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      Sugar-sweetened beverage purchases in urban Peru before the implementation of taxation and warning label policies: a baseline study

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          Abstract

          Background

          Sugar-sweetened beverage consumption is associated with obesity and chronic disease. In 2018, Peru increased the tax on high-sugar beverages (≥6 g of sugar per 100 mL) from 17 to 25%, yet little is known about pre-existing beverage trends or demographic characteristics associated with purchases in the country. The aim of this study was to explore beverage purchasing trends from 2016 to 2017 and examine variation in purchase volume by sociodemographic characteristics among urban households in Peru.

          Methods

          This study used monthly household purchase data from a panel of 5145 households from January 2016–December 2017 from Kantar WorldPanel Peru. Beverage purchases were categorized by type and tax status under the 2018 regulation (untaxed, lower-sugar taxed, high-sugar taxed). To assess beverage purchasing trends, per-capita volume purchases were regressed on a linear time trend, with month dummies for seasonality and clustered standard errors. Mean volume purchases by beverage tax status (total liters purchased per month), overall and by key demographic characteristics (education, socioeconomic status, and geographic region), were calculated. Mean volume by beverage type was assessed to identify the largest contributors to total beverage volume.

          Results

          The trends analysis showed a decline in total beverage volume of − 52 mL/capita/month (95% CI: − 72, − 32) during the 24-month study period. Over 99% of households purchased untaxed beverages in a month, while > 92% purchased high-sugar taxed beverages. Less than half of all households purchased low-sugar taxed beverages in a month and purchase volume was low (0.3 L/capita/month). Untaxed beverage purchases averaged 9.4 L/capita/month, while households purchased 2.8 L/capita/month of high-sugar taxed beverages in 2017. Across tax categories, volume purchases were largest in the high education and high socioeconomic (SES) groups, with substantial variation by geographic region. The highest volume taxed beverage was soda (2.3 L/capita/month), while the highest volume untaxed beverages were milk and bottled water (1.9 and 1.7 L/capita/month, respectively).

          Conclusions

          Nearly all households purchased high-sugar taxed beverages, although volume purchases of taxed and untaxed beverages declined slightly from 2016 to 2017. Households with high SES and high education purchased the highest volume of taxed beverages, highlighting the need to consider possible differential impacts of the tax policy change by sub-population groups.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12889-022-14762-w.

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          Most cited references38

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          Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support.

          Research electronic data capture (REDCap) is a novel workflow methodology and software solution designed for rapid development and deployment of electronic data capture tools to support clinical and translational research. We present: (1) a brief description of the REDCap metadata-driven software toolset; (2) detail concerning the capture and use of study-related metadata from scientific research teams; (3) measures of impact for REDCap; (4) details concerning a consortium network of domestic and international institutions collaborating on the project; and (5) strengths and limitations of the REDCap system. REDCap is currently supporting 286 translational research projects in a growing collaborative network including 27 active partner institutions.
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            Ultra-processed foods: what they are and how to identify them

            The present commentary contains a clear and simple guide designed to identify ultra-processed foods. It responds to the growing interest in ultra-processed foods among policy makers, academic researchers, health professionals, journalists and consumers concerned to devise policies, investigate dietary patterns, advise people, prepare media coverage, and when buying food and checking labels in shops or at home. Ultra-processed foods are defined within the NOVA classification system, which groups foods according to the extent and purpose of industrial processing. Processes enabling the manufacture of ultra-processed foods include the fractioning of whole foods into substances, chemical modifications of these substances, assembly of unmodified and modified food substances, frequent use of cosmetic additives and sophisticated packaging. Processes and ingredients used to manufacture ultra-processed foods are designed to create highly profitable (low-cost ingredients, long shelf-life, emphatic branding), convenient (ready-to-consume), hyper-palatable products liable to displace all other NOVA food groups, notably unprocessed or minimally processed foods. A practical way to identify an ultra-processed product is to check to see if its list of ingredients contains at least one item characteristic of the NOVA ultra-processed food group, which is to say, either food substances never or rarely used in kitchens (such as high-fructose corn syrup, hydrogenated or interesterified oils, and hydrolysed proteins), or classes of additives designed to make the final product palatable or more appealing (such as flavours, flavour enhancers, colours, emulsifiers, emulsifying salts, sweeteners, thickeners, and anti-foaming, bulking, carbonating, foaming, gelling and glazing agents).
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              Dynamics of the double burden of malnutrition and the changing nutrition reality

              The double burden of malnutrition (DBM), defined as the simultaneous manifestation of both undernutrition and overweight and obesity, affects most low-income and middle-income countries (LMICs). This Series paper describes the dynamics of the DBM in LMICs and how it differs by socioeconomic level. This Series paper shows that the DBM has increased in the poorest LMICs, mainly due to overweight and obesity increases. Indonesia is the largest country with a severe DBM, but many other Asian and sub-Saharan African countries also face this problem. We also discuss that overweight increases are mainly due to very rapid changes in the food system, particularly the availability of cheap ultra-processed food and beverages in LMICs, and major reductions in physical activity at work, transportation, home, and even leisure due to introductions of activity-saving technologies. Understanding that the lowest income LMICs face severe levels of the DBM and that the major direct cause is rapid increases in overweight allows identifying selected crucial drivers and possible options for addressing the DBM at all levels.
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                Author and article information

                Contributors
                taillie@unc.edu
                Journal
                BMC Public Health
                BMC Public Health
                BMC Public Health
                BioMed Central (London )
                1471-2458
                20 December 2022
                20 December 2022
                2022
                : 22
                : 2389
                Affiliations
                [1 ]GRID grid.10698.36, ISNI 0000000122483208, Department of Nutrition, , University of North Carolina at Chapel Hill, ; Chapel Hill, NC USA
                [2 ]GRID grid.11100.31, ISNI 0000 0001 0673 9488, CRONICAS Center of Excellence in Chronic Diseases, , Universidad Peruana Cayetano Heredia, ; Lima, Peru
                [3 ]GRID grid.10698.36, ISNI 0000000122483208, Carolina Population Center, , University of North Carolina at Chapel Hill, ; Chapel Hill, NC USA
                [4 ]GRID grid.11100.31, ISNI 0000 0001 0673 9488, School of Medicine, , Universidad Peruana Cayetano Heredia, ; Lima, Peru
                [5 ]GRID grid.1005.4, ISNI 0000 0004 4902 0432, The George Institute for Global Health, UNSW, ; Sydney, NSW Australia
                [6 ]GRID grid.10698.36, ISNI 0000000122483208, Gillings School of Global Public Health, , University of North Carolina at Chapel Hill, ; 123 W Franklin St, Ste 2107, Chapel Hill, NC 27516 USA
                Article
                14762
                10.1186/s12889-022-14762-w
                9764463
                36539775
                7c04d4fa-d3fa-42a0-81c1-ab33c9bc2857
                © The Author(s) 2022

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 30 July 2022
                : 28 November 2022
                Categories
                Research
                Custom metadata
                © The Author(s) 2022

                Public health
                nutrition policy,socioeconomic factors,sugar-sweetened beverages,taxation,obesity,peru
                Public health
                nutrition policy, socioeconomic factors, sugar-sweetened beverages, taxation, obesity, peru

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