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dc.contributor.author
Alcaraz, Andrea
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Pichón-riviere, Andres
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Palacios, Alfredo
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Bardach, Ariel Esteban
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Balan, Dario Javier
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Perelli, Lucas
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Augustovski, Federico Ariel
dc.contributor.author
Ciapponi, Agustín
dc.date.available
2023-09-19T17:38:29Z
dc.date.issued
2021-12
dc.identifier.citation
Alcaraz, Andrea; Pichón-riviere, Andres; Palacios, Alfredo; Bardach, Ariel Esteban; Balan, Dario Javier; et al.; Sugar sweetened beverages attributable disease burden and the potential impact of policy interventions: a systematic review of epidemiological and decision models; BioMed Central; BMC Public Health; 21; 1; 12-2021; 1-11
dc.identifier.issn
1471-2458
dc.identifier.uri
http://hdl.handle.net/11336/212145
dc.description.abstract
Background: Around 184,000 deaths per year could be attributable to sugar-sweetened beverages (SSBs) consumption worldwide. Epidemiological and decision models are important tools to estimate disease burden. The purpose of this study was to identify models to assess the burden of diseases attributable to SSBs consumption or the potential impact of health interventions. Methods: We carried out a systematic review and literature search up to August 2018. Pairs of reviewers independently selected, extracted, and assessed the quality of the included studies through an exhaustive description of each model’s features. Discrepancies were solved by consensus. The inclusion criteria were epidemiological or decision models evaluating SSBs health interventions or policies, and descriptive SSBs studies of decision models. Studies published before 2003, cost of illness studies and economic evaluations based on individual patient data were excluded. Results: We identified a total of 2766 references. Out of the 40 included studies, 45% were models specifically developed to address SSBs, 82.5% were conducted in high-income countries and 57.5% considered a health system perspective. The most common model’s outcomes were obesity/overweight (82.5%), diabetes (72.5%), cardiovascular disease (60%), mortality (52.5%), direct medical costs (57.35%), and healthy years -DALYs/QALYs- (40%) attributable to SSBs. 67.5% of the studies modelled the effect of SSBs on the outcomes either entirely through BMI or through BMI plus diabetes independently. Models were usually populated with inputs from national surveys -such us obesity prevalence, SSBs consumption-; and vital statistics (67.5%). Only 55% reported results by gender and 40% included children; 30% presented results by income level, and 25% by selected vulnerable groups. Most of the models evaluated at least one policy intervention to reduce SSBs consumption (92.5%), taxes being the most frequent strategy (75%). Conclusions: There is a wide range of modelling approaches of different complexity and information requirements to evaluate the burden of disease attributable to SSBs. Most of them take into account the impact on obesity, diabetes and cardiovascular disease, mortality, and economic impact. Incorporating these tools to different countries could result in useful information for decision makers and the general population to promote a deeper implementation of policies to reduce SSBs consumption.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
BioMed Central
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by/2.5/ar/
dc.subject
BURDEN OF DISEASE
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DECISION MODELS
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ECONOMIC EVALUATIONS
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EPIDEMIOLOGICAL MODELS
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HEALTH POLICIES
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SUGAR SWEETENED BEVERAGES (SSBS)
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Otras Ciencias de la Salud
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Ciencias de la Salud
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CIENCIAS MÉDICAS Y DE LA SALUD
dc.title
Sugar sweetened beverages attributable disease burden and the potential impact of policy interventions: a systematic review of epidemiological and decision models
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2023-09-19T13:10:54Z
dc.journal.volume
21
dc.journal.number
1
dc.journal.pagination
1-11
dc.journal.pais
Reino Unido
dc.journal.ciudad
Londres
dc.description.fil
Fil: Alcaraz, Andrea. Instituto de Efectividad Clínica y Sanitaria; Argentina
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Fil: Pichón-riviere, Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Epidemiología y Salud Pública. Instituto de Efectividad Clínica y Sanitaria. Centro de Investigaciones en Epidemiología y Salud Pública; Argentina
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Fil: Palacios, Alfredo. Instituto de Efectividad Clínica y Sanitaria; Argentina
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Fil: Bardach, Ariel Esteban. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Epidemiología y Salud Pública. Instituto de Efectividad Clínica y Sanitaria. Centro de Investigaciones en Epidemiología y Salud Pública; Argentina
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Fil: Balan, Dario Javier. Instituto de Efectividad Clínica y Sanitaria; Argentina
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Fil: Perelli, Lucas. Instituto de Efectividad Clínica y Sanitaria; Argentina
dc.description.fil
Fil: Augustovski, Federico Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Epidemiología y Salud Pública. Instituto de Efectividad Clínica y Sanitaria. Centro de Investigaciones en Epidemiología y Salud Pública; Argentina
dc.description.fil
Fil: Ciapponi, Agustín. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Epidemiología y Salud Pública. Instituto de Efectividad Clínica y Sanitaria. Centro de Investigaciones en Epidemiología y Salud Pública; Argentina
dc.journal.title
BMC Public Health
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-021-11046-7
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1186/s12889-021-11046-7
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