general, how do you rate your health?“. We categorized SRH into excellent/very good, good, and fair/poor. In the descriptive statistics part, we used mean ± standard deviation or number (ratio) for quantitative and qualitative variables, respectively. The chi-squared test and one-way analysis of variance were used to calculate the percentage and mean for demographic characteristics across tertiles of SRH. An analysis of covariance was used to compare the means of energy, macronutrients, the HEI, and its component variables across the tertiles of SRH.

Results

The final sample included 795 participants (68.2% female; mean ± standard deviation age: 44.81 ± 10.62 years) whose 40% reported excellent/very good SRH, and 30% reported good and fair/poor SRH separately. There was no association between body mass index, physical activity, education, health status, smoking, and sleep duration with SRH. After adjustment, the total HEI score and its component scores did not differ across the tertiles of SRH status. However, participants with good SRH had a higher intake of total energy (mean difference (MD): 180.33 Kcal, P value < 0.001), total fat (MD: 8.15 gr, P value = 0.002), and total carbohydrates (MD: 20.18 gr, P value = 0.004) than those with fair/poor SRH.

Conclusion

According to our findings, fair/poor SRH was associated with a lower consumption of total energy, total fat, and total carbohydrates in Iranian adults. Additional observational studies would be necessary to clarify these findings.

Peer Review reports

Introduction

Self-rated health (SRH) is one of the most commonly evaluated health conceptions in population-based and clinical studies [1, 2]. SRH asks people to rate their general health qualitatively via a short question [3]. It has been identified in many studies as a strong predictor of mortality and might predict the incidence of diseases [4]. Some studies have shown that poor SRH status could predict greater healthcare utilization and diminish physical performance in the adult population [3, 5]. The total cost of physical or psychological disorders and illnesses, including healthcare expenses and lost economic productivity, amounts to trillions [6]. Therefore, SRH as a screening tool [2] might be helpful to lower the healthcare budget. SRH affects the healthy behaviors of people. For older adults, SRH is a retrospective health history assessment and is, therefore, more indicative of their health status than many blood markers [7].

In the past, nutritional epidemiology mostly focused on the relationship between diseases and specific nutrients, such as vitamins, or specific food groups, such as vegetables and fruits. However, currently, more studies are focused on dietary patterns and evaluating the quality and variety of the whole diet [5]. Based on dietary guidelines, the diet plan should be low-fat, rich in fruits and vegetables, and generally have a high nutrient density [5]. There are different ways to assess diet quality, such as the food frequency questionnaire (FFQ), healthy eating index (HEI), alternative healthy eating index (AHEI), etc [5, 8, 9]... The HEI was created on dietary guidelines for Americans, and the scoring was based on adequacy components (foods to eat more of for good health) and moderation components (foods to limit for good health) [10]. Both HEI and AHEI scores ranged from 0 to 100, where a higher score presents a healthier diet [11]. A cross-sectional study in Tehran recently estimated the mean HEI score was 52.5, while it was 62.3 in 2001 [12, 13]. A systematic review assessed the diet quality using AHEI, and the worldwide mean score was 40.3 among 185 countries from 1990 to 2018. Another systematic review of cohort studies found an association between higher scores of HEI and AHEI with lower risk of all-cause mortality (20%), cardiovascular disease (20%), cancer (14%), type 2 diabetes (19%), and neurodegenerative disease (18%) [14]. One study reported that those who consumed equal to or less than two servings of fruits and vegetables per day or consumed high-fat foods mostly had poor/fair SRH scores [15]. Another cross-sectional study revealed a significant and negative association between overweight and low physical activity with SRH [16].

To date, the status of SRH has not been investigated in Iran. Furthermore, studies exploring the relationship between SRH and the quality of diet, particularly HEI, are scarce. We wanted to determine whether having a better SRH can be associated with a better healthy diet. Conducting this study will help us to have a better understanding of SRH and self-assessment among Iranians. Therefore, this study aimed to determine the association between healthy eating index and self-rated health in adults living in Tehran.

Methods

Study design

The study was a cross-sectional population-based survey of those aged 20–59 years from 2021 to 2022. The data were collected from 850 healthy adult men and women through two-stage cluster sampling. In the first stage, a simple random sample was selected within 25 healthcare centers across five different geographic areas of Tehran, and a convenient sampling method was used for the second stage. People who visited health centers in Tehran and met the inclusion criteria were informed about the implementation and objectives of the study via informed consent forms. The research was approved by the Tehran University of Medical Science Human Research Ethics Committee (IR.TUMS.MEDICINE.REC.1401.604).

Data collection

A demographic questionnaire was used for general information through face-to-face interviews. It included age (year), sex (male/female), education level (illiterate/under diploma/diploma/university), occupation (employed/unemployed), marital status (single/married), smoking (yes/quit smoking/no), health status (healthy/one disease/comorbidity), and sleep duration.

Dietary intake assessment

We used a validated and reliable semiquantitative FFQ with 168 food items for each participant to assess their dietary intake. The nutritionist asked about FFQs from the participants through face-to-face interviews. The macro- and micronutrient intake were analyzed using Iranian-designed Nutrition IV Software (First Database, San Bruno, CA).

HEI was calculated based on predetermined criteria by the United States Department of Agriculture [17]. The 2015 version of this index has nine components related to adequacy and four related to moderation. The total score is the sum of the score of adequacy components (i.e. foods to eat more of for good health) and moderation components (i.e. foods to limit for good health). The HEI scores ranged from 0 to 100, where a higher score presents a healthier die [18]. The adequacy part includes the following: (1) Total fruit (includes fruit juice), (2) Whole fruits (all forms except fruit juice), (3) Total vegetables (includes any beans and peas), (4) Greens and beans (includes any beans and peas), (5) Whole grains, (6) Dairy (includes all milk products, such as fluid milk, yogurt, and cheese, and fortified soy beverages), (7) Total protein foods (beans and peas are included here (and not with vegetables) when the Total Protein Foods standard is otherwise not met), (8) Seafood and plant proteins (includes seafood, nuts, seeds, soy products (other than beverages) as well as beans and peas if they counted as Total Protein Foods), and (9) Fatty acids (ratio of poly- and monounsaturated fatty acids to saturated fatty acids). The moderation components consist of (1) refined grains, (2) sodium, (3) added sugars, and (4) saturated fats [18].

Self-rated health assessment

SRH was assessed by asking one question, “In general, how do you rate your health?“. The answers include excellent, very good, good, fair, and poor [19]. For this study, we combined the “excellent, very good” responses as one subgroup and “fair, poor” responses as another. Therefore, SRH responses were categorized into excellent/very good, good, and fair/poor. This method aligns with other studies that have used the SRH status question [2, 20] and makes a better differentiation between positive and negative responses [21].

Physical activity

We used the short form of the international physical activity questionnaire, validated for the Iranian population [22]. Participants were questioned about the time spent on vigorous, moderate, and walking activities within the last seven days. The physical activity score was calculated based on the metabolic equivalent minutes per week (MET-minutes/week). At last, the physical activity level is categorized into low (< 600 MET-min/week), moderate (600–3000 MET-min/week), and high levels (> 3000 MET-min/week) [23].

Assessment of blood pressure

Blood pressure was measured twice by a digital sphygmomanometer (Beurer, BC 08, Germany) after at least 10–15 min of rest. An average of two blood pressures was reported for each person.

Anthropometric measurements

The participant’s height without shoes was measured using a wall stadiometer with a sensitivity of 0.1 cm (Seca, Germany). Weight was evaluated by a digital scale (808 Seca, Germany) with an accuracy of 0.1 kg with minimum clothes on. Body mass index (BMI) was calculated by dividing the weight (kg) by the square of the height (m) [24]. Based on the WHO, the BMI cut-off points for determining underweight, normal weight, overweight, and obesity are < 18.5, 18.5–24.9, 25-29.9, and ≥ 30, respectively [25]. Waist (WC) and hip (HC) circumferences were measured with a flexible nonelastic metric tape. WC was measured between the lowest rib and the Iliac crest during exhalation, while HC was at the point that yielded the maximum diameter over the buttocks [24]. The waist-to-hip ratio (WHR) was calculated by dividing the WC (cm) by HC (cm) [26]. The waist-to-height ratio (WHtR) was computed by dividing the WC (cm) by height (cm) [27]. We applied a single nutritionist performing all the measurements to reduce the odds of subjective errors.

Statistical analysis

The general characteristics of the participants are displayed as the mean and standard deviation or number and percent. We categorized SRH into excellent/very good, good, and fair/poor. The normality test of the data was through the Kolmogorov‒Smirnov test and the Q‒Q plot to determine the normal distribution of the data. The chi-squared test and one-way analysis of variance (ANOVA) were calculated as the percentage and mean for demographic characteristics across tertiles of SRH. To compare the means of energy, macronutrients, the HEI, and its component variables across the tertiles of SRH, we applied an analysis of covariance (ANCOVA), adjusting for age, sex, education, occupation, marital status, smoking status, health status, physical activity, and BMI. All analyses were performed with SPSS (SPSS Inc., version 26) software. A p-value less than 0.05 accounted for a significant difference.

Results

Based on Table 1, the mean ± standard deviation of the participant’s age was 44.81 ± 10.62 years old. Of 850 participants, 17 were excluded due to underreporting, extreme values for protein and total fat intake, and 38 due to lack of information. The final sample included 795 participants, and 542 were female. In total, 40% of the population reported excellent/very good SRH, and 30% reported good and fair/poor SRH separately.

Table 1 General characteristics of study participants
Full size table

Table 2 shows the frequency and the mean of some demographic characteristics across tertiles of SRH. There was no association between BMI, physical activity, education, health status, smoking, or sleep duration, and SRH.

Table 2 The percentage for demographic characteristics across tertiles of self-rated health
Full size table

Table 3 indicates the multivariate-adjusted means of the HEI and its component scores across tertiles of SRH status. The results from the Tukey post hoc test showed that participants with good SRH compared with fair/poor SRH had significant differences in total energy consumption (mean difference (MD): 180.33 Kcal, P value < 0.001), total carbohydrate (MD: 20.18 gr, P value = 0.004), and total fat intake (MD: 8.15 gr, P value = 0.002). Additionally, those with good SRH had lower scores for Total Vegetable (P value = 0.058), Greens and Beans (P value = 0.059), and Dairy (P value = 0.042) compared with participants with fair/poor SRH. However, after adjusting for confounders, the marginal and significant differences were all gone.

Table 3 Multivariate adjusted means for healthy eating index and component scores across tertiles of self-rated health status among Iranian adults
Full size table

Discussion

In this cross-sectional study, we aimed to investigate the association between a healthy eating index (HHEI) and self-rated health (SRH) in adults living in Tehran. Our study found that 40% (318 participants) reported excellent/very good SRH, 30.1% (239 participants) reported good SRH, and 29.9% (238 participants) reported fair/poor SRH. There were no statistically significant associations between BMI, physical activity, education, health status, smoking, or sleep duration, and SRH. After adjustment, the total HEI score and its component scores did not differ across the tertiles of SRH status. However, participants with good SRH had a higher intake of total energy, total fat, and total carbohydrates than those with fair/poor SRH.

Two studies involving younger populations reported similar findings. A cross-sectional study among 1504 US adolescents found no significant association between HEI score and SRH. However, further analysis revealed specific dietary differences: those with excellent-good SRH had a higher vegetable score, while those with fair/poor SRH had a higher total fat intake score [3]. A cohort study conducted from 2003 to 2012 on 953 German participants also found no significant association between SRH and those with high healthy nutrition scores and below-average scores in the physical activity and media use index [28]. The studies suggest this might be due to developmental differences and potentially limited awareness of healthy eating habits in younger individuals [3, 28].

Several studies support the association between unhealthy lifestyle factors and poorer SRH. The Spanish DiSA-UMH study found that poorer SRH was linked to lower adherence to the Mediterranean diet, lower physical activity levels, excess weight, and smoking among university students [29]. Similarly, studies by Zarini et al. and Collins et al. linked fair/poor SRH to higher fat intake [5, 15], lower fruit and vegetable intake, and lower physical activity, particularly among females [15]. These findings align with our null findings for BMI and smoking, as reported in another study conducted in a rural Greek population [2].

Some studies reported positive associations between HEI and SRH, contrasting with our findings. Vaudin et al. observed a link between better SRH and a more favorable HEI score in older adults [20]. Additionally, studies in rural populations found associations between healthier diets and better SRH [1, 2], while lower education and chronic diseases were linked to poorer SRH [2]. A large survey [30] also reported associations between poor sleep, physical inactivity, and poor diet quality with higher odds of poor SRH. However, it’s important to note that the participants in this survey had reported “good” SRH earlier.

Possible explanations for these contrasting findings include:

Population differences: The studies with contrasting findings involved different age groups, health statuses, and potentially socioeconomic backgrounds compared to our study population.

Health awareness: Individuals with chronic diseases might have higher health awareness due to more frequent medical consultations, potentially leading to healthier dietary choices [15].

Confounding factors: Many variables beyond those we adjusted for in our study, such as socioeconomic status [31, 32] and mental health [32], can influence SRH.

This study has some limitations. First, some confounders, such as social well-being, were not adjusted. Second, the cross-sectional design and the lack of significant associations between HEI and SRH might mirror low power due to the small sample size in this analysis. Our study also has some strengths. The strengths of the current observational study include a sample representative of Tehran’s general population, the first study in Iran around this field, using the latest version of the HEI, a gold standard tool for assessing usual food intake (FFQ), and the inclusion of a large number of covariates.

Conclusion

This is the first attempt to relate SRH status to HEI in healthy Iranian adults. The total HEI score did not vary by SRH status. In detail, those with good SRH had a higher intake of total energy, total fat, and total carbohydrates than those with fair/poor SRH. Additional observational studies are needed to clarify these findings.

Data availability

The datasets analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

SRH:

self-rated health

FFQ:

food frequency questionnaire

HEI:

healthy eating index

BMI:

Body mass index

WC:

Waist circumference

HC:

hip circumferences

WHR:

waist-to-hip ratio

WHtR:

waist-to-height ratio

SD:

standard deviation

ANOVA:

one-way analysis of variance

ANCOVA:

analysis of covariance

MD:

mean difference

References

  1. An R, Xiang X, Liu J, Guan C. Diet and self-rated health among oldest-old Chinese. Arch Gerontol Geriatr. 2018;76:125–32.

    Article  PubMed  Google Scholar 

  2. Darviri C, Fouka G, Gnardellis C, Artemiadis AK, Tigani X, Alexopoulos EC. Determinants of self-rated health in a representative sample of a rural population: a cross-sectional study in Greece. Int J Environ Res Public Health. 2012;9(3):943–54.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Goodwin DK, Knol LL, Eddy JM, Fitzhugh EC, Kendrick OW, Donahue RE. The relationship between self-rated health status and the overall quality of dietary intake of US adolescents. J Am Diet Assoc. 2006;106(9):1450–3.

    Article  PubMed  Google Scholar 

  4. Loftfield E, Yi S, Immerwahr S, Eisenhower D. Construct validity of a single-item, self-rated question of diet quality. J Nutr Educ Behav. 2015;47(2):181–7.

    Article  PubMed  Google Scholar 

  5. Collins CE, Young AF, Hodge A. Diet quality is associated with higher nutrient intake and self-rated health in mid-aged women. J Am Coll Nutr. 2008;27(1):146–57.

    Article  PubMed  Google Scholar 

  6. Saklayen MG. The global epidemic of the metabolic syndrome. Curr Hypertens Rep. 2018;20(2):12.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Wang K, Zhang A, Sun F, Hu RX. Self-rated Health among older Chinese americans: the roles of Acculturation and Family Cohesion. J Appl Gerontol. 2021;40(4):387–94.

    Article  PubMed  Google Scholar 

  8. Guenther PM, Casavale KO, Reedy J, Kirkpatrick SI, Hiza HA, Kuczynski KJ, Kahle LL, Krebs-Smith SM. Update of the healthy eating index: HEI-2010. J Acad Nutr Diet. 2013;113(4):569–80.

    Article  PubMed  Google Scholar 

  9. Kennedy ET, Ohls J, Carlson S, Fleming K. The healthy eating index: design and applications. J Am Diet Assoc. 1995;95(10):1103–8.

    Article  CAS  PubMed  Google Scholar 

  10. Vahid F, Jalili M, Rahmani W, Nasiri Z, Bohn T. A higher healthy eating index is Associated with decreased markers of inflammation and lower odds for being Overweight/Obese based on a case-control study. Nutrients. 2022;14(23):5127.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Miller V, Webb P, Cudhea F, Shi P, Zhang J, Reedy J, Erndt-Marino J, Coates J, Mozaffarian D. Global dietary quality in 185 countries from 1990 to 2018 show wide differences by nation, age, education, and urbanicity. Nat Food. 2022;3(9):694–702.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Yazdani V, Zeraattalab-Motlagh S, Jayedi A, Majdi M, Mirrafiei A, Martami F, Djafarian K, Shab-Bidar S. The association between self-reported nocturnal sleep duration, irregularity in daily energy intake and diet quality in a sample of Iranian adults. Public Health Nutr. 2023;26(8):1609–16.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Diet quality indices and the risk of type 2 diabetes in the Tehran Lipid and Glucose Study. BMJ Open Diabetes Research & Care 2022, 10(5):e002818.

  14. Morze J, Danielewicz A, Hoffmann G, Schwingshackl L. Diet Quality as assessed by the healthy eating index, alternate healthy eating Index, Dietary approaches to stop hypertension score, and Health outcomes: a second update of a systematic review and Meta-analysis of Cohort studies. J Acad Nutr Diet. 2020;120(12):1998–2031. e1915.

    Article  PubMed  Google Scholar 

  15. Zarini GG, Vaccaro JA, Canossa Terris MA, Exebio JC, Tokayer L, Antwi J, Ajabshir S, Cheema A, Huffman FG. Lifestyle behaviors and self-rated health: the living for health program. J Environ Public Health. 2014;2014:315042.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Aguilar-Palacio I, Gil-Lacruz AI, Sánchez-Recio R, Rabanaque MJ. Self-rated health in Europe and its determinants: does generation matter? Int J Public Health. 2018;63(2):223–32.

    Article  PubMed  Google Scholar 

  17. Guenther PM, Reedy J, Krebs-Smith SM, Reeve BB. Evaluation of the healthy eating Index-2005. J Am Diet Assoc. 2008;108(11):1854–64.

    Article  PubMed  Google Scholar 

  18. Krebs-Smith SM, Pannucci TE, Subar AF, Kirkpatrick SI, Lerman JL, Tooze JA, Wilson MM, Reedy J. Update of the healthy eating index: HEI-2015. J Acad Nutr Diet. 2018;118(9):1591–602.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Krause NM, Jay GM. What do global self-rated health items measure? Med Care. 1994;32(9):930–42.

    Article  CAS  PubMed  Google Scholar 

  20. Vaudin A, Wambogo E, Moshfegh A, Sahyoun NR. Awareness and use of nutrition information predict measured and self-rated diet quality of older adults in the USA. Public Health Nutr. 2021;24(7):1687–97.

    Article  PubMed  Google Scholar 

  21. Manderbacka K, Lundberg O. Examining points of reference of self-rated health among Swedish oldest old. Arch Gerontol Geriatr. 1996;23(1):47–60.

    Article  CAS  PubMed  Google Scholar 

  22. Vasheghani-Farahani A, Tahmasbi M, Asheri H, Ashraf H, Nedjat S, Kordi R. The Persian, last 7-day, long form of the International Physical Activity Questionnaire: translation and validation study. Asian J Sports Med. 2011;2(2):106–16.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Ainsworth B, Herrmann S, Meckes N, Bassett D, Tudor-Locke C, Greer J, Vezina J, Whitt-Glover M, Leon A. 2011 Compendium of Physical activities: a second update of codes and MET values. Med Sci Sports Exerc. 2011;43:1575–81.

    Article  PubMed  Google Scholar 

  24. Physical status. The use and interpretation of anthropometry. Report of a WHO Expert Committee. World Health Organ Tech Rep Ser. 1995;854:1–452.

    Google Scholar 

  25. Barba C, Cavalli-Sforza T, Cutter J, Darnton-Hill I, Deurenberg P, Yap M, Gill T, James P, Ko G, Miu AH, et al. Appropriate body Mass Index for Asian populations and its implications for policy and intervention strategies. Lancet. 2004;363:157–63.

    Article  Google Scholar 

  26. World Health Organisation. Waist Circumference and Waist-hip Ratio: Report of a WHO Expert Consultation, [http://www.who.int/nutrition/publications/obesity/WHO_report_waistcircumference_and_waisthip_ratio/en/].

  27. Ashwell M, Gibson S. Waist-to-height ratio as an indicator of ‘early health risk’: simpler and more predictive than using a ‘matrix’ based on BMI and waist circumference. BMJ Open. 2016;6(3):e010159.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Spengler S, Mess F, Schmocker E, Woll A. Longitudinal associations of health-related behavior patterns in adolescence with change of weight status and self-rated health over a period of 6 years: results of the MoMo longitudinal study. BMC Pediatr. 2014;14:242.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Barrios-Vicedo R, Navarrete-Muñoz EM, García de la Hera M, González-Palacios S, Valera-Gran D, Checa-Sevilla JF, Gimenez-Monzo D, Vioque J. [A lower adherence to Mediterranean diet is associated with a poorer self-rated health in university population]. Nutr Hosp. 2014;31(2):785–92.

    PubMed  Google Scholar 

  30. Oftedal S, Rayward AT, Fenton S, Duncan MJ. Sleep, diet, activity, and incident poor self-rated health: a population-based cohort study. Health Psychol. 2021;40(4):252–62.

    Article  PubMed  Google Scholar 

  31. Cheng G, Yan Y. Sociodemographic, health-related, and social predictors of subjective well-being among Chinese oldest-old: a national community-based cohort study. BMC Geriatr. 2021;21(1):124.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Meyer OL, Castro-Schilo L, Aguilar-Gaxiola S. Determinants of mental health and self-rated health: a model of socioeconomic status, neighborhood safety, and physical activity. Am J Public Health. 2014;104(9):1734–41.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

Special thanks go to all those who participated in this study.

Funding

This manuscript has been granted by the Tehran University of Medical Sciences (Grant No: 57728).

Author information

Authors and Affiliations

  1. Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences (TUMS), No 44, Hojjat-dost Alley, Naderi St., Keshavarz Blvd, 14167-53955, Tehran, 14155/6117, Iran

    Bahareh Jabbarzadeh-Ganjeh & Sakineh Shab-Bidar

  2. Department of Clinical Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences (TUMS), 14167-53955, Tehran, Iran

    Kurosh Djafarian

  3. Sports Medicine Research Center, Neuroscience Institute, Tehran University of Medical Sciences (TUMS), Tehran, Iran

    Sakineh Shab-Bidar

Authors
  1. Bahareh Jabbarzadeh-Ganjeh
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kurosh Djafarian
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sakineh Shab-Bidar
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

B.J-G and S.S-B contributed to the conception/design of the research; B.J-G contributed to the analysis, interpretation of the data, and drafting the first version of the manuscript; S.S-B and K.DJ critically revised the manuscript; and S.S-B agree to be fully accountable for ensuring the integrity and accuracy of the work. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Sakineh Shab-Bidar.

Ethics declarations

Ethics approval and consent to participate

The sample collection was made possible by the coordination of the Health Bureau of the Municipality of Tehran and the cooperation of the health care centers of Tehran. The study was approved by the ethical committee of the Tehran University of Medical Sciences (Ethics No. IR.TUMS.MEDICINE.REC.1401.604). All participants signed an informed consent form to participate statement.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jabbarzadeh-Ganjeh, B., Djafarian, K. & Shab-Bidar, S. Association of healthy eating index and self-rated health in adults living in Tehran: a cross-sectional study. BMC Public Health 24, 1106 (2024). https://doi.org/10.1186/s12889-024-18568-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12889-024-18568-w

Keywords

BMC Public Health

ISSN: 1471-2458

Contact us