The University of Adelaide, Adelaide, SA, Australia,
Int J Public Health. 2013 Oct;58(5):683-93. doi: 10.1007/s00038-013-0484-z. Epub 2013 Jul 23.
This review evaluates existing co-benefit models for emission and health outcomes of counterfactual scenarios of reduced meat consumption at a population level.
A novel assessment process was developed, combining selected measures from the Cochrane Review quality assessment tools, from the PRISMA checklist, and model quality measures identified by the authors during the preliminary phases of the review process.
Four emission models and three health outcome models have been identified which show great variation in model characteristics and qualities. The estimated counterfactual scenario emission effects presented in the included studies ranged from a reduction of <3-30 % and reduction in the burden of disease ranged from 1 to 16 %. Meta-analysis could not be conducted due to high heterogeneity of model characteristics.
All co-benefit studies estimated that reducing population meat consumption could reduce greenhouse gas emissions and the burden of disease. However, important attention must be paid to nutrition balance and a systematic approach in input and output attribute parameters is recommended for better model quality.
本综述评估了现有的协同效益模型，这些模型用于评估人群层面减少肉类消费的反事实情景对排放和健康结果的影响。
开发了一种新的评估流程，结合了 Cochrane 综述质量评估工具、PRISMA 清单以及作者在综述过程初步阶段确定的模型质量措施中选定的措施。
确定了四个排放模型和三个健康结果模型，这些模型在模型特征和质量方面存在很大差异。纳入研究中估计的反事实情景排放效应范围从减少<3-30%不等，疾病负担减少范围从 1 到 16%不等。由于模型特征的高度异质性，无法进行荟萃分析。
所有协同效益研究都估计减少人群肉类消费可以减少温室气体排放和疾病负担。然而，必须高度关注营养平衡，并建议采用系统方法输入和输出属性参数，以提高模型质量。
