BackgroundFrequent consumption of excess amounts of sugar‐sweetened beverages (SSB) is a risk factor for obesity, type 2 diabetes, cardiovascular disease and dental caries. Environmental interventions, i.e. interventions that alter the physical or social environment in which individuals make beverage choices, have been advocated as a means to reduce the consumption of SSB.ObjectivesTo assess the effects of environmental interventions (excluding taxation) on the consumption of sugar‐sweetened beverages and sugar‐sweetened milk, diet‐related anthropometric measures and health outcomes, and on any reported unintended consequences or adverse outcomes.Search methodsWe searched 11 general, specialist and regional databases from inception to 24 January 2018. We also searched trial registers, reference lists and citations, scanned websites of relevant organisations, and contacted study authors.Selection criteriaWe included studies on interventions implemented at an environmental level, reporting effects on direct or indirect measures of SSB intake, diet‐related anthropometric measures and health outcomes, or any reported adverse outcome. We included randomised controlled trials (RCTs), non‐randomised controlled trials (NRCTs), controlled before‐after (CBA) and interrupted‐time‐series (ITS) studies, implemented in real‐world settings with a combined length of intervention and follow‐up of at least 12 weeks and at least 20 individuals in each of the intervention and control groups. We excluded studies in which participants were administered SSB as part of clinical trials, and multicomponent interventions which did not report SSB‐specific outcome data. We excluded studies on the taxation of SSB, as these are the subject of a separate Cochrane Review.Data collection and analysisTwo review authors independently screened studies for inclusion, extracted data and assessed the risks of bias of included studies. We classified interventions according to the NOURISHING framework, and synthesised results narratively and conducted meta‐analyses for two outcomes relating to two intervention types. We assessed our confidence in the certainty of effect estimates with the GRADE framework as very low, low, moderate or high, and presented ‘Summary of findings’ tables.Main resultsWe identified 14,488 unique records, and assessed 1030 in full text for eligibility. We found 58 studies meeting our inclusion criteria, including 22 RCTs, 3 NRCTs, 14 CBA studies, and 19 ITS studies, with a total of 1,180,096 participants. The median length of follow‐up was 10 months. The studies included children, teenagers and adults, and were implemented in a variety of settings, including schools, retailing and food service establishments. We judged most studies to be at high or unclear risk of bias in at least one domain, and most studies used non‐randomised designs. The studies examine a broad range of interventions, and we present results for these separately.Labelling interventions (8 studies): We found moderate‐certainty evidence that traffic‐light labelli...

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BackgroundResearch on Neglected Tropical Diseases (NTDs) has increased in recent decades, and significant need-gaps in diagnostic and treatment tools remain. Analysing bibliometric data from published research is a powerful method for revealing research efforts, partnerships and expertise. We aim to identify and map NTD research networks in Germany and their partners abroad to enable an informed and transparent evaluation of German contributions to NTD research.Methodology/Principal FindingsA SCOPUS database search for articles with German author affiliations that were published between 2002 and 2012 was conducted for kinetoplastid and helminth diseases. Open-access tools were used for data cleaning and scientometrics (OpenRefine), geocoding (OpenStreetMaps) and to create (Table2Net), visualise and analyse co-authorship networks (Gephi). From 26,833 publications from around the world that addressed 11 diseases, we identified 1,187 (4.4%) with at least one German author affiliation, and we processed 972 publications for the five most published-about diseases. Of those, we extracted 4,007 individual authors and 863 research institutions to construct co-author networks. The majority of co-authors outside Germany were from high-income countries and Brazil. Collaborations with partners on the African continent remain scattered. NTD research within Germany was distributed among 220 research institutions. We identified strong performers on an individual level by using classic parameters (number of publications, h-index) and social network analysis parameters (betweenness centrality). The research network characteristics varied strongly between diseases.Conclusions/SignificanceThe share of NTD publications with German affiliations is approximately half of its share in other fields of medical research. This finding underlines the need to identify barriers and expand Germany’s otherwise strong research activities towards NTDs. A geospatial analysis of research collaborations with partners abroad can support decisions to strengthen research capacity, particularly in low- and middle-income countries, which were less involved in collaborations than high-income countries. Identifying knowledge hubs within individual researcher networks complements traditional scientometric indicators that are used to identify opportunities for collaboration. Using free tools to analyse research processes and output could facilitate data-driven health policies. Our findings contribute to the prioritisation of efforts in German NTD research at a time of impending local and global policy decisions.

BackgroundEconomic growth in low- and middle-income countries (LMIC) has raised interest in how disease burden patterns are related to economic development. Meanwhile, poverty-related diseases are considered to be neglected in terms of research and development (R&D).ObjectivesDeveloping intuitive and meaningful metrics to measure how different diseases are related to poverty and neglected in the current R&D system.DesignWe measured how diseases are related to economic development with the income relation factor (IRF), defined by the ratio of disability-adjusted life-years (DALYs) per 100,000 inhabitants in LMIC versus that in high-income countries. We calculated the IRF for 291 diseases and injuries and 67 risk factors included in the Global Burden of Disease Study 2010. We measured neglect in R&D with the neglect factor (NF), defined by the ratio of disease burden in DALYs (as percentage of the total global disease burden) and R&D expenditure (as percentage of total global health-related R&D expenditure) for 26 diseases.ResultsThe disease burden varies considerably with the level of economic development, shown by the IRF (median: 1.38; interquartile range (IQR): 0.79–6.3). Comparison of IRFs from 1990 to 2010 highlights general patterns of the global epidemiological transition. The 26 poverty-related diseases included in our analysis of neglect in R&D are responsible for 13.8% of the global disease burden, but receive only 1.34% of global health-related R&D expenditure. Within this group, the NF varies considerably (median: 19; IQR: 6–52).ConclusionsThe IRF is an intuitive and meaningful metric to highlight shifts in global disease burden patterns. A large shortfall exists in global R&D spending for poverty-related and neglected diseases, with strong variations between diseases.

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Simulation modeling can be useful to estimate the long-term health and economic impacts of population-based dietary policies. We conducted a systematic scoping review following the PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews) guideline to map and critically appraise economic evaluations of population-based dietary policies using simulation models. We searched Medline, Embase, and EconLit for studies published in English after 2005. Modeling studies were mapped based on model type, dietary policy, and nutritional target, and modeled risk factor–outcome pathways were analyzed. We included 56 studies comprising 136 model applications evaluating dietary policies in 21 countries. The policies most often assessed were reformulation (34/136), taxation (27/136), and labeling (20/136); the most common targets were salt/sodium (60/136), sugar-sweetened beverages (31/136), and fruit and vegetables (15/136). Model types included Markov-type (35/56), microsimulation (11/56), and comparative risk assessment (7/56) models. Overall, the key diet-related risk factors and health outcomes were modeled, but only 1 study included overall diet quality as a risk factor. Information about validation was only reported in 19 of 56 studies and few studies (14/56) analyzed the equity impacts of policies. Commonly included cost components were health sector (52/56) and public sector implementation costs (35/56), as opposed to private sector (18/56), lost productivity (11/56), and informal care costs (3/56). Most dietary policies (103/136) were evaluated as cost-saving independent of the applied costing perspective. An analysis of the main limitations reported by authors revealed that model validity, uncertainty of dietary effect estimates, and long-term intervention assumptions necessitate a careful interpretation of results. In conclusion, simulation modeling is widely applied in the economic evaluation of population-based dietary policies but rarely takes dietary complexity and the equity dimensions of policies into account. To increase relevance for policymakers and support diet-related disease prevention, economic effects beyond the health sector should be considered, and transparent conduct and reporting of model validation should be improved.