Association of adherence to the dietary approach to stop hypertension diet and diet quality indices among women in Tehran: A cross sectional study

Introduction

DASH (Dietary approach to stop hypertension) diet is one of the healthy dietary patterns that was established for patients with hypertension in the 1990s.¹ The DASH diet is characterized by a high amount of fiber including fruits, vegetables, and whole grains and a low intake of sodium and sweets while emphasizing the consumption of low-fat dairy products, white meat, and nuts.¹ Adherence to the DASH dietary pattern has demonstrated beneficial effects on the treatment of hypertension, cardiovascular diseases, type 2 diabetes mellitus and metabolic syndrome.^2-4 Indeed, previous studies have shown that nutrition status is closely related to the inception of these diseases.^5-8 To clarify other positive aspects of this healthy diet, examining the DASH diet based on other dietary quality indices will be helpful.

Several indices of healthy eating have been developed to reveal the level of adherence to a specified dietary pattern in the last three decades. They provide an approach which assesses diet quality as a whole compared to the less preferred method of individual nutrient content and the consideration of single foods.⁹ Diet quality refers to both food variety and nutrient adequacy.¹⁰ Previous studies indicated that the dietary diversity score (DDS), Alternative Healthy Eating Index (AHEI), nutrient adequacy ratio (NAR) and mean adequacy ratio (MAR), as well as dietary energy density (DED), are suitable indicators for diet quality assessments.^11,12 DDS focuses on the variety of food intake to reduce mortality and morbidity.¹³ Furthermore, it has been shown that DDS is a good indicator for the adequacy of some micro-nutrients. Prior studies reported that DDS is associated with cardiovascular risk factors,¹⁴ obesity, abdominal adiposity,¹⁵ and metabolic syndrome.^12,16 Other diet quality indices emphasize the consumption of healthy foods and the restriction of less healthy ones.^12,17

Due to the previous research in Tehran it is evident that overall diet quality status of Tehranian women needs to be improved. Based on the 2015 Dietary Guidelines, the DASH dietary pattern is an example of a healthy eating pattern that can be considered practical and accessible to the public. While the relationship between the DASH diet and chronic metabolic disease has been studied,^18-20 the association between the DASH diet and other dietary quality indices is not well understood. Specifically, the DASH diet has not been investigated regarding the overall diet quality status of women in Iran. The present study aimed to assess the association between the DASH diet score and diet quality indices among Iranian women.

Materials and Methods

Results

In this cross-sectional study, the study sample consisted of 304 women with a mean age of 32.04 (SD 8.63) years. All participants initially recruited for the study were characterized to have a normal total energy intake and were included in study analyses. No participants were excluded for under or over reporting energy intake. General characteristics and anthropometric indices of the participants across the tertiles of DASH score are indicated in Table 1. The lowest tertile presents the lowest compliance and the highest one corresponds to the highest compliance for DASH dietary pattern. DASH score tertiles (from the lowest to the highest) consisted of 108, 101 and 95 participants, respectively. As shown in Table 1, there were no significant differences in demographic characteristics (age, educational level, disease background, family history of diseases, and physical activity) and anthropometric indices (BMI and WC) among DASH categories. Although the prevalence of overweight/obesity (51.0% vs. 43.0%; P = 0.74) and abdominal obesity (48.0 vs. 40.0%; P = 0.65) were greater in the lowest tertile compared to the highest one, no significant differences were found among categories.

Dietary intake patterns of participants are outlined in Table 2. There was no significant difference in total energy intake (P = 0.13), carbohydrate (P = 0.73), protein (P = 0.86) and dietary fiber (P = 0.06) across the DASH tertiles. However, participants in the lowest tertile consumed a diet higher in fat compared to those in the highest tertile (71.10 (SD 24.53) vs. 57.64 (SD 23.76) g/day, respectively; P = 0.0001). Specifically, significant differences in fat consumption were indicated between first and third tertiles (P≤ 0.01) and the second and third tertiles (P = 0.004). Among main food groups, there were statistically significant differences observed in fruit, and dairy intake across DASH categories (P = 0.0001 for all variables). Significant differences were observed between first and second tertiles (P = 0.01) and first and third tertiles (P ≤ 0.01) for fruit consumption. Similarly, the significant differences indicated in dairy intake were observed between first and second tertiles (P = 0.04) and first and third tertiles (P ≤ 0.001). No significant differences were found between tertiles for meat (P = 0.19) or grain consumption (P = 0.76). As presented in Table 2, there were no significant differences in mineral (zinc, iron, and calcium) and vitamin (C, D, B12, B2, B6, and A) intake in participants with a higher adherence to the DASH dietary eating pattern compared to participants with a lower adherence (P> 0.05 in all variables).

Diet quality indices across the tertiles of DASH eating pattern are represented in Table 3 and Table 4. Although not significant, participants in the second tertile had the most diverse diet (mean score = 5.52 [SD 1.25]) compared to the first (mean score = 5.10 [SD 1.15]) and third (mean score = 5.47 [SD 1.01]) tertiles. However, a significant difference was only observed between the first and second (P = 0.01) and first and third tertiles (P = 0.01). Our findings indicate that the second tertile of the dairy DDS was significantly higher than both the first (P = 0.006) and third tertile (P = 0.003). Yet the DDS across fruit (P = 0.01) and vegetable (P = 0.001) groups significantly increased from the first to the third tertile. Significant differences in fruit intake were observed between first and third tertiles (P = 0.005) whereas significant differences for vegetables were observed between first and second tertiles (P = 0.03) and first and third tertiles (P = 0.001). There were no significant relationships indicated in the NAR of mineral or vitamins measured and this translated to no significant difference calculated in the MAR index across the DASH tertiles. A partial correlation assessment to determine the interaction between DASH score and dietary quality while controlling for energy intake, age, educational level and income represented in Table 5. A significant correlation between DASH score and Mediterranean score was observed (P = 0.001).

Discussion

The DASH diet is a healthy dietary pattern that has previously demonstrated potential benefits in the treatment of chronic diseases such as Crohn’s disease and diabetes.²⁸ Typically its’ beneficial effects are attributed to the intake of a combination of healthy food groups. To calculate DASH score, participants who consumed more fruits, vegetables, whole grains, and nuts received a greater score compared to participants with a higher intake of meat, sodium and sweetened beverages.²⁹ Further examination of the healthy dietary pattern exhibited in the DASH diet compared to other dietary quality indices will provide constructive information that can translate into the value and utility of this dietary pattern as a treatment and prevention tool. To our knowledge, the current study is the first in which the association between DASH score and other dietary quality indices has been examined in a healthy population.

We found that there were no differences in anthropometric indices among women in the tertiles of the DASH diet. This is in agreement with the 2003-2012 National Health and Nutrition Examination Surveys that demonstrated that there was no significant correlation between DASH score, body weight and waist circumference in American children and adolescents.³⁰ In contrast, Saneei et al reported that there was an inverse correlation between the higher range of DASH score and waist circumference.⁴ In the present study, no considerable differences were reported for total energy intake among the participants in the tertiles of the DASH diet; the level of physical activity were similar among tertiles. Due to similar total energy intake and physical activity, such findings were expected.

Participants with higher adherence to the DASH diet consumed less fat, while they reported more consumption of fruits, vegetables, and dairy products. However this did not translate into significant differences observed in independent nutrients across DASH score tertiles. There are no prior studies that compare the intake of specific nutrients across DASH score tertiles. However, Wang et al established that the DASH diet does in fact provide sufficient amounts of nutrients such as vitamin C, riboflavin, thiamin, vitamin B6, folate, niacin, vitamin B12, magnesium, calcium, zinc, copper, and iron³¹ while Azadbakht et al reported that mean intake of vitamin C, magnesium, potassium and calcium were higher in the DASH diet compared to a control diet included a macronutrient composition of 50%–60% carbohydrates, 15%–20% protein, 30% total fat and 5% simple sugars which was close to a standard Iranian dietary pattern.¹⁸

The present cross-sectional study indicated that a greater adherence to the DASH diet is inversely associated with DED and AHEI. However, there was no correlation between DASH diet adherence, MAR and NAR. Furthermore, participants in the top DASH tertile had higher DDS to DED ratio, while women in the second tertile had a more diverse diet. It is notable that we obtained weak correlations between DASH and other diet quality indices, whereas some of them were statistically significant. Studies with larger sample size are needed to clarify these associations.

As the DASH diet emphasizes the high intake of fruits and vegetables and low consumption of fat and sugar sources, such findings were expected. Some studies reported that DED was associated with an increased risk of developing diabetes. They also suggested that DED is an independent predictor for increased fasting insulin levels, and obesity.^32-34 Participants in the second DASH tertile demonstrated the highest DDS. The DASH eating pattern is characterized by high amounts of fiber and protein, whole grains, fruits and vegetables, low-fat dairy products, fish, poultry, nuts and sufficient amounts of minerals.¹ Indeed, participants with greater adherence to the DASH diet had the highest score of dietary diversity for fruits and vegetables. Our study was in line with earlier reports which indicate that participants with a higher DDS consumed more fruits and vegetables.^14,23,35 Participants in the highest DASH tertile were characterized by a higher DDS to DED ratio. This relationship was further supported after adjusting for total energy intake. This index examines the effects of dietary diversity and energy density simultaneously, and therefore is more suitable than considering each index independently.

There was a negative partial correlation between AHEI and DASH score while controlling for energy intake, age and educational level r = -0.20, P≤ 0.001 which was statistically significant. Although both diets are considered as healthy dietary patterns, this significant difference may be attributed to the inclusion and scoring of different food items. Indeed, AHEI considers the ratio of white to red meat, dietary fiber, types of fat (PUFA/SFA and trans fatty acid), multi-vitamin intake and alcohol while the DASH score does not. Similarly, the DASH dietary pattern limits the amount of fat, compared to AHEI which emphasizes the classification of fat, but not the quantity.

Although the present study was the first to examine the association between the DASH diet and other dietary quality for the first time, there were several study limitations that should be identified. We could not clarify the cause and effect correlation due to the cross-sectional design. Therefore, prospective studies are needed to evaluate these associations with in a longitudinal study design. Although a major strength of the study includes all healthy female participants, because the participants were only women we are unable to extrapolate our findings to men. All Iranian women were recruited from the same city, and therefore the population may have been too homogeneous to find strong differences. As such, our study findings may not adequately reflect Iranian women in general. Using FFQ as a retrospective dietary assessment tool may cause misclassification, however efforts were made to employ an adapted and validated FFQ.

Our findings indicate that a greater adherence to the DASH dietary pattern is inversely associated with DED and AHEI scores. There was no significant interaction reported between following the DASH diet, MAR, and NAR. Furthermore, the DDS to DED ratio in the highest tertile was greater than the lowest one. Future studies are needed to evaluate the association between the DASH diet and diet quality indices over a longer period of time, and include a larger geographical recruitment region. Observations should be made in both genders in order to delineate any differences that may be attributed to sex. It is recommended for prospective studies to employ dietary assessment tool to reduce participant reporting errors. According to the results, participants who were more adherent to the DASH diet had higher intakes vegetable, fruit, and dairy food groups. There was a positive association between the DASH diet and DDS as an indicator of diet quality assessment. Based on our results the DASH dietary pattern can be considered as a high-quality healthy eating pattern. The promotion and introduction of the healthy eating patterns outlined in the DASH diet can ultimately have important beneficial applications to not only policy decisions but the treatment and prevention of chronic metabolic dysfunction.

Ethical approval

The present study was approved by the ethics committee of Tehran University of Medical Sciences under approval number 94-04-161-31112.

Competing interests

The authors declare that they have no competing interests.

Funding

This study is supported by Tehran University of Medical Sciences (grant number: 94-04-161-31112) and the National Elites Foundation and Iran National Science Foundation (grant number: BN092).

Authors’ contributions

LA and BL designed the study; NB, ED, HA and MA contributed to data collection; data analysis was done by NB and LA; results were interpreted by ED, LA and BL; the report was drafted by NB, BL, LA, HA, KS and MA; critical revision of the report for important intellectual content was done by all the investigators.

Acknowledgments

We would like to express our thanks to the Tehran University of Medical Sciences for approving the project number 94-04-161-31112 and the National Elites Foundation and Iran National Science Foundation for financial support.

References

1. Rifai L, Silver MA. A review of the DASH diet as an optimal dietary plan for symptomatic heart failure. Prog Cardiovasc Dis 2016;58(5):548-54. doi: 10.1016/j.pcad.2015.11.001. [Crossref]
2. Barak F, Falahi E, Keshteli AH, Yazdannik A, Esmaillzadeh A. Adherence to the dietary approaches to stop hypertension (DASH) diet in relation to obesity among Iranian female nurses. Public Health Nutr 2015;18(4):705-12. doi: 10.1017/s1368980014000822. [Crossref]
3. Azadbakht L, Surkan PJ, Esmaillzadeh A, Willett WC. The dietary approaches to stop hypertension eating plan affects C-reactive protein, coagulation abnormalities, and hepatic function tests among type 2 diabetic patients. J Nutr 2011;141(6):1083-8. doi: 10.3945/jn.110.136739. [Crossref]
4. Saneei P, Salehi-Abargouei A, Esmaillzadeh A, Azadbakht L. Influence of dietary approaches to stop hypertension (DASH) diet on blood pressure: a systematic review and meta-analysis on randomized controlled trials. Nutr Metab Cardiovasc Dis 2014;24(12):1253-61. doi: 10.1016/j.numecd.2014.06.008. [Crossref]
5. Ghane Basiri M, Sotoudeh G, Djalali M, Reza Eshraghian M, Noorshahi N, Rafiee M, et al. Association of major dietary patterns with general and abdominal obesity in iranian patients with type 2 diabetes mellitus. Int J Vitam Nutr Res 2015;85(3-4):145-55. doi: 10.1024/0300-9831/a000233. [Crossref]
6. Neyestani TR, Nikooyeh B, Hajifaraji M, Kalayi A. The prevalence of zinc deficiency and its correlation with iron status and economical living area in 9 - 12-year-old children. Int J Vitam Nutr Res 2016;86(1-2):18-26. doi: 10.1024/0300-9831/a000240. [Crossref]
7. Shivappa N, Hebert JR, Askari F, Kardoust Parizi M, Rashidkhani B. Increased Inflammatory Potential of Diet is Associated with Increased Risk of Prostate Cancer in Iranian Men. Int J Vitam Nutr Res 2016;86(3-4):161-8. doi: 10.1024/0300-9831/a000395. [Crossref]
8. Shivappa N, Hebert JR, Rashidkhani B, Ghanavati M. Inflammatory potential of diet is associated with increased odds of cataract in a case-control study from Iran. Int J Vitam Nutr Res 2017;87(1-2):17-24. doi: 10.1024/0300-9831/a000420. [Crossref]
9. Alkerwi A, Vernier C, Crichton GE, Sauvageot N, Shivappa N, Hebert JR. Cross-comparison of diet quality indices for predicting chronic disease risk: findings from the Observation of Cardiovascular Risk Factors in Luxembourg (ORISCAV-LUX) study. Br J Nutr 2015;113(2):259-69. doi: 10.1017/s0007114514003456. [Crossref]
10. Burrows TL, Collins K, Watson J, Guest M, Boggess MM, Neve M, et al. Validity of the Australian recommended food score as a diet quality index for pre-schoolers. Nutr J 2014;13:87. doi: 10.1186/1475-2891-13-87. [Crossref]
11. Hashemi Kani A, Alavian SM, Esmaillzadeh A, Adibi P, Azadbakht L. Dietary quality indices and biochemical parameters among patients with non alcoholic fatty liver disease (NAFLD). Hepat Mon 2013;13(7):e10943. doi: 10.5812/hepatmon.10943. [Crossref]
12. Azadbakht L, Akbari F, Esmaillzadeh A. Diet quality among Iranian adolescents needs improvement. Public Health Nutr 2015;18(4):615-21. doi: 10.1017/s1368980014000767. [Crossref]
13. Pinket AS, De Craemer M, Huybrechts I, De Bourdeaudhuij I, Deforche B, Cardon G, et al. Diet quality in European pre-schoolers: evaluation based on diet quality indices and association with gender, socio-economic status and overweight, the ToyBox-study. Public Health Nutr 2016;19(13):2441-50. doi: 10.1017/s1368980016000604. [Crossref]
14. Azadbakht L, Mirmiran P, Esmaillzadeh A, Azizi F. Dietary diversity score and cardiovascular risk factors in Tehranian adults. Public Health Nutr 2006;9(6):728-36. doi: 10.1079/PHN2005887. [Crossref]
15. Azadbakht L, Esmaillzadeh A. Dietary diversity score is related to obesity and abdominal adiposity among Iranian female youth. Public Health Nutr 2011;14(1):62-9. doi: 10.1017/s1368980010000522. [Crossref]
16. Azadbakht L, Mirmiran P, Azizi F. Dietary diversity score is favorably associated with the metabolic syndrome in Tehranian adults. Int J Obes (Lond) 2005;29(11):1361-7. doi: 10.1038/sj.ijo.0803029. [Crossref]
17. Azadbakht L, Mohammadifard N, Akhavanzanjani M, Taheri M, Golshahi J, Haghighatdoost F. The association between dietary glycemic index, glycemic load and diet quality indices in Iranian adults: results from Isfahan Healthy Heart Program. Int J Food Sci Nutr 2016;67(2):161-9. doi: 10.3109/09637486.2015.1134443. [Crossref]
18. Azadbakht L, Izadi V, Ehsani S, Esmaillzadeh A. Effects of the dietary approaches to stop hypertension (DASH) eating plan on the metabolic side effects of corticosteroid medications. J Am Coll Nutr 2016;35(4):285-90. doi: 10.1080/07315724.2014.991459. [Crossref]
19. Blumenthal JA, Babyak MA, Hinderliter A, Watkins LL, Craighead L, Lin PH, et al. Effects of the DASH diet alone and in combination with exercise and weight loss on blood pressure and cardiovascular biomarkers in men and women with high blood pressure: the ENCORE study. Arch Intern Med 2010;170(2):126-35. doi: 10.1001/archinternmed.2009.470. [Crossref]
20. Svetkey LP, Sacks FM, Obarzanek E, Vollmer WM, Appel LJ, Lin PH, et al. The DASH Diet, Sodium Intake and Blood Pressure Trial (DASH-sodium): rationale and design. DASH-Sodium Collaborative Research Group. J Am Diet Assoc 1999;99(8 Suppl):S96-104. doi: 10.1016/s0002-8223(99)00423-x. [Crossref]
21. Craig CL, Marshall AL, Sjostrom M, Bauman AE, Booth ML, Ainsworth BE, et al. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc 2003;35(8):1381-95. doi: 10.1249/01.mss.0000078924.61453.fb. [Crossref]
22. Saraf-Bank S, Haghighatdoost F, Esmaillzadeh A, Larijani B, Azadbakht L. Adherence to Healthy Eating Index-2010 is inversely associated with metabolic syndrome and its features among Iranian adult women. Eur J Clin Nutr 2017;71(3):425-30. doi: 10.1038/ejcn.2016.173. [Crossref]
23. Azadbakht L, Haghighatdoost F, Feizi A, Esmaillzadeh A. Breakfast eating pattern and its association with dietary quality indices and anthropometric measurements in young women in Isfahan. Nutrition 2013;29(2):420-5. doi: 10.1016/j.nut.2012.07.008. [Crossref]
24. Kant AK, Schatzkin A, Ziegler RG. Dietary diversity and subsequent cause-specific mortality in the NHANES I epidemiologic follow-up study. J Am Coll Nutr 1995;14(3):233-8. doi: 10.1080/07315724.1995.10718501. [Crossref]
25. Hariri N, Darafshi Ghahroudi S, Nasseri E, Bondarianzadeh D, Houshyar-Rad A, Zayeri F. Evaluation of the alternative healthy eating index as a predictor of 10-year cardiovascular disease risk in a group of Iranian employees. J Hum Nutr Diet 2017;30(4):499-505. doi: 10.1111/jhn.12416. [Crossref]
26. Kohlboeck G, Sausenthaler S, Standl M, Koletzko S, Bauer CP, von Berg A, et al. Food intake, diet quality and behavioral problems in children: results from the GINI-plus/LISA-plus studies. Ann Nutr Metab 2012;60(4):247-56. doi: 10.1159/000337552. [Crossref]
27. Hiza HA, Casavale KO, Guenther PM, Davis CA. Diet quality of Americans differs by age, sex, race/ethnicity, income, and education level. J Acad Nutr Diet 2013;113(2):297-306. doi: 10.1016/j.jand.2012.08.011. [Crossref]
28. Drehmer M, Odegaard AO, Schmidt MI, Duncan BB, Cardoso LO, Matos SMA, et al. Brazilian dietary patterns and the dietary approaches to stop hypertension (DASH) diet-relationship with metabolic syndrome and newly diagnosed diabetes in the ELSA-Brasil study. Diabetol Metab Syndr 2017;9:13. doi: 10.1186/s13098-017-0211-7. [Crossref]
29. Rai SK, Fung TT, Lu N, Keller SF, Curhan GC, Choi HK. The Dietary Approaches to stop hypertension (DASH) diet, Western diet, and risk of gout in men: prospective cohort study. BMJ 2017;357:j1794. doi: 10.1136/bmj.j1794. [Crossref]
30. Cohen JFW, Lehnerd ME, Houser RF, Rimm EB. Dietary approaches to stop hypertension diet, weight status, and blood pressure among children and adolescents: National Health and Nutrition Examination Surveys 2003-2012. J Acad Nutr Diet 2017;117(9):1437-44.e2. doi: 10.1016/j.jand.2017.03.026. [Crossref]
31. Reedy J, Krebs-Smith SM. A comparison of food-based recommendations and nutrient values of three food guides: USDA’s MyPyramid, NHLBI’s dietary approaches to stop hypertension eating plan, and Harvard’s healthy eating pyramid. J Am Diet Assoc 2008;108(3):522-8. doi: 10.1016/j.jada.2007.12.014. [Crossref]
32. Mendoza JA, Drewnowski A, Christakis DA. Dietary energy density is associated with obesity and the metabolic syndrome in U.S. adults. Diabetes Care 2007;30(4):974-9. doi: 10.2337/dc06-2188. [Crossref]
33. Wang J, Luben R, Khaw KT, Bingham S, Wareham NJ, Forouhi NG. Dietary energy density predicts the risk of incident type 2 diabetes: the European Prospective Investigation of Cancer (EPIC)-Norfolk Study. Diabetes Care 2008;31(11):2120-5. doi: 10.2337/dc08-1085. [Crossref]
34. Wang J, Zhang W, Sun L, Yu H, Ni QX, Risch HA, et al. Dietary energy density is positively associated with risk of pancreatic cancer in urban Shanghai Chinese. J Nutr 2013;143(10):1626-9. doi: 10.3945/jn.113.178129. [Crossref]
35. Haghighatdoost F, Sarrafzadegan N, Mohammadifard N, Sajjadi F, Maghroon M, Boshtam M, et al. Healthy eating index and cardiovascular risk factors among Iranians. J Am Coll Nutr 2013;32(2):111-21. doi: 10.1080/07315724.2013.767590. [Crossref]