Life expectancy gains from dietary modifications: a comparative modeling study in 7 countries

\ua9 2024 The Author(s). Background: Eating healthier is associated with a range of favorable health outcomes. Our previous model estimated the impact of dietary changes on life expectancy gains but did not consider height, weight, or physical activity. Objectives: We aimed to estimate the increase in life expectancy resulting from the transition from typical national dietary patterns to longevity-optimizing dietary changes, more feasible dietary modifications, and optimized vegan dietary changes in China, France, Germany, Iran, Norway, the United Kingdom, and the United States. Methods: Our modeling study used data from meta-analyses presenting dose-response relationships between intake of 15 food groups and mortality. Background mortality data were from the Global Burden of Disease Study. We used national food intake data and adjusted for height, weight, and physical activity level. Results: For 40-y-olds, estimated life expectancy gains ranged from 6.2 y (with uncertainty interval [UI]: 5.7, 7.5 y) for Chinese females to 9.7 y (UI: 8.1, 11.3 y) for United States males following sustained changes from typical country-specific dietary patterns to longevity-optimized dietary changes, and from 5.2 y (UI: 4.0, 6.5 y) for Chinese females to 8.7 y (UI: 7.1, 10.3 y) for United States males following changes to optimized vegan dietary changes. Conclusions: A sustained change from country-specific typical dietary pattern patterns to longevity-optimized dietary changes, more feasible dietary changes, or optimized vegan dietary changes are all projected to result in substantial life expectancy gains across ages and countries. These changes included more whole grains, legumes, and nuts and less red/processed meats and sugars and sugar-sweetened beverages. The largest gains from dietary changes would be in the United States

Co-design of a personalised digital intervention to improve vegetable intake in adults living in Australian rural communities

\ua9 2024, The Author(s). Background: Diets low in vegetables are a main contributor to the health burden experienced by Australians living in rural communities. Given the ubiquity of smartphones and access to the Internet, digital interventions may offer an accessible delivery model for a dietary intervention in rural communities. However, no digital interventions to address low vegetable intake have been co-designed with adults living in rural areas. This paper describes the co-design of a digital intervention to improve vegetable intake with rural community members and research partners. Methods: Active participants in the co-design process were adults ≥ 18 years living in three rural Australian communities (total n = 57) and research partners (n = 4) representing three local rural governments and one peak non-government health organisation. An iterative co-design process was undertaken to understand the needs (pre-design phase) and ideas (generative phase) of the target population. Eight online workshops and a community survey were conducted between July and December 2021. The MoSCoW prioritisation method was used to help participants identify the ‘Must-have, Should-have, Could-have, and Won’t-have or will not have right now’ features and functions of the digital intervention. Workshops were transcribed and inductively analysed using NVivo. Convergent and divergent themes were identified between the workshops and community survey to identify how to implement the digital intervention in the community. Results: Consensus was reached on a concept for a digital intervention that addressed individual and food environment barriers to vegetable intake, specific to rural communities. Implementation recommendations centred on (i) food literacy approaches to improve skills via access to vegetable-rich recipes and healthy eating resources, (ii) access to personalisation options and behaviour change support, and (iii) improving the community food environment by providing information on and access to local food initiatives. Conclusions: Rural-dwelling adults expressed preferences for personalised intervention features that can enhance food literacy and engagement with community food environments. This research will inform the development of the prototyping (evaluation phase) and feasibility testing (post-design phase) of this intervention

Life expectancy can increase by up to 10 years following sustained shifts towards healthier diets in the United Kingdom

\ua9 2023, The Author(s).Adherence to healthy dietary patterns can prevent the development of non-communicable diseases and affect life expectancy. Here, using a prospective population-based cohort data from the UK Biobank, we show that sustained dietary change from unhealthy dietary patterns to the Eatwell Guide dietary recommendations is associated with 8.9 and 8.6 years gain in life expectancy for 40-year-old males and females, respectively. In the same population, sustained dietary change from unhealthy to longevity-associated dietary patterns is associated with 10.8 and 10.4 years gain in life expectancy in males and females, respectively. The largest gains are obtained from consuming more whole grains, nuts and fruits and less sugar-sweetened beverages and processed meats. Understanding the contribution of sustained dietary changes to life expectancy can provide guidance for the development of health policies

Validation of a digital photographic method for assessment of dietary quality of school lunch sandwiches brought from home.

Background: It is a challenge to assess children's dietary intake. The digital photographic method (DPM) may be an objective method that can overcome some of these challenges. Objective: The aim of this study was to evaluate the validity and reliability of a DPM to assess the quality of dietary intake from school lunch sandwiches brought from home among children aged 7–13 years. Design: School lunch sandwiches (n=191) were prepared to represent randomly selected school lunch sandwiches from a large database. All components were weighed to provide an objective measure of the composition. The lunches were photographed using a standardised DPM. From the digital images, the dietary components were estimated by a trained image analyst using weights or household measures and the dietary quality was assessed using a validated Meal Index of Dietary Quality (Meal IQ). The dietary components and the Meal IQ obtained from the digital images were validated against the objective weighed foods of the school lunch sandwiches. To determine interrater reliability, the digital images were evaluated by a second image analyst. Results: Correlation coefficients between the DPM and the weighed foods ranged from 0.89 to 0.97. The proportion of meals classified in the same or an adjacent quartile ranged from 98% (starch) to 100% (fruits, vegetables, fish, whole grain, and Meal IQ). There was no statistical difference between fish, fat, starch, whole grains, and Meal IQ using the two methods. Differences were found for fruits and vegetables; Bland–Altman analyses showed a tendency to underestimate high amounts of these variables using the DPM. For interrater reliability, kappa statistics ranged from 0.59 to 0.82 across the dietary components and Meal IQ. Conclusions: The standardised DPM is a valid and reliable method for assessing the dietary quality of school lunch sandwiches brought from home

Personalised nutrition advice reduces intake of discretionary foods and beverages: findings from the Food4Me randomised controlled trial

Background: The effect of personalised nutrition advice on discretionary foods intake is unknown. To date, two national classifications for discretionary foods have been derived. This study examined changes in intake of discretionary foods and beverages following a personalised nutrition intervention using these two classifications. Methods: Participants were recruited into a 6-month RCT across seven European countries (Food4Me) and were randomised to receive generalised dietary advice (control) or one of three levels of personalised nutrition advice (based on diet [L1], phenotype [L2] and genotype [L3]). Dietary intake was derived from an FFQ. An analysis of covariance was used to determine intervention effects at month 6 between personalised nutrition (overall and by 10 levels) and control on i) percentage energy from discretionary items and ii) percentage contribution of total fat, SFA, total sugars and salt to discretionary intake, defined by Food Standards Scotland (FSS) and Australian Dietary Guidelines (ADG) classifications. Results: Of the 1607 adults at baseline, n=1270 (57% female) completed the intervention. Percentage sugars from FSS discretionary items was lower in personalised nutrition vs control (19.0 \ub1 0.37 vs 21.1 \ub1 0.65; P=0.005). Percentage energy (31.2 \ub1 0.59 vs 32.7 \ub1 0.59; P=0.031), percentage total fat (31.5 \ub1 0.37 vs 33.3 \ub1 0.65; P=0.021), SFA (36.0 \ub1 0.43 vs 37.8 \ub1 0.75; P=0.034) and sugars (31.7 \ub1 0.44 vs 34.7 \ub1 0.78; P<0.001) from ADG discretionary items were lower in personalised nutrition vs control. There were greater reductions in ADG percentage energy and percentage total fat, SFA and salt for those randomised to L3 vs L2. 21Conclusions: Compared with generalised dietary advice, personalised nutrition advice achieved greater reductions in discretionary foods intake when the classification included all foods high in fat, added sugars and salt. Future personalised nutrition approaches may be 24 used to target intakes of discretionary foods

Higher vegetable protein consumption, assessed by an isoenergetic macronutrient exchange model, is associated with a lower presence of overweight and obesity in the web-based Food4me European study

The objective was to evaluate differences in macronutrient intake and to investigate the possible association between consumption of vegetable protein and the risk of overweight/obesity, within the Food4Me randomised, online intervention. Differences in macronutrient consumption among the participating countries grouped by EU Regions (Western Europe, British Isles, Eastern Europe and Southern Europe) were assessed. Relation of protein intake, within isoenergetic exchange patterns, from vegetable or animal sources with risk of overweight/obesity was assessed through the multivariate nutrient density model and a multivariate-adjusted logistic regression.A total of 2413 subjects who completed the Food4Me screening were included, with self-reported data on age, weight, height, physical activity and dietary intake. As success rates on reducing overweight/obesity are very low, form a public health perspective, the elaboration of policies for increasing intakes of vegetable protein and reducing animal protein and sugars, may be a method of combating overweight/obesity at a population level

The sugar and energy in non-carbonated sugar-sweetened beverages: a cross-sectional study.

BACKGROUND: The consumption of non-carbonated sugar-sweetened beverages (NCSSBs) has many adverse health effects. However, the sugar and energy content in NCSSBs sold in China remain unknown. We aimed to investigate the sugar and energy content of NCSSBs in China and how these contents were labelled. METHODS: A cross-sectional survey was conducted in 15 supermarkets in Haidian District, Beijing from July to October 2017. The product packaging and nutrient information panels of NCSSBs were recorded to obtain type of products (local/imported), serving size, nutrient contents of carbohydrate, sugar and energy. For those NCSSBs without sugar content information, we used carbohydrate content as a replacement. RESULTS: A total of 463 NCSSBs met the inclusion criteria and were included in our analysis. The median of sugar content and energy content was 9.6 [interquartile range (IQR): 7.1-11.3] g/100 ml and 176 (IQR: 121-201) kJ/100 ml. The median of sugar contents in juice drinks, tea-based beverages, sports drinks and energy drinks were 10.4, 8.5, 5.0 and 7.4 g/100 ml. Imported products had higher sugar and energy content than local products. There were 95.2% products of NCSSBs receiving a 'red'(high) label for sugars per portion according to the UK criteria, and 81.6% products exceeding the daily free sugar intake recommendation from the World Health Organization (25 g). There were 82 (17.7%) products with sugar content on the nutrition labels and 60.2% of them were imported products. CONCLUSIONS: NCSSBs had high sugar and energy content, and few of them provided sugar content information on their nutrition labels especially in local products. Measures including developing better regulation of labelling, reducing sugar content and restricting the serving size are needed for reducing sugar intakes in China

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Supervised multivariate analysis of sequence groups to identify specificity determining residues

<p>Abstract</p> <p>Background</p> <p>Proteins that evolve from a common ancestor can change functionality over time, and it is important to be able identify residues that cause this change. In this paper we show how a supervised multivariate statistical method, Between Group Analysis (BGA), can be used to identify these residues from families of proteins with different substrate specifities using multiple sequence alignments.</p> <p>Results</p> <p>We demonstrate the usefulness of this method on three different test cases. Two of these test cases, the Lactate/Malate dehydrogenase family and Nucleotidyl Cyclases, consist of two functional groups. The other family, Serine Proteases consists of three groups. BGA was used to analyse and visualise these three families using two different encoding schemes for the amino acids.</p> <p>Conclusion</p> <p>This overall combination of methods in this paper is powerful and flexible while being computationally very fast and simple. BGA is especially useful because it can be used to analyse any number of functional classes. In the examples we used in this paper, we have only used 2 or 3 classes for demonstration purposes but any number can be used and visualised.</p