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NOVA 食品组的能量贡献及墨西哥人口中超加工食品消费的社会人口学决定因素。

Energy contribution of NOVA food groups and sociodemographic determinants of ultra-processed food consumption in the Mexican population.

机构信息

1Nutrition and Health Research Center,National Institute of Public Health,Cuernavaca,Morelos,Mexico.

2Núcleo de Pesquisas Epidemiológicas em Nutricão e Saúde,Universidade de São Paulo,São Paulo,SP,Brazil.

出版信息

Public Health Nutr. 2018 Jan;21(1):87-93. doi: 10.1017/S1368980017002129. Epub 2017 Sep 22.

Abstract

OBJECTIVE

To identify the energy contributions of NOVA food groups in the Mexican diet and the associations between individual sociodemographic characteristics and the energy contribution of ultra-processed foods (UPF).

DESIGN

We classified foods and beverages reported in a 24 h recall according to the NOVA food framework into: (i) unprocessed or minimally processed foods; (ii) processed culinary ingredients; (iii) processed foods; and (iv) UPF. We estimated the energy contribution of each food group and ran a multiple linear regression to identify the associations between sociodemographic characteristics and UPF energy contribution.

SETTING

Mexican National Health and Nutrition Survey 2012.

SUBJECTS

Individuals ≥1 years old (n 10 087).

RESULTS

Unprocessed or minimally processed foods had the highest dietary energy contribution (54·0 % of energy), followed by UPF (29·8 %), processed culinary ingredients (10·2 %) and processed foods (6·0 %). The energy contribution of UPF was higher in: pre-school-aged children v. other age groups (3·8 to 12·5 percentage points difference (pp)); urban areas v. rural (5·6 pp); the Central and North regions v. the South (2·7 and 8·4 pp, respectively); medium and high socio-economic status v. low (4·5 pp, in both); and with higher head of household educational level v. without education (3·4 to 7·8 pp).

CONCLUSIONS

In 2012, about 30 % of energy in the Mexican diet came from UPF. Our results showed that younger ages, urbanization, living in the North region, high socio-economic status and high head of household educational level are sociodemographic factors related to higher consumption of UPF in Mexico.

摘要

目的

确定 NOVA 食品组在墨西哥饮食中的能量贡献,以及个体社会人口特征与超加工食品(UPF)能量贡献之间的关系。

设计

我们根据 NOVA 食品框架,将 24 小时回忆中报告的食物和饮料分为:(i)未加工或最低限度加工的食物;(ii)加工烹饪成分;(iii)加工食品;和(iv)UPF。我们估计了每个食品组的能量贡献,并进行了多元线性回归,以确定社会人口特征与 UPF 能量贡献之间的关系。

地点

墨西哥国家健康和营养调查 2012 年。

对象

年龄≥1 岁的个体(n 10087)。

结果

未加工或最低限度加工的食物的饮食能量贡献最高(占能量的 54.0%),其次是 UPF(29.8%)、加工烹饪成分(10.2%)和加工食品(6.0%)。UPF 的能量贡献在以下方面更高:学龄前儿童 v. 其他年龄组(3.8 至 12.5 个百分点差异(pp));城市地区 v. 农村(5.6 pp);中北部地区 v. 南部(分别为 2.7 和 8.4 pp);中高社会经济地位 v. 低(两者均为 4.5 pp);以及家庭主要成员受教育程度较高 v. 没有教育(3.4 至 7.8 pp)。

结论

2012 年,墨西哥饮食中约 30%的能量来自 UPF。我们的结果表明,年龄较小、城市化、居住在北部地区、较高的社会经济地位和家庭主要成员较高的教育水平是与墨西哥 UPF 消费较高相关的社会人口因素。

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本文引用的文献

1
Ultra-processed foods and added sugars in the Chilean diet (2010).
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2
Consumption of ultra-processed foods predicts diet quality in Canada.
Appetite. 2017 Jan 1;108:512-520. doi: 10.1016/j.appet.2016.11.006. Epub 2016 Nov 4.
3
Ultraprocessed food consumption and risk of overweight and obesity: the University of Navarra Follow-Up (SUN) cohort study.
Am J Clin Nutr. 2016 Nov;104(5):1433-1440. doi: 10.3945/ajcn.116.135004. Epub 2016 Oct 12.
4
[Food prices in Brazil: prefer cooking to ultra-processed foods].
Cad Saude Publica. 2016 Aug 29;32(8):e00104715. doi: 10.1590/0102-311X00104715.
5
Usual Intake of Added Sugars and Saturated Fats Is High while Dietary Fiber Is Low in the Mexican Population.
J Nutr. 2016 Sep;146(9):1856S-65S. doi: 10.3945/jn.115.218214. Epub 2016 Aug 10.
7
Ultra-processed foods and the nutritional dietary profile in Brazil.
Rev Saude Publica. 2015;49:38. doi: 10.1590/S0034-8910.2015049006132. Epub 2015 Jul 10.
8
Ultra-processed food consumption in children from a Basic Health Unit.
J Pediatr (Rio J). 2015 Nov-Dec;91(6):535-42. doi: 10.1016/j.jped.2015.01.007. Epub 2015 Jun 16.
9
Consumption of ultra-processed foods and their impact on the diet of young adults.
Rev Saude Publica. 2015;49:28. doi: 10.1590/s0034-8910.2015049005572. Epub 2015 May 26.
10
Trends in consumption of ultra-processed foods and obesity in Sweden between 1960 and 2010.
Public Health Nutr. 2015 Dec;18(17):3096-107. doi: 10.1017/S1368980015000506. Epub 2015 Mar 25.

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