Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Higher dietary glycemic load is inversely associated with stress prevalence among Iranian adults

Higher dietary glycemic load is inversely associated with stress prevalence among Iranian adults Background: Psychological disorders including depression, anxiety, and stress comprise a huge public health problem. The aim of this cross-sectional study is to assess the relationship between dietary glycemic index (DGI) and glycemic load (DGL) and mental disorders. Method: Participants (n = 10,000) aged 20–69 were randomly selected from 200 clusters in Yazd from the recruit- ment phase of Yazd Health Study. The dietary intake of study participants was collected by a reliable and validated food frequency questionnaire consisting of 178 food items. DGI and DGL were calculated from the FFQ data using previously published reference values. To assess psychological disorders an Iranian validated short version of a self- reported questionnaire Depression Anxiety Stress Scales 21 was used. Results: There were no significant associations between DGI and DGL with odds of depression or anxiety in crude and adjusted models. However, individuals in the highest quartiles of DGL had the lowest odds of stress (OR: 0.69; 95% CI 0.47–1, P-trend = 0.023). This association remained significant after adjustment for potential confounding variables in model I (OR: 0.45; 95% CI 0.22–0.9, P-trend = 0.023), model II (OR: 0.46; 95% CI 0.22–0.96, P-trend = 0.039) and model III (OR: 0.46; 95% CI 0.22–0.96, P-trend = 0.042). Conclusion: In conclusion, consumption of foods with higher GL was associated with lower odds of stress; however, no significant association was found between DGI or DGL and risk of depression and anxiety. Performing further stud- ies with longitudinal design is suggested to confirm these results. Keywords: Anxiety, Depression, Dietary glycemic index, Dietary glycemic load, Stress Introduction genetic, biological, and environmental factors involved Psychological disorders including depression, anxiety, in its onset and progression [2]. The underlying mecha - and stress comprise a huge public health problem, affect - nisms are not fully understood, which may explain the ing about 31% to 41% of the world population in 2020 [1]. poor response (50%) of current pharmacotherapies [3]. The pathophysiology of mental disorders is complex, with Among the environmental factors, dietary intakes have long been demonstrated to be associated with mental disorders. For example, diets rich in fruits and vegeta- Ali Amirinejad and Mina Darand are both in the first name position bles have a general positive impact on mental health [4] *Correspondence: khayyatzadeh@yahoo.com whereas a western diet (characterized by high intake of Nutrition and Food Security Research Center, Shahid Sadoughi University fried food, processed meat, refined carbohydrate and of Medical Sciences, Shohadaye Gomnam BLD, ALEM Square, Yazd, Iran confectionary) is associated with mental disorders [5]. Full list of author information is available at the end of the article © The Author(s) 2022. 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:// creat iveco mmons. org/ licen ses/ by/4. 0/. The Creative Commons Public Domain Dedication waiver (http:// creat iveco mmons. org/ publi cdoma in/ zero/1. 0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Amirinejad et al. BMC Neuroscience (2022) 23:28 Page 2 of 9 The impact of dietary carbohydrate intake on health which has been conducted on 10,000 participants aged outcomes and disease has increasingly been in focus in 20–70  years since 2014. The participants were ran - recent years [6]. However, the link between the various domly selected from 200 clusters in Yazd Greater Area. aspects of carbohydrate and psychological health remains The profile and details of this study were published else - unclear. The effects of foods to increase blood glucose are where [24]. Written informed consent was taken from different and this property is considered the glycemic all participants. The research was approved by the Eth - index (GI), a quality rating of how individual foods raise ics Committee of Shahid Sadoughi University of Medical blood sugar levels. In fact, GI is the increase in postpran- Sciences, Yazd, Iran (Ethic code: 931188). Data regarding dial blood glucose after consumption of a specific car - current and history of chronic diseases, smoking status, bohydrate portion of a food compared with glucose or socio-demographic characteristics including age, gen- white bread [7]. When we consume high-GI foods, blood der, marital status and education level were obtained by glucose and subsequently insulin concentrations are rap- interview and standard questionnaires. Participants were idly increased, while smaller and slower elevation of post- excluded on the following: under or over estimation of prandial blood glucose and insulin levels are observed energy intake (total daily energy intake less than 800 or following intake of low-GI foods. Refined grains such as higher than 6500  kcal/day), pregnancy, following a spe- white bread, rice, potatoes and sugary products are con- cial diet and taking antidepressants. After exclusion, 7384 sidered high-GI foods, whereas vegetables, whole grain participants (3673 men and 3711women) participated in and legumes are included in low-GI groups [8]. Dietary the study. glycemic load (GL) is the product of a food’s GI and total available carbohydrate content, and provides both Dietary assessment the quality and quantity the of carbohydrates [9]. Thus, Dietary intake of study participants was collected by GL represents a more accurate view of a food’s real-life a reliable and validated food frequency questionnaire effects on postprandial glucose and insulin response. (FFQ) consisting of 178 food items designed for an Ira- The prevalence of psychological disorders is much nian population [25]. FFQs were completed during higher in patients with diabetes [10] and some stud- face-to-face interviews and reported dietary intakes ies show a link between DGI and DGL with psychologi- in household measures were converted to grams and cal disorders [11–13], suggesting glucose metabolism entered to the Nutritionist IV software (First Databank might play a mechanistic role. Indeed, high GI and GL Inc., Hearst Corp., San Bruno, CA, USA). To calculate foods provoke insulin secretion leading to subsequent daily nutrient intake values for each participant, the US hypoglycemia which impact on the nervous system and Department of Agriculture’s (USDA) national nutrient result in psychological disorders [14]. However, increased databank was used [26]. insulin levels from high GI/GL diets may facilitate deliv- ery of tryptophan in the brain and increase the synthesis Dietary glycemic index and load calculation of serotonin, a neurotransmitter associated with mood The total DGI was calculated based on the following for - improvement [15]. On the other hand, most of fruits and mula: GIa × available carbohydrate total available carbohydrate. vegetables which are the good source of dietary fiber and The available carbohydrate content of foods was calcu - several antioxidant compound such as phytochemical are lated as total carbohydrate minus fiber [27]. The total classified in the medium and low GI foods [16]. These carbohydrate and fiber contents of foods were adapted nutrients had positive effects on mental disorders in pre - from the US Department of Agriculture food-composi- vious studies [17, 18]. tion table [28]. Food items with low carbohydrate content Totally, the literature in this field is equivocal, prob - (less than 3.5  g available carbohydrate per serving) like ably due to study design, sample size, duration, and other tomatoes, pickles, cabbage, cucumbers, lettuce, cheese, components of the diet that may explain this inconsist- sausages, eggs, mayonnaise were excluded because GI ency [19–23]. Therefore, due to the necessity of con - values of these foods could not be tested [29]. Of the 178 ducting more high-quality research, we investigated the and 121 food and beverage items in the FFQs of YaHS- association of DGI and DGL with depression, anxiety, TAMYS study, 43 (24.1%) and 32 (24.4%) items contained and stress in a large Iranian population. less than 3.5  g available carbohydrate/serving, respec- tively. Eventually, the calculation of GI was carried out Materials and methods based on the remaining 135 items in the YaHS-TAMYS. Study population GI values for 108 food items in the YaHS-TAMYS study We used data from the enrollment phase of Yazd were adapted from the international references [16, 30]. Health Study (YaHS) conducted from September 2014 for Iranian specific foods not covered in the interna - to December 2015. YaHS is a prospective cohort study tional tables (6 items), the Iranian GI tables were used A mirinejad et al. BMC Neuroscience (2022) 23:28 Page 3 of 9 [31], because the GI of all food items was not covered. diabetes, and hypertension were additionally adjusted. GI values for the remaining food items which were not Further adjustment was for BMI in the final model. available, neither in Iranian nor on the international P-values < 0.05 were considered statistically significant. tables, such as some traditional sweets and desserts, were To analyze the data, the statistical Package for Social Sci- gained based on physically and chemically similar foods. ences (SPSS) (version 23.0, SPSS Inc., Chicago, Illinois, For example, the GI value for gaz, a traditional food item USA) was used. highly consumed in Yazd city and mainly made of flour, almonds, and sugar, was considered to be the same as Results sugar. When more than one GI value from a different Overall, 7384 participants were included (3673 men and brand was available, the mean GI value was applied (e.g. 3711 women). The prevalence of psychological disorders rice and dates). The GIs of mixed meals were obtained did not significantly differ among quartiles of DGI and based on GI values of each of the meal’s components [28]. DGL. BMI, marital status, education level, multi-vitamin For all derived GI values, glucose was used as the refer- supplement use, and hypertension were significantly dif - ence food. Finally, DGL was calculated by multiplying the ferent among quartiles of DGI. Furthermore, significant dietary GI by the total daily available carbohydrate intake differences were seen for age, physical activity, mari - and dividing the result by 100 [28]. tal status, gender, employment status, education level, multi-vitamin supplement use, hypertension, and diabe- Anthropometric measurements tes across quartiles of DGL (Table 1). Body weight was measured using a portable digital scale Dietary nutrients and energy adjusted food groups are analyzer with an accuracy of 0.1  kg. The participants presented in Table 2. The one-way ANOVA test followed stood in the middle of the scale, wearing the minimum by Bonferroni post-hoc analysis revealed significant dif - possible clothing. Height was also measured in a stand- ferences between all dietary nutrients and food groups ing position, while barefoot with the head placed in the including, energy intake; percentage energy from protein, Frankfurt position. Body Mass Index (BMI) was calcu- carbohydrate, and fat intake; cholesterol; saturated fatty lated, body weight (kg)/height (m ). acid; vitamin E; vitamin C; folic acid; magnesium; fruits; vegetables; red meat; fish, dairy; whole grains; refined Psychological health assessment grains; sugars; salt; legumes and nuts. Significant differ - An Iranian validated short version of the self-report ences among the quartiles of DGI and DGL are shown questionnaire for depression, anxiety and stress (DASS with different letters “a” or “b”. 21) consisting of seven items per subscale was used [32]. The association between DGI and DGL with the The individuals read each statement and recorded their respective prevalence of depression, anxiety and stress reply according to a 4-point Likert scale ranging from in crude and adjusted models are presented in Table  3. 0 (does not apply to me at all) to 3 (applies to me very There were no significant associations between DGI much or most of the time). The scores were summed for and DGL with odds of depression or anxiety in crude items of each scale. As the long form of DASS has 42 and adjusted models. However, individuals in the high- items, we multiplied the final score of each scale by two. est quartiles of DGL had the lowest odds of stress (OR: The individuals were considered to have depression, anx - 0.69; 95% CI 0.47–1, P-trend = 0.023). This association iety, and stress if they obtain total scores of ≥ 10, ≥ 8 and remained significant after adjustment for potential con - ≥ 15, respectively. founding variables in model I (OR: 0.45; 95% CI 0.22–0.9, P-trend = 0.023), model II (OR: 0.46; 95% CI 0.22–0.96, Statistical analysis P-trend = 0.039) and model III (OR: 0.46; 95% CI 0.22– The normality of data was assessed using the Kolmogo - 0.96, P-trend = 0.042). rov–Smirnov test. Continuous and categorical variables were compared across quartiles of DGI and DGL using analysis of variance (ANOVA) and chi-square tests Discussion respectively. The differences between nutrients and die - This cross-sectional study assessed the association of tary intake of each quartile were assessed using a Bonfer- dietary DGI and DGL with psychological disorders in roni post-hoc analysis. Logistic regression was applied an Iranian population. No significant association was to evaluate the relationship between DGI and DGL with observed between DGI and odds of depression, anxi- psychological disorders in crude and adjusted models. ety, and stress in crude and adjusted models. There was Model I was adjusted for age, gender, and total energy also no significant relationship between DGL and odds intake. In model II, marital status, smoking, education of depression or anxiety in crude and adjusted models; level, employment status, salt intake, multi-vitamins use, Amirinejad et al. BMC Neuroscience (2022) 23:28 Page 4 of 9 Table 1 General characteristics of participants across quartiles of GI and GL Variable GI GL Total Q1 Q2 Q3 Q4 P-value Q1 Q2 Q3 Q4 P-value Depression, yes (%) 578 (8.1) 148 (8.3) 142 (7.9) 130 (7.2) 158 (8.9) 0.326 158 (8.8) 153 (8.6) 132 (7.3) 135 (7.6) 0.252 Anxiety, yes (%) 754 (10.5) 186 (10.4) 186 (10.3) 170 (9.5) 212 (11.9) 0.113 200 (11.1) 190 (10.7) 183 (10.1) 181 (10.2) 0.710 Stress, yes (%) 238 (3.3) 58 (3.2) 65 (3.6) 54 (3) 61 (3.4) 0.776 68 (3.8) 69 (3.9) 54 (3) 47 (2.7) 0.106 BMI (kg/m ) < 18.5 247 (3.3) 61 (3.2) 63 (3.3) 75 (4) 48 (2.5) 0.018 57 (3) 55 (2.9) 73 (3.9) 62 (3.3) 0.112 18.5–24.9 2339 (30.9) 595 (31.4) 618 (32.6) 586 (30.9) 540 (28.5) 577 (30.5) 630 (33.3) 577 (30.5) 555 (29.3) > 25 4988 (65.9) 1237 (65.3) 1213 (64) 1233 (65.1) 1305 (68.9) 1259 (66.5) 1209 (63.8) 1244 (65.7) 1276 (67.4) Age (%) 20–29 years 1586 (21.5) 419 (22.7) 404 (21.8) 404 (217) 359 (19.6) 0.052 322 (17.4) 404 (22) 433 (23.4) 427 (23.2) < 0.01 30–39 years 1598 (20.8) 383 (20.8) 395 (21.4) 380 (20.4) 440 (24) 324 (17.5) 405 (22) 429 (23.1) 440 (23.9) 40–49 years 1586 (21.5) 387 (21) 413 (22.3) 393 (21.1) 393 (21.4) 404 (21.8) 397 (21.6) 399 (21.5) 386 (21) 50–59 years 1402 (19) 377 (20.4) 347 (18.8) 348 (18.7) 330 (18) 392 (21.2) 341 (18.5) 323 (17.4) 346 (18.8) 60–69 years 1215 (16.4) 279 (15.1) 290 (15.7) 334 (18) 312 (17) 409 (22.1) 293 (15.9) 270 (14.6) 243 (13.2) Physical activity (Met_min/week) 901.1 ± 905.1 890.8 ± 883.1 894.5 ± 910.5 877.5 ± 875 942.4 ± 950.3 0.156 826.6 ± 876.7 896.8 ± 896.4 932.8 ± 903 949 ± 939.7 < 0.01 Marriage (%) Single 856 (11.6) 232 (12.6) 225 (12.2) 206 (11.1) 193 (10.6) 0.019 178 (9.6) 224 (12.2) 220 (11.9) 234 (12.8) 0.001 Married 6264 (85.1) 1575 (85.6) 1567 (84.8) 1570 (85.9) 1570 (85.9) 1587 (86) 1541 (84.2) 1585 (85.6) 1551 (84.6) Widowed or divorced 240 (3.3) 61 (3.3) 40 (2.2) 75 (4.1) 64 (3.5) 80 (4.3) 65 (3.6) 46 (2.5) 49 (2.7) Smoking status (%) Never smoker 6328 (87.8) 1582 (87.6) 1576 (87) 1617 (89) 1553 (87.5) 0.496 1609 (88.4) 1567 (86.9) 1587 (87.7) 1565 (88.3) 0.520 Current smoker 766 (10.6) 194 (10.7) 207 (11.4) 177 (9.7) 188 (10.6) 190 (10.4) 200 (11.1) 192 (10.6) 184 (10.4) Ex_smoker 113 (1.6) 29 (1.6) 29 (1.6) 22 (1.2) 33 (1.9) 22 (1.2) 36 (2) 31 (1.7) 24 (1.4) Gender, male (%) 3673 (49.7) 909 (49.1) 927 (50.2) 917 (49.5) 920 (50.2) 0.877 831 (44.8) 923 (50.3) 967 (52) 952 (51.9) < 0.01 Job (%) Unemployed 1415 (19.5) 353 (19.6) 325 (17.9) 357 (19.6) 380 (21.1) 0.336 358 (19.8) 359 (19.9) 306 (16.8) 392 (21.7) < 0.01 Government employee 3537 (48.8) 898 (49.8) 898 (49.5) 904 (49.6) 837 (46.5) 960 (53.1) 898 (49.7) 876 (48.1) 803 (44.4) Manual worker 247 (3.4) 60 (3.3) 66 (3.6) 56 (3.1) 65 (3.6) 61 (3.4) 53 (2.9) 67 (3.7) 66 (3.6) Freelance job 2046 (28.2) 492 (27.3) 530 (29.1) 505 (27.7) 519 (28.8) 428 (23.7) 497 (27.5) 572 (31.4) 549 (30.3) Education (%) Illiterate 1776 (24.1) 438 (23.7) 418 (22.7) 500 (27) 420 (23.1) 0.004 562 (30.5) 401 (21.8) 406 (22) 407 (22.3) < 0.01 Middle school 2095 (28.5) 501 (27.2) 508 (27.6) 514 (27.7) 527 (31.4) 527 (28.6) 549 (29.9) 494 (26.7) 525 (28.7) Diploma 2289 (31.1) 611 (33.1) 590 (32) 553 (29.8) 535 (29.4) 520 (28.2) 557 (30.3) 629 (34) 583 (31.9) Bachelors degree 995 (13.5) 253 (13.7) 261 (14.2) 204 (12.9) 241 (13.2) 201 (10.9) 270 (14.7) 260 (14.1) 264 (14.4) Master and doctor 205 (2.8) 42 (2.3) 65 (3.5) 47 (2.5) 51 (2.8) 35 (1.9) 62 (3.4) 59 (3.2) 49 (2.7) A mirinejad et al. BMC Neuroscience (2022) 23:28 Page 5 of 9 Table 1 (continued) Variable GI GL Total Q1 Q2 Q3 Q4 P-value Q1 Q2 Q3 Q4 P-value Multi-vitamins supplement (%) Never 6407 (86.1) 1727 (94.3) 1715 (91.9) 1619 (86.4) 1346 (72.1) > 0.01 1741 (94.2) 1727 (93.7) 1691 (90) 1248 (66.8) < 0.01 1–3/month 482 (6.5) 44 (2.4) 67 (3.6) 95 (5.1) 276 (14.8) 34 (1.8) 37 (2) 64 (3.4) 347 (18.6) Minimal once a week 549 (7.4) 60 (3.3) 85 (4.6) 159 (8.5) 245 (13.1) 73 (4) 79 (4.3) 124 (6.6) 273 (14.6) Diabetes, yes (%) 912 (12) 233 (12.3) 209 (11) 244 (12.9) 226 (11.9) 0.358 313 (16.5) 229 (12.1) 194 (10.2) 176 (9.3) < 0.01 Hypertension, yes (%) 1135 (15) 280 (14.8) 280 (14.8) 321 (16.9) 254 (13.4) 0.023 350 (18.5) 286 (14.1) 277 (14.6) 240 (12.7) < 0.01 GI glycemic index, GL glycemic load a 2 Obtained from χ test and one-way anova for categorical and continuous variables, respectively Data are presented as mean ± standard deviation (SD) Amirinejad et al. BMC Neuroscience (2022) 23:28 Page 6 of 9 Table 2 Dietary intake of study participants among the quartiles of GI & GL Quartiles of GI Quartiles of GL Total Q1 Q2 Q3 Q4 P-value Q1 Q2 Q3 Q4 P-value Nutrients a b b b a b b b Energy intake (kcal) 2897 ± 1378 2438 ± 1061 2864 ± 1351 3634 ± 1351 2897 ± 1378 < 0.001 1646 ± 419.3 2199 ± 494.1 3019 ± 744.9 4721 ± 1111 < 0.001 a b b a b b b Protein (% of total 16.16 ± 0.04 16.82 ± 0.04 16.73 ± 0.03 16.24 ± 0.04 14.86 ± 0.04 < 0.001 17.84 ± 0.04 16.59 ± 0.03 16.11 ± 0.03 14.10 ± 0.04 < 0.001 daily energy) a b b a b b b Carbohydrate (% of 56.12 ± 0.09 53.81 ± 0.08 54.58 ± 0.08 56.00 ± 0.08 60.09 ± 11.21 < 0.001 52.55 ± 0.07 55.40 ± 0.07 55.87 ± 0.09 60.67 ± 0.10 < 0.001 total daily energy) a b a b b Fat (% of total daily 33.61 ± 0.09 32.90 ± 0.07 32.67 ± 0.07 32.85 ± 0.07 0.36 ± 0.12 < 0.001 33.24 ± 0.06 31.53 ± 0.06 33.38 ± 0.09 36.28 ± 0.11 < 0.001 energy) a b a b b Cholesterol (mg) 394.8 ± 391.3 363.5 ± 396.1 394.1 ± 326.6 391.1 ± 336.4 430.6 ± 483.4 < 0.001 286.3 ± 322.9 318.4 ± 206.4 432.7 ± 390.9 542 ± 521.8 < 0.001 a b b b a b b b SFA (g) 31.04 ± 18.36 27.13 ± 15.36 29.58 ± 17.43 30.48 ± 17.28 36.98 ± 21.39 < 0.001 19.56 ± 9.62 24.3 ± 11.47 32.47 ± 15.22 47.8 ± 20.82 < 0.001 a b b b Vitamin E (mg/day) 11.36 ± 11.66 11.92 ± 11.85 11.52 ± 11.80 10.98 ± 12.02 11.01 ± 10.92 0.038 7.70 ± 7.16 9.55 ± 8.93 12.72 ± 13.28 15.45 ± 14.19 < 0.001 a b b a b b b Vitamin C (mg) 210.5 ± 188.7 196.2 ± 169 218.3 ± 214.3 219.2 ± 169.6 208.5 ± 197.1 < 0.001 115.1 ± 54.12 166.8 ± 92 243.2 ± 148.4 317.1 ± 292.6 < 0.001 a b a b b b Folic acid (µg) 379.8 ± 228 354.6 ± 215.5 361.9 ± 217.7 370.8 ± 216.6 432.1 ± 251.8 < 0.001 230.7 ± 93.18 300 ± 127.6 410.8 ± 193.8 577.8 ± 276.8 < 0.001 a b b a b b b Magnesium (mg) 339.3 ± 179.6 309.6 ± 155.2 322.9 ± 166.2 336.2 ± 180.7 339.3 ± 179.6 < 0.001 199.7 ± 58.38 262.8 ± 79.31 359 ± 125.2 535.7 ± 198.7 < 0.001 Food groups (g/1000 kcal) a b b a b b b Fruits 184.3 ± 138.4 205.6 ± 145.1 202.3 ± 141.8 192.3 ± 130.3 136.9 ± 124.1 < 0.001 187.8 ± 109.9 204.8 ± 128.1 202.8 ± 151.3 184.3 ± 138.4 < 0.001 a b b b a b b b Vegetables 96.6 ± 77.29 112 ± 82.82 104.1 ± 78.03 97.77 ± 75.50 72.76 ± 66.25 < 0.001 119.6 ± 81.3 104.7 ± 69.75 96.78 ± 81.41 65.57 ± 65.10 < 0.001 a b b b a b b b Red meat 20.46 ± 18.37 22.60 ± 17.77 24.60 ± 21.13 20.12 ± 16.43 14.51 ± 16.16 < 0.001 25.29 ± 20.43 23.65 ± 16.75 20.90 ± 19.34 11.99 ± 13.15 < 0.001 a b b a b b Fish 7 ± 13.56 5.90 ± 11.50 6.70 ± 12.80 7.48 ± 14.42 7.91 ± 15.14 < 0.001 5.85 ± 9.99 5.65 ± 10.98 7.65 ± 14.93 8.85 ± 16.90 < 0.001 a b b b a b b b Dairy 89.84 ± 60.16 106.99 ± 76.74 94.95 ± 53.32 89.96 ± 53.41 67.47 ± 45.57 < 0.001 104.2 ± 53.30 95.85 ± 52.83 86.20 ± 59.35 73.09 ± 69.35 < 0.001 a b b b a b b b Legumes and nuts 25.20 ± 19.14 29.78 ± 25.53 25.64 ± 18.63 24.07 ± 14.99 21.31 ± 14.35 < 0.001 27.80 ± 18.12 25.24 ± 18.01 25.30 ± 20.19 22.46 ± 19.80 < 0.001 a b b a b b b Whole grains 29.95 ± 27.33 26.68 ± 20.58 32.32 ± 24.55 33.81 ± 27.92 27.01 ± 33.82 < 0.001 34.97 ± 24.53 37.83 ± 28.35 29.25 ± 28.89 17.77 ± 22.65 < 0.001 a b b b a b b Refined grains 85.67 ± 58.18 126.70 ± 66.74 93.05 ± 47.27 67.95 ± 41.92 55 ± 45.87 < 0.001 100.5 ± 54 102 ± 49.75 82.02 ± 59.34 58.11 ± 58.05 < 0.001 a b b b Sugars 12.63 ± 11.64 10.21 ± 7.58 11.88 ± 9.05 13.36 ± 11.61 15.07 ± 15.98 < 0.001 12.14 ± 9.27 12.74 ± 9.42 12.80 ± 12.58 12.84 ± 14.47 0.210 a b a b b b Salt 2.94 ± 3.68 3.21 ± 2.94 3.22 ± 3.45 3.14 ± 3.89 2.21 ± 4.21 < 0.001 4.24 ± 3.83 3.61 ± 3.11 2.41 ± 3.37 1.52 ± 3.73 < 0.001 GI glycemic index, GL glycemic load Obtained from one-way ANOVA followed by Bonferroni post-hoc test First quartile is considered as reference quartile Significant difference between quartile with reference quartile (P value < 0.05) A mirinejad et al. BMC Neuroscience (2022) 23:28 Page 7 of 9 Table 3 Multivariable-adjusted ORs (and 95% CIs) for depression, anxiety and stress across quartiles of GI and GL GI quartile GL quartiles Variables Q1 Q2 Q3 Q4 P-trend Q1 Q2 Q3 Q4 P-trend Depression [n (%)] Crude 1.00 0.94 (0.74–1.20) 0.86 (0.67–1.10) 1.08 (0.85–1.36) 0.672 1.00 0.96 (0.75–1.22) 0.78 (0.61–1.01) 1.10 (0.87–1.39) 0.717 Adjusted model1 1.00 0.96 (0.75–1.22) 0.87 (0.68–1.12) 1.16 (0.90–1.48) 0.403 1.00 1.01 (0.79–1.29) 0.86 (0.64–1.15) 0.97 (0.63–1.50) 0.546 Adjusted model2 1.00 0.096 (0.74–1.24) 0.84 (0.64–1.10) 1.11 (0.85–1.46) 0.679 1.00 1.00 (0.77–1.30) 0.86 (0.63–1.18) 0.97 (0.61–1.56) 0.579 Adjusted model3 1.00 0.096 (0.74–1.24) 0.84 (0.64–1.10) 1.12 (0.85–1.46) 0.653 1.00 1.00 (0.77–1.30) 0.86 (0.63–1.18) 0.97 (0.61–1.55) 0.604 Anxiety [n (%)] Crude 1.00 0.99 (0.80–1.22) 0.90 (0.72–1.12) 1.16 (0.94–1.43) 0.248 1.00 0.95 (0.77–1.17) 0.89 (0.72–1.10) 0.90 (0.73–1.12) 0.292 Adjusted model1 1.00 1.00 (0.80–1.24) 0.91 (0.73–1.13) 1.22 (0.98–1.52) 0.157 1.00 0.96 (0.77–1.20) 0.90 (0.70–1.17) 0.94 (0.64–1.38) 0.568 Adjusted model2 1.00 0.99 (0.78–1.25) 0.89 (0.70–1.13) 1.17 (0.92–1.49) 0.343 1.00 0.94 (0.74–1.20) 0.90 (0.68–1.19) 0.91 (0.60–1.38) 0.542 Adjusted model3 1.00 0.99 (0.78–1.25) 0.89 (0.70–1.13) 0.94 (0.87–1.02) 0.323 1.00 0.94 (0.74–1.20) 0.90 (0.68–1.18) 0.91 (0.60–1.38) 0.573 Stress [n (%)] Crude 1.00 1.11 (0.77–1.60) 0.92 (0.63–1.35) 1.06 (0.73–1.53) 0.990 1.00 1.02 (0.72–1.44) 0.77 (0.54–1.11) 0.69 (0.47–1.00) 0.023 Adjusted model1 1.00 1.13 (0.79–1.63) 0.93 (0.63–1.36) 1.12 (0.76–1.65) 0.839 1.00 0.97 (0.67–1.38) 0.64 (0.41–1.00) 0.45 (0.22–0.90) 0.023 Adjusted model2 1.00 1.02 (0.69–1.51) 0.87 (0.57–1.31) 1.09 (0.072–1.65) 0.881 1.00 1.07 (0.68–1.50) 0.65 (0.40–1.05) 0.46 (0.22–0.96) 0.039 Adjusted model3 1.00 1.02 (0.69–1.51) 0.87 (0.57–1.31) 1.10 (0.72–1.66) 0.888 1.00 0.98 (0.68–1.42) 0.72 (0.40–1.05) 0.46 (0.22–0.96) 0.042 GI glycemic index, GL glycemic load These values are odds ratios (95% CIs) Obtained from logistic regression by considering quartiles of GI & GL as ordinal variable Adjusted for age, gender and total energy intake Additionally adjusted for physical activity, marital status, smoking, education, job status, multi-vitamins use, diabetes, hypertension Further adjustment BMI Amirinejad et al. BMC Neuroscience (2022) 23:28 Page 8 of 9 however, higher DGL was associated with lower odds of patients with chronic disease. Furthermore, although the stress in all models. FFQ used in this study was validated for carbohydrate A systematic review and meta-analysis by Salari- and intake of other nutrients, the validation for DGI or moghaddam et  al. [33] was performed on studies with DGL was not performed. Thus, the observed association different designs to investigate the possible relation may be real or related to the quality of the questionnaire. between DGI or DGL and depression. In line with our Also, due to the absence of a reliable Iranian food compo- results, no significant association between DGI or DGL sition table the USDA food-nutrient database was used, and odds of depression was found in cross-sectional which is another limitation of this study. Finally, residual studies. Although a positive association was observed confounding from unknown or unmeasured variables between DGI and risk of depression in cohort studies, could affect our results. the number of studies was limited (n = 2) with significant heterogeneity between them [33]. Conclusion Our results showed no significant association between In summary, an inverse association was found between DGI or DGL and odds of anxiety. In agreement with the DGL and likelihood of stress among Iranian adults. How- current study, Haghighatdoost et  al., after adjusting for ever, considering this point that long-term consumption confounders (marital status, education, physical activity, of food with high GL may increase the risk of chronic dis- smoking, dietary intakes, and BMI) showed similar find - eases especially obesity and diabetes, we can not recom- ings [19]. Another study with a cross-over clinical trial mend high glycemic load dietary sources to the general design examined the effects of a high GL diet on mental population. Therefore, to clarify the effects of DGL or health. Consuming 28 days of a high GL diet did not alter DGI on psychological profiles, further longitudinal stud - tension-anxiety compared to the diet with a low GL [34]. ies such as randomized controlled trials are needed in at- There was also no association between DGI and stress. risk populations. However, in line with a previous study [19], being in the Acknowledgements highest quartiles of DGL in our study was associated We thank Yazd people who participated in YaHS. with lower odds of stress. This inverse association can be Author contributions attributed to the effects of sugar-rich foods on the hypo - SK, MaM, AN and AA: designed and conducted the study; MD and MoM: ana- thalamic–pituitary–adrenal (HPA) axis. Under stressful lyzed the data; MD and AA: wrote the manuscript SK, ID, and MoM: critically conditions, the HPA releases stress hormones (corticos- revised the manuscript; SK, AN and MaM: supervised the study. All authors read and approved the final manuscript. teroids) that increase the desire for sugar rich foods that provide inhibitory feedback on the hypothalamus. There - Funding fore, participants of the higher quartiles of DGL con- This study is supported by Shahid Sadoughi University of Medical Sciences. sumed more sugar-rich foods, which can lower stress Availability of data and materials by decreasing HPA axis activity [35, 36]. Furthermore, The data and materials of the current study are available from the correspond- serotonin is a neurotransmitter that has an essential role ing author on reasonable request. in mood regulation. Foods with high GL induce insulin secretion which facilitates tryptophan uptake and sero- Declarations tonin production in the brain and thereby lowers stress Ethics approval and consent to participate [15]. However, it must be kept in mind that long-term We confirm that all methods were carried out in accordance with Shahid consumption of food with high GL leads to blood glucose Sadoughi University of Medical Sciences guidelines and regulations. Written informed consent was taken from all participants. The research was approved fluctuations and increase the risk of diabetes [37]. Thus, by the Ethics Committee of Shahid Sadoughi University of Medical Sciences, caution should be taken to account when interpreting Yazd, Iran (Ethic code: 931188). these results since several studies reported that patients Consent for publication with diabetes have a higher risk of mental disorders com- Not applicable. pared to healthy people [38–40]. Besides the potential strengths of our study such as a Competing interests Not applicable. large sample size covering both urban and rural areas, recruitment of well-trained interviewers, using a com- Author details prehensive and validated FFQ for evaluating dietary Nutrition and Food Security Research Center, Shahid Sadoughi University of Medical Sciences, Shohadaye Gomnam BLD, ALEM Square, Yazd, Iran. intake, and controlling for possible confounders, there Department of Nutrition, School of Public Health, Shahid Sadoughi University are some limitations. First, the cross-sectional data of of Medical Sciences, Yazd, Iran. Department of Clinical Nutrition, School this study prevents any inference of causality between of Nutrition and Food Science, Isfahan University of Medical Sciences, Isfahan, Iran. Food Security Research Center, Isfahan University of Medical Sciences, DGL and stress. Second, no biochemical measures were Isfahan, Iran. Research Institute of Sport and Exercise Sciences, Liverpool John assessed in our study, which might limit the detection of Moores University, Liverpool, UK. Nuffield Department of Population Health, A mirinejad et al. BMC Neuroscience (2022) 23:28 Page 9 of 9 University of Oxford, Richard Doll Building, Old Road Campus, Oxford OX3 cross-sectional study of young and middle-aged Japanese women. Eur J 7LF, UK. Yazd Cardiovascular Research Center, Non-Communicable Disease Nutr. 2018;57(6):2261–73. Institute, Shahid Sadoughi University of Medical Sciences, Yazd, Iran. 24. Mirzaei M, et al. Cohort profile: the Yazd health study (YaHS): a popula- tion-based study of adults aged 20–70 years (study design and baseline Received: 22 February 2022 Accepted: 9 May 2022 population data). Int J Epidemiol. 2018;47(3):697–698h. 25. Esfahani FH, et al. Reproducibility and relative validity of food group intake in a food frequency questionnaire developed for the Tehran lipid and glucose study. J Epidemiol. 2010;20(2):150–8. 26. Pehrsson PR, Haytowitz DB, Holden JM, Perry CR, Beckler DG. USDA’s national food and nutrient analysis program: Food sampling. J Food References Compos Anal. 2000;13(4):379–89. 1. Wu T, et al. Prevalence of mental health problems during the COVID- 27. Wolever TM, et al. Food glycemic index, as given in glycemic index tables, 19 pandemic: a systematic review and meta-analysis. J Aec ff t Disord. is a significant determinant of glycemic responses elicited by composite 2021;281:91–8. breakfast meals. Am J Clin Nutr. 2006;83(6):1306–12. 2. Gray L, Hannan AJ. Dissecting cause and effect in the pathogenesis of 28. Haytowitz D, et al. USDA national nutrient database for standard refer- psychiatric disorders: genes, environment and behaviour. Curr Mol Med. ence, release 24. Washington, DC: US Department of Agriculture; 2011. 2007;7(5):470–8. 29. Ma Y, et al. Association between dietary carbohydrates and body weight. 3. Pfau ML, Ménard C, Russo SJ. Inflammatory mediators in mood disorders: Am J Epidemiol. 2005;161(4):359–67. therapeutic opportunities. Annu Rev Pharmacol Toxicol. 2018;58:411–28. 30. Foster-Powell K, Holt SH, Brand-Miller JC. International table of glycemic 4. Guzek D, et al. Fruit and vegetable dietary patterns and mental health index and glycemic load values: 2002. Am J Clin Nutr. 2002;76(1):5–56. in women: a systematic review. Nutr Rev. 2021. https:// doi. org/ 10. 1093/ 31. Taleban F, Esmaeili M. Glycemic index of Iranian foods. Tehran: National nutrit/ nuab0 07. Nutrition and Food Technology Research Institute publication; 1999. 5. Oddy WH, et al. Dietary patterns, body mass index and inflammation: 32. Sahebi A, Asghari MJ, Salari RS. Validation of depression anxiety and stress pathways to depression and mental health problems in adolescents. scale (DASS-21) for an Iranian population. 2005. Brain Behav Immun. 2018;69:428–39. 33. Salari-Moghaddam A, et al. Glycemic index, glycemic load, and 6. Liu Y-S, et al. Dietary carbohydrate and diverse health outcomes: umbrella depression: a systematic review and meta-analysis. Eur J Clin Nutr. review of 30 systematic reviews and meta-analyses of 281 observational 2019;73(3):356–65. studies. Front Nutr. 2021. https:// doi. org/ 10. 3389/ fnut. 2021. 670411. 34. Breymeyer KL, et al. Subjective mood and energy levels of healthy weight 7. Jenkins DJ, et al. Glycemic index of foods: a physiological basis for carbo- and overweight/obese healthy adults on high-and low-glycemic load hydrate exchange. Am J Clin Nutr. 1981;34(3):362–6. experimental diets. Appetite. 2016;107:253–9. 8. Esfahani A, et al. The glycemic index: physiological significance. J Am Coll 35. Ulrich-Lai YM, Ostrander MM, Herman JP. HPA axis dampening by limited Nutr. 2009;28(sup4):439S-445S. sucrose intake: reward frequency vs. caloric consumption. Physiol Behav. 9. Sheard NF, et al. Dietary carbohydrate (amount and type) in the preven- 2011;103(1):104–10. tion and management of diabetes: a statement by the American diabetes 36. Adam TC, Epel ES. Stress, eating and the reward system. Physiol Behav. association. Diabetes Care. 2004;27(9):2266–71. 2007;91(4):449–58. 10. Kan C, et al. A systematic review and meta-analysis of the asso- 37. Livesey G, et al. Dietary glycemic index and load and the risk of type 2 ciation between depression and insulin resistance. Diabetes Care. diabetes: assessment of causal relations. Nutrients. 2019;11(6):1280. 2013;36(2):480–9. 38. Boden MT. Prevalence of mental disorders and related functioning and 11. Mwamburi DM, et al. Depression and glycemic intake in the homebound treatment engagement among people with diabetes. J Psychosom Res. elderly. J Aec ff t Disord. 2011;132(1–2):94–8. 2018;106:62–9. 12. Aparicio A, et al. Dietary glycaemic load and odds of depression in a 39. Lin EH, et al. Mental disorders among persons with diabetes— group of institutionalized elderly people without antidepressant treat- results from the world mental health surveys. J Psychosom Res. ment. Eur J Nutr. 2013;52(3):1059–66. 2008;65(6):571–80. 13. Murakami K, et al. Dietary glycemic index and load and the risk of post- 40. Lopez-Herranz M, Jiménez-García R. Mental health among Spanish adults partum depression in Japan: the Osaka maternal and child health study. J with diabetes: findings from a population-based case-controlled study. Aec ff t Disord. 2008;110(1–2):174–9. Int J Environ Res Public Health. 2021;18(11):6088. 14. Anderson RJ, et al. The prevalence of comorbid depression in adults with diabetes: a meta-analysis. Diabetes Care. 2001;24(6):1069–78. 15. Markus CR. Eec ff ts of carbohydrates on brain tryptophan availability and Publisher’s Note stress performance. Biol Psychol. 2007;76(1–2):83–90. Springer Nature remains neutral with regard to jurisdictional claims in pub- 16. Atkinson FS, Brand-Miller JC. International tables of glycemic index lished maps and institutional affiliations. and glycemic load values 2021: a systematic review. Am J Clin Nutr. 2021;114(5):1625–32. 17. Darooghegi Mofrad M, et al. Association of dietary phytochemical index and mental health in women: a cross-sectional study. Br J Nutr. 2019;121(9):1049–56. 18. Pereira GA, et al. Association of dietary total antioxidant capacity with depression, anxiety, and sleep disorders: a systematic review of observa- Re Read ady y to to submit y submit your our re researc search h ? Choose BMC and benefit fr ? Choose BMC and benefit from om: : tional studies. J Clin Transl Res. 2021;7(5):631–40. 19. Haghighatdoost F, et al. Glycemic index, glycemic load, and common fast, convenient online submission psychological disorders. Am J Clin Nutr. 2016;103(1):201–9. thorough peer review by experienced researchers in your field 20. Lamport DJ, et al. Acute glycaemic load breakfast manipulations do not attenuate cognitive impairments in adults with type 2 diabetes. Clin Nutr. rapid publication on acceptance 2013;32(2):265–72. support for research data, including large and complex data types 21. Ma Y, et al. A randomized clinical trial comparing low-glycemic index • gold Open Access which fosters wider collaboration and increased citations versus ADA dietary education among individuals with type 2 diabetes. maximum visibility for your research: over 100M website views per year Nutrition. 2008;24(1):45–56. • 22. Gopinath B, et al. Association between carbohydrate nutrition and prevalence of depressive symptoms in older adults. Br J Nutr. At BMC, research is always in progress. 2016;116(12):2109–14. Learn more biomedcentral.com/submissions 23. Minobe N, et al. Higher dietary glycemic index, but not glycemic load, is associated with a lower prevalence of depressive symptoms in a http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png BMC Neuroscience Springer Journals

Higher dietary glycemic load is inversely associated with stress prevalence among Iranian adults

Download PDF
9 pages

Loading next page...
 
/lp/springer-journals/higher-dietary-glycemic-load-is-inversely-associated-with-stress-y364m3kru4

References (38)

Publisher
Springer Journals
Copyright
Copyright © The Author(s) 2022
eISSN
1471-2202
DOI
10.1186/s12868-022-00713-z
Publisher site
See Article on Publisher Site

Abstract

Background: Psychological disorders including depression, anxiety, and stress comprise a huge public health problem. The aim of this cross-sectional study is to assess the relationship between dietary glycemic index (DGI) and glycemic load (DGL) and mental disorders. Method: Participants (n = 10,000) aged 20–69 were randomly selected from 200 clusters in Yazd from the recruit- ment phase of Yazd Health Study. The dietary intake of study participants was collected by a reliable and validated food frequency questionnaire consisting of 178 food items. DGI and DGL were calculated from the FFQ data using previously published reference values. To assess psychological disorders an Iranian validated short version of a self- reported questionnaire Depression Anxiety Stress Scales 21 was used. Results: There were no significant associations between DGI and DGL with odds of depression or anxiety in crude and adjusted models. However, individuals in the highest quartiles of DGL had the lowest odds of stress (OR: 0.69; 95% CI 0.47–1, P-trend = 0.023). This association remained significant after adjustment for potential confounding variables in model I (OR: 0.45; 95% CI 0.22–0.9, P-trend = 0.023), model II (OR: 0.46; 95% CI 0.22–0.96, P-trend = 0.039) and model III (OR: 0.46; 95% CI 0.22–0.96, P-trend = 0.042). Conclusion: In conclusion, consumption of foods with higher GL was associated with lower odds of stress; however, no significant association was found between DGI or DGL and risk of depression and anxiety. Performing further stud- ies with longitudinal design is suggested to confirm these results. Keywords: Anxiety, Depression, Dietary glycemic index, Dietary glycemic load, Stress Introduction genetic, biological, and environmental factors involved Psychological disorders including depression, anxiety, in its onset and progression [2]. The underlying mecha - and stress comprise a huge public health problem, affect - nisms are not fully understood, which may explain the ing about 31% to 41% of the world population in 2020 [1]. poor response (50%) of current pharmacotherapies [3]. The pathophysiology of mental disorders is complex, with Among the environmental factors, dietary intakes have long been demonstrated to be associated with mental disorders. For example, diets rich in fruits and vegeta- Ali Amirinejad and Mina Darand are both in the first name position bles have a general positive impact on mental health [4] *Correspondence: khayyatzadeh@yahoo.com whereas a western diet (characterized by high intake of Nutrition and Food Security Research Center, Shahid Sadoughi University fried food, processed meat, refined carbohydrate and of Medical Sciences, Shohadaye Gomnam BLD, ALEM Square, Yazd, Iran confectionary) is associated with mental disorders [5]. Full list of author information is available at the end of the article © The Author(s) 2022. 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:// creat iveco mmons. org/ licen ses/ by/4. 0/. The Creative Commons Public Domain Dedication waiver (http:// creat iveco mmons. org/ publi cdoma in/ zero/1. 0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Amirinejad et al. BMC Neuroscience (2022) 23:28 Page 2 of 9 The impact of dietary carbohydrate intake on health which has been conducted on 10,000 participants aged outcomes and disease has increasingly been in focus in 20–70  years since 2014. The participants were ran - recent years [6]. However, the link between the various domly selected from 200 clusters in Yazd Greater Area. aspects of carbohydrate and psychological health remains The profile and details of this study were published else - unclear. The effects of foods to increase blood glucose are where [24]. Written informed consent was taken from different and this property is considered the glycemic all participants. The research was approved by the Eth - index (GI), a quality rating of how individual foods raise ics Committee of Shahid Sadoughi University of Medical blood sugar levels. In fact, GI is the increase in postpran- Sciences, Yazd, Iran (Ethic code: 931188). Data regarding dial blood glucose after consumption of a specific car - current and history of chronic diseases, smoking status, bohydrate portion of a food compared with glucose or socio-demographic characteristics including age, gen- white bread [7]. When we consume high-GI foods, blood der, marital status and education level were obtained by glucose and subsequently insulin concentrations are rap- interview and standard questionnaires. Participants were idly increased, while smaller and slower elevation of post- excluded on the following: under or over estimation of prandial blood glucose and insulin levels are observed energy intake (total daily energy intake less than 800 or following intake of low-GI foods. Refined grains such as higher than 6500  kcal/day), pregnancy, following a spe- white bread, rice, potatoes and sugary products are con- cial diet and taking antidepressants. After exclusion, 7384 sidered high-GI foods, whereas vegetables, whole grain participants (3673 men and 3711women) participated in and legumes are included in low-GI groups [8]. Dietary the study. glycemic load (GL) is the product of a food’s GI and total available carbohydrate content, and provides both Dietary assessment the quality and quantity the of carbohydrates [9]. Thus, Dietary intake of study participants was collected by GL represents a more accurate view of a food’s real-life a reliable and validated food frequency questionnaire effects on postprandial glucose and insulin response. (FFQ) consisting of 178 food items designed for an Ira- The prevalence of psychological disorders is much nian population [25]. FFQs were completed during higher in patients with diabetes [10] and some stud- face-to-face interviews and reported dietary intakes ies show a link between DGI and DGL with psychologi- in household measures were converted to grams and cal disorders [11–13], suggesting glucose metabolism entered to the Nutritionist IV software (First Databank might play a mechanistic role. Indeed, high GI and GL Inc., Hearst Corp., San Bruno, CA, USA). To calculate foods provoke insulin secretion leading to subsequent daily nutrient intake values for each participant, the US hypoglycemia which impact on the nervous system and Department of Agriculture’s (USDA) national nutrient result in psychological disorders [14]. However, increased databank was used [26]. insulin levels from high GI/GL diets may facilitate deliv- ery of tryptophan in the brain and increase the synthesis Dietary glycemic index and load calculation of serotonin, a neurotransmitter associated with mood The total DGI was calculated based on the following for - improvement [15]. On the other hand, most of fruits and mula: GIa × available carbohydrate total available carbohydrate. vegetables which are the good source of dietary fiber and The available carbohydrate content of foods was calcu - several antioxidant compound such as phytochemical are lated as total carbohydrate minus fiber [27]. The total classified in the medium and low GI foods [16]. These carbohydrate and fiber contents of foods were adapted nutrients had positive effects on mental disorders in pre - from the US Department of Agriculture food-composi- vious studies [17, 18]. tion table [28]. Food items with low carbohydrate content Totally, the literature in this field is equivocal, prob - (less than 3.5  g available carbohydrate per serving) like ably due to study design, sample size, duration, and other tomatoes, pickles, cabbage, cucumbers, lettuce, cheese, components of the diet that may explain this inconsist- sausages, eggs, mayonnaise were excluded because GI ency [19–23]. Therefore, due to the necessity of con - values of these foods could not be tested [29]. Of the 178 ducting more high-quality research, we investigated the and 121 food and beverage items in the FFQs of YaHS- association of DGI and DGL with depression, anxiety, TAMYS study, 43 (24.1%) and 32 (24.4%) items contained and stress in a large Iranian population. less than 3.5  g available carbohydrate/serving, respec- tively. Eventually, the calculation of GI was carried out Materials and methods based on the remaining 135 items in the YaHS-TAMYS. Study population GI values for 108 food items in the YaHS-TAMYS study We used data from the enrollment phase of Yazd were adapted from the international references [16, 30]. Health Study (YaHS) conducted from September 2014 for Iranian specific foods not covered in the interna - to December 2015. YaHS is a prospective cohort study tional tables (6 items), the Iranian GI tables were used A mirinejad et al. BMC Neuroscience (2022) 23:28 Page 3 of 9 [31], because the GI of all food items was not covered. diabetes, and hypertension were additionally adjusted. GI values for the remaining food items which were not Further adjustment was for BMI in the final model. available, neither in Iranian nor on the international P-values < 0.05 were considered statistically significant. tables, such as some traditional sweets and desserts, were To analyze the data, the statistical Package for Social Sci- gained based on physically and chemically similar foods. ences (SPSS) (version 23.0, SPSS Inc., Chicago, Illinois, For example, the GI value for gaz, a traditional food item USA) was used. highly consumed in Yazd city and mainly made of flour, almonds, and sugar, was considered to be the same as Results sugar. When more than one GI value from a different Overall, 7384 participants were included (3673 men and brand was available, the mean GI value was applied (e.g. 3711 women). The prevalence of psychological disorders rice and dates). The GIs of mixed meals were obtained did not significantly differ among quartiles of DGI and based on GI values of each of the meal’s components [28]. DGL. BMI, marital status, education level, multi-vitamin For all derived GI values, glucose was used as the refer- supplement use, and hypertension were significantly dif - ence food. Finally, DGL was calculated by multiplying the ferent among quartiles of DGI. Furthermore, significant dietary GI by the total daily available carbohydrate intake differences were seen for age, physical activity, mari - and dividing the result by 100 [28]. tal status, gender, employment status, education level, multi-vitamin supplement use, hypertension, and diabe- Anthropometric measurements tes across quartiles of DGL (Table 1). Body weight was measured using a portable digital scale Dietary nutrients and energy adjusted food groups are analyzer with an accuracy of 0.1  kg. The participants presented in Table 2. The one-way ANOVA test followed stood in the middle of the scale, wearing the minimum by Bonferroni post-hoc analysis revealed significant dif - possible clothing. Height was also measured in a stand- ferences between all dietary nutrients and food groups ing position, while barefoot with the head placed in the including, energy intake; percentage energy from protein, Frankfurt position. Body Mass Index (BMI) was calcu- carbohydrate, and fat intake; cholesterol; saturated fatty lated, body weight (kg)/height (m ). acid; vitamin E; vitamin C; folic acid; magnesium; fruits; vegetables; red meat; fish, dairy; whole grains; refined Psychological health assessment grains; sugars; salt; legumes and nuts. Significant differ - An Iranian validated short version of the self-report ences among the quartiles of DGI and DGL are shown questionnaire for depression, anxiety and stress (DASS with different letters “a” or “b”. 21) consisting of seven items per subscale was used [32]. The association between DGI and DGL with the The individuals read each statement and recorded their respective prevalence of depression, anxiety and stress reply according to a 4-point Likert scale ranging from in crude and adjusted models are presented in Table  3. 0 (does not apply to me at all) to 3 (applies to me very There were no significant associations between DGI much or most of the time). The scores were summed for and DGL with odds of depression or anxiety in crude items of each scale. As the long form of DASS has 42 and adjusted models. However, individuals in the high- items, we multiplied the final score of each scale by two. est quartiles of DGL had the lowest odds of stress (OR: The individuals were considered to have depression, anx - 0.69; 95% CI 0.47–1, P-trend = 0.023). This association iety, and stress if they obtain total scores of ≥ 10, ≥ 8 and remained significant after adjustment for potential con - ≥ 15, respectively. founding variables in model I (OR: 0.45; 95% CI 0.22–0.9, P-trend = 0.023), model II (OR: 0.46; 95% CI 0.22–0.96, Statistical analysis P-trend = 0.039) and model III (OR: 0.46; 95% CI 0.22– The normality of data was assessed using the Kolmogo - 0.96, P-trend = 0.042). rov–Smirnov test. Continuous and categorical variables were compared across quartiles of DGI and DGL using analysis of variance (ANOVA) and chi-square tests Discussion respectively. The differences between nutrients and die - This cross-sectional study assessed the association of tary intake of each quartile were assessed using a Bonfer- dietary DGI and DGL with psychological disorders in roni post-hoc analysis. Logistic regression was applied an Iranian population. No significant association was to evaluate the relationship between DGI and DGL with observed between DGI and odds of depression, anxi- psychological disorders in crude and adjusted models. ety, and stress in crude and adjusted models. There was Model I was adjusted for age, gender, and total energy also no significant relationship between DGL and odds intake. In model II, marital status, smoking, education of depression or anxiety in crude and adjusted models; level, employment status, salt intake, multi-vitamins use, Amirinejad et al. BMC Neuroscience (2022) 23:28 Page 4 of 9 Table 1 General characteristics of participants across quartiles of GI and GL Variable GI GL Total Q1 Q2 Q3 Q4 P-value Q1 Q2 Q3 Q4 P-value Depression, yes (%) 578 (8.1) 148 (8.3) 142 (7.9) 130 (7.2) 158 (8.9) 0.326 158 (8.8) 153 (8.6) 132 (7.3) 135 (7.6) 0.252 Anxiety, yes (%) 754 (10.5) 186 (10.4) 186 (10.3) 170 (9.5) 212 (11.9) 0.113 200 (11.1) 190 (10.7) 183 (10.1) 181 (10.2) 0.710 Stress, yes (%) 238 (3.3) 58 (3.2) 65 (3.6) 54 (3) 61 (3.4) 0.776 68 (3.8) 69 (3.9) 54 (3) 47 (2.7) 0.106 BMI (kg/m ) < 18.5 247 (3.3) 61 (3.2) 63 (3.3) 75 (4) 48 (2.5) 0.018 57 (3) 55 (2.9) 73 (3.9) 62 (3.3) 0.112 18.5–24.9 2339 (30.9) 595 (31.4) 618 (32.6) 586 (30.9) 540 (28.5) 577 (30.5) 630 (33.3) 577 (30.5) 555 (29.3) > 25 4988 (65.9) 1237 (65.3) 1213 (64) 1233 (65.1) 1305 (68.9) 1259 (66.5) 1209 (63.8) 1244 (65.7) 1276 (67.4) Age (%) 20–29 years 1586 (21.5) 419 (22.7) 404 (21.8) 404 (217) 359 (19.6) 0.052 322 (17.4) 404 (22) 433 (23.4) 427 (23.2) < 0.01 30–39 years 1598 (20.8) 383 (20.8) 395 (21.4) 380 (20.4) 440 (24) 324 (17.5) 405 (22) 429 (23.1) 440 (23.9) 40–49 years 1586 (21.5) 387 (21) 413 (22.3) 393 (21.1) 393 (21.4) 404 (21.8) 397 (21.6) 399 (21.5) 386 (21) 50–59 years 1402 (19) 377 (20.4) 347 (18.8) 348 (18.7) 330 (18) 392 (21.2) 341 (18.5) 323 (17.4) 346 (18.8) 60–69 years 1215 (16.4) 279 (15.1) 290 (15.7) 334 (18) 312 (17) 409 (22.1) 293 (15.9) 270 (14.6) 243 (13.2) Physical activity (Met_min/week) 901.1 ± 905.1 890.8 ± 883.1 894.5 ± 910.5 877.5 ± 875 942.4 ± 950.3 0.156 826.6 ± 876.7 896.8 ± 896.4 932.8 ± 903 949 ± 939.7 < 0.01 Marriage (%) Single 856 (11.6) 232 (12.6) 225 (12.2) 206 (11.1) 193 (10.6) 0.019 178 (9.6) 224 (12.2) 220 (11.9) 234 (12.8) 0.001 Married 6264 (85.1) 1575 (85.6) 1567 (84.8) 1570 (85.9) 1570 (85.9) 1587 (86) 1541 (84.2) 1585 (85.6) 1551 (84.6) Widowed or divorced 240 (3.3) 61 (3.3) 40 (2.2) 75 (4.1) 64 (3.5) 80 (4.3) 65 (3.6) 46 (2.5) 49 (2.7) Smoking status (%) Never smoker 6328 (87.8) 1582 (87.6) 1576 (87) 1617 (89) 1553 (87.5) 0.496 1609 (88.4) 1567 (86.9) 1587 (87.7) 1565 (88.3) 0.520 Current smoker 766 (10.6) 194 (10.7) 207 (11.4) 177 (9.7) 188 (10.6) 190 (10.4) 200 (11.1) 192 (10.6) 184 (10.4) Ex_smoker 113 (1.6) 29 (1.6) 29 (1.6) 22 (1.2) 33 (1.9) 22 (1.2) 36 (2) 31 (1.7) 24 (1.4) Gender, male (%) 3673 (49.7) 909 (49.1) 927 (50.2) 917 (49.5) 920 (50.2) 0.877 831 (44.8) 923 (50.3) 967 (52) 952 (51.9) < 0.01 Job (%) Unemployed 1415 (19.5) 353 (19.6) 325 (17.9) 357 (19.6) 380 (21.1) 0.336 358 (19.8) 359 (19.9) 306 (16.8) 392 (21.7) < 0.01 Government employee 3537 (48.8) 898 (49.8) 898 (49.5) 904 (49.6) 837 (46.5) 960 (53.1) 898 (49.7) 876 (48.1) 803 (44.4) Manual worker 247 (3.4) 60 (3.3) 66 (3.6) 56 (3.1) 65 (3.6) 61 (3.4) 53 (2.9) 67 (3.7) 66 (3.6) Freelance job 2046 (28.2) 492 (27.3) 530 (29.1) 505 (27.7) 519 (28.8) 428 (23.7) 497 (27.5) 572 (31.4) 549 (30.3) Education (%) Illiterate 1776 (24.1) 438 (23.7) 418 (22.7) 500 (27) 420 (23.1) 0.004 562 (30.5) 401 (21.8) 406 (22) 407 (22.3) < 0.01 Middle school 2095 (28.5) 501 (27.2) 508 (27.6) 514 (27.7) 527 (31.4) 527 (28.6) 549 (29.9) 494 (26.7) 525 (28.7) Diploma 2289 (31.1) 611 (33.1) 590 (32) 553 (29.8) 535 (29.4) 520 (28.2) 557 (30.3) 629 (34) 583 (31.9) Bachelors degree 995 (13.5) 253 (13.7) 261 (14.2) 204 (12.9) 241 (13.2) 201 (10.9) 270 (14.7) 260 (14.1) 264 (14.4) Master and doctor 205 (2.8) 42 (2.3) 65 (3.5) 47 (2.5) 51 (2.8) 35 (1.9) 62 (3.4) 59 (3.2) 49 (2.7) A mirinejad et al. BMC Neuroscience (2022) 23:28 Page 5 of 9 Table 1 (continued) Variable GI GL Total Q1 Q2 Q3 Q4 P-value Q1 Q2 Q3 Q4 P-value Multi-vitamins supplement (%) Never 6407 (86.1) 1727 (94.3) 1715 (91.9) 1619 (86.4) 1346 (72.1) > 0.01 1741 (94.2) 1727 (93.7) 1691 (90) 1248 (66.8) < 0.01 1–3/month 482 (6.5) 44 (2.4) 67 (3.6) 95 (5.1) 276 (14.8) 34 (1.8) 37 (2) 64 (3.4) 347 (18.6) Minimal once a week 549 (7.4) 60 (3.3) 85 (4.6) 159 (8.5) 245 (13.1) 73 (4) 79 (4.3) 124 (6.6) 273 (14.6) Diabetes, yes (%) 912 (12) 233 (12.3) 209 (11) 244 (12.9) 226 (11.9) 0.358 313 (16.5) 229 (12.1) 194 (10.2) 176 (9.3) < 0.01 Hypertension, yes (%) 1135 (15) 280 (14.8) 280 (14.8) 321 (16.9) 254 (13.4) 0.023 350 (18.5) 286 (14.1) 277 (14.6) 240 (12.7) < 0.01 GI glycemic index, GL glycemic load a 2 Obtained from χ test and one-way anova for categorical and continuous variables, respectively Data are presented as mean ± standard deviation (SD) Amirinejad et al. BMC Neuroscience (2022) 23:28 Page 6 of 9 Table 2 Dietary intake of study participants among the quartiles of GI & GL Quartiles of GI Quartiles of GL Total Q1 Q2 Q3 Q4 P-value Q1 Q2 Q3 Q4 P-value Nutrients a b b b a b b b Energy intake (kcal) 2897 ± 1378 2438 ± 1061 2864 ± 1351 3634 ± 1351 2897 ± 1378 < 0.001 1646 ± 419.3 2199 ± 494.1 3019 ± 744.9 4721 ± 1111 < 0.001 a b b a b b b Protein (% of total 16.16 ± 0.04 16.82 ± 0.04 16.73 ± 0.03 16.24 ± 0.04 14.86 ± 0.04 < 0.001 17.84 ± 0.04 16.59 ± 0.03 16.11 ± 0.03 14.10 ± 0.04 < 0.001 daily energy) a b b a b b b Carbohydrate (% of 56.12 ± 0.09 53.81 ± 0.08 54.58 ± 0.08 56.00 ± 0.08 60.09 ± 11.21 < 0.001 52.55 ± 0.07 55.40 ± 0.07 55.87 ± 0.09 60.67 ± 0.10 < 0.001 total daily energy) a b a b b Fat (% of total daily 33.61 ± 0.09 32.90 ± 0.07 32.67 ± 0.07 32.85 ± 0.07 0.36 ± 0.12 < 0.001 33.24 ± 0.06 31.53 ± 0.06 33.38 ± 0.09 36.28 ± 0.11 < 0.001 energy) a b a b b Cholesterol (mg) 394.8 ± 391.3 363.5 ± 396.1 394.1 ± 326.6 391.1 ± 336.4 430.6 ± 483.4 < 0.001 286.3 ± 322.9 318.4 ± 206.4 432.7 ± 390.9 542 ± 521.8 < 0.001 a b b b a b b b SFA (g) 31.04 ± 18.36 27.13 ± 15.36 29.58 ± 17.43 30.48 ± 17.28 36.98 ± 21.39 < 0.001 19.56 ± 9.62 24.3 ± 11.47 32.47 ± 15.22 47.8 ± 20.82 < 0.001 a b b b Vitamin E (mg/day) 11.36 ± 11.66 11.92 ± 11.85 11.52 ± 11.80 10.98 ± 12.02 11.01 ± 10.92 0.038 7.70 ± 7.16 9.55 ± 8.93 12.72 ± 13.28 15.45 ± 14.19 < 0.001 a b b a b b b Vitamin C (mg) 210.5 ± 188.7 196.2 ± 169 218.3 ± 214.3 219.2 ± 169.6 208.5 ± 197.1 < 0.001 115.1 ± 54.12 166.8 ± 92 243.2 ± 148.4 317.1 ± 292.6 < 0.001 a b a b b b Folic acid (µg) 379.8 ± 228 354.6 ± 215.5 361.9 ± 217.7 370.8 ± 216.6 432.1 ± 251.8 < 0.001 230.7 ± 93.18 300 ± 127.6 410.8 ± 193.8 577.8 ± 276.8 < 0.001 a b b a b b b Magnesium (mg) 339.3 ± 179.6 309.6 ± 155.2 322.9 ± 166.2 336.2 ± 180.7 339.3 ± 179.6 < 0.001 199.7 ± 58.38 262.8 ± 79.31 359 ± 125.2 535.7 ± 198.7 < 0.001 Food groups (g/1000 kcal) a b b a b b b Fruits 184.3 ± 138.4 205.6 ± 145.1 202.3 ± 141.8 192.3 ± 130.3 136.9 ± 124.1 < 0.001 187.8 ± 109.9 204.8 ± 128.1 202.8 ± 151.3 184.3 ± 138.4 < 0.001 a b b b a b b b Vegetables 96.6 ± 77.29 112 ± 82.82 104.1 ± 78.03 97.77 ± 75.50 72.76 ± 66.25 < 0.001 119.6 ± 81.3 104.7 ± 69.75 96.78 ± 81.41 65.57 ± 65.10 < 0.001 a b b b a b b b Red meat 20.46 ± 18.37 22.60 ± 17.77 24.60 ± 21.13 20.12 ± 16.43 14.51 ± 16.16 < 0.001 25.29 ± 20.43 23.65 ± 16.75 20.90 ± 19.34 11.99 ± 13.15 < 0.001 a b b a b b Fish 7 ± 13.56 5.90 ± 11.50 6.70 ± 12.80 7.48 ± 14.42 7.91 ± 15.14 < 0.001 5.85 ± 9.99 5.65 ± 10.98 7.65 ± 14.93 8.85 ± 16.90 < 0.001 a b b b a b b b Dairy 89.84 ± 60.16 106.99 ± 76.74 94.95 ± 53.32 89.96 ± 53.41 67.47 ± 45.57 < 0.001 104.2 ± 53.30 95.85 ± 52.83 86.20 ± 59.35 73.09 ± 69.35 < 0.001 a b b b a b b b Legumes and nuts 25.20 ± 19.14 29.78 ± 25.53 25.64 ± 18.63 24.07 ± 14.99 21.31 ± 14.35 < 0.001 27.80 ± 18.12 25.24 ± 18.01 25.30 ± 20.19 22.46 ± 19.80 < 0.001 a b b a b b b Whole grains 29.95 ± 27.33 26.68 ± 20.58 32.32 ± 24.55 33.81 ± 27.92 27.01 ± 33.82 < 0.001 34.97 ± 24.53 37.83 ± 28.35 29.25 ± 28.89 17.77 ± 22.65 < 0.001 a b b b a b b Refined grains 85.67 ± 58.18 126.70 ± 66.74 93.05 ± 47.27 67.95 ± 41.92 55 ± 45.87 < 0.001 100.5 ± 54 102 ± 49.75 82.02 ± 59.34 58.11 ± 58.05 < 0.001 a b b b Sugars 12.63 ± 11.64 10.21 ± 7.58 11.88 ± 9.05 13.36 ± 11.61 15.07 ± 15.98 < 0.001 12.14 ± 9.27 12.74 ± 9.42 12.80 ± 12.58 12.84 ± 14.47 0.210 a b a b b b Salt 2.94 ± 3.68 3.21 ± 2.94 3.22 ± 3.45 3.14 ± 3.89 2.21 ± 4.21 < 0.001 4.24 ± 3.83 3.61 ± 3.11 2.41 ± 3.37 1.52 ± 3.73 < 0.001 GI glycemic index, GL glycemic load Obtained from one-way ANOVA followed by Bonferroni post-hoc test First quartile is considered as reference quartile Significant difference between quartile with reference quartile (P value < 0.05) A mirinejad et al. BMC Neuroscience (2022) 23:28 Page 7 of 9 Table 3 Multivariable-adjusted ORs (and 95% CIs) for depression, anxiety and stress across quartiles of GI and GL GI quartile GL quartiles Variables Q1 Q2 Q3 Q4 P-trend Q1 Q2 Q3 Q4 P-trend Depression [n (%)] Crude 1.00 0.94 (0.74–1.20) 0.86 (0.67–1.10) 1.08 (0.85–1.36) 0.672 1.00 0.96 (0.75–1.22) 0.78 (0.61–1.01) 1.10 (0.87–1.39) 0.717 Adjusted model1 1.00 0.96 (0.75–1.22) 0.87 (0.68–1.12) 1.16 (0.90–1.48) 0.403 1.00 1.01 (0.79–1.29) 0.86 (0.64–1.15) 0.97 (0.63–1.50) 0.546 Adjusted model2 1.00 0.096 (0.74–1.24) 0.84 (0.64–1.10) 1.11 (0.85–1.46) 0.679 1.00 1.00 (0.77–1.30) 0.86 (0.63–1.18) 0.97 (0.61–1.56) 0.579 Adjusted model3 1.00 0.096 (0.74–1.24) 0.84 (0.64–1.10) 1.12 (0.85–1.46) 0.653 1.00 1.00 (0.77–1.30) 0.86 (0.63–1.18) 0.97 (0.61–1.55) 0.604 Anxiety [n (%)] Crude 1.00 0.99 (0.80–1.22) 0.90 (0.72–1.12) 1.16 (0.94–1.43) 0.248 1.00 0.95 (0.77–1.17) 0.89 (0.72–1.10) 0.90 (0.73–1.12) 0.292 Adjusted model1 1.00 1.00 (0.80–1.24) 0.91 (0.73–1.13) 1.22 (0.98–1.52) 0.157 1.00 0.96 (0.77–1.20) 0.90 (0.70–1.17) 0.94 (0.64–1.38) 0.568 Adjusted model2 1.00 0.99 (0.78–1.25) 0.89 (0.70–1.13) 1.17 (0.92–1.49) 0.343 1.00 0.94 (0.74–1.20) 0.90 (0.68–1.19) 0.91 (0.60–1.38) 0.542 Adjusted model3 1.00 0.99 (0.78–1.25) 0.89 (0.70–1.13) 0.94 (0.87–1.02) 0.323 1.00 0.94 (0.74–1.20) 0.90 (0.68–1.18) 0.91 (0.60–1.38) 0.573 Stress [n (%)] Crude 1.00 1.11 (0.77–1.60) 0.92 (0.63–1.35) 1.06 (0.73–1.53) 0.990 1.00 1.02 (0.72–1.44) 0.77 (0.54–1.11) 0.69 (0.47–1.00) 0.023 Adjusted model1 1.00 1.13 (0.79–1.63) 0.93 (0.63–1.36) 1.12 (0.76–1.65) 0.839 1.00 0.97 (0.67–1.38) 0.64 (0.41–1.00) 0.45 (0.22–0.90) 0.023 Adjusted model2 1.00 1.02 (0.69–1.51) 0.87 (0.57–1.31) 1.09 (0.072–1.65) 0.881 1.00 1.07 (0.68–1.50) 0.65 (0.40–1.05) 0.46 (0.22–0.96) 0.039 Adjusted model3 1.00 1.02 (0.69–1.51) 0.87 (0.57–1.31) 1.10 (0.72–1.66) 0.888 1.00 0.98 (0.68–1.42) 0.72 (0.40–1.05) 0.46 (0.22–0.96) 0.042 GI glycemic index, GL glycemic load These values are odds ratios (95% CIs) Obtained from logistic regression by considering quartiles of GI & GL as ordinal variable Adjusted for age, gender and total energy intake Additionally adjusted for physical activity, marital status, smoking, education, job status, multi-vitamins use, diabetes, hypertension Further adjustment BMI Amirinejad et al. BMC Neuroscience (2022) 23:28 Page 8 of 9 however, higher DGL was associated with lower odds of patients with chronic disease. Furthermore, although the stress in all models. FFQ used in this study was validated for carbohydrate A systematic review and meta-analysis by Salari- and intake of other nutrients, the validation for DGI or moghaddam et  al. [33] was performed on studies with DGL was not performed. Thus, the observed association different designs to investigate the possible relation may be real or related to the quality of the questionnaire. between DGI or DGL and depression. In line with our Also, due to the absence of a reliable Iranian food compo- results, no significant association between DGI or DGL sition table the USDA food-nutrient database was used, and odds of depression was found in cross-sectional which is another limitation of this study. Finally, residual studies. Although a positive association was observed confounding from unknown or unmeasured variables between DGI and risk of depression in cohort studies, could affect our results. the number of studies was limited (n = 2) with significant heterogeneity between them [33]. Conclusion Our results showed no significant association between In summary, an inverse association was found between DGI or DGL and odds of anxiety. In agreement with the DGL and likelihood of stress among Iranian adults. How- current study, Haghighatdoost et  al., after adjusting for ever, considering this point that long-term consumption confounders (marital status, education, physical activity, of food with high GL may increase the risk of chronic dis- smoking, dietary intakes, and BMI) showed similar find - eases especially obesity and diabetes, we can not recom- ings [19]. Another study with a cross-over clinical trial mend high glycemic load dietary sources to the general design examined the effects of a high GL diet on mental population. Therefore, to clarify the effects of DGL or health. Consuming 28 days of a high GL diet did not alter DGI on psychological profiles, further longitudinal stud - tension-anxiety compared to the diet with a low GL [34]. ies such as randomized controlled trials are needed in at- There was also no association between DGI and stress. risk populations. However, in line with a previous study [19], being in the Acknowledgements highest quartiles of DGL in our study was associated We thank Yazd people who participated in YaHS. with lower odds of stress. This inverse association can be Author contributions attributed to the effects of sugar-rich foods on the hypo - SK, MaM, AN and AA: designed and conducted the study; MD and MoM: ana- thalamic–pituitary–adrenal (HPA) axis. Under stressful lyzed the data; MD and AA: wrote the manuscript SK, ID, and MoM: critically conditions, the HPA releases stress hormones (corticos- revised the manuscript; SK, AN and MaM: supervised the study. All authors read and approved the final manuscript. teroids) that increase the desire for sugar rich foods that provide inhibitory feedback on the hypothalamus. There - Funding fore, participants of the higher quartiles of DGL con- This study is supported by Shahid Sadoughi University of Medical Sciences. sumed more sugar-rich foods, which can lower stress Availability of data and materials by decreasing HPA axis activity [35, 36]. Furthermore, The data and materials of the current study are available from the correspond- serotonin is a neurotransmitter that has an essential role ing author on reasonable request. in mood regulation. Foods with high GL induce insulin secretion which facilitates tryptophan uptake and sero- Declarations tonin production in the brain and thereby lowers stress Ethics approval and consent to participate [15]. However, it must be kept in mind that long-term We confirm that all methods were carried out in accordance with Shahid consumption of food with high GL leads to blood glucose Sadoughi University of Medical Sciences guidelines and regulations. Written informed consent was taken from all participants. The research was approved fluctuations and increase the risk of diabetes [37]. Thus, by the Ethics Committee of Shahid Sadoughi University of Medical Sciences, caution should be taken to account when interpreting Yazd, Iran (Ethic code: 931188). these results since several studies reported that patients Consent for publication with diabetes have a higher risk of mental disorders com- Not applicable. pared to healthy people [38–40]. Besides the potential strengths of our study such as a Competing interests Not applicable. large sample size covering both urban and rural areas, recruitment of well-trained interviewers, using a com- Author details prehensive and validated FFQ for evaluating dietary Nutrition and Food Security Research Center, Shahid Sadoughi University of Medical Sciences, Shohadaye Gomnam BLD, ALEM Square, Yazd, Iran. intake, and controlling for possible confounders, there Department of Nutrition, School of Public Health, Shahid Sadoughi University are some limitations. First, the cross-sectional data of of Medical Sciences, Yazd, Iran. Department of Clinical Nutrition, School this study prevents any inference of causality between of Nutrition and Food Science, Isfahan University of Medical Sciences, Isfahan, Iran. Food Security Research Center, Isfahan University of Medical Sciences, DGL and stress. Second, no biochemical measures were Isfahan, Iran. Research Institute of Sport and Exercise Sciences, Liverpool John assessed in our study, which might limit the detection of Moores University, Liverpool, UK. Nuffield Department of Population Health, A mirinejad et al. BMC Neuroscience (2022) 23:28 Page 9 of 9 University of Oxford, Richard Doll Building, Old Road Campus, Oxford OX3 cross-sectional study of young and middle-aged Japanese women. Eur J 7LF, UK. Yazd Cardiovascular Research Center, Non-Communicable Disease Nutr. 2018;57(6):2261–73. Institute, Shahid Sadoughi University of Medical Sciences, Yazd, Iran. 24. Mirzaei M, et al. Cohort profile: the Yazd health study (YaHS): a popula- tion-based study of adults aged 20–70 years (study design and baseline Received: 22 February 2022 Accepted: 9 May 2022 population data). Int J Epidemiol. 2018;47(3):697–698h. 25. Esfahani FH, et al. Reproducibility and relative validity of food group intake in a food frequency questionnaire developed for the Tehran lipid and glucose study. J Epidemiol. 2010;20(2):150–8. 26. Pehrsson PR, Haytowitz DB, Holden JM, Perry CR, Beckler DG. USDA’s national food and nutrient analysis program: Food sampling. J Food References Compos Anal. 2000;13(4):379–89. 1. Wu T, et al. Prevalence of mental health problems during the COVID- 27. Wolever TM, et al. Food glycemic index, as given in glycemic index tables, 19 pandemic: a systematic review and meta-analysis. J Aec ff t Disord. is a significant determinant of glycemic responses elicited by composite 2021;281:91–8. breakfast meals. Am J Clin Nutr. 2006;83(6):1306–12. 2. Gray L, Hannan AJ. Dissecting cause and effect in the pathogenesis of 28. Haytowitz D, et al. USDA national nutrient database for standard refer- psychiatric disorders: genes, environment and behaviour. Curr Mol Med. ence, release 24. Washington, DC: US Department of Agriculture; 2011. 2007;7(5):470–8. 29. Ma Y, et al. Association between dietary carbohydrates and body weight. 3. Pfau ML, Ménard C, Russo SJ. Inflammatory mediators in mood disorders: Am J Epidemiol. 2005;161(4):359–67. therapeutic opportunities. Annu Rev Pharmacol Toxicol. 2018;58:411–28. 30. Foster-Powell K, Holt SH, Brand-Miller JC. International table of glycemic 4. Guzek D, et al. Fruit and vegetable dietary patterns and mental health index and glycemic load values: 2002. Am J Clin Nutr. 2002;76(1):5–56. in women: a systematic review. Nutr Rev. 2021. https:// doi. org/ 10. 1093/ 31. Taleban F, Esmaeili M. Glycemic index of Iranian foods. Tehran: National nutrit/ nuab0 07. Nutrition and Food Technology Research Institute publication; 1999. 5. Oddy WH, et al. Dietary patterns, body mass index and inflammation: 32. Sahebi A, Asghari MJ, Salari RS. Validation of depression anxiety and stress pathways to depression and mental health problems in adolescents. scale (DASS-21) for an Iranian population. 2005. Brain Behav Immun. 2018;69:428–39. 33. Salari-Moghaddam A, et al. Glycemic index, glycemic load, and 6. Liu Y-S, et al. Dietary carbohydrate and diverse health outcomes: umbrella depression: a systematic review and meta-analysis. Eur J Clin Nutr. review of 30 systematic reviews and meta-analyses of 281 observational 2019;73(3):356–65. studies. Front Nutr. 2021. https:// doi. org/ 10. 3389/ fnut. 2021. 670411. 34. Breymeyer KL, et al. Subjective mood and energy levels of healthy weight 7. Jenkins DJ, et al. Glycemic index of foods: a physiological basis for carbo- and overweight/obese healthy adults on high-and low-glycemic load hydrate exchange. Am J Clin Nutr. 1981;34(3):362–6. experimental diets. Appetite. 2016;107:253–9. 8. Esfahani A, et al. The glycemic index: physiological significance. J Am Coll 35. Ulrich-Lai YM, Ostrander MM, Herman JP. HPA axis dampening by limited Nutr. 2009;28(sup4):439S-445S. sucrose intake: reward frequency vs. caloric consumption. Physiol Behav. 9. Sheard NF, et al. Dietary carbohydrate (amount and type) in the preven- 2011;103(1):104–10. tion and management of diabetes: a statement by the American diabetes 36. Adam TC, Epel ES. Stress, eating and the reward system. Physiol Behav. association. Diabetes Care. 2004;27(9):2266–71. 2007;91(4):449–58. 10. Kan C, et al. A systematic review and meta-analysis of the asso- 37. Livesey G, et al. Dietary glycemic index and load and the risk of type 2 ciation between depression and insulin resistance. Diabetes Care. diabetes: assessment of causal relations. Nutrients. 2019;11(6):1280. 2013;36(2):480–9. 38. Boden MT. Prevalence of mental disorders and related functioning and 11. Mwamburi DM, et al. Depression and glycemic intake in the homebound treatment engagement among people with diabetes. J Psychosom Res. elderly. J Aec ff t Disord. 2011;132(1–2):94–8. 2018;106:62–9. 12. Aparicio A, et al. Dietary glycaemic load and odds of depression in a 39. Lin EH, et al. Mental disorders among persons with diabetes— group of institutionalized elderly people without antidepressant treat- results from the world mental health surveys. J Psychosom Res. ment. Eur J Nutr. 2013;52(3):1059–66. 2008;65(6):571–80. 13. Murakami K, et al. Dietary glycemic index and load and the risk of post- 40. Lopez-Herranz M, Jiménez-García R. Mental health among Spanish adults partum depression in Japan: the Osaka maternal and child health study. J with diabetes: findings from a population-based case-controlled study. Aec ff t Disord. 2008;110(1–2):174–9. Int J Environ Res Public Health. 2021;18(11):6088. 14. Anderson RJ, et al. The prevalence of comorbid depression in adults with diabetes: a meta-analysis. Diabetes Care. 2001;24(6):1069–78. 15. Markus CR. Eec ff ts of carbohydrates on brain tryptophan availability and Publisher’s Note stress performance. Biol Psychol. 2007;76(1–2):83–90. Springer Nature remains neutral with regard to jurisdictional claims in pub- 16. Atkinson FS, Brand-Miller JC. International tables of glycemic index lished maps and institutional affiliations. and glycemic load values 2021: a systematic review. Am J Clin Nutr. 2021;114(5):1625–32. 17. Darooghegi Mofrad M, et al. Association of dietary phytochemical index and mental health in women: a cross-sectional study. Br J Nutr. 2019;121(9):1049–56. 18. Pereira GA, et al. Association of dietary total antioxidant capacity with depression, anxiety, and sleep disorders: a systematic review of observa- Re Read ady y to to submit y submit your our re researc search h ? Choose BMC and benefit fr ? Choose BMC and benefit from om: : tional studies. J Clin Transl Res. 2021;7(5):631–40. 19. Haghighatdoost F, et al. Glycemic index, glycemic load, and common fast, convenient online submission psychological disorders. Am J Clin Nutr. 2016;103(1):201–9. thorough peer review by experienced researchers in your field 20. Lamport DJ, et al. Acute glycaemic load breakfast manipulations do not attenuate cognitive impairments in adults with type 2 diabetes. Clin Nutr. rapid publication on acceptance 2013;32(2):265–72. support for research data, including large and complex data types 21. Ma Y, et al. A randomized clinical trial comparing low-glycemic index • gold Open Access which fosters wider collaboration and increased citations versus ADA dietary education among individuals with type 2 diabetes. maximum visibility for your research: over 100M website views per year Nutrition. 2008;24(1):45–56. • 22. Gopinath B, et al. Association between carbohydrate nutrition and prevalence of depressive symptoms in older adults. Br J Nutr. At BMC, research is always in progress. 2016;116(12):2109–14. Learn more biomedcentral.com/submissions 23. Minobe N, et al. Higher dietary glycemic index, but not glycemic load, is associated with a lower prevalence of depressive symptoms in a

Journal

BMC Neuroscience – Springer Journals

Published: May 20, 2022

Keywords: Anxiety; Depression; Dietary glycemic index; Dietary glycemic load; Stress

There are no references for this article.