Tehran Lipid and Glucose Study - Archives of Iranian Medicine

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Original Article

Low Carbohydrate Diet Score does not Predict Metabolic Syndrome in Children and Adolescents: Tehran Lipid and Glucose Study Ghazaleh Eslamian MSc1, 3DUYLQ0LUPLUDQ3K'‡2,3, Golaleh Asghari MSc2, Firoozeh Hosseini-Esfahani MSc2, Emad Yuzbashian BSc2, Fereidoun Azizi MD4 Abstract Background:7KHDLPRIWKHVWXG\ZDVWRHYDOXDWHWKHDELOLW\RIDORZFDUERK\GUDWHGLHWVFRUH /&' WRSUHGLFWWKHRFFXUUHQFHRIWKH PHWDEROLFV\QGURPH 0HW6 DQGLWVFRPSRQHQWVLQDJURXSRI7HKUDQLFKLOGUHQDQGDGROHVFHQWVDIWHU\HDUVRIIROORZXS Methods:'LHWVFRUHVZHUHFDOFXODWHGXVLQJDYDOLGDWHGVHPLTXDQWLWDWLYHIRRGIUHTXHQF\TXHVWLRQQDLUHIRUSDUWLFLSDQWVDJHG±\HDUV VHOHFWHGIURPWKH7HKUDQ/LSLGDQG*OXFRVH6WXG\FRKRUW7KH/&'ZDVFDOFXODWHGEDVHGRQLQWDNHRIFDUERK\GUDWHPRQRXQVDWXUDWHGIDWW\ DFLGVUH¿QHGJUDLQVDQGYHJHWDEOHSURWHLQLQWDNHH[SUHVVHGDVDSHUFHQWDJHRIHQHUJ\DVZHOODV¿EHUQQSRO\XQVDWXUDWHGIDWW\DFLGV DQGJO\FHPLFORDG7KHKLJKHUWKHVFRUHWKHPRUHFORVHO\WKHSDUWLFLSDQW¶VGLHWIROORZHGWKHSDWWHUQRI/&'7KHLQFLGHQFHRI0HW6DQGLWV components was calculated three years later. Results:7KHPHDQDJHRIWKHSDUWLFLSDQWVZDV“\HDUVDQGZHUHER\V7KHLQFLGHQFHUDWHVRI0HW6KLJKEORRGSUHVVXUH KLJKWULJO\FHULGHVORZ+'/&DEGRPLQDOREHVLW\DQGKLJKEORRGJOXFRVHZHUHDQGUHVSHFWLYHO\ &RPSDUHGWRWKRVHLQWKHORZHVWTXDUWLOHRI/&'VFRUHDIWHUDGMXVWLQJIRUDJHVH[SK\VLFDODFWLYLW\DQGHQHUJ\LQWDNHSDUWLFLSDQWVLQWKH KLJKHVWTXDUWLOHRI/&'VFRUHKDGRGGVUDWLRVRI &,±  &,±  &,±   &,±  &,± DQG &,± ZLWKWKHLQFLGHQFHRI0HW6KLJKEORRGSUHVVXUHKLJKWULJO\FHULGHV ORZ+'/&DEGRPLQDOREHVLW\DQGKLJKEORRGJOXFRVH Conclusion:1RDVVRFLDWLRQZDVIRXQGEHWZHHQ/&'DQGWKHLQFLGHQFHRI0HW6RULWVFRPSRQHQWVLQFKLOGUHQDQGDGROHVFHQWVLQ7HKUDQ DIWHU\HDUVRIIROORZXS Keywords: $GROHVFHQWVFKLOGUHQORZFDUERK\GUDWHGLHWPHWDEROLFV\QGURPH

Cite this article as: Eslamian G, Mirmiran P, Asghari G, Hosseini-Esfahani F, Youzbashian E, Azizi F. Low Carbohydrate Diet Score does not Predict Metabolic Syndrome in Children and Adolescents: Tehran Lipid and Glucose Study. Arch Iran Med. 2014; 17(6): 417 – 422.

Introduction

T

he prevalence of childhood overweight and obesity has increased at an alarming rate worldwide.1 Since overweight or obese children are much more likely to become overweight or obese adults,2, 3 increased childhood overweight and obesity is clearly a major contributor to adulthood obesity4 as well as the global burden of diseases.5 Childhood obesity is linked to underachievement and lower self-esteem in school6 and is strongly associated with risk factors for cardiovascular diseases, diabetes, orthopedic problems, mental disorders and also the metabolic syndrome (MetS).7,8 According to the third report of the National Cholesterol Education Program Adult Treatment Panel III (ATP $XWKRUV¶DI¿OLDWLRQV1Students’ Research Committee, Faculty of Nutrition Sciences and Food Technology, Shahid Beheshti University of Medical Sciences, Tehran, Iran. 2Nutrition and Endocrine Research Center, Obesity Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran. 3Department of Clinical Nutrition and Dietetics, Faculty of Nutrition Sciences and Food Technology, National Nutrition and Food Technology Research Institute, Shahid Beheshti University of Medical Sciences, Tehran, Iran. 4Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran. ‡&RUUHVSRQGLQJ DXWKRU DQG UHSULQWV Parvin Mirmiran PhD, Nutrition and Endocrine Research Center, Obesity Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran. P.O. Box: 19395-4763, Tehran, Iran. Tel: +98 (21) 223 57 484, Fax: +98-21-224 16 264, 224 02 463, E-mail: [email protected]

III), the MetS is now recognized as a secondary target for riskreduction therapy9 and according to the International Diabetes Federation (IDF), the global prevalence of MetS is increasing in children.10 A recent study in Tehran showed that the MetS is highly prevalent in Iranian adolescents, particularly among overweight adolescents.11 It is evident that obesity develops as the result of an inactive lifestyle and a positive energy balance.12 However, the evidence remains inconclusive in children. Some studies have indicated a positive association between adiposity and dietary fat13–16 while others have not.17–207KHUHDUHRQO\IHZVWXGLHVZKLFKKDYHVSHFL¿cally showed macronutrient intake in relation to Body Mass Index (BMI) and Waist circumference (WC) in children.21,22 Although a relationship has been observed between fat intake and the insulin sensitivity index (SI) in adolescents,23 neither dietary fat nor carbohydrate was associated with SI in a prepubertal subset of their cohort.24 Limited data exist in children on dietary determinants of features of the MetS in children. A study showed that the dietary macronutrient composition is a predictor of Insulin resistance (IR) and systolic blood pressure (BP), but not resistin, adiponectin, or leptin concentrations.25 Considering the elevated prevalence of MetS in Iranian adolescents and the importance of distribution of macronutrients in dietary intakes, the purpose of the current study was to investigate

Archives of Iranian Medicine, Volume 17, Number 6, June 2014 417

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the association between MetS and its individual components and the dietary proportion of carbohydrates, protein and fat as well as fatty acid and protein subtypes and glycemic load (GL) in the frame of a low carbohydrate diet (LCD) score in Tehrani children and adolescents.

the nearest 0.1 cm, while the shoulders were in a normal position. BMI was calculated as weight (Kg) divided by square of height (m2) (28).

Dietary intake assessment A validated semi-quantitative food frequency questionnaire 27 (FFQ), which contained 168 food items, was used by trained Materials and Methods dietitians with at least 5 years of experience in the TLGS survey28 in face-to-face interviews to evaluate the usual dietary intakes of Study population The subjects in this study were selected from the third phase participants. The participants were asked to report their consump(2006–2008) of the Tehran Lipid and Glucose Study (TLGS)26 tion frequency during the previous year on a daily, weekly, or and were followed up to the fourth phase (2009–2011). Out of monthly basis, and data were then converted to the mean daily the 12523 initial participants, 3462 were randomly selected for intakes assuming that one month equals 30.5 days. Portion sizes of consumed foods, which were reported in housedietary assessment, categorized by age and sex. For the current VWXG\  LQGLYLGXDOV DJHG • \U DQG  \U ZHUH LQFOXGHG KROGPHDVXUHVZHUHVSHFL¿HGDFFRUGLQJWRWKH86'HSDUWPHQWRI Subjects with incomplete physical activity, anthropometric, and Agriculture (USDA) standard portion sizes (e.g., apple, 1 medibiochemical data (n = 29) and those over- or underreported (n = um; bread, 1 slice; dairy, 1 cup) and were then converted to grams.   ZHUH H[FOXGHG 2YHU RU XQGHUUHSRUWLQJ ZDV GH¿QHG DV WKH When unable to use the USDA portion sizes, household measures reported energy intake divided by the predicted energy intake, (e.g., beans, 1 tablespoon; chicken meat, 1 leg or wing; rice, 1 and reports that did not qualify for ±3SD range were excluded. large or small plate) were used alternatively.29 The estimates of Furthermore, subjects who had MetS (n = 69), high blood pres- nutrient intake are derived from the dietary sources alone. Since sure (n = 53), high triglycerides (n = 168), low HDL-C (n = 242), the Iranian food composition table (FCT) is incomplete and prohigh blood glucose (n = 12), or abdominal obesity (n = 145) were vides limited data on the nutrient content of raw foods and beverexcluded for individual analysis of incidence of MetS and its ages,30 analyses of energy and nutrients of foods and beverages components. Some individuals fell into more than one exclusion were carried out using the USDA FCT.31 However, for some food category. After an average follow-up of 3.6 years, 401, 437, 347, items such as Kashk which are not listed in the USDA FCT, Ira290, 479, and 352 subjects remained for the analysis of MetS, nian FCT was used alternatively.30 Moreover, for analyzing the blood pressure, triglycerides, HDL-C, blood glucose, and waist energy and nutrient contents of mixed food items (e.g. pizza), usual restaurant recipes were used. circumference, respectively. Since the Iranian Food Table of GI is incomplete,32 analyses of The design of this study was approved by the institutional ethics FRPPLWWHHRIWKH5HVHDUFK,QVWLWXWHIRU(QGRFULQH6FLHQFHVDI¿OLDW- GI content of foods and beverages were carried out using the ined with the Shahid Beheshti University of Medical Sciences, and in- ternational tables of GI and GL values: 2008.33 However, the Iraformed written consent was obtained from the participants’ parents. nian Food Table of GI was used for some foods (like traditional Iranian breads) that are not listed in the international tables of GI and GL values: 2008. Food items for which a GI had not been Clinical and laboratory measurements To measure blood pressure, the participants remained seated for reported were attributed the GI of the nearest comparable food PLQXWHVWKHQDTXDOL¿HGSK\VLFLDQXVLQJDVWDQGDUGPHUFXU\ item (e.g., tangerines were assigned the GI of oranges) or were sphygmomanometer with the cuff placed on the right arm, mea- calculated using recipes. Lack of information about the GI of vegsured blood pressure twice and the mean values were used. Blood etables and legumes was resolved by calculating a mean GI for samples, at baseline and during follow up, were drawn between usually consumed vegetables and legumes in our study. The GI is 7:00 and 9:00 a.m. from all study participants after 12–14 hr based on the postprandial blood glucose response compared with overnight fasting. All the blood analyses were done at the TLGS white bread. Average dietary GI and GL were derived from the research laboratory on the day of blood collection. Fasting plas- FFQ as follows: $YHUDJHGLHWDU\*, > FDUERK\GUDWHFRQWHQWRIHDFKIRRGLWHP  ma glucose (FPG) was measured by the enzymatic colorimetric method using glucose oxidase. Serum HDL-C was measured after × (number of servings/d) × (GI)] /total daily carbohydrate intake Dietary GL = (carbohydrate content of each food item) × (numprecipitation of the apolipoprotein B-containing lipoproteins with phosphotungstic acid and serum triglycerides (TGs) were assayed ber of servings/d) × (GI) using an enzymatic colorimetric method with glycerol phosphate Calculation of the low-carbohydrate-diet score oxidase. These analyses were performed using commercial kits We divided the study participants into 11 strata for each com(Pars Azmoon Inc., Tehran, Iran) and a Selectra 2 auto analyzer ponent; i.e. carbohydrate, mono unsaturated fatty acids (MUFA), 9LWDO6FLHQWL¿F6SDQNHUHQ7KH1HWKHUODQGV  UH¿QHG JUDLQV DQG YHJHWDEOH SURWHLQ LQWDNH H[SUHVVHG DV D SHU,QWHUDQGLQWUDDVVD\FRHI¿FLHQWVRIYDULDWLRQVDWEDVHOLQHZHUH both 2.2% for FPG, 2 and 0.5% for HDL-C and 1.6 and 0.6% for FHQWDJHRIHQHUJ\DVZHOODV¿EHU J.FDO QQSRO\XQsaturated fatty acids (PUFA) and GL (Table 1). For MUFA, n3/ TGs, respectively. Q38)$YHJHWDEOHSURWHLQDQG¿EHUDGROHVFHQWVLQWKHKLJKHVW stratum received 10 points for that macronutrient; adolescents in Anthropometric measurements Weight was measured, while participants were minimally the next stratum received 9 points, and so on down to adolescents clothed without shoes, using digital scales (Seca 707, Seca Corp., in the lowest stratum who received 0 points. For carbohydrates, Hanover, MD; range 0.1–150 kg) and recorded to the nearest 100 UH¿QHGJUDLQVDQG*/WKHRUGHURIWKHVWUDWDZDVUHYHUVHGWKRVH g. Standing height was measured without shoes, using a tape to with the lowest carbohydrate intake received 10 points and those 418 Archives of Iranian Medicine, Volume 17, Number 6, June 2014

*(VODPLDQ30LUPLUDQ*$VJKDULHWDO Table 1. Criteria for determining low carbohydrate diet score. Score

CHO (% energy)

Fiber (g/1000 kcal)

MUFA (% energy)

n3/n6 PUFA ratio

5H¿QHGJUDLQV CHO (% energy)

0 • ” ” ” • 1 62.62–65.33 8.15–9.50 7.98–8.89 0.07–0.07 29.56–34.29 2 60.76–62.61 9.51–10.67 8.99–9.56 0.08–0.07 26.48–29.55 3 59.22–60.75 10.68–11.77 9.57–10.21 0.08–0.08 23.77–26.47 4 57.57–59.21 11.78–12.85 10.22–10.94 0.09–0.08 21.59–23.76 5 56.38–57.65 12.86–13.88 10.95–11.53 0.09–0.09 19.52–21.58 6 54.82–56.37 13.89–15.19 11.54–12.04 0.10–0.09 17.39–19.51 7 53.26–54.81 15.20–16.87 12.05–12.65 0.10–0.10 15.33–17.38 8 50.81–53.25 16.88–18.81 12.66–13.41 0.11–0.11 13.12–15.32 9 46.65–50.80 18.82–21.68 13.42–14.91 0.12–0.13 10.23–13.11 10 ” • • • ” CHO = carbohydrate; MUFA = monounsaturated fatty acid; PUFA = polyunsaturated fatty acid

Vegetable protein (% energy)

Glycemic load

” 3.93–4.51 4.52–4.94 4.95–5.22 5.23–5.51 5.52–5.76 5.77–6.08 6.09–6.42 6.43–7.02 7.03–7.94 •

• 92.66–114.43 79.98–92.65 71.16–79.88 65.69–71.15 57.78–65.68 51.75–57.77 45.93–51.74 38.31–45.92 31.00–38.30 ”

viation (SD), after testing for normal distribution for quantitative variables and percentages for qualitative variables. Student’s t test DQGȤ2 test were used for comparison of continuous and categorical variables between genders, respectively. Normality of all variables was checked by Kolmogorov-Smirnov test. The participants were FDWHJRUL]HGDFFRUGLQJWRTXDUWLOHVRIFDUERK\GUDWHVFRUH ” ±±DQG• 7RWHVWOLQHDUWUHQGDFURVVTXDUWLOHVRI LCD, the median of the respective quartile was assigned as the exposure and the intake of food items or food groups as the continuous dependent variable. Logistic binary regression was used to assess the association of LCD score and incidence of MetS and 'H¿QLWLRQRIWKHFRPSRQHQWVRIWKHPHWDEROLFV\QGURPH its components. Two models were constructed: Model 1 was ad%HFDXVH QR XQLYHUVDOO\ DFFHSWHG GH¿QLWLRQ H[LVWV IRU 0HW6 LQ justed for age and gender, and model 2 was additionally adjusted FKLOGUHQWKHGH¿QLWLRQSURSRVHGE\&RRNet al was used.34 It de- for physical activity and energy intake. Age and physical activity ¿QHV0HW6DVWKUHHRUPRUHRIWKHIROORZLQJ)DVWLQJ7*V• score were entered in all models as continuous variables. PJ»G/+'/FKROHVWHUROPJ»G/:&•th percentile for age and sex, according to national reference curves35; systolic blood Results SUHVVXUH 6%3 DQG»RUGLDVWROLFEORRGSUHVVXUH '%3 •th percentile for sex, age and height, from the National Heart, Lung, and The study population was composed of 45.4% boys and 54.6% Blood Institute’s recommended cut-off points36, and fasting blood girls with mean ages of 13.4 ± 3.6 and 14.3 ± 3.7 years, respecJOXFRVH•PJ»G/DFFRUGLQJWRWKHUHFHQWUHFRPPHQGDWLRQVRI tively. In this population, over an average follow-up of three years, the American Diabetes Association.37 there were 7.5%, 11%, 15%, 12.3%, 18.3%, and 6.9% documentAfter about 3 years of follow up, the following criteria were ed cases of MetS, high blood pressure, high triglycerides, high XVHG IRU GH¿QLQJ 0HW6 LQ DGXOWV DFFRUGLQJ WR WKH MRLQW LQWHULP FBS, abdominal obesity, and low HDL-C, respectively. Particistatement (JIS)38ZKLFKUHTXLUHVWKHSUHVHQFHRIDQ\WKUHHRI¿YH pants with higher adherence of LCD were more likely to be girls, ULVNIDFWRUVRIWKHIROORZLQJ L $EGRPLQDOREHVLW\DV:&• and have lower WC, FPG, SBP, and DBP (P < 0.05, Table 2). FP IRU ZRPHQ DQG • FP IRU PHQ DFFRUGLQJ SRSXODWLRQ DQG Baseline dietary intakes of the participants across quartiles of FRXQWU\VSHFL¿FFXWRIISRLQWVIRU,UDQLDQV39 LL )3*•PJ the low carbohydrate diet score are shown in Table 3. The daily G/RUPHGLFDOWUHDWPHQW LLL )DVWLQJ7*V•PJG/RUPHGL- intakes of total protein, animal protein, total fat, SFA, MUFA, caltreatment; (iv) Fasting HDL-C