Nutr J
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EAT-Lancet Commission's Planetary Health Diet proposed a diet that integrates nutrition and sustainability considerations, however its affordability is unknown in many country-specific contexts, including Australia. The aim of this study is to develop a healthy and sustainable food basket modelled on the Planetary Health Diet to determine the affordability of the Planetary Health Diet basket across various socio-economic groups, and compare this affordability with a food basket modelled on the typical current diet, in an Australian setting. ⋯ These results can help to inform public health and food policy aimed at achieving a healthy and sustainable future for all Australians, including reductions in overweight/obesity rates and increased food security.
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Comparative Study
Healthy eating index versus alternate healthy index in relation to diabetes status and health markers in U.S. adults: NHANES 2007-2010.
It remains to be determined whether the Alternate Healthy Eating Index 2010 (AHEI-2010) or the Healthy Eating Index 2010 (HEI-2010) is preferably recommended as means to assess dietary quality in people with type 2 diabetes (T2DM). ⋯ Neither total HEI-2010 nor AHEI-2010 scores performed better in terms of their relationship with diabetes status. However, the significant relationships between 1) diabetes status and health markers and 2) between HEI-2010 and AHEI-2010 scores and health markers suggest that diet has some influence on T2DM.
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University represents a key transition into adulthood for many adolescents but there are associated concerns about health and behaviours. One important aspect relates to diet and there is emerging evidence that university students may consume poor quality diets, with potential implications for body weight and long-term health. This research aimed to characterise dietary patterns of university students in the UK and their sociodemographic and lifestyle antecedents. ⋯ Food intake varied amongst university students. A substantial proportion of students followed health-promoting diets, which had good nutrient profiles obviating a need for dietary intervention. However, some students consumed poor diets, incurred greater food costs and practised unfavourable lifestyle behaviours, which may have long-term health effects. University policy to improve students' diets should incorporate efforts to promote student engagement in cooking and food preparation, and increased availability of low cost healthier food items.
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The need for a better understanding of food consumption behaviour within its behavioural context has sparked the interest of nutrition researchers for user-documented food consumption data collected outside the research context using publicly available nutrition apps. The study aims to characterize the scientific, technical, legal and ethical features of this data in order to identify the opportunities and challenges associated with using this data for nutrition research. ⋯ Due to its magnitude, diversity, and interconnectedness, user-documented food consumption data offers promising opportunities for a better understanding of habitual food consumption behaviour and its determinants. Non-standardized or non-documented food data compilation procedures, data exchange protocols and formats, terms of use and privacy statements, however, limit possibilities to integrate, process and share user-documented food consumption data. An ongoing research effort is required, to keep pace with the technical advancements of food consumption apps, their evolving data networks and the legal and ethical regulations related to protecting app users and their personal data.
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Secondary data containing the locations of food outlets is increasingly used in nutrition and obesity research and policy. However, evidence evaluating these data is limited. This study validates two sources of secondary food environment data: Ordnance Survey Points of Interest data (POI) and food hygiene data from the Food Standards Agency (FSA), against street audits in England and appraises the utility of these data. ⋯ POI and FSA data have good agreement with street audits; although both datasets had geographic biases which may need to be accounted for in analyses. Use of POI proprietary classifications is an accurate method for classifying outlets, providing time savings compared to manual classification of outlets.