Estimated dietary iodine intake as a predictor of placental size: evidence from the ELSPAC study.

BACKGROUND: The relationship between low iodine status and pregnancy-associated comorbidities has been known for decades. The relationship between iodine intake and placental pathologies is, however, far less clear. This study was designed to examine the relationship between dietary iodine intake and placental size while also focusing on typical adverse pregnancy outcomes. METHOD: The dietary iodine intake of 4711 pregnant women enrolled in the Czech part of the European Longitudinal Study of Pregnancy and Childhood (ELSPAC) in 1990-1991 was established using a 145-item food frequency questionnaire. Multivariate linear regression models were used to estimate the relationship between dietary iodine intake during pregnancy and placental weight. Additional models were constructed to investigate the relationship between estimated dietary iodine intake and adverse birth outcomes. RESULTS: The estimated average iodine intake in the ELSPAC cohort was 106.6 µg/day. In the fully adjusted model, estimated dietary iodine intake was found to be significantly negatively associated with placental weight (ß = -0.025, 95% CI: -0.044; -0.006, p = 0.011). Moreover, estimated dietary iodine intake was found to be significantly positively associated with the birth weight / placental weight ratio in the fully adjusted model (ß = -0.024, 95% CI: 0.004; 0.043, p = 0.016). CONCLUSIONS: This study provides evidence of a relationship between estimated dietary iodine intake and placental weight and the birth weight / placental weight ratio. Additional research is warranted to provide more insight into the role of iodine in early as well as late placentation.

Association of Glutathione S-Transferase Polymorphisms with Dietary Composition but Not Anthropometry in Obese as Well as Nonobese Individuals.

OBJECTIVES: Glutathione S-transferases (GSTs) are detoxifying enzymes for a number of substrates, including some food compounds. Selected GST polymorphisms have been proven to significantly affect enzymatic activity; however, it is unclear whether this altered metabolism influences dietary composition. The objective of this study was to locate the correlation between GST polymorphisms and selected nutritional parameters, namely, fiber and vitamin C intake. METHODS: This study was conducted on a cohort of 472 individuals (mean age 45.26 years; mean body mass index [BMI] 32.36) from the South Moravian region of the Czech Republic. Basic anthropometrical parameters were measured and no association was found for the selected polymorphisms. Polymorphisms in GSTA1, GSTM1, and GSTT1 were genotyped using a polymerase chain reaction (PCR)-based methodology. Food intake was monitored using a self-administered 7-day questionnaire that was subsequently analyzed with a special focus on vitamin C intake, fiber intake, and total energy intake. RESULTS: For GSTA1 and GSTM1 polymorphisms, an association was observed with fiber intake. Though no association was found with vitamin C intake, mean vitamin C intake was found to be higher than recommended daily values. No association was found with either daily energy intake or anthropometric parameters. CONCLUSION: Based on our results, GST polymorphisms seem to affect dietary composition; however, they have no effect on total energy intake or any association with obesity.

Allelic variants in vitamin D receptor gene are associated with adiposity measures in the central-European population.

BACKGROUND: There is an increasing body of evidence suggesting that vitamin D is involved in ethiopathogenesis of obesity and therefore the aim of the study was to investigate whether 5 selected SNPs in VDR (vitamin D receptor) gene are associated also with anthropometry in the obese and non-obese Central-European population. METHODS: A total of 882 Central European Caucasian individuals of Czech origin were recruited (n = 882, 232 M/650 F) and weight, height, BMI, lean body mass, fat mass, body fat, waist and hip circumference, waist-hip ratio (WHR) and skinfold thickness were measured. Univariate and multivariate models were constructed in order to investigate the relationship between anthropometry and VDR polymorphisms. RESULTS: In the univariate modeling, the CC genotype of FokI SNP was associated with reduced waist circumference (ß = -3.48; 95%CI:-7.11;0.15; p = 0.060), sum of skin fold thickness (ß = -6.53, 95% CI: -12.96;-0.11; p = 0.046) as well as total % of body fat (ß = -3.14, 95% CI: -5.18;-1.09; p = 0.003) compared to TT genotype. The AC genotype of ApaI SNP was associated with reduced waist circumference compared to AA genotype (ß = -4.37, 95% CI: -7.54;-1.20; p = 0.007). GG genotype of EcoRV SNP was associated with reduced sum of skin fold thickness compared to AA genotype (ß = -7.77, 95% CI: -14.34;-1.21; p = 0.020). In the multivariate modelling, multiple significant associations of VDR with investigated traits were observed, too. CONCLUSION: Our study suggests that genetic variability in the VDR region may be an important factor influencing anthropometric characteristics associated with obesity.

Higher Energy Intake Variability as Predisposition to Obesity: Novel Approach Using Interquartile Range.

OBJECTIVE: It is known that total energy intake and its distribution during the day influences human anthropometric characteristics. However, possible association between variability in total energy intake and obesity has thus far remained unexamined. This study was designed to establish the influence of energy intake variability of each daily meal on the anthropometric characteristics of obesity. METHODS: A total of 521 individuals of Czech Caucasian origin aged 16­73 years (390 women and 131 men) were included in the study, 7-day food records were completed by all study subjects and selected anthropometric characteristics were measured. The interquartile range (IQR) of energy intake was assessed individually for each meal of the day (as a marker of energy intake variability) and subsequently correlated with body mass index (BMI), body fat percentage (%BF), waist-hip ratio (WHR), and waist circumference (cW). RESULTS: Four distinct models were created using multiple logistic regression analysis and backward stepwise logistic regression. The most precise results, based on the area under the curve (AUC), were observed in case of the %BF model (AUC=0.895) and cW model (AUC=0.839). According to the %BF model, age (p<0.001) and IQR-lunch (p<0.05) seem to play an important prediction role for obesity. Likewise, according to the cW model, age (p<0.001), IQR-breakfast (p<0.05) and IQR-dinner (p <0.05) predispose patients to the development of obesity. The results of our study show that higher variability in the energy intake of key daily meals may increase the likelihood of obesity development. CONCLUSIONS: Based on the obtained results, it is necessary to emphasize the regularity in meals intake for maintaining proper body composition.