Point-of-choice kilocalorie labelling practices in large, out-of-home food businesses: a preobservational versus post observational study of labelling practices following implementation of The Calorie Labelling (Out of Home Sector) (England) Regulations 2021.

BACKGROUND AND OBJECTIVES: On 6 April 2022, the UK government implemented mandatory kilocalorie (kcal) labelling regulations for food and drink products sold in the out-of-home food sector (OHFS) in England. Previous assessments of kcal labelling practices in the UK OHFS found a low prevalence of voluntary implementation and poor compliance with labelling recommendations. This study aimed to examine changes in labelling practices preimplementation versus post implementation of mandatory labelling regulations in 2022. METHODS: In August-December 2021 (preimplementation) and August-November 2022 (post implementation), large OHFS businesses (250 or more employees) subject to labelling regulations were visited. At two time points, a researcher visited the same 117 food outlets (belonging to 90 unique businesses) across four local authorities in England. Outlets were rated for compliance with government regulations for whether kcal labelling was provided at any or all point of choice, provided for all eligible food and drink items, provided per portion for sharing items, if labelling was clear and legible and if kcal reference information was displayed. RESULTS: There was a significant increase (21% preimplementation vs 80% post implementation, OR=40.98 (95% CI 8.08 to 207.74), p<0.001) in the proportion of outlets providing any kcal labelling at point-of-choice post implementation. Only 15% of outlets met all labelling compliance criteria post implementation, with a minority of outlets not presenting labelling in a clear (33%) or legible (29%) way. CONCLUSION: The number of large businesses in the OHFS providing kcal labelling increased following the implementation of mandatory labelling regulations. However, around one-fifth of eligible outlets sampled were not providing kcal labelling 4-8 months after the regulations came into force, and the majority of businesses only partially complied with government guidance. More effective enforcement may be required to further improve kcal labelling practices in the OHFS in England. PREREGISTRATION: Study protocol and analysis strategy preregistered on Open Science Framework (https://osf.io/pfnm6/).

Forest disturbance increases functional diversity but decreases phylogenetic diversity of an arboreal tropical ant community.

Tropical rainforest trees host a diverse arthropod fauna that can be characterised by their functional diversity (FD) and phylogenetic diversity (PD). Human disturbance degrades tropical forests, often coinciding with species invasion and altered assembly that leads to a decrease in FD and PD. Tree canopies are thought to be particularly vulnerable, but rarely investigated. Here, we studied the effects of forest disturbance on an ecologically important invertebrate group, the ants, in a lowland rainforest in New Guinea. We compared an early successional disturbed plot (secondary forest) to an old-growth plot (primary forest) by exhaustively sampling their ant communities in a total of 852 trees. We expected that for each tree community (1) disturbance would decrease FD and PD in tree-dwelling ants, mediated through species invasion. (2) Disturbance would decrease ant trait variation due to a more homogeneous environment. (3) The main drivers behind these changes would be different contributions of true tree-nesting species and visiting species. We calculated FD and PD based on a species-level phylogeny and 10 ecomorphological traits. Furthermore, we assessed by data exclusion the influence of species, which were not nesting in individual trees (visitors) or only nesting species (nesters), and of non-native species on FD and PD. Primary forests had higher ant species richness and PD than secondary forest. However, we consistently found increased FD in secondary forest. This pattern was robust even if we decoupled functional and phylogenetic signals, or if non-native ant species were excluded from the data. Visitors did not contribute strongly to FD, but they increased PD and their community weighted trait means often varied from nesters. Moreover, all community-weighted trait means changed after forest disturbance. Our finding of contradictory FD and PD patterns highlights the importance of integrative measures of diversity. Our results indicate that the tree community trait diversity is not negatively affected, but possibly even enhanced by disturbance. Therefore, the functional diversity of arboreal ants is relatively robust when compared between old-growth and young trees. However, further study with higher plot-replication is necessary to solidify and generalise our findings.

Assessing the healthiness of menus of all out-of-home food outlets and its socioeconomic patterns in Great Britain.

Food environment research predominantly focuses on the spatial distribution of out-of-home food outlets. However, the healthiness of food choices available within these outlets has been understudied, largely due to resource constraints. In this study, we propose an innovative, low-resource approach to characterise the healthiness of out-of-home food outlets at scale. Menu healthiness scores were calculated for food outlets on JustEat, and a deep learning model was trained to predict these scores for all physical out-of-home outlets in Great Britain, based on outlet names. Our findings highlight the "double burden" of the unhealthy food environment in deprived areas where there tend to be more out-of-home food outlets, and these outlets tend to be less healthy. This methodological advancement provides a nuanced understanding of out-of-home food environments, with potential for automation and broad geographic application.

A simple method to account for thermal boundary layers during the estimation of CTmax in small ectotherms.

As temperatures rise, understanding how ectotherms will become impacted by thermal stress is of critical importance. In this context, many researchers quantify critical temperatures - these are the upper (CTmax) and lower (CTmin) thermal limits at which organisms can no longer function. Most studies estimate CTs using bath-based methods where organisms are submerged within a set thermal environment. Plate-based methods (i.e. hot plates), however, offer huge opportunity for automation and are readily available in many lab settings. Plates, however, generate a unidirectional thermal boundary layer above their surface which means that the temperatures experienced by organisms of different sizes is different. This boundary layer effect can bias estimates of critical temperatures. Here, we test the hypothesis that biases in critical temperature estimation on hot plates are driven by organism height. We also quantify the composition of the boundary layer in order to correct for these biases. We assayed four differently sized species of UK ants for their CTmax in dry baths (with no boundary layer) and on hot plates (with a boundary layer). We found that hot plates overestimated the CTmax values of the different ants, and that this overestimate was larger for taller species. By statistically modelling the thickness of the thermal boundary layer, and combining with estimates of species height, we were able to correct this overestimation and eliminate methodological differences. Our study provides two main findings. First, we provide evidence that organism height is positively related to the bias present in plate-based estimates of CTmax. Second, we show that a relatively simple statistical model can correct for this bias. By using simple corrections for boundary layer effects, as we have done here, researchers could open up a new possibility space in the design and implementation of thermal tolerance assays using plates rather than restrictive dry or water baths.

Kilocalorie labelling in the out-of-home sector: an observational study of business practices and consumer behaviour prior to implementation of the mandatory calorie labelling policy in England, 2022.

BACKGROUND: Regulations mandating kilocalorie (kcal) labelling for large businesses in the out-of-home food sector (OHFS) came into force on 6th April 2022 as a policy to reduce obesity in England. To provide indicators of potential reach and impact, kcal labelling practices were studied in the OHFS, and customer purchasing and consumption behaviours prior to implementation of the mandatory kcal labelling policy in England. METHODS: From August-December 2021, large OHFS businesses subject to the kcal labelling regulations were visited prior to regulations coming into force on 6th April 2022. 3308 customers were recruited from 330 outlets and collected survey information on the number of kcal purchased and consumed by customers, customers' knowledge of the kcal content of their purchases, and customers noticing and use of kcal labelling. In a subset of 117 outlets, data was collected on nine recommended kcal labelling practices. RESULTS: The average number of kcals purchased (1013 kcal, SD = 632 kcal) was high with 69% of purchases exceeding the recommendation of a maximum of 600 kcal per meal. Participants underestimated the energy content of their purchased meals by on average 253 kcal (SD = 644 kcals). In outlets providing kcal labelling in which customer survey data was collected, a minority of customers reported noticing (21%) or using (20%) kcal labelling. Out of the 117 outlets assessed for kcal labelling practices, 24 (21%) provided any in-store kcal labelling. None of the outlets met all nine aspects of recommended labelling practices. CONCLUSIONS: Prior to implementation of 2022 kcal labelling policy, the majority of sampled OHFS large business outlets in England did not provide kcal labelling. Few customers noticed or used the labels and on average customers purchased and consumed substantially more energy than recommended in public health guidelines. The findings suggest that reliance on voluntary action for kcal labelling implementation failed to produce widespread, consistent, and adequate kcal labelling practices.

dsSurvival 2.0: privacy enhancing survival curves for survival models in the federated DataSHIELD analysis system.

OBJECTIVE: Survival models are used extensively in biomedical sciences, where they allow the investigation of the effect of exposures on health outcomes. It is desirable to use diverse data sets in survival analyses, because this offers increased statistical power and generalisability of results. However, there are often challenges with bringing data together in one location or following an analysis plan and sharing results. DataSHIELD is an analysis platform that helps users to overcome these ethical, governance and process difficulties. It allows users to analyse data remotely, using functions that are built to restrict access to the detailed data items (federated analysis). Previous works have provided survival modelling functionality in DataSHIELD (dsSurvival package), but there is a requirement to provide functions that offer privacy enhancing survival curves that retain useful information. RESULTS: We introduce an enhanced version of the dsSurvival package which offers privacy enhancing survival curves for DataSHIELD. Different methods for enhancing privacy were evaluated for their effectiveness in enhancing privacy while maintaining utility. We demonstrated how our selected method could enhance privacy in different scenarios using real survival data. The details of how DataSHIELD can be used to generate survival curves can be found in the associated tutorial.

Ecological strategies of (pl)ants: Towards a world-wide worker economic spectrum for ants.

Current global challenges call for a rigorously predictive ecology. Our understanding of ecological strategies, imputed through suites of measurable functional traits, comes from decades of work that largely focussed on plants. However, a key question is whether plant ecological strategies resemble those of other organisms.Among animals, ants have long been recognised to possess similarities with plants: as (largely) central place foragers. For example, individual ant workers play similar foraging roles to plant leaves and roots and are similarly expendable. Frameworks that aim to understand plant ecological strategies through key functional traits, such as the 'leaf economics spectrum', offer the potential for significant parallels with ant ecological strategies.Here, we explore these parallels across several proposed ecological strategy dimensions, including an 'economic spectrum', propagule size-number trade-offs, apparency-defence trade-offs, resource acquisition trade-offs and stress-tolerance trade-offs. We also highlight where ecological strategies may differ between plants and ants. Furthermore, we consider how these strategies play out among the different modules of eusocial organisms, where selective forces act on the worker and reproductive castes, as well as the colony.Finally, we suggest future directions for ecological strategy research, including highlighting the availability of data and traits that may be more difficult to measure, but should receive more attention in future to better understand the ecological strategies of ants. The unique biology of eusocial organisms provides an unrivalled opportunity to bridge the gap in our understanding of ecological strategies in plants and animals and we hope that this perspective will ignite further interest. Read the free Plain Language Summary for this article on the Journal blog.

Testing the context dependence of ant nutrient preference across habitat strata and trophic levels in Neotropical biomes.

Animals are integrated into the wider ecosystem via their foraging and behavior. The compensation hypothesis predicts that animals target their foraging efforts (i) toward nutrients that are scarce in the environment and (ii) toward nutrients that are not present in the usual diet of species, which varies across trophic levels. Understanding how foraging for resources varies locally, such as across habitat strata, and trophic levels will help to elucidate the links between the local environment and communities to the ecological functions that animals mediate. We examined whether the relative resource use of ants varies consistently along a habitat strata gradient and across trophic levels across Neotropical biomes. We placed 4500 baited tubes, each containing one of five liquid resources (sugar, amino acid, lipid, sodium, and distilled water) in one of three habitat strata (subterranean, epigaeic, and arboreal) across 60 transects in Amazon, Atlantic Forest, Caatinga, Cerrado, Pampa, and Pantanal biomes. We assessed the relative resource use of all ants across the habitat strata and among two different trophic groups across biomes. The relative preference for sugar increased from subterranean to arboreal strata in all biomes, while the relative preference for lipids decreased at this gradient in five biomes. We also found that in general sugar-consuming ants foraged more for sugar and less for lipids than predatory ants across biomes. Conversely, we found no consistency across biomes in nutrient preference of amino acid and sodium across habitat strata or trophic levels. Overall, our results indicate sugar limitation in the arboreal stratum and lipid limitation on the ground across biomes and that the trophic level of ants strongly determines their foraging efforts-possibly because ants try to fix their dietary nutrient imbalances. Hence, our findings suggest strong local niche partitioning of sugar and lipid use across habitat strata and trophic levels and that other large spatial scale processes influence the local amino acid and sodium dynamics.

Os animais se integram nos ecossistemas pelos seus esforços e comportamento de forrageio. A hipótese da compensação prevê que os animais direcionam seus esforços de forrageio para (i) nutrientes que são escassos no ambiente e (ii) para nutrientes que não estão presentes em sua dieta, que variam entre os níveis tróficos. Assim, entender como a busca de recursos varia localmente entre os estratos de habitat e entre níveis tróficos, ajudará a entender as conexões entre o ambiente e suas comunidades com as funções ecológicas mediadas pelos animais. Avaliamos se o uso relativo de recursos das formigas varia consistentemente em um gradiente de estratos de habitat e em diferentes níveis tróficos nos biomas Neotropicais. Disponibilizamos um total de 4.500 tubos contendo um de cinco recursos líquidos (açúcar, aminoácido, lipídio, sódio e água destilada) em três estratos de habitat (subterrâneo, epigéico e arbóreo) em 60 transectos distribuídos nos biomas Amazônia, Mata Atlântica, Caatinga, Cerrado, Pampa e Pantanal. Avaliamos o uso relativo de recursos de todas as formigas ao longo dos estratos de habitat e entre dois grupos tróficos diferentes nos biomas. A preferência relativa por açúcar aumentou do estrato subterrâneo para o arbóreo em todos os biomas, enquanto a preferência relativa por lipídios diminuiu neste gradiente em cinco biomas. Também descobrimos que, em geral, as formigas consumidoras de açúcar procuram mais açúcar e menos lipídios do que as formigas predadoras nos biomas. Por outro lado, não encontramos consistência entre biomas na preferência nutricional de aminoácidos e sódio nos estratos de habitat ou níveis tróficos. No geral, nossos resultados indicam limitação de açúcar no estrato arbóreo e limitação de lipídios no solo em todos os biomas e que o nível trófico das formigas determina fortemente seus esforços de forrageamento - possivelmente porque as formigas tentam corrigir seus desequilíbrios de nutrientes na dieta. Portanto, nossas descobertas sugerem forte partição de nicho local de uso de açúcar e lipídios em estratos de habitat e níveis tróficos e que outros processos de grande escala espacial influenciam a dinâmica local de aminoácidos e sódio.

Life course of retrospective harmonization initiatives: key elements to consider.

Optimizing research on the developmental origins of health and disease (DOHaD) involves implementing initiatives maximizing the use of the available cohort study data; achieving sufficient statistical power to support subgroup analysis; and using participant data presenting adequate follow-up and exposure heterogeneity. It also involves being able to undertake comparison, cross-validation, or replication across data sets. To answer these requirements, cohort study data need to be findable, accessible, interoperable, and reusable (FAIR), and more particularly, it often needs to be harmonized. Harmonization is required to achieve or improve comparability of the putatively equivalent measures collected by different studies on different individuals. Although the characteristics of the research initiatives generating and using harmonized data vary extensively, all are confronted by similar issues. Having to collate, understand, process, host, and co-analyze data from individual cohort studies is particularly challenging. The scientific success and timely management of projects can be facilitated by an ensemble of factors. The current document provides an overview of the 'life course' of research projects requiring harmonization of existing data and highlights key elements to be considered from the inception to the end of the project.

Monitoring the Nutrient Composition of Food Prepared Out-of-Home in the United Kingdom: Database Development and Case Study.

BACKGROUND: Hand transcribing nutrient composition data from websites requires extensive human resources and is prone to error. As a result, there are limited nutrient composition data on food prepared out of the home in the United Kingdom. Such data are crucial for understanding and monitoring the out-of-home food environment, which aids policy making. Automated data collection from publicly available sources offers a potential low-resource solution to address this gap. OBJECTIVE: In this paper, we describe the first UK longitudinal nutritional database of food prepared out of the home, MenuTracker. As large chains will be required to display calorie information on their UK menus from April 2022, we also aimed to identify which chains reported their nutritional information online in November 2021. In a case study to demonstrate the utility of MenuTracker, we estimated the proportions of menu items exceeding recommended energy and nutrient intake (eg, >600 kcal per meal). METHODS: We have collated nutrient composition data of menu items sold by large chain restaurants quarterly since March 2021. Large chains were defined as those with 250 employees or more (those covered by the new calorie labeling policy) or belonging to the top 100 restaurants based on sales volume. We developed scripts in Python to automate the data collection process from business websites. Various techniques were used to harvest web data and extract data from nutritional tables in PDF format. RESULTS: Automated Python programs reduced approximately 85% of manual work, totaling 500 hours saved for each wave of data collection. As of January 2022, MenuTracker has 76,405 records from 88 large out-of-home food chains at 4 different time points (ie, March, June, September, and December) in 2021. In constructing the database, we found that one-quarter (24.5%, 256/1043) of large chains, which are likely to be subject to the United Kingdom's calorie menu labeling regulations, provided their nutritional information online in November 2021. Across these chains, 24.7% (16,391/66,295) of menu items exceeded the UK government's recommendation of a maximum of 600 kcal for a single meal. Comparable figures were 46.4% (29,411/63,416) for saturated fat, 34.7% (21,964/63,388) for total fat, 17.6% (11,260/64,051) for carbohydrates, 17.8% (11,434/64,059) for sugar, and 35.2% (22,588/64,086) for salt. Furthermore, 0.7% to 7.1% of the menu items exceeded the maximum daily recommended intake for these nutrients. CONCLUSIONS: MenuTracker is a valuable resource that harnesses the power of data science techniques to use publicly available data online. Researchers, policy makers, and consumers can use MenuTracker to understand and assess foods available from out-of-home food outlets. The methods used in development are available online and can be used to establish similar databases elsewhere.

dsSurvival: Privacy preserving survival models for federated individual patient meta-analysis in DataSHIELD.

OBJECTIVE: Achieving sufficient statistical power in a survival analysis usually requires large amounts of data from different sites. Sensitivity of individual-level data, ethical and practical considerations regarding data sharing across institutions could be a potential challenge for achieving this added power. Hence we implemented a federated meta-analysis approach of survival models in DataSHIELD, where only anonymous aggregated data are shared across institutions, while simultaneously allowing for exploratory, interactive modelling. In this case, meta-analysis techniques to combine analysis results from each site are a solution, but an analytic workflow involving local analysis undertaken at individual studies hinders exploration. Thus, the aim is to provide a framework for performing meta-analysis of Cox regression models across institutions without manual analysis steps for the data providers. RESULTS: We introduce a package (dsSurvival) which allows privacy preserving meta-analysis of survival models, including the calculation of hazard ratios. Our tool can be of great use in biomedical research where there is a need for building survival models and there are privacy concerns about sharing data.

dsSynthetic: synthetic data generation for the DataSHIELD federated analysis system.

OBJECTIVE: Platforms such as DataSHIELD allow users to analyse sensitive data remotely, without having full access to the detailed data items (federated analysis). While this feature helps to overcome difficulties with data sharing, it can make it challenging to write code without full visibility of the data. One solution is to generate realistic, non-disclosive synthetic data that can be transferred to the analyst so they can perfect their code without the access limitation. When this process is complete, they can run the code on the real data. RESULTS: We have created a package in DataSHIELD (dsSynthetic) which allows generation of realistic synthetic data, building on existing packages. In our paper and accompanying tutorial we demonstrate how the use of synthetic data generated with our package can help DataSHIELD users with tasks such as writing analysis scripts and harmonising data to common scales and measures.

Associations between exploratory dietary patterns and incident type 2 diabetes: a federated meta-analysis of individual participant data from 25 cohort studies.

PURPOSE: In several studies, exploratory dietary patterns (DP), derived by principal component analysis, were inversely or positively associated with incident type 2 diabetes (T2D). However, findings remained study-specific, inconsistent and rarely replicated. This study aimed to investigate the associations between DPs and T2D in multiple cohorts across the world. METHODS: This federated meta-analysis of individual participant data was based on 25 prospective cohort studies from 5 continents including a total of 390,664 participants with a follow-up for T2D (3.8-25.0 years). After data harmonization across cohorts we evaluated 15 previously identified T2D-related DPs for association with incident T2D estimating pooled incidence rate ratios (IRR) and confidence intervals (CI) by Piecewise Poisson regression and random-effects meta-analysis. RESULTS: 29,386 participants developed T2D during follow-up. Five DPs, characterized by higher intake of red meat, processed meat, French fries and refined grains, were associated with higher incidence of T2D. The strongest association was observed for a DP comprising these food groups besides others (IRRpooled per 1 SD = 1.104, 95% CI 1.059-1.151). Although heterogeneity was present (I2 = 85%), IRR exceeded 1 in 18 of the 20 meta-analyzed studies. Original DPs associated with lower T2D risk were not confirmed. Instead, a healthy DP (HDP1) was associated with higher T2D risk (IRRpooled per 1 SD = 1.057, 95% CI 1.027-1.088). CONCLUSION: Our findings from various cohorts revealed positive associations for several DPs, characterized by higher intake of red meat, processed meat, French fries and refined grains, adding to the evidence-base that links DPs to higher T2D risk. However, no inverse DP-T2D associations were confirmed.

The response of ants to climate change.

Ants (Hymenoptera: Formicidae) are one of the most dominant terrestrial organisms worldwide. They are hugely abundant, both in terms of sheer numbers and biomass, on every continent except Antarctica and are deeply embedded within a diversity of ecological networks and processes. Ants are also eusocial and colonial organisms-their lifecycle is built on the labor of sterile worker ants who support a small number of reproductive individuals. Given the climatic changes that our planet faces, we need to understand how various important taxonomic groups will respond; this includes the ants. In this review, we synthesize the available literature to tackle this question. The answer is complicated. The ant literature has focused on temperature, and we broadly understand the ways in which thermal changes may affect ant colonies, populations, and communities. In general, we expect that species living in the Tropics, and in thermally variable microhabitats, such as the canopy and leaf litter environments, will be negatively impacted by rising temperatures. Species living in the temperate zones and those able to thermally buffer their nests in the soil or behaviorally avoid higher temperatures, however, are likely to be unaffected or may even benefit from a changed climate. How ants will respond to changes to other abiotic drivers associated with climate change is largely unknown, as is the detail on how altered ant populations and communities will ramify through their wider ecological networks. We discuss how eusociality may allow ants to adapt to, or tolerate, climate change in ways that solitary organisms cannot and we identify key geographic and phylogenetic hotspots of climate vulnerability and resistance. We finish by emphasizing the key research questions that we need to address moving forward so that we may fully appreciate how this critical insect group will respond to the ongoing climate crisis.

Associations of early-life pet ownership with asthma and allergic sensitization: A meta-analysis of more than 77,000 children from the EU Child Cohort Network.

BACKGROUND: Studies examining associations of early-life cat and dog ownership with childhood asthma have reported inconsistent results. Several factors could explain these inconsistencies, including type of pet, timing, and degree of exposure. OBJECTIVE: Our aim was to study associations of early-life cat and dog ownership with asthma in school-aged children, including the role of type (cat vs dog), timing (never, prenatal, or early childhood), and degree of ownership (number of pets owned), and the role of allergic sensitization. METHODS: We used harmonized data from 77,434 mother-child dyads from 9 birth cohorts in the European Union Child Cohort Network when the child was 5 to 11 years old. Associations were examined through the DataSHIELD platform by using adjusted logistic regression models, which were fitted separately for each cohort and combined by using random effects meta-analysis. RESULTS: The prevalence of early-life cat and dog ownership ranged from 12% to 45% and 7% to 47%, respectively, and the prevalence of asthma ranged from 2% to 20%. There was no overall association between either cat or dog ownership and asthma (odds ratio [OR] = 0.97 [95% CI = 0.87-1.09] and 0.92 [95% CI = 0.85-1.01], respectively). Timing and degree of ownership did not strongly influence associations. Cat and dog ownership were also not associated with cat- and dog-specific allergic sensitization (OR = 0.92 [95% CI = 0.75-1.13] and 0.93 [95% CI = 0.57-1.54], respectively). However, cat- and dog-specific allergic sensitization was strongly associated with school-age asthma (OR = 6.69 [95% CI = 4.91-9.10] and 5.98 [95% CI = 3.14-11.36], respectively). There was also some indication of an interaction between ownership and sensitization, suggesting that ownership may exacerbate the risks associated with pet-specific sensitization but offer some protection against asthma in the absence of sensitization. CONCLUSION: Our findings do not support early-life cat and dog ownership in themselves increasing the risk of school-age asthma, but they do suggest that ownership may potentially exacerbate the risks associated with cat- and dog-specific allergic sensitization.

Socioeconomic inequalities in food outlet access through an online food delivery service in England: A cross-sectional descriptive analysis.

Online food delivery services facilitate 'online' access to food outlets selling food prepared away-from-home. Online food outlet access has not previously been investigated in England or across an entire country. Systematic differences in online food outlet access could exacerbate existing health inequalities, which is a public health concern. However, this is not known. Across postcode districts in England (n = 2118), we identified and described the number of food outlets and unique cuisine types accessible online from the market leader (Just Eat). We investigated associations with area-level deprivation using adjusted negative binomial regression models. We also compared the number of food outlets accessible online with the number physically accessible in the neighbourhood (1600m Euclidean buffers of postcode district geographic centroids) and investigated associations with deprivation using an adjusted general linear model. For each outcome, we predicted means and 95% confidence intervals. In November 2019, 29,232 food outlets were registered to accept orders online. Overall, the median number of food outlets accessible online per postcode district was 63.5 (IQR; 16.0-156.0). For the number of food outlets accessible online as a percentage of the number accessible within the neighbourhood, the median was 63.4% (IQR; 35.6-96.5). Analysis using negative binomial regression showed that online food outlet access was highest in the most deprived postcode districts (n = 106.1; 95% CI: 91.9, 120.3). The number of food outlets accessible online as a percentage of those accessible within the neighbourhood was highest in the least deprived postcode districts (n = 86.2%; 95% CI: 78.6, 93.7). In England, online food outlet access is socioeconomically patterned. Further research is required to understand how online food outlet access is related to using online food delivery services.

Heterogeneity of Associations between Total and Types of Fish Intake and the Incidence of Type 2 Diabetes: Federated Meta-Analysis of 28 Prospective Studies Including 956,122 Participants.

The association between fish consumption and new-onset type 2 diabetes is inconsistent and differs according to geographical location. We examined the association between the total and types of fish consumption and type 2 diabetes using individual participant data from 28 prospective cohort studies from the Americas (6), Europe (15), the Western Pacific (6), and the Eastern Mediterranean (1) comprising 956,122 participants and 48,084 cases of incident type 2 diabetes. Incidence rate ratios (IRRs) for associations of total fish, shellfish, fatty, lean, fried, freshwater, and saltwater fish intake and type 2 diabetes were derived for each study, adjusting for a consistent set of confounders and combined across studies using random-effects meta-analysis. We stratified all analyses by sex due to observed interaction (p = 0.002) on the association between fish and type 2 diabetes. In women, for each 100 g/week higher intake the IRRs (95% CIs) of type 2 diabetes were 1.02 (1.01-1.03, I2 = 61%) for total fish, 1.04 (1.01-1.07, I2 = 46%) for fatty fish, and 1.02 (1.00-1.04, I2 = 33%) for lean fish. In men, all associations were null. In women, we observed variation by geographical location: IRRs for total fish were 1.03 (1.02-1.04, I2 = 0%) in the Americas and null in other regions. In conclusion, we found evidence of a neutral association between total fish intake and type 2 diabetes in men, but there was a modest positive association among women with heterogeneity across studies, which was partly explained by geographical location and types of fish intake. Future research should investigate the role of cooking methods, accompanying foods and environmental pollutants, but meanwhile, existing dietary regional, national, or international guidelines should continue to guide fish consumption within overall healthy dietary patterns.

Orchestrating privacy-protected big data analyses of data from different resources with R and DataSHIELD.

Combined analysis of multiple, large datasets is a common objective in the health- and biosciences. Existing methods tend to require researchers to physically bring data together in one place or follow an analysis plan and share results. Developed over the last 10 years, the DataSHIELD platform is a collection of R packages that reduce the challenges of these methods. These include ethico-legal constraints which limit researchers' ability to physically bring data together and the analytical inflexibility associated with conventional approaches to sharing results. The key feature of DataSHIELD is that data from research studies stay on a server at each of the institutions that are responsible for the data. Each institution has control over who can access their data. The platform allows an analyst to pass commands to each server and the analyst receives results that do not disclose the individual-level data of any study participants. DataSHIELD uses Opal which is a data integration system used by epidemiological studies and developed by the OBiBa open source project in the domain of bioinformatics. However, until now the analysis of big data with DataSHIELD has been limited by the storage formats available in Opal and the analysis capabilities available in the DataSHIELD R packages. We present a new architecture ("resources") for DataSHIELD and Opal to allow large, complex datasets to be used at their original location, in their original format and with external computing facilities. We provide some real big data analysis examples in genomics and geospatial projects. For genomic data analyses, we also illustrate how to extend the resources concept to address specific big data infrastructures such as GA4GH or EGA, and make use of shell commands. Our new infrastructure will help researchers to perform data analyses in a privacy-protected way from existing data sharing initiatives or projects. To help researchers use this framework, we describe selected packages and present an online book (https://isglobal-brge.github.io/resource_bookdown).

Associations of Total Legume, Pulse, and Soy Consumption with Incident Type 2 Diabetes: Federated Meta-Analysis of 27 Studies from Diverse World Regions.

BACKGROUND: The consumption of legumes is promoted as part of a healthy diet in many countries but associations of total and types of legume consumption with type 2 diabetes (T2D) are not well established. Analyses across diverse populations are lacking despite the availability of unpublished legume consumption data in prospective cohort studies. OBJECTIVE: To examine the prospective associations of total and types of legume intake with the risk of incident T2D. METHODS: Meta-analyses of associations between total legume, pulse, and soy consumption and T2D were conducted using a federated approach without physical data-pooling. Prospective cohorts were included if legume exposure and T2D outcome data were available and the cohort investigators agreed to participate. We estimated incidence rate ratios (IRRs) and CIs of associations using individual participant data including ≤42,473 incident cases among 807,785 adults without diabetes in 27 cohorts across the Americas, Eastern Mediterranean, Europe, and Western Pacific. Random-effects meta-analysis was used to combine effect estimates and estimate heterogeneity. RESULTS: Median total legume intake ranged from 0-140 g/d across cohorts. We observed a weak positive association between total legume consumption and T2D (IRR = 1.02, 95% CI: 1.01 to 1.04) per 20 g/d higher intake, with moderately high heterogeneity (I2 = 74%). Analysis by region showed no evidence of associations in the Americas, Eastern Mediterranean, and Western Pacific. The positive association in Europe (IRR = 1.05, 95% CI: 1.01 to 1.10, I2 = 82%) was mainly driven by studies from Germany, UK, and Sweden. No evidence of associations was observed for the consumption of pulses or soy. CONCLUSIONS: These findings suggest no evidence of an association of legume intakes with T2D in several world regions. The positive association observed in some European studies warrants further investigation relating to overall dietary contexts in which legumes are consumed, including accompanying foods which may be positively associated with T2D.

Automatic classification of takeaway food outlet cuisine type using machine (deep) learning.

BACKGROUND AND PURPOSE: Researchers have not disaggregated neighbourhood exposure to takeaway ('fast-') food outlets by cuisine type sold, which would otherwise permit examination of differential impacts on diet, obesity and related disease. This is partly due to the substantial resource challenge of manual classification of unclassified takeaway outlets at scale. We describe the development of a new model to automatically classify takeaway food outlets, by 10 major cuisine types, based on business name alone. MATERIAL AND METHODS: We used machine (deep) learning, and specifically a Long Short Term Memory variant of a Recurrent Neural Network, to develop a predictive model trained on labelled outlets (n = 14,145), from an online takeaway food ordering platform. We validated the accuracy of predictions on unseen labelled outlets (n = 4,000) from the same source. RESULTS: Although accuracy of prediction varied by cuisine type, overall the model (or 'classifier') made a correct prediction approximately three out of four times. We demonstrated the potential of the classifier to public health researchers and for surveillance to support decision-making, through using it to characterise nearly 55,000 takeaway food outlets in England by cuisine type, for the first time. CONCLUSIONS: Although imperfect, we successfully developed a model to classify takeaway food outlets, by 10 major cuisine types, from business name alone, using innovative data science methods. We have made the model available for use elsewhere by others, including in other contexts and to characterise other types of food outlets, and for further development.