Iron Bioavailability Should be Considered when Modeling Omnivorous, Vegetarian, and Vegan Diets.

BACKGROUND: To lower environmental impact of human food consumption, replacement of animal proteins with plant-based proteins is encouraged. However, the lower iron bioavailability of plant-based foods is rarely considered when designing healthy and sustainable diets by using diet modeling. The estimated absorbable iron content of vegetarian and vegan menu plans might therefore be too optimistic. OBJECTIVE: The main aim of this study was to investigate and compare the impact of various methods to estimate absorbable iron intake on the nutritional adequacy of omnivorous, vegetarian, and vegan menu plans designed for women of reproductive age. METHODS: A diet model was developed to design menu plans consisting of a selection of meals that best complied with nutritional requirements. Meals used for modeling were created based on food intake data from the National Health and Nutrition Examination Survey (NHANES). For each meal, absorbable iron concentrations were estimated by using 2 constant absorption factors (18% and 10%) and 2 diet-dependent absorption equations (Conway and Hallberg). For each absorption method and diet type, we used the diet model to design the optimal menu plan. Retrospectively, menu plans were evaluated by estimating the absorbable iron content by using the other absorption methods. RESULTS: Retrospective diet-dependent absorbable iron estimates were consistently lower than estimates based on constant absorption factors. Using diet-dependent estimates increased absorbable iron by optimizing enhancer and inhibitor concentrations. CONCLUSION: Iron bioavailability should be considered when modeling diets.

Developing feasible healthy diets for Ethiopian women of reproductive age: a linear goal programming approach.

OBJECTIVE: To develop a healthy diet for Ethiopian women closely resembling their current diet and taking fasting periods into account while tracking the cost difference. DESIGN: Linear goal programming models were built for three scenarios (non-fasting, continuous fasting and intermittent fasting). Each model minimised a function of deviations from nutrient reference values for eleven nutrients (protein, Ca, Fe, Zn, folate, and the vitamins A, B1, B2, B3, B6, and B12). The energy intake in optimised diets could only deviate 5 % from the current diet. SETTINGS: Five regions are included in the urban and rural areas of Ethiopia. PARTICIPANTS: Two non-consecutive 24-h dietary recalls (24HDR) were collected from 494 Ethiopian women of reproductive age from November to December 2019. RESULTS: Women's mean energy intake was well above 2000 kcal across all socio-demographic subgroups. Compared to the current diet, the estimated intake of several food groups was considerably higher in the optimised modelled diets, that is, milk and dairy foods (396 v. 30 g/d), nuts and seeds (20 v. 1 g/d) and fruits (200 v. 7 g/d). Except for Ca and vitamin B12 intake in the continuous fasting diet, the proposed diets provide an adequate intake of the targeted micronutrients. The proposed diets had a maximum cost of 120 Ethiopian birrs ($3·5) per d, twice the current diet's cost. CONCLUSION: The modelled diets may be feasible for women of reproductive age as they are close to their current diets and fulfil their energy and nutrient demands. However, the costs may be a barrier to implementation.

Designing healthier and acceptable diets using data envelopment analysis.

OBJECTIVE: The objective of this research is to propose methodology that can be used to benchmark current diets based on their nutrient intakes and to provide guidelines for improving less healthy diets in a way that is acceptable for the studied population. DESIGN: We discuss important limitations of current diet models that use optimisation techniques to design healthier and acceptable diets. We illustrate how data envelopment analysis could be used to overcome such limitations, and we describe mathematical models that can be used to calculate not only healthier but also acceptable diets. SETTING: We used data from the Nutrition Questionnaires plus dataset of habitual diets of a general population of adult men and women in The Netherlands (n 1735). PARTICIPANTS: Adult population. RESULTS: We calculated healthier diets with substantial higher intakes of protein, fibre, Fe, Ca, K, Mg and vitamins, and substantially lower intakes of Na, saturated fats and added sugars. The calculated diets are combinations of current diets of individuals that belong to the same age/gender group and comprise of food item intakes in proportions observed in the sample. CONCLUSIONS: The proposed methodology enables the benchmarking of existing diets and provides a framework for proposing healthier alternative diets that resemble the current diet in terms of foods intake as much as possible.

Optimising the selection of food items for FFQs using Mixed Integer Linear Programming.

OBJECTIVE: To support the selection of food items for FFQs in such a way that the amount of information on all relevant nutrients is maximised while the food list is as short as possible. DESIGN: Selection of the most informative food items to be included in FFQs was modelled as a Mixed Integer Linear Programming (MILP) model. The methodology was demonstrated for an FFQ with interest in energy, total protein, total fat, saturated fat, monounsaturated fat, polyunsaturated fat, total carbohydrates, mono- and disaccharides, dietary fibre and potassium. RESULTS: The food lists generated by the MILP model have good performance in terms of length, coverage and R 2 (explained variance) of all nutrients. MILP-generated food lists were 32-40 % shorter than a benchmark food list, whereas their quality in terms of R 2 was similar to that of the benchmark. CONCLUSIONS: The results suggest that the MILP model makes the selection process faster, more standardised and transparent, and is especially helpful in coping with multiple nutrients. The complexity of the method does not increase with increasing number of nutrients. The generated food lists appear either shorter or provide more information than a food list generated without the MILP model.

A linear programming based method for designing menus for controlled feeding trials.

BACKGROUND: Controlled feeding trials are an important method to determine cause-effect relationships between dietary intake and metabolic parameters, risk factors, or health outcomes. Participants of a controlled feeding trial receive full-day menus during a prespecified period of time. The menus have to comply with the nutritional and operational standards of the trial. Levels of nutrients under investigation should differ sufficiently between intervention groups, and be as similar as possible for all energy levels within intervention groups. Levels of other key nutrients should be as similar as possible for all participants. All menus have to be varied and manageable. Designing these menus is both a nutritional and a computational challenge that relies largely on the expertise of the research dietician. The process is very time consuming, and last-minute disruptions are very hard to manage. OBJECTIVE: This paper demonstrates a mixed integer linear programming model to support the design of menus for controlled feeding trials. METHODS: The model is demonstrated for a trial that involved consumption of individualized, isoenergetic menus with either a low or a high protein content. RESULTS: All menus generated by the model comply with all standards of the trial. The model allows for including tight ranges on nutrient composition, and complex design features. The model is very helpful in managing contrast and similarity of key nutrient intake levels between groups and energy levels, and in coping with many energy levels and nutrients. The model helps to propose several alternative menus and to manage last-minute disruptions. The model is flexible; it can easily be adapted to suit trials with other components or different nutritional requirements. CONCLUSIONS: The model helps to design menus in a fast, objective, transparent, and reproducible way. It greatly facilitates the design procedure for menus in controlled feeding trials and lowers development costs.

Are postprandial glucose responses sufficiently person-specific to use in personalized dietary advice? Design of the RepEAT study: a fully controlled dietary intervention to determine the variation in glucose responses.

Introduction: An elevated postprandial glucose response is associated with an increased risk of cardiometabolic diseases. Existing research suggests large heterogeneity in the postprandial glucose responses to identical meals and food products between individuals, but the effect of other consumed meals during the day and the order of meals during the day on the heterogeneity in postprandial glucose responses still needs to be investigated. In addition, the robustness of the glucose responses to meals or foods is still unknown. Objectives: The overall aim of the project is to assess whether the glucose response to a meal is sufficiently person-specific to use in personalized dietary advice. We aim to answer the question: "How replicable are glucose responses to meals within individuals and how consistent is the variation in glucose responses between individuals?" Methods: The question will be assessed under standardized conditions of a 9-week fully controlled dietary intervention in which all meals are the same between individuals and consumed in a fixed order at a fixed time. 63 apparently healthy men and women with a BMI of 25-40 kg/m2 and aged 45-75 years were enrolled in the RepEAT study (NCT05456815), of whom 53 participants completed the study. The RepEAT study comprised a fully controlled dietary intervention of nine weeks, consisting of three repetitive periods of three weeks. Within each three-week period, a variety of meals and food products were offered during breakfast, lunch, dinner and in between meal snacks. Throughout the dietary intervention, glucose was continuously monitored using Freestyle Libre Pro IQ monitors. Physical activity was monitored using the ActiGraph and ActivPAL. To measure the association between glucose responses and an individual's phenotype, various measurements were performed before the start of the dietary intervention including an oral glucose tolerance test, a high-fat mixed meal challenge, assessment of body fat distribution including liver fat (MRI/MRS), and cardiometabolic markers. Discussion: The repetitive and fully controlled nature of the dietary study allows detailed assessment of the replicability of the glucose responses to meals and food products within individuals. Furthermore, the consistency of the variation between individuals independent of insulin resistance will be determined.