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BackgroundProinflammatory biomarkers levels are increased among patients with cardiovascular disease, and it is known that both the presence of insulin resistance and diet may influence those levels. However, these associations are not well studied among patients with established cardiovascular disease. Our objective is to compare inflammatory biomarker levels among cardiovascular disease secondary prevention patients with and without insulin resistance, and to evaluate if there is any association between plasma fatty acid levels and inflammatory biomarker levels among them.MethodsIn this cross-sectional sub-study from the BALANCE Program Trial, we collected data from 359 patients with established cardiovascular disease. Plasma fatty acids and inflammatory biomarkers (interleukin (IL)-1β, IL-6, IL-8, IL-10, IL-12, high sensitive C-reactive protein (hs-CRP), adiponectin, and tumor necrosis factor (TNF)-alpha) were measured. Biomarkers and plasma fatty acid levels of subjects across insulin resistant and not insulin resistant groups were compared, and general linear models were used to examine the association between plasma fatty acids and inflammatory biomarkers.ResultsSubjects with insulin resistance had a higher concentration of hs-CRP (p = 0.002) and IL-6 (p = 0.002) than subjects without insulin resistance. Among subjects without insulin resistance there was a positive association between stearic fatty acid and IL-6 (p = 0.032), and a negative association between alpha-linolenic fatty acid and pro-inflammatory biomarkers (p < 0.05). Among those with insulin resistance there was a positive association between monounsaturated fatty acids and arachidonic fatty acid and adiponectin (p < 0.05), and a negative association between monounsaturated and polyunsaturated fatty acids and pro-inflammatory biomarkers (p < 0.05), as well as a negative association between polyunsaturated fatty acids and adiponectin (p < 0.05). Our study has not found any association between hs-CRP and plasma fatty acids.ConclusionsSubjects in secondary prevention for cardiovascular disease with insulin resistance have a higher concentration of hs-CRP and IL-6 than individuals without insulin resistance, and these inflammatory biomarkers are positively associated with saturated fatty acids and negatively associated with unsaturated fatty acids.Electronic supplementary materialThe online version of this article (10.1186/s12937-018-0342-1) contains supplementary material, which is available to authorized users.

Food is widely acknowledged as a significant contributor to climate change. Yet, estimates of food-related greenhouse gas emissions frequently consider supply chain stages only up to farm gate or regional distribution centres. Here, we estimate greenhouse gas emissions associated with different cooking methods and appliances in the UK. Data on current cooking practices were collected through a survey with more than 700 respondents. Results reveal that home cooking accounts for as much as 61% of total emissions associated with specific foods, and that this can be substantially reduced through alternative, readily available cooking practices.

BackgroundThe diet of the Brazilian Cardioprotective Nutritional Program (BALANCE) classifies food into four groups and sets the daily amount to be consumed. The dietary approach of BALANCE is different from other dietary recommendations; therefore, it is not possible to use existing dietary indexes (DI) to assess patient’s adequacy to BALANCE diet. For this reason, it is important to develop a specific dietary index based on BALANCE diet.This study aims to describe the development of the BALANCE DI, evaluate its internal consistency, construct and content validity and population characteristics associated with the index.MethodsWe analyzed baseline data from the BALANCE randomized clinical trial (https://www.clinicaltrials.gov/; NCT01620398). The four food groups of the diet were adopted as index components. Points ranging from 0 to 10 were given to each index component. Internal consistency was evaluated by correlation coefficients between total score and component scores, as well as Cronbach’s Alpha. Content and construct validity were assessed by checking how nutrients are associated with the index and if the index could distinguish between groups with known differences in diet, respectively. Crude and adjusted linear regression analyses were performed to evaluate population characteristics associated with the index.ResultsThe analysis included 2044 subjects (58.6% men). The average of the total index was higher among women (p < 0,05). The components of the index showed low correlations with each other. The correlations between each individual component with the total index were > 0.40. Cronbach’s alpha coefficient was 0.66. High scores in the index were inversely associated (p < 0,05) with energy, total fat, monounsaturated fat (MUFA) and cholesterol; they were positively associated (p < 0,05) with carbohydrates and fiber. Hypertensive men and diabetic women had higher scores, while male smokers had lower scores.ConclusionsThe BALANCE DI showed reliability and construct validity similar to other DI. It also detected characteristics of individuals that are associated with higher or lower index scores.

In this paper, we discuss the use of natural language processing and artificial intelligence to analyze nutritional and sustainability aspects of recipes and food. We present the state-of-the-art and some use cases, followed by a discussion of challenges. Our perspective on addressing these is that while they typically have a technical nature, they nevertheless require an interdisciplinary approach combining natural language processing and artificial intelligence with expert domain knowledge to create practical tools and comprehensive analysis for the food domain.

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Aimed at improving the quality of school meals, the Sustainable School Program (SSP) implemented low-carbon meals, twice a week, in 155 schools of 4 municipalities, reaching more than 32,000 students. This study evaluated the environmental impact and nutritional viability of this intervention for this population. The 15 most repeated meals from the conventional and sustainable menus were selected, and we considered the school age group and number of meals served per student/day. Nutritional information was calculated using validated food composition tables, nutritional adequacy was assessed using National School Feeding Program (PNAE) requirements, the level of processing was considered using NOVA classification, and greenhouse gas emissions (GHGE) were estimated using food life cycle assessment (LCA) validated data. We found both conventional and sustainable food menus are equivalent, in terms of nutrients, except for calcium, iron, and magnesium. Sustainable food menus were cholesterol-free. However, there was a reduction of up to 17% in GHGE, depending on the school age group analysed. Considering the greater energy efficiency and lower environmental impact of these food menus, the SSP, therefore, demonstrates that a substantial reduction in climate impact is feasible, successful, and can be an inspiration to other regions globally.

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