Nutritional requirements and responses of all organisms are estimated using various models representing the response to different dietary levels of the nutrient in question. To help nutritionists design experiments for estimating responses and requirements, we developed a simulation workbook using Microsoft Excel. The objective of the present study was to demonstrate the influence of different numbers of nutrient levels, ranges of nutrient levels and replications per nutrient level on the estimates of requirements based on common nutritional response models. The user provides estimates of the shape of the response curve, requirements and other parameters and observation to observation variation. The Excel workbook then produces 1–1000 randomly simulated responses based on the given response curve and estimates the standard errors of the requirement (and other parameters) from different models as an indication of the expected power of the experiment. Interpretations are based on the assumption that the smaller the standard error of the requirement, the more powerful the experiment. The user can see the potential effects of using one or more subjects, different nutrient levels, etc., on the expected outcome of future experiments. From a theoretical perspective, each organism should have some enzyme-catalysed reaction whose rate is limited by the availability of some limiting nutrient. The response to the limiting nutrient should therefore be similar to enzyme kinetics. In conclusion, the workbook eliminates some of the guesswork involved in designing experiments and determining the minimum number of subjects needed to achieve desired outcomes.

I prophylaxis is the most effective strategy to eradicate I deficiency disorders, but it has been shown to affect the thyroid disease pattern. In this study, we assessed the frequency of thyroid disorders in an adult population living in two areas of southern Italy after implementing I prophylaxis. To this aim, a cross-sectional, population-based study including 489 subjects from an I-deficient rural and an I-sufficient urban area of southern Italy was conducted. Thyroid ultrasound was performed on all participants, and urine and blood samples were collected from each subject. The levels of thyroid-stimulating hormone (TSH), thyroglobulin (TgAb) and thyroperoxidase antibodies (TPOAb), urinary I excretion (UIE), and thyroid volume and echogenicity were evaluated. We found that the median UIE was higher in the urban than in the rural area (P=0·004), whereas the prevalence of subjects affected by goitre was higher in the rural compared with the urban area (P=0·003). Positive TgAb rather than TPOAb were more frequent in subjects from the urban area compared with the rural area (P=0·009). The hypoechoic pattern at thyroid ultrasound (HT-US) was similar between the two areas, but TgAb were significantly higher (P=0·01) in HT-US subjects from the urban area. The frequency of elevated TSH did not differ between the two screened populations, and no changes were found for TgAb positivity in subjects with high TSH in the urban compared with the rural area. Our findings support that the small risks of I supplementation are far outweighed by the substantial benefits of correcting I deficiency, although continued monitoring of populations is necessary.

A lower BMI has been reported among consumers of organic foods, but this relationship has never been examined in a prospective design study. Our aim was to prospectively investigate the association between frequency of organic food consumption and weight change. We analysed data from 62 224 participants of the NutriNet-Santé cohort (78 % women, mean age=45 years) with information on consumption frequency of organic foods, dietary intake and repeated anthropometric data. For sixteen products, participants reported their consumption frequency of labelled organic foods (never, occasionally, most of the time). An organic score (OS) with a maximum of thirty-two points was computed. The associations of the OS (modeled as quartiles (Q)) with change in BMI during follow-up (on average 3·1 years) and with the risk of overweight and obesity were estimated by ANCOVA and multivariable logistic regression. A lower BMI increase was observed across quartiles of the OS (mean difference Q4 v. Q1=−0·16 (95 % CI −0·32, −0·01). An increase in the OS was associated with a lower risk of overweight and obesity (among non-overweight and non-obese participants at inclusion): OR for Q4 v. Q1 were 0·77 (95 % CI 0·68, 0·86) and 0·69 (95 % CI 0·58, 0·82), respectively. Concerning obesity risk, the association was stronger among participants with higher adherence to nutritional guidelines. This study supports a strong protective role of consumption frequency of organic foods with regard to the risk of overweight and obesity that depends on overall dietary quality. Upon confirmation, these results may contribute to fine-tune nutritional guidelines by accounting for farming practices in food production.