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将诺瓦食物分类应用于2017 - 2018年家庭预算调查:监测对巴西人口膳食指南建议的遵循情况。

Application of the Nova food classification to the 2017-2018 Household Budget Survey: monitoring adherence to the recommendations of the Dietary Guidelines for the Brazilian Population.

作者信息

Cruz Gabriela Lopes da, Andrade Giovanna Calixto, Rauber Fernanda, Levy Renata Bertazzi, Louzada Maria Laura da Costa

机构信息

Universidade de São Paulo, Faculdade de Saúde Pública, Departamento de Nutrição, São Paulo, SP, Brazil.

Universidade de São Paulo, Núcleo de Pesquisas Epidemiológicas em Nutrição e Saúde, São Paulo, SP, Brazil.

出版信息

Epidemiol Serv Saude. 2025 May 12;34:e20240369. doi: 10.1590/S2237-96222025v34e20240369.en. eCollection 2025.

DOI:10.1590/S2237-96222025v34e20240369.en
PMID:40366948
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12077547/
Abstract

OBJECTIVE

To describe the food categorization method of the 2017-2018 Household Budget Survey as per the Nova classification, bringing transparency and replicability to the process of monitoring adherence to the recommendations of the Dietary Guidelines for the Brazilian Population.

METHODS

The foods reported in the Survey were classified in four stages, namely: identification of culinary preparations and items composed of more than one food; determination of the recipe for culinary preparations and items to be disaggregated; application of the Nova classification; sensitivity analysis.

RESULTS

After disaggregation, 1,856 items were classified according to the Nova classification, consisting of 1,050 unprocessed or minimally processed foods, 54 processed culinary ingredients, 160 processed foods and 592 ultra-processed foods. Foods whose classification raised questions during the accounted for 4% of the total dietary energy. The contribution of ultra-processed food to total caloric intake varied from 19.7% (95% confidence interval [95%CI] 19.3; 20.1) to 17.7% (95%CI 17.4; 18.1) after conducting sensitivity analysis.

CONCLUSION

Using a standardized method to apply the Nova classification to the Household Budget Survey was effective and led to estimates whose uncertainties minimally affected the overall results. The methodology presented can be replicated in future editions of the Household Budget Survey and other food consumption studies, strengthening food and nutritional surveillance as applied to the Dietary Guidelines.

摘要

目的

根据新星分类法描述2017 - 2018年家庭预算调查的食物分类方法,为监测巴西人口饮食指南建议的遵循情况提供透明度和可重复性。

方法

调查中报告的食物分类分四个阶段进行,即:识别烹饪制剂和由多种食物组成的项目;确定烹饪制剂和待分解项目的食谱;应用新星分类法;敏感性分析。

结果

分解后,根据新星分类法对1856个项目进行了分类,包括1050种未加工或最低限度加工的食物、54种加工烹饪原料、160种加工食品和592种超加工食品。分类过程中存在疑问的食物占总膳食能量的4%。进行敏感性分析后,超加工食品对总热量摄入的贡献从19.7%(95%置信区间[95%CI] 19.3;20.1)降至17.7%(95%CI 17.4;18.1)。

结论

使用标准化方法将新星分类法应用于家庭预算调查是有效的,且得出的估计值其不确定性对总体结果的影响最小。所提出的方法可在家庭预算调查的未来版本和其他食物消费研究中复制,加强应用于饮食指南的食物和营养监测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5923/12077547/46a616e83062/2237-9622-ress-34-e20240369-f2-pt.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5923/12077547/487e17d62a00/2237-9622-ress-34-e20240369-f1-en.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5923/12077547/6434b5fb81f1/2237-9622-ress-34-e20240369-f2-en.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5923/12077547/fbe593477d27/2237-9622-ress-34-e20240369-f1-pt.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5923/12077547/46a616e83062/2237-9622-ress-34-e20240369-f2-pt.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5923/12077547/487e17d62a00/2237-9622-ress-34-e20240369-f1-en.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5923/12077547/6434b5fb81f1/2237-9622-ress-34-e20240369-f2-en.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5923/12077547/fbe593477d27/2237-9622-ress-34-e20240369-f1-pt.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5923/12077547/46a616e83062/2237-9622-ress-34-e20240369-f2-pt.jpg

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