Contribution of different vegetable types to exogenous nitrate and nitrite exposure

This study reports the levels of nitrate and nitrite of 34 vegetable samples, including different varieties of cabbage, lettuce, spinaches, parsley and turnips, collected in several locations of an intensive agricultural area (Modivas, Vila do Conde, northern Portugal). Nitrate levels ranged between 54 and 2440 mg NO-3 kg-1, while nitrite levels ranged between 1.1 and 57 mg NO-2 kg-1. The maximum residue levels established for nitrate in spinach and lettuce samples were not exceeded. Nitrate and nitrite levels reported in the literature for the same type of samples are reviewed, as well as the contribution of vegetables to nitrate and nitrite dietary exposure of populations.

Relationship of milk intake and physical activity to abdominal obesity among adolescents

Background: Diet and physical activity (PA) are recognized as important factors to prevent abdominal obesity (AO), which is strongly associated with chronic diseases. Some studies have reported an inverse association between milk consumption and AO. Objective: This study examined the association between milk intake, PA and AO in adolescents. Methods: A cross-sectional study was conducted with 1209 adolescents, aged 15–18 from the Azorean Archipelago, Portugal in 2008. AO was defined by a waist circumference at or above the 90th percentile. Adolescent food intake was measured using a semi-quantitative food frequency questionnaire, and milk intake was categorized as ‘low milk intake’ (<2 servings per day) or ‘high milk intake’ ( 2 servings per day). PA was assessed via a self-report questionnaire, and participants were divided into active (>10 points) and low-active groups ( 10 points) on the basis of their reported PA. They were then divided into four smaller groups, according to milk intake and PA: (i) low milk intake/low active; (ii) low milk intake/active; (iii) high milk intake/low active and (iv) high milk intake/active. The association between milk intake, PA and AO was evaluated using logistic regression analysis, and the results were adjusted for demographic, body mass index, pubertal stage and dietary confounders. Results: In this study, the majority of adolescents consumed semi-skimmed or skimmed milk (92.3%). The group of adolescents with high level of milk intake and active had a lower proportion of AO than did other groups (low milk intake/low active: 34.2%; low milk intake/active: 26.9%; high milk intake/low active: 25.7%; high milk intake/active: 21.9%, P = 0.008). After adjusting for confounders, low-active and active adolescents with high levels of milk intake were less likely to have AO, compared with low-active adolescents with low milk intake (high milk intake/low active, odds ratio [OR] = 0.412, 95% confidence intervals [CI]: 0.201– 0.845; high milk intake/active adolescents, OR = 0.445, 95% CI: 0.235–0.845).Conclusion: High milk intake seems to have a protective effect on AO, regardless of PA level

Assessment of nutritional and metabolic profiles of pea shoots: The new ready-to-eat baby-leaf vegetable

Pea-shoots are a new option as ready-to-eat baby-leaf vegetable. However, data about the nutritional composition and the shelf-life stability of these leaves, especially their phytonutrient composition is scarce. In this work, the macronutrient, micronutrient and phytonutrients profile of minimally processed pea shoots were evaluated at the beginning and at the end of a 10-day storage period. Several physicochemical characteristics (color, pH, total soluble solids, and total titratable acidity) were also monitored. Standard AOAC methods were applied in the nutritional value evaluation, while chromatographic methods with UV–vis and mass detection were used to analyze free forms of vitamins (HPLC-DAD-ESI-MS/MS), carotenoids (HPLC-DAD-APCI-MSn) and flavonoid compounds (HPLC-DAD-ESI-MSn). Atomic absorption spectrometry (HR-CS-AAS) was employed to characterize the mineral content of the leaves. As expected, pea leaves had a high water (91.5%) and low fat (0.3%) and carbohydrate (1.9%) contents, being a good source of dietary fiber (2.1%). Pea shoots showed a high content of vitamins C, E and A, potassium and phosphorous compared to other ready-to-eat green leafy vegetables. The carotenoid profile revealed a high content of β-carotene and lutein, typical from green leafy vegetables. The leaves had a mean flavonoid content of 329 mg/100 g of fresh product, mainly composed by glycosylated quercetin and kaempferol derivatives. Pea shoots kept their fresh appearance during the storage being color maintained throughout the shelf-life. The nutritional composition was in general stable during storage, showing some significant (p < 0.05) variation in certain water-soluble vitamins.

Pre-meal tomato (Lycopersicon esculentum) intake can have anti-obesity effects in young women?

The effect of pre-meal tomato intake in the anthropometric indices and blood levels of triglycerides, cholesterol, glucose, and uric acid of a young women population (n=35, 19.6 ± 1.3 years) was evaluated. During 4 weeks, daily, participants ingested a raw ripe tomato (~90 g) before lunch. Their anthropometric and biochemical parameters were measured repeatedly during the follow-up time. At the end of the 4 weeks, significant reductions were observed on body weight (-1.09 ± 0.12 kg on average), % fat (-1.54 ± 0.52%), fasting blood glucose (-5.29 ± 0.80 mg/dl), triglycerides (-8.31 ± 1.34 mg/dl), cholesterol (-10.17 ± 1.21 mg/ dl), and uric acid (-0.16 ± 0.04 mg/dl) of the participants. The tomato pre-meal ingestion seemed to interfere positively in body weight, fat percentage, and blood levels of glucose, triglycerides, cholesterol, and uric acid of the young adult women that participated in this study.

Modeling Vegetable Fractals by means of Fractional-order Equations

This paper characterizes four ‘fractal vegetables’: (i) cauliflower (brassica oleracea var. Botrytis); (ii) broccoli (brassica oleracea var. italica); (iii) round cabbage (brassica oleracea var. capitata) and (iv) Brussels sprout (brassica oleracea var. gemmifera), by means of electrical impedance spectroscopy and fractional calculus tools. Experimental data is approximated using fractional-order models and the corresponding parameters are determined with a genetic algorithm. The Havriliak-Negami five-parameter model fits well into the data, demonstrating that classical formulae can constitute simple and reliable models to characterize biological structures.

Children’s Indoor Exposures to (Ultra)Fine Particles in an Urban Area: Comparison Between School and Home Environments

Due to their detrimental effects on human health, scientific interest in ultrafine particles (UFP), has been increasing but available information is far from comprehensive. Children, who represent one of the most susceptible subpopulation, spend the majority of time in schools and homes. Thus, the aim of this study is to (1) assess indoor levels of particle number concentrations (PNC) in ultrafine and fine (20–1000 nm) range at school and home environments and (2) compare indoor respective dose rates for 3- to 5-yr-old children. Indoor particle number concentrations in range of 20–1000 nm were consecutively measured during 56 d at two preschools (S1 and S2) and three homes (H1–H3) situated in Porto, Portugal. At both preschools different indoor microenvironments, such as classrooms and canteens, were evaluated. The results showed that total mean indoor PNC as determined for all indoor microenvironments were significantly higher at S1 than S2. At homes, indoor levels of PNC with means ranging between 1.09 × 104 and 1.24 × 104 particles/cm3 were 10–70% lower than total indoor means of preschools (1.32 × 104 to 1.84 × 104 particles/cm3). Nevertheless, estimated dose rates of particles were 1.3- to 2.1-fold higher at homes than preschools, mainly due to longer period of time spent at home. Daily activity patterns of 3- to 5-yr-old children significantly influenced overall dose rates of particles. Therefore, future studies focusing on health effects of airborne pollutants always need to account for children’s exposures in different microenvironments such as homes, schools, and transportation modes in order to obtain an accurate representation of children overall exposure.