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      Environmental interventions to reduce the consumption of sugar‐sweetened beverages and their effects on health

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          Frequent 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.


          To 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 methods

          We 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 criteria

          We 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 analysis

          Two 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 results

          We 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 labelling is associated with decreasing sales of SSBs, and low‐certainty evidence that nutritional rating score labelling is associated with decreasing sales of SSBs. For menu‐board calorie labelling reported effects on SSB sales varied.

          Nutrition standards in public institutions (16 studies): We found low‐certainty evidence that reduced availability of SSBs in schools is associated with decreased SSB consumption. We found very low‐certainty evidence that improved availability of drinking water in schools and school fruit programmes are associated with decreased SSB consumption. Reported associations between improved availability of drinking water in schools and student body weight varied.

          Economic tools (7 studies): We found moderate‐certainty evidence that price increases on SSBs are associated with decreasing SSB sales. For price discounts on low‐calorie beverages reported effects on SSB sales varied.

          Whole food supply interventions (3 studies): Reported associations between voluntary industry initiatives to improve the whole food supply and SSB sales varied.

          Retail and food service interventions (7 studies): We found low‐certainty evidence that healthier default beverages in children’s menus in chain restaurants are associated with decreasing SSB sales, and moderate‐certainty evidence that in‐store promotion of healthier beverages in supermarkets is associated with decreasing SSB sales. We found very low‐certainty evidence that urban planning restrictions on new fast‐food restaurants and restrictions on the number of stores selling SSBs in remote communities are associated with decreasing SSB sales. Reported associations between promotion of healthier beverages in vending machines and SSB intake or sales varied.

          Intersectoral approaches (8 studies): We found moderate‐certainty evidence that government food benefit programmes with restrictions on purchasing SSBs are associated with decreased SSB intake. For unrestricted food benefit programmes reported effects varied. We found moderate‐certainty evidence that multicomponent community campaigns focused on SSBs are associated with decreasing SSB sales. Reported associations between trade and investment liberalisation and SSB sales varied.

          Home‐based interventions (7 studies): We found moderate‐certainty evidence that improved availability of low‐calorie beverages in the home environment is associated with decreased SSB intake, and high‐certainty evidence that it is associated with decreased body weight among adolescents with overweight or obesity and a high baseline consumption of SSBs.

          Adverse outcomes reported by studies, which may occur in some circumstances, included negative effects on revenue, compensatory SSB consumption outside school when the availability of SSBs in schools is reduced, reduced milk intake, stakeholder discontent, and increased total energy content of grocery purchases with price discounts on low‐calorie beverages, among others. The certainty of evidence on adverse outcomes was low to very low for most outcomes.

          We analysed interventions targeting sugar‐sweetened milk separately, and found low‐ to moderate‐certainty evidence that emoticon labelling and small prizes for the selection of healthier beverages in elementary school cafeterias are associated with decreased consumption of sugar‐sweetened milk. We found low‐certainty evidence that improved placement of plain milk in school cafeterias is not associated with decreasing sugar‐sweetened milk consumption.

          Authors' conclusions

          The evidence included in this review indicates that effective, scalable interventions addressing SSB consumption at a population level exist. Implementation should be accompanied by high‐quality evaluations using appropriate study designs, with a particular focus on the long‐term effects of approaches suitable for large‐scale implementation.

          Cutting back on sugar‐sweetened beverages: What works?

          What are sugar‐sweetened beverages?

          Sugar‐sweetened beverages (SSBs) are cold and hot drinks with added sugar. Common SSBs are non‐diet soft drinks, regular soda, iced tea, sports drinks, energy drinks, fruit punches, sweetened waters, and sweetened tea and coffee.

          Why are SSBs an important health topic?

          Research shows that people who drink a lot of SSBs often gain weight. Drinking a lot of SSBs can also increase the risk of diabetes, heart disease, and dental decay. Doctors therefore recommend that children, teenagers and adults drink fewer SSBs. Governments, businesses, schools and workplaces have taken various measures to support healthier beverage choices.

          What is the aim of this review?

          We wanted to find out whether the measures taken so far have been successful in helping people to drink fewer SSBs to improve their health. We focused on measures that change the environment in which people make beverage choices. We did not look at studies on educational programmes or on SSB taxes, as these are examined in separate reviews. (We did, however, examine price increases on SSB which were not due to taxes.) We searched for all available studies meeting clearly‐defined criteria to answer this question. This review reflects the state of the evidence up until January 2018.

          What studies did we find?

          We found 58 studies, which included more than one million adults, teenagers and children. Most studies lasted about one year, and were done in schools, stores or restaurants.

          Some studies used methods that are not very reliable. For example, in some studies participants were simply asked how much SSB they drank, which is not very reliable, as people sometimes forget how much SSB they drank. Some of the findings of our review may therefore change when more and better studies become available.

          What do these studies tell us?

          We have found some evidence that some of the measures implemented to help people drink fewer SSBs have been successful, including the following:

          ▪ Labels which are easy to understand, such as traffic‐light labels, and labels which rate the healthfulness of beverages with stars or numbers.

          ▪ Limits to the availability of SSB in schools (e.g. replacing SSBs with water in school cafeterias).

          ▪ Price increases on SSBs in restaurants, stores and leisure centres.

          ▪ Children’s menus in chain restaurants which include healthier beverages as their standard beverage.

          ▪ Promotion of healthier beverages in supermarkets.

          ▪ Government food benefits (e.g. food stamps) which cannot be used to buy SSBs.

          ▪ Community campaigns focused on SSBs.

          ▪ Measures that improve the availability of low‐calorie beverages at home, e.g. through home deliveries of bottled water and diet beverages.

          We have also found some evidence that improved availability of drinking water and diet beverages at home can help people lose weight.

          There are also other measures which may influence how much SSB people drink, but for these the available evidence is less certain.

          Some, but not all studies found that such measures can have effects which were not intended and which may be negative. Some studies reported that profits of stores and restaurants decreased when the measures were implemented, but other studies showed that profits increased or stayed the same. Children who get free drinking water in schools may drink less milk. Some studies reported that people were unhappy with the measures.

          We also looked at studies on sugar‐sweetened milk. We found that small prizes for children who chose plain milk in their school cafeteria, as well as emoticon labels, may help children drink less sugar‐sweetened milk. However, this may also drive up the share of milk which is wasted because children choose but do not drink it.

          What does this mean in practice?

          Our review shows that measures which change the environment in which people make beverage choices can help people drink less SSB. Based on our findings we suggest that such measures may be used more widely. Government officials, business people and health professionals implementing such measures should work together with researchers to find out more about their effects in the short and long term.

          Related collections

          Most cited references 553

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          The simultaneous increases in obesity in almost all countries seem to be driven mainly by changes in the global food system, which is producing more processed, affordable, and effectively marketed food than ever before. This passive overconsumption of energy leading to obesity is a predictable outcome of market economies predicated on consumption-based growth. The global food system drivers interact with local environmental factors to create a wide variation in obesity prevalence between populations. Within populations, the interactions between environmental and individual factors, including genetic makeup, explain variability in body size between individuals. However, even with this individual variation, the epidemic has predictable patterns in subpopulations. In low-income countries, obesity mostly affects middle-aged adults (especially women) from wealthy, urban environments; whereas in high-income countries it affects both sexes and all ages, but is disproportionately greater in disadvantaged groups. Unlike other major causes of preventable death and disability, such as tobacco use, injuries, and infectious diseases, there are no exemplar populations in which the obesity epidemic has been reversed by public health measures. This absence increases the urgency for evidence-creating policy action, with a priority on reduction of the supply-side drivers. Copyright © 2011 Elsevier Ltd. All rights reserved.
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              ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions

              Non-randomised studies of the effects of interventions are critical to many areas of healthcare evaluation, but their results may be biased. It is therefore important to understand and appraise their strengths and weaknesses. We developed ROBINS-I (“Risk Of Bias In Non-randomised Studies - of Interventions”), a new tool for evaluating risk of bias in estimates of the comparative effectiveness (harm or benefit) of interventions from studies that did not use randomisation to allocate units (individuals or clusters of individuals) to comparison groups. The tool will be particularly useful to those undertaking systematic reviews that include non-randomised studies.

                Author and article information

                Cochrane Database Syst Rev
                Cochrane Database Syst Rev
                The Cochrane Database of Systematic Reviews
                John Wiley & Sons, Ltd (Chichester, UK )
                12 June 2019
                June 2019
                29 May 2019
                12 June 2019
                : 2019
                : 6
                Ludwig‐Maximilians‐University Munich deptInstitute for Medical Informatics, Biometry and Epidemiology, Pettenkofer School of Public Health Marchioninistr. 15MunichGermany81377
                University College London deptGreat Ormond Street Institute of Child Health LondonUK
                School of Medicine, Technical University of Munich deptInstitute of Nutritional Medicine, Else Kroener‐Fresenius Centre for Nutritional Medicine MunichGermany
                Author notes

                Editorial Group: Cochrane Public Health Group.

                CD012292 CD012292.pub2
                Copyright © 2019 The Authors. Cochrane Database of Systematic Reviews published by John Wiley & Sons, Ltd. on behalf of The Cochrane Collaboration.

                This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial License, which allows remixing, tweaking, and building upon the original work non-commercially, and although the new works must also acknowledge the original work and be non-commercial, derivative works don’t have to be licensed under the same terms.

                Medicine General & Introductory Medical Sciences


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