Feeding the Worlth Healthily: the Challenge of Measuring the effects of Agriculture on Health

Agricultural production, food systems and population health are intimately linked. While there is a strong evidence base to inform our knowledge of what constitutes a healthy human diet, we know little about actual food production or consumption in many populations and how developments in the food and agricultural system will affect dietary intake patterns and health. The paucity of information on food production and consumption is arguably most acute in low- and middle-income countries, where it is most urgently needed to monitor levels of under-nutrition, the health impacts of rapid dietary transition and the increasing ‘double burden’ of nutrition-related disease. Food availability statistics based on food commodity production data are currently widely used as a proxy measure of national-level food consumption, but using data from the UK and Mexico we highlight the potential pitfalls of this approach. Despite limited resources for data collection, better systems of measurement are possible. Important drivers to improve collection systems may include efforts to meet international development goals and partnership with the private sector. A clearer understanding of the links between the agriculture and food system and population health will ensure that health becomes a critical driver of agricultural change

Cost of the Diet: a method and software to calculate the lowest cost of meeting recommended intakes of energy and nutrients from local foods

Background When food is available, the main obstacle to access is usually economic: people may not be able to afford a nutritious diet, even if they know what foods to eat. The Cost of the Diet method and software was developed to apply linear programming to better understand the extent to which poverty may affect people’s ability to meet their nutritional specifications. This paper describes the principles of the method; the mathematics underlying the linear programming; the parameters and assumptions on which the calculations are based; and then illustrates the output of the software using examples taken from assessments. Results The software contains five databases: the energy and nutrient content of foods; the energy and nutrient specifications of individuals; predefined groups of individuals in typical households; the portion sizes of foods; and currency conversion factors. Data are collected during a market survey to calculate the average cost of foods per 100 g while focus group discussions are used to assess local dietary habits and preferences. These data are presented to a linear programming solver within the software which selects the least expensive combination of local foods for four standard diets that meet specifications for: energy only; energy and macronutrients; energy, macronutrients and micronutrients; and energy, macronutrients and micronutrients but with constraints on the amounts per meal that are consistent with typical dietary habits. Most parameters in the software can be modified by users to examine the potential impact of a wide range of theoretical interventions. The output summarises for each diet the costs, quantity and proportion of energy and nutrient specifications provided by all the foods selected for a given individual or household by day, week, season and year. When the cost is expressed as a percentage of income, the affordability of the diet can be estimated. Conclusions The Cost of the Diet method and software could be used to inform programme design and behaviour change communication in the fields of nutrition, food security, livelihoods and social protection as well as to influence policies and advocacy debates on the financial cost of meeting energy and nutrient specifications

Scientific Opinion on the re-evaluation of Quinoline Yellow (E 104) as a food additive:Question No EFSA-Q-2008-223

The Panel on Food Additives and Nutrient Sources added to Food provides a scientific opinion re-evaluating the safety of Quinoline Yellow (E 104). Quinoline Yellow has been previously evaluated by the Joint FAO/WHO Expert Committee on Food Additives (JECFA) in 1975, 1978 and 1984, and the EU Scientific Committee for Food (SCF) in 1984. Both committees established an Acceptable Daily Intake (ADI) of 0-10 mg/kg body weight (bw). Studies not evaluated by JECFA and the SCF included a chronic toxicity and carcinogenicity study with a reproductive toxicity phase in rats and a study on behaviour in children by McCann et al. from 2007. The latter study concluded that exposure to a mixture of colours including Quinoline Yellow resulted in increased hyperactivity in 8- to 9-years old children. The Panel concurs with the conclusion from a previous EFSA opinion on the McCann et al. study that the findings of the study cannot be used as a basis for altering the ADI. The Panel notes that Quinoline Yellow was negative in in vitro genotoxicity as well as in long term carcinogenicity studies. The Panel concludes that the currently available database on semi-chronic, reproductive, developmental and long-term toxicity of Quinoline Yellow, including a study in rats not apparently taken into consideration by JECFA or the SCF, provides a rationale for re-definition of the ADI. Using the NOAEL of 50 mg/kg bw/day provided by the chronic toxicity and carcinogenicity study with a reproductive toxicity phase carried out in rats and applying an uncertainty factor of 100 to this NOAEL, the Panel establishes an ADI of 0.5 mg/kg bw/day. The Panel notes that at the maximum levels of use of Quinoline Yellow, refined intake estimates are generally well over the ADI of 0.5 mg/kg bw/day

Comparison of methods for the microbiological identification and profiling of cronobacter species from ingredients used in the preparation of infant formula

Cronobacter spp. (formerly Enterobacter sakazakii) can be isolated from a wide range of foods and environments, and its association with neonatal infections has drawn considerable attention from regulatory authorities. The principle route of neonatal infection has been identified as the ingestion of contaminated infant formula. A number of methods have been developed to identify Cronobacter spp., however these were before the most recent (2012 ) taxonomic revision of the genus into seven species. In this study, phenotyping, protein profiling and molecular methods were used to identify Cronobacter strains which had been recently isolated from ingredients used in the preparation of infant formula. Pulsed field gel electrophoresis revealed that different Cronobacter strains had been recovered from the same food products. All isolates were identified as C sakazakii according to four genus specific PCR-probes and protein profiling using MALDI-TOF analysis. However, 16S rDNA sequence analyses and fusA allele sequencing gave more accurate identification: four strains were C sakazakii, one strain was C malonaticus and the remaining strain was C universalis. Multilocus sequence typing showed the strains were different sequence types. These results demonstrate the presence of different Cronobacter species in food ingredients used in the preparation of infant formula, and also the need for molecular identification and profiling methods to be revised according to taxonomic revisions

EFSA CEF Panel (EFSA Panel on Food Contact Materials, Enzymes, Flavourings and Processing Aids), 2014. Scientific Opinion on Flavouring Group Evaluation 213, Revision 1 (FGE.213Rev1): Consideration of genotoxic potential for α , β -Unsaturated Alicyclic ketones and precursors from chemical subgroup 2.7 of FGE.19. EFS

The Panel on Food Contact Materials, Enzymes, Flavourings and Processing Aids of the European Food Safety Authority was requested to evaluate the genotoxic potential of 26 flavouring substances from subgroup 2.7 of FGE.19 in the Flavouring Group Evaluation 213. In the first version of FGE.213 the Panel concluded based on available genotoxicity data that a concern regarding genotoxicity could be ruled out for [FL-no: 07.047, 07.056, 07.057, 07.075, 07.076, 07.080, 07.117, 07.118, 07.119, 07.120 and 07.168], but for the remaining 15 substances in subgroup 2.7 further genotoxicity data were required. Based on new submitted genotoxicity data, the Panel concluded in FGE.213Rev1 that the concern regarding genotoxicity could be ruled out for 13 substances in subgroup 2.7 [FL-no: 02.106, 07.008, 07.010, 07.041, 07.083, 07.089, 07.108, 07.109, 07.127, 07.136, 07.200, 07.224 and 09.305] but not for maltol [FL-no: 07.014] and maltyl isobutyrate [FL-no: 09.525]

Determinants of appetite ratings: the role of age, gender, BMI, physical activity, smoking habits, and diet/weight concern

Appetite measures are often recorded by visual analogue scales (VAS), and are assumed to reflect central nervous system (CNS) perceptions and sensations. However, little is known about how physiological, psychological, social, and cultural factors influence VAS.To investigate whether age, gender, body mass index (BMI), smoking habits, physical activity, diet behaviour, and menstruation cycle are determinants of appetite ratings.We investigated appetite ratings in different groups of a population during a single meal test, including 178 healthy women (98) and men (80), aged 20–60 years with a BMI of 18.5–35.0 kg/m2. Subjects consumed an evening meal composed to meet individual requirements of energy content and recommendations regarding macronutrient composition. Before and every half hour until 3 hours after the meal, subjects filled out VAS for satiety, fullness, hunger, and prospective food intake. They also filled in a questionnaire on eating/slimming behaviour.Multiple linear regression analyses showed that gender and age were the most powerful predictors of postprandial satiety (p<0.001, adj. R 2=0.19) and hunger (p<0.001, adj. R 2=0.15). Repeated measures general linear model (GLM) analyses revealed that women felt more satisfied than men (p<0.001) and older subjects felt more satisfied than younger (p<0.01). Furthermore, light/no exercisers felt more satisfied and less hungry than hard/moderate exercisers (p<0.05), but these differences disappeared after adjusting for age and gender. Smokers rated their prospective consumption lower than non-smokers (p < 005) and women in the ovulation phase felt less hungry than women in the menstruation phase (p<005). Neither BMI nor diet/weight concern were significantly associated with appetite ratings.Appetite ratings differed according to age, gender, and physical activity and to a lesser degree for smoking habits and menstruation cycle. Appetite ratings were not influenced by BMI and diet/weight concern. These factors should be considered when planning studies and analysing data concerning appetite sensations

Measuring Malnutrition

Summary The nutritional condition of an individual, or the extent of malnutrition in a population, can be measured either in terms of outcomes , i.e. current status, or in terms of inputs , i.e rates of consumption of nutrients and/or energy in diets. A review of the methods of measurement in common use for these two approaches, and of their technical limitations, is followed by an account of the problems of interpretation of these in the light of contemporary ideas about the causes of growth faltering in children. Also discussed is the basis for standards of normality for growth and for nutrient intake levels, and the extent to which adaptive changes in behaviour or physiology may compensate for low levels of intake. It is concluded that, provided these problems are recognised, nutritional indicators can play a useful role in assessing overall food and health situations, particularly when accompanied by other complementary measurements of the effects of the health environment of the households and their social and economic characteristics

Urban agriculture: a global analysis of the space constraint to meet urban vegetable demand

Urban agriculture (UA) has been drawing a lot of attention recently for several reasons: the majority of the world population has shifted from living in rural to urban areas; the environmental impact of agriculture is a matter of rising concern; and food insecurity, especially the accessibility of food, remains a major challenge. UA has often been proposed as a solution to some of these issues, for example by producing food in places where population density is highest, reducing transportation costs, connecting people directly to food systems and using urban areas efficiently. However, to date no study has examined how much food could actually be produced in urban areas at the global scale. Here we use a simple approach, based on different global-scale datasets, to assess to what extent UA is constrained by the existing amount of urban space. Our results suggest that UA would require roughly one third of the total global urban area to meet the global vegetable consumption of urban dwellers. This estimate does not consider how much urban area may actually be suitable and available for UA, which likely varies substantially around the world and according to the type of UA performed. Further, this global average value masks variations of more than two orders of magnitude among individual countries. The variations in the space required across countries derive mostly from variations in urban population density, and much less from variations in yields or per capita consumption. Overall, the space required is regrettably the highest where UA is most needed, i.e., in more food insecure countries. We also show that smaller urban clusters (i.e., <100 km2 each) together represent about two thirds of the global urban extent; thus UA discourse and policies should not focus on large cities exclusively, but should also target smaller urban areas that offer the greatest potential in terms of physical space

Can personality close the intention-behavior gap for healthy eating? An examination with the HEXACO personality traits

The aim of this study was to investigate the predictive and moderating effects of HEXACO personality factors, in addition to theory of planned behavior (TPB) variables, on fruit and vegetable consumption. American college students (N = 1036) from 24 institutions were administered the TPB, HEXACO and a self-reported fruit and vegetable consumption measure. The TPB predicted 11–17% of variance in fruit and vegetable consumption, with greater variance accounted for in healthy weight compared to overweight individuals. Personality did not significantly improve the prediction of behavior above TPB constructs; however, conscientiousness was a significant incremental predictor of intention in both healthy weight and overweight/obese groups. While support was found for the TPB as an important predictor of fruit and vegetable consumption in students, little support was found for personality factors. Such findings have implications for interventions designed to target students at risk of chronic disease