The association between dietary glycemic index and disease severity among the women with episodic migraine.

PURPOSE: To our knowledge, no studies have evaluated the association between dietary glycemic index (GI) and glycemic load (GL) with migraine-related clinical symptoms. METHODS: This cross-sectional study was conducted among 266 women with episodic migraine. The migraine disability assessment (MIDAS) was used to evaluate migraine-related disability in the recent three months. Visual analogue scales (VAS) were also employed to examine migraine-related pains. Glycemic index and glycemic load indices were calculated using the nutritional information obtained from the food frequency questionnaire. RESULTS: The study participants had a mean age of 34.32 ± 7.86 years. It was observed that individuals in the quartile 4 of GI and GL reported significantly higher consumption of calories, carbohydrates, proteins, and fats (P < 0.05). In the unadjusted models, those in the quartile 4 of GI and GL had significantly increased odds of experiencing severe pain (based on VAS score) (OR = 2.09, 95% CI = 1.37-2.70, P < 0.001 for dietary GI, and OR = 1.75, 95% CI = 1.16-2.79, P = 0.005 for dietary GL). Additionally, compared to participants in the quartile 1 of GI and GL, those in the quartile 4 of GI and GL were more likely to suffer from severe disability (P < 0.05). CONCLUSION: We found a significant positive correlation between the consumption of foods with higher GI and GL and the clinical conditions related to migraine disease. However, due to the cross-sectional nature of the study, it is not possible to establish a cause-and-effect relationship for the observed results.

The association between glycemic index, glycemic load and total carbohydrate intake and risk of premature coronary artery disease: Iran Premature Coronary Artery Disease Study (IPAD) - A Case-Control Study.

BACKGROUND AND AIMS: The association between glycemic index (GI), glycemic load (GL), total carbohydrate intake, and risk of cardiovascular diseases has been controversial. Premature coronary artery disease (PCAD) is characterized by the age of onset lower than 55 and 65 respectively in men and women. The aim of the current study is to investigate the relationship between GI, GL and carbohydrate levels and the risk of PCAD in Iran. METHODS AND RESULTS: In total, 419 healthy people and 553 patients struggling with PCAD have participated in this case-control study. Dietary GI and GL were calculated using a validated food frequency questionnaire at the baseline. Crude and multivariable logistic regression were used to assess the relationship between GI, GL, and total carbohydrate intake and risk of PCAD. The mean age of participants was 51.13 ± 6.90 and 46 % of them were women. A significant direct relationship was observed between higher carbohydrate intake (OR: 1.74, 95%CI: 1.27-2.38) and GL levels (OR: 1.56, 95 % CI:1.14-2.14) and risk of PCAD. These associations were not significant after adjusting for potential variables. No significant association has been observed between GI and odds of PCAD even after controlling for all covariates. CONCLUSION: We found no significant association between GI, GL, and total carbohydrate intake and risk of premature coronary heart disease. Further observational and clinical trials are required to assess this relationship.

Association of dietary glycemic index and glycemic load with the risk of gestational diabetes mellitus: a systematic review and dose-response meta-analysis.

OBJECTIVE: To comprehensively assess the dose-response association between dietary glycemic index (GI) and glycemic load (GL) and gestational diabetes mellitus (GDM) risk. METHODS: PubMed, Embase, Cochrane Library, Web of Science, CNKI, WanFang, and VIP databases were searched up to May 29, 2024. Studies with at least three exposure categories were included. Dose-response analysis was also performed when covariates were adjusted in the included studies. RESULTS: Thirteen studies involving 39,720 pregnant women were included. A linear relationship was found between GI and the risk of GDM (χ2 = 4.77, Pnon-linearity = .0923). However, association was not significant (χ2 = 0.06, p = .8000). For every unit increase in GI (range 0-30), GDM risk increased by 0.29%. After adjusting for covariates, the linear relationship persisted (χ2 = 4.95, Pnon-linearity = .084) with no significant association (χ2 = 0.08, p = .7775). For GL, a linear relationship was also found (χ2 = 4.17, Pnon-linearity =.1245), but GL was not significantly associated with GDM risk (χ2 = 2.63, p = .1049). The risk of GDM increased by 0.63% per unit increase in GL. After covariate adjustment, a significant association was observed (χ2 = 6.28, p = .0122). CONCLUSION: No significant association between GI and GDM risk was found. After adjusting for covariates, GL shows a significant association with GDM risk. Our findings emphasize the importance of considering dietary GL in managing the risk of GDM. Future research should continue to explore these relationships with standardized diagnostic criteria and robust adjustment for potential confounders.

Dietary glycemic index and glycemic load predict longitudinal change in glycemic and cardio-metabolic biomarkers among old diabetic adults living in a resource-poor country.

This study aims to investigate longitudinal associations between the dietary glycemic index (GI) and glycemic load (GL) and changes in glycemic and cardio-metabolic outcomes. A 28-month retrospective cohort study included 110 Vietnamese diabetic patients, collecting their dietary GI and GL values along with blood biochemical data from baseline 24-h dietary recall and medical records. Latent class growth modelling identified three distinct HbA1c trajectories during the follow-up period, with 51% of patients achieving good glycemic control. The adjusted linear mixed-effect model showed that 1 unit increase in logarithms in dietary GL was associated with a 0.14% increase in the log-HbA1c. Among poorly controlled diabetic patients, baseline GL values were positively correlated with increases in HbA1c; GI showed effects on changes in fasting plasma glucose and the triglyceride-glucose (TyG) index. No significant association was observed in patients with good glycemic control.

Evaluation of the effect of obesity, dietary glycemic index and metabolic profiles on the cardiovascular risk in children with classical phenylketonuria.

OBJECTIVES: To compare the glycemic index(GI),obesity,echocardiographic,and arterial stiffness measurements with the healthy control group to evaluate the cardiovascular risk of pediatric classical phenylketonuria(PKU). METHODS: The study was a prospective observational,involving 104 pediatric volunteers between 2019 and 2020.Two groups were formed:the PKU patient group and the healthy control group.These two groups were further divided into three subgroups:obese,overweight,and normal weight.The patients' anthropometric measurements,body fat analysis,biochemical analysis, GI and glycemic load(GL),arterial stiffness measurements,and echocardiographic findings were recorded. RESULTS: The PKU patient group's glucose,total cholesterol,LDL,and HDL values were significantly lower than the healthy control group(p = 0.010 for glucose and p = 0.001 for total cholesterol,LDL and HDL).Triglyceride levels were higher in the PKU patient group than in the healthy controls(109.6 vs. 76.7 mg/dl,p = 0.001). GI and GL were significantly lower in the PKU patient group than in the healthy control group(GI 453 vs. 392.9,p = 0.017 and GL 101.1 vs. 85.5,p = 0.036).Left ventricular mass(LVM)-z-score and LVM index were significantly higher in the PKU group than in the healthy control group(LVM z-score 0.9 vs. 0.5,p = 0.014 and LVM index 38.9 vs. 32.7 g/m2.7,p = 0.001). A moderately statistically significant positive correlation was found between the mean phenylalanine(phe) value and pulse wave velocity(PWV) among the PKU patient groups(R: 0.477,p < 0.001).A moderately statistically significant positive correlation was also found between waist circumference and PWV in the PKU patient group(R:0.541, p < 0.001). CONCLUSIONS: Our study found that close follow-up of phe levels and PWV is more critical than obesity, GI, and GL in the cardiovascular evaluation of classical PKU patients.A large number of multicenter pediatric studies are needed in this area.

Glycemic Load, Dietary Fiber, Added Sugar, and Spontaneous Abortion in Two Preconception Cohorts.

BACKGROUND: Spontaneous abortion (SAB)-pregnancy loss before the 20th week of gestation-has adverse psychological and physical sequelae. Some medical conditions known to affect insulin sensitivity, including polycystic ovary syndrome and diabetes, can affect the risk of SAB. No prior studies have examined glycemic load and incidence of SAB in populations without conditions known to affect insulin sensitivity. OBJECTIVES: We prospectively evaluated the association between preconception glycemic load and intake of carbohydrates, dietary fiber, and added sugar and risk of SAB. METHODS: During 2013-2020, we recruited pregnancy planners from Denmark (SnartForaeldre.dk; SF) and the United States and Canada (Pregnancy Study Online; PRESTO). Participants completed a baseline questionnaire and a cohort-specific FFQ evaluated for validity. We estimated preconception glycemic load and intake of carbohydrates, dietary fiber, and added sugar from individual foods and mixed recipes. We included 2238 SF and 4246 PRESTO participants who reported a pregnancy during the course of the study. SAB data were derived from questionnaires and population registries. We used Cox proportional hazards regression to estimate HRs and 95% CIs. RESULTS: In the study population, 15% of SF participants and 22% of PRESTO participants experienced SAB. Across both cohorts, there was no appreciable association between glycemic load, carbohydrate quality, dietary fiber, or added sugar intake and SAB. Compared with daily mean glycemic load <110, the HR for women with daily mean glycemic load ≥130 was 0.76 (95% CI: 0.52, 1.10) in SF and 1.01 (95% CI: 0.86, 1.19) in PRESTO. CONCLUSIONS: Diets with high glycemic load, carbohydrates, and added sugars were not consistently associated with risk of SAB in parallel analyses of 2 preconception cohort studies of women in North America and Denmark.

Carbohydrate quality indices and colorectal cancer risk: a case-control study.

BACKGROUND: Colorectal cancer (CRC) is the fourth and third most common cancer in Iran and the world, respectively. Carbohydrates can lead to the proliferation of cancer cells, including CRC. The current study aimed to investigate the association between glycemic load (GL), insulin load (IL), glycemic index (GI), insulin index (II), low-carbohydrate diet score (LCDS), and carbohydrate quality index (CQI) with CRC odds. METHODS: The present case-control study was performed on 71 CRC cases and 142 controls in the Hospital Cancer Organization and three general hospitals in Tehran, Iran. We calculated the dietary GI, GL, IL, II, CQI, and LCDS by a validated food frequency questionnaire. RESULTS: The results indicated that people who were in the highest tertile of the GI had higher odds of CRC compared to the lower tertile (in the adjusted model: odds ratio (OR) = 3.89; 95% confidence interval (CI): 1.71-8.84). On the contrary, people who were in the highest tertile of the CQI and LCDS had significantly lower odds of CRC compared to the lower tertile (in the adjusted model: tertile (T) 2-OR = 0.24; 95% CI: 0.11-0.53 and T3-OR = 0.15; 95% CI: 0.06-0.39 for CQI and T2-OR = 0.33; 95% CI: 0.13-0.79 and T3-OR = 0.28; 95% CI: 0.10-0.82 for LCDS). Also, IL was positively associated with the odds of CRC after adjusting for confounding factors (T2-OR = 2.46; CI: 1.08-5.61 and T3- OR = 2.80; 95% CI: 1.07-7.31). Regarding the GL, only individuals who were in the second tertile had significantly higher odds of CRC compared to the first tertile (OR = 2.42; CI: 1.07-5.47). CONCLUSION: According to the findings, it is recommended to use a diet with high-quality carbohydrates and low GI and GL to minimize the odds of developing CRC. People should also be encouraged to have a balanced carbohydrate intake.

Are Unhealthy Diets Contributing to the Rapid Rise of Type 2 Diabetes in India?

The prevalence of diabetes is increasing at an alarming rate globally, particularly in India. In the urban areas, the prevalence of diabetes among adults aged ≥20 y, which was around 2% in the early 1970's, has increased by >20% in 50 y. The rapid nutrition transition due to high economic growth rates increased urbanization and globalization has resulted in higher intakes of processed refined grain staples, mainly white rice in Southern and Eastern India and refined wheat in Northern and Western India. This coupled with inadequate quantity and quality of protein; unhealthy fats; lower intake of vegetables, fruits, and fiber; and a sedentary lifestyle are the main drivers of the diabetes epidemic in India. This review attempts to discuss both the quality and quantity of Indian diets with specific reference to macronutrients. This review also outlines some of the strategies that can be employed to slow down the diabetes epidemic in this region. We believe that the lessons learned from India would be applicable to other developing nations as well, particularly to the South East Asian region.

Effects of a low glycemic index or low glycemic load diet on pregnant women at high risk of gestational diabetes: A meta-analysis of randomized controlled trials.

AIMS: To evaluate the effect of low glycemic index or low glycemic load diets on maternal and neonatal outcomes at high risk of gestational diabetes mellitus (GDM). DATA SYNTHESIS: Several databases (PubMed, Cochrane Library, Web of Science, Embase, OVID, Clinical Trials. gov, China National Knowledge Infrastructure, China Biomedical Database, and Wanfang Database) were searched from January 1990 to January 2022 (updated to November 2022). Randomized controlled trials of low glycemic index diets interventions for women at high risk of GDM were included. From 2131 articles initially were screened, after eliminating duplicates, 1749 titles and abstracts were analyzed. 71 documents that met the inclusion criteria were selected and 3 documents were obtained through searching the reference lists. After reading the full text, 10 studies were retained. Two authors evaluated the studies, extracted data and conducted quality assessment independently. A total of 10 studies with 2304 patients met the inclusion criteria. Compared with the control group, a low glycemic index diet could control the range of weight gain (WMD -1.01, 95% CI -1.41 to -0.61), decrease the incidence of excessive weight gain (OR 0.69, 95% CI 0.54-0.87), lessen the incidence of large-for-gestational-age infants (OR 0.32, 95% CI 0.16-0.62) and reduce the incidence of preterm infants (OR 0.45, 95% CI 0.29-0.71). CONCLUSION: A low glycemic index or low glycemic load diet could control maternal weight gain, reduce the incidence of excessive weight gain, and decrease the incidence of large-for-gestational-age infants and preterm infants in group with high risk of GDM. PROSPERO: CRD42022322697.

How do carbohydrate quality indices influence on bone mass density in postmenopausal women? A case-control study.

BACKGROUND: Carbohydrates are the primary energy source in Asian countries, including Iran. An emerging method can be used to measure the quality of carbohydrates, including the carbohydrate quality index (CQI), which includes a variety of components. Low-carbohydrate diet score (LCDS) has been proposed as a new method of scoring micronutrient intake that could provide a reasonable explanation for the link between diet and the risk of chronic diseases. OBJECTIVE: This study aimed to investigate the relationship between CQI, LCDS, glycemic index (GI), glycemic load (GL), insulin load (IL), and insulin index (II) with bone mass density (BMD) in postmenopausal women. METHOD: In this case-control study, 131 postmenopausal women with osteoporosis/osteopenia and 131 healthy postmenopausal women aged 45-65 participated. The dual-energy X-ray absorptiometry (DEXA) method measured the BMD of the lumbar vertebrae and femoral neck. A validated semi-quantitative food frequency questionnaire was used to assess dietary intake. Logistic regression were used to evaluate the relation between GI, GL, II, IL, CQI, and LCDS with BMD. RESULTS: Diets with higher GI increased the risk of osteopenia and osteoporosis, but LCDS and CQI decreased the risk of osteopenia and osteoporosis. CONCLUSION: These findings suggest that a higher intake of fruits and vegetables and receiving various dietary vitamins, minerals, and antioxidant compounds may be a useful way to prevent osteopenia in Iranian women.

[Association of dietary glycemic load during pregnancy with gestational weight gain and fetal physical development].

OBJECTIVE: To investigate the situation of women's dietary glycemic load during pregnancy and explore the correlations between dietary glycemic index(GI) and gestational weight gain and fetal physical development. METHODS: The study was conducted in women in the third trimester of pregnancy and their new-born babies. The gestational dietary information was collected through a 3-day 24-hour dietary review. The general demographic information, diet and physical exercise, and weight were collected in questionnaire investigations, and the glycemic load during pregnancy were calculated. Participant were dived into low-glycemic-load group, middle-glycemic-load group and high-glycemic-load group according to the glycemic load. Gestational weigh gain, birth weight and birth length were measured. Multiple linear regression were used to analyze the relationship between glycemic load during pregnancy and gestational weight gain and fetal growth. RESULTS: The mean gestational glycemic load was 149.21±46.33. Women in high-glycemic-load group had higher intake of grain, potato, bacteria and algae, fruit, poultry and dairy but lower intake of aquatic product(P<0.05). The mean gestational weight gain was(15.03±4.35)kg. The mean fetal weight and birth length was(3229.18±375.09)g and(49.60±1.48)cm. Women in high-glycemic-load group had higher gestational weight gain(P<0.05). Multiple linear regression indicated that dietary glycemic load during pregnancy was postively correlated with gestational weight gain and birth length(ß_1=0.011, ß=0.003, P<0.05). CONCLUSION: The higher dietary glycemic load during pregnancy is, the higher gestational weight gain and birth length will be.

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 recruitment 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 studies with longitudinal design is suggested to confirm these results.

Dietary glycemic index, glycemic load, and chronic disease: an umbrella review of meta-analyses of prospective cohort studies.

We aimed to present a comprehensive review of the association of dietary glycemic index (GI) and load (GL) with the risk of chronic disease. Published meta-analyses of prospective observational studies evaluating the association of dietary GI and GL with risk of chronic disease were identified by a search in PubMed and Scopus to November, 2020. Summary relative risks (SRRs) were recalculated using random-effects models. The certainty of evidence was rated by the GRADE approach. Eighteen meta-analyses of prospective cohort studies, reporting 19 SRRs for dietary GI and 17 SRRs for dietary GL were identified. There was a positive association between dietary GI and the risk of type 2 diabetes, coronary heart disease, and colorectal, breast, and bladder cancers, as well as between dietary GL and the risk of coronary heart disease, type 2 diabetes, and stroke. With regard to cancers at other sites, there was no significant association. The certainty of evidence ranged from very low to low. Although by GRADE classification no associations were rated stronger than low, they were classified as one grade higher when the NutriGrade system was used. Further research is needed to add evidence for the relation of dietary GI and GL with cancer risk.

Dietary glycemic index, glycemic load and cancer risk: a meta-analysis of prospective cohort studies.

PURPOSE: There is considerable inconsistency in results regarding the association of dietary glycemic index (GI) and glycemic load (GL) with cancer risk. We therefore conducted this systematic review and dose-response meta-analysis of prospective cohort studies to evaluate the relationship between dietary GI/GL and cancer risk. METHODS: We searched PubMed and Web of Science for prospective cohort studies of dietary GI/GL in relation to risks of all types of cancer up to 31 March 2021. We used a random-effect model to calculate summary relative risks (RR) and 95% confidence intervals (CI). The certainty of evidence was assessed by the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach. This study was registered at PROSPERO (CRD42020215338). RESULTS: Overall, 55 cohorts were included in the meta-analysis. We assessed the relationship between dietary GI or GL and risks of 23 cancer types, including hormone-related cancers, cancers from digestive system, respiratory system, urinary system and other cancer sites. High GI diet increased overall risk of cancer with low certainty of evidence (highest vs lowest categories, n = 3, RR 1.04, 95% CI 1.01-1.07). For site-specific cancers, high GI diet increased risks of lung cancer (highest vs lowest categories, n = 5, RR 1.08, 95% CI 1.01-1.18) and breast cancer (highest vs lowest categories, n = 14, RR 1.05, 95% CI 1.01-1.09), especially for postmenopausal breast cancer (highest vs lowest categories, n = 10, RR 1.06, 95% CI 1.00-1.13), all with low certainty of evidence. Additionally, dietary GI was positively related to risk of bladder cancer with low certainty of evidence (highest vs lowest categories, n = 3, RR 1.23, 95% CI 1.09-1.40), as well as negatively related to ovarian cancer risk with very low certainty of evidence (highest vs lowest categories, n = 4, RR 0.83, 95% CI 0.69-1.00) and lymphoma risk with low certainty of evidence (highest vs lowest categories, n = 2, RR 0.84, 95% CI 0.72-0.98). Besides, we found an inverse association of dietary GL with lung cancer risk with low certainty of evidence (highest vs lowest categories, n = 5, RR 0.87, 95% CI 0.80-0.94). CONCLUSION: High dietary GI increased overall cancer risk with low certainty of evidence. For site-specific cancers, high GI diet increased the risks of breast cancer with low certainty of evidence and lung cancer with low certainty of evidence. Dietary GL was inversely associated with lung cancer risk with low certainty of evidence.

Associations of dietary glycemic index and load during pregnancy with blood pressure, placental hemodynamic parameters and the risk of gestational hypertensive disorders.

PURPOSE: The aim of this study was to examine the associations of dietary glycemic index and load with gestational blood pressure, placental hemodynamic parameters and the risk of gestational hypertensive disorders. METHODS: In a population-based cohort among 3378 pregnant Dutch women, dietary glycemic index and load were assessed from food frequency questionnaires at median 13.4 (95% range 9.9-22.9) weeks gestation. Blood pressure was measured in early-, mid- and late-pregnancy. Placental hemodynamic parameters were measured in mid- and late-pregnancy by ultrasound. Data on gestational hypertensive disorders was acquired from medical records. RESULTS: Mean dietary glycemic index (SD) was 58 (3) and mean dietary glycemic load (SD) was 155 (47). Dietary glycemic index was not associated with blood pressure, placental hemodynamic parameters and the risk of gestational hypertensive disorders. Higher dietary glycemic load SDS was associated with a higher diastolic blood pressure in early-pregnancy, remaining after adjustment for socio-demographic and lifestyle factors ((0.98 (95% CI 0.35-1.61) mmHg per SDS increase in glycemic load). No other associations of glycemic load with blood pressure or placental hemodynamic parameters and the risk of gestational hypertensive disorders were present. No significant associations of dietary glycemic index and load quartiles with longitudinal blood pressure patterns from early to late-pregnancy were present. CONCLUSION: Within this low-risk pregnant population, we did not find consistent associations of dietary glycemic index and load with blood pressure, placental hemodynamic parameters and the risk of gestational hypertensive disorders. Further studies need to assess whether the effects on gestational hemodynamic adaptations are more pronounced among high-risk women with an impaired glucose metabolism.

The interaction between glycemic index, glycemic load, and the genetic variant ADIPOQ T45G (rs2241766) in the risk of colorectal cancer: a case-control study in a Korean population.

PURPOSE: The glycemic index (GI), glycemic load (GL), and adiponectin level contribute to glycemic response and insulin sensitivity in the body. Studies have shown that tumor development is related to glycemic disorders; however, the results are contradictory. We aimed to investigate the association of GI and GL with colorectal cancer (CRC) risk in a Korean population and their possible interactions with the genetic variant ADIPOQ T45G. METHODS AND RESULTS: A case-control study including 2096 participants with 695 CRC cases was conducted. The results showed that diets with high GI or GL were significantly associated with an increased risk of CRC [odds ratio (OR) = 5.44, 95% confidence interval (CI) 3.85-7.68; OR = 4.43, 95% CI 3.18-6.15, respectively; all p-trends < 0.001]. Moreover, even with a low-GI and low-GL diet, G/G genotype carriers may have 2.93-fold and 3.77-fold higher risk of rectal cancer compared to carriers of other genotypes (T/T + T/G), (OR = 2.93, 95% CI 1.01-8.59, p-interaction = 0.011 for GI; OR = 3.77, 95% CI 1.46-9.77, p-interaction = 0.025 for GL). CONCLUSIONS: Overall, our study suggests positive associations of GI and GL with CRC risk. Moreover, the associations of GI and GL with rectal cancer risk could be modified by ADIPOQ T45G in a Korean population. Further studies with larger sample sizes are needed to confirm our findings.

Dietary glycemic index and glycemic load mediate the effect of CARTPT rs2239670 gene polymorphism on metabolic syndrome and metabolic risk factors among adults with obesity.

INTRODUCTION: The importance of genetic and dietary factors in occurrence and progression of chronic diseases such as metabolic syndrome (MetS) has been established. However, complex interrelationships, including direct and indirect effects of these variables are yet to be clarified. So, our aim was to investigate the mediating role of glycemic indices in the relationship between CARTPT rs2239670 polymorphism, socio-demographic and psychological factors and metabolic risk factors and the presence of MetS in adults with obesity. METHODS: In a cross-sectional study of 288 apparently healthy adults with obesity aged 20-50 years, dietary glycemic index (GI) and glycemic load (GL) were measured using a validated semi-quantitative food frequency questionnaire (FFQ). Biochemical parameters, blood pressure and anthropometric indicators were assayed by standard methods. Genotyping was carried out by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) technique. Structural equation modeling (SEM) was used in the statistical analysis. RESULTS: CARTPT rs2239670 had a positive direct effect on MetS (B = 0.037 ± 0.022; P = 0.043) and, on the other hand, this variant was found to be indirectly associated with MetS presence through mediation of GI (B = 0.039 ± 0.017; P = 0.009). CARTPT was a significant predictor of both dietary GI and GL (B = 1.647 ± 0.080 and B = 3.339 ± 0.242, respectively). Additionally, glycemic indicators appeared to mediate the association of age and gender with LDL-C (B = 0.917 ± 0.332; P = 0.006) and HDL (B = 1.047 ± 0.484; P = 0.031), respectively. GI showed a positive relationship with LDL-C (P = 0.024) in men and similar relationships were found between GL and LDL-C (P = 0.050) and cholesterol (P = 0.022) levels in women. CONCLUSION: The SEM findings suggest a hypothesis of the mediating effect of glycemic indices in the relationship between genetic susceptibility to obesity and MetS presence. Our findings need to be confirmed with large prospective studies.

Interaction of MC4R rs17782313 variants and dietary carbohydrate quantity and quality on basal metabolic rate and general and central obesity in overweight/obese women: a cross-sectional study.

BACKGROUND: Recent studies have shown that dietary carbohydrate quantity and quality as well as genetic variants may contribute to determining the metabolic rate and general and central obesity. This study aimed to examine interactions between melanocortin 4 receptor gene (MC4R) rs17782313 and dietary carbohydrate intake, glycemic index (GI), and glycemic load (GL) on body mass index (BMI), waist circumferences (WC), basal metabolic rate (BMR), and BMR/kg in overweight/obese women. METHODS: A total of 282 Iranian women (BMI ≥ 25) aged 18-56 years were enrolled in this cross-sectional study. All participants were assessed for blood parameters, body composition, BMR, and dietary intake. Dietary carbohydrate intake, GI, and GL were determined using a valid, reliable 147-item food frequency questionnaire. MC4R rs17782313 was genotyped by the restriction fragment length polymorphism (PCR-RFLP) method. RESULTS: After adjustment for age and energy intake, significant interactions were observed between carbohydrate intake and MC4R rs17782313 in terms of BMI (P Interaction = 0.007), WC (P Interaction = 0.02), and BMR/kg (P Interaction = 0.003) in this way that higher carbohydrate intake, compared with lower intake, was associated with an increase in BMI and WC for individuals with C allele carriers (TC + CC genotypes), while related to an increase in BMR/kg for those carrying the TT genotype. No significant interaction was found between MC4R rs17782313 and GI and GL on BMI, WC, BMR/kg, and BMR. CONCLUSIONS: Interactions between the MC4R rs17782313 and carbohydrate intake probably can have an effect on BMI, WC, and BMR/kg in overweight/obese women.

Association between dietary glycemic index and glycemic load and glioma: a case-control study.

OBJECTIVE: Although glycemic index (GI) and load (GL) have been linked with several health outcomes, no information is available linking dietary GI and GL with glioma. This study aimed to investigate the relationship between dietary GI and GL and odds of glioma. METHODS: This hospital-based case-control study was conducted between November 2009 and September 2011 in the hospital affiliated to Shahid Beheshti University of Medical Sciences. We recruited 128 newly diagnosed cases of glioma and 256 age- and sex-matched controls. All cases were pathologically diagnosed with glioma patients, with no history of any type of other pathologically confirmed cancers and chemotherapy or radiotherapy (due to cancers). Dietary GI and GL were measured by using a validated, self-administered, dish-based, semi-quantitative food-frequency questionnaire. RESULT: A significant positive association was found between dietary GI and glioma (OR: 3.01; 95% CI: 1.75-5.17, P < 0.001); such that after considering for potential confounders, participants in the highest tertile of dietary GI had 3.51 times greater risk of glioma than those in the lowest tertile (OR: 3.51; 95% CI: 1.69-7.28, Ptrend = 0.001). Furthermore, we observed a significant positive association between dietary and glioma (OR: 3.74; 95% CI: 1.97-6.11, Ptrend < 0.001). This association remained significant even after further controlling for potential confounders (OR: 2.42; 95% CI: 1.02-5.69, Ptrend = 0.04). DISCUSSION: We observed a significant positive association between dietary GI and GL and risk of glioma in adults. However, prospective cohort studies are required to confirm this association.

Dietary glycemic load and its association with glucose metabolism and lipid profile in young adults.

BACKGROUND AND AIM: To evaluate the association of Glycemic Load (GL) with glucose metabolism and blood lipids among young adults. METHODS AND RESULTS: This study included 1538 participants (51% females), evaluated at 21 years of age as part of the EPITeen cohort. The GL of each individual was obtained from the assessment of their dietary intake by using a 86-item semi-quantitative food frequency questionnaire. The evaluation included anthropometric measurements and a fasting blood sample was used to measure glucose, insulin, triglycerides, total cholesterol, high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C). Insulin resistance was calculated based on the homeostasis model method (HOMA-IR). The association between the GL and the biochemical parameters was evaluated by linear regression models using ß and 95% confidence intervals (95% CI), stratified by sex and adjusted for body mass index (BMI), energy and fiber intake, and self-perceived social class. No association was found between GL and the glucose metabolism parameters after adjustment. Regarding blood lipids, a positive association was found with LDL-C (ß = 1.507, 95% CI 0.454; 2.561 for females; ß = 0.216, 95% CI -0.587; 1.020 for males) and a negative association with HDL-C (ß = -0.647, 95% CI -1.112; -0.181 for females; ß = -0.131, 95% CI -0.422; 0.160 for males). CONCLUSIONS: Our results suggest that, in healthy young subjects, a high GL diet may have a negative impact on lipid profile.