Dietary amino acids and anthropometric indices: Tehran Lipid and Glucose Study.

Objective: Recent studies investigated the role of amino acids (AAs) in weight management. We aimed to determine the association between AAs and three-year change of anthropometric indices and incident obesity. Materials and methods: Height, weight, hip, and waist circumference (WC) were collected at baseline and follow up. Three-year changes in anthropometric indices and obesity incident according to body mass index (BMI) (overweight & obesity) and WC cutoffs (obesity-WC) were ascertained. Dietary intakes of AAs were collected at baseline, using a food frequency questionnaire. Data analyses were conducted on 4976 adult participants and two subsamples, including 1,570 and 2,918 subjects, for assessing the AAs relationship with 3-year changes on anthropometric indices and obesity incident. Results: Lysine and aspartic acid were positively associated with higher weight change, whereas acidic AAs, cysteine, and glutamic acid showed a negative correlation with weight change. Furthermore, a weak positive correlation was shown for alkaline AAs, lysine, and valine with WC; however, acidic AAs, tryptophan, cysteine, and glutamic acid were negatively associated with WC. Aromatic and acidic AAs also demonstrated a weak negative relation with changes in BAI. Phenylalanine and Aromatic AAs showed a negative association with overweight &obesity incidence adjusting for potential confounders. Each quartile increases the dietary lysine, arginine, alanine, methionine, aspartic acid, and alkaline AAs related to a greater risk of obesity-WC, while tryptophan, glutamic acid, proline, and acidic AAs associated with lower obesity-WC risk. Conclusion: Our results suggested that certain dietary AAs may potentially change anthropometric indices and risk of obesity incident.

Dietary amino acids and anthropometric indices: Tehran Lipid and Glucose Study

ABSTRACT Objective: Recent studies investigated the role of amino acids (AAs) in weight management. We aimed to determine the association between AAs and three-year change of anthropometric indices and incident obesity. Materials and methods: Height, weight, hip, and waist circumference (WC) were collected at baseline and follow up. Three-year changes in anthropometric indices and obesity incident according to body mass index (BMI) (overweight & obesity) and WC cutoffs (obesity-WC) were ascertained. Dietary intakes of AAs were collected at baseline, using a food frequency questionnaire. Data analyses were conducted on 4976 adult participants and two subsamples, including 1,570 and 2,918 subjects, for assessing the AAs relationship with 3-year changes on anthropometric indices and obesity incident. Results: Lysine and aspartic acid were positively associated with higher weight change, whereas acidic AAs, cysteine, and glutamic acid showed a negative correlation with weight change. Furthermore, a weak positive correlation was shown for alkaline AAs, lysine, and valine with WC; however, acidic AAs, tryptophan, cysteine, and glutamic acid were negatively associated with WC. Aromatic and acidic AAs also demonstrated a weak negative relation with changes in BAI. Phenylalanine and Aromatic AAs showed a negative association with overweight &obesity incidence adjusting for potential confounders. Each quartile increases the dietary lysine, arginine, alanine, methionine, aspartic acid, and alkaline AAs related to a greater risk of obesity-WC, while tryptophan, glutamic acid, proline, and acidic AAs associated with lower obesity-WC risk. Conclusion: Our results suggested that certain dietary AAs may potentially change anthropometric indices and risk of obesity incident.

Modified Healthy Eating Index and Incidence of Metabolic Syndrome in Children and Adolescents: Tehran Lipid and Glucose Study.

OBJECTIVE: To assess the relationship between modified healthy eating index (mHEI) with the development of metabolic syndrome (MetS) among children and adolescents. STUDY DESIGN: Dietary data were collected using a food frequency questionnaire among 424 healthy subjects, aged 6-18 years. The components of mHEI were grains, vegetables and fruits, dairy, red to white meat ratio, butter, sweet snacks, sweetened beverages, salty snacks, and fast food. Multivariable logistic regression models were used to estimate the incidence of MetS after 3.6 years of follow-up in each quartile of the mHEI score, adjusted for baseline age, sex, total energy intake, physical activity, and body mass index. RESULTS: The mean ± SD age and mHEI scores of participants were 13.6 ± 3.7 years and 55.9 ± 10.0, respectively, at baseline. MetS developed in 11% of the participants at the end of follow-up. After adjustment for confounders, the occurrences of MetS decreased in the highest quartile compared with the lowest quartile of the mHEI score (OR = 0.35, 95% CI 0.13-0.98, P for trend = .025). In addition, higher scores of mHEI components including fruits, salty snacks, and fast food were associated with lower risk of MetS. CONCLUSIONS: Higher scores of mHEI as an indicator of diet quality may hinder the development of MetS among children and adolescents.

Dietary Approaches to Stop Hypertension (DASH) Dietary Pattern Is Associated with Reduced Incidence of Metabolic Syndrome in Children and Adolescents.

OBJECTIVE: To assess the association of adherence to Dietary Approaches to Stop Hypertension (DASH)-style diet with development of metabolic syndrome (MetS) in children and adolescents. STUDY DESIGN: Dietary data were collected using a valid and reliable food frequency questionnaire among 425 healthy subjects, aged 6-18 years. MetS was defined as the presence of at least 3 of the following according to the Cook criteria: waist circumference ≥90th percentile for sex and age according to national reference curves; systolic blood pressure and/or diastolic blood pressure ≥90th percentile for sex, age, and height; fasting plasma glucose ≥100 mg/dL; triglycerides ≥110 mg/dL; and high-density lipoprotein cholesterol <40 mg/dL. The DASH-style diet score was assessed based on 8 components: high intakes of whole grain, vegetables, fruits, nuts, legumes; moderate amounts of low-fat dairy products; and low intake of red and processed meat, sweetened beverages, and sodium. Multivariable logistic regression models were used to estimate the OR and 95% CI after 3.6 years of follow-up for developing MetS in each quartile of DASH score after adjustment for baseline confounders. RESULTS: Mean ± SD for age and DASH score were 13.6 ± 3.7 years and 24.1 ± 4.3, respectively, at baseline. The OR (95% CI) of developing MetS in the highest, compared with the lowest, quartile of DASH score was 0.36 (0.14-0.94) with a linear decreasing trend (P for trend = .023). Also, incidence of hypertension, high fasting plasma glucose, and abdominal obesity decreased with higher adherence to DASH diet (P < .05 for all). CONCLUSIONS: Our findings indicate the relationship of adherence to DASH-style diet with MetS and some of its components in both children and adolescents.

Adolescence metabolic syndrome or adiposity and early adult metabolic syndrome.

OBJECTIVE: To investigate the predictive role of adolescent metabolic syndrome (MetS) in development of early adult MetS, independent of adult body mass index (BMI). STUDY DESIGN: 1424 adolescents (639 boys), participants of the Tehran Lipid and Glucose Study, followed for 10.4 years, were analyzed and logistic regression models were developed. Using the areas under the receiver operating characteristic curve, the discriminatory ability of adolescent MetS and overweight or obesity was evaluated. Net reclassification improvement was calculated to determine the accuracy of classification by adolescent MetS in place of overweight or obesity. RESULTS: The mean ± SD of age and BMI were 14.6 ± 2.2 years and 20.3 ± 4.2 kg/m(2), respectively. The prevalence of MetS was 13.3% and 14.6% at baseline and after follow-up, respectively. The risk of developing early adult MetS among subjects who were overweight or obese in adolescence but nonobese as adults (OR: 1.65) was lower than the risk among subjects who were obese as adults but nonobese as adolescents (OR: 8.45). After adjustment for adult BMI, adolescent MetS and overweight or obesity did not show any association with the risk of adult MetS. Area under the receiver operating characteristic curve was higher for obesity (0.619) than MetS (0.589) and the net reclassification improvement value for MetS was 1.5% (P = .398). CONCLUSION: Adolescent MetS or adiposity did not predict early adult MetS independent of adult BMI. The addition of adolescent MetS to obesity does not improve the predictive power for early adult MetS.