基于Nova分类的两个饮食质量评分的描述和性能
Caroline Dos Santos Costa1, Francine Silva Dos Santos1,2, Kamila Tiemann Gabe1,3
1Universidade de São Paulo. Faculdade de Saúde Pública. Núcleo de Pesquisas Epidemiológicas em Nutrição e Saúde. São Paulo, SP, Brasil.
Revista de saude publica
|November 28, 2024
概括
两个新的饮食质量评分有效地衡量了巴西未加工或微加工的全植物食品和超加工食品的摄入量. 这些经过验证的工具可以监测人口的饮食质量,并为公共卫生战略提供信息.
科学领域:
- 营养流行病学 营养流行病学
- 公共卫生营养 公共卫生营养
- 食品系统分类食品系统分类
背景情况:
- 饮食质量评估对公共健康至关重要.
- 诺瓦分类系统根据加工水平对食品进行分类.
- 需要低负荷工具来评估遵守健康饮食模式.
研究的目的:
- 引入和验证两种低负担饮食质量评分.
- 评估分数能够反映饮食中未加工或最小加工的全植物食品 (WPF) 和超加工食品 (UPF) 的比例.
- 用NutriNet-巴西队列评估巴西人口中这些分数的表现.
主要方法:
- 使用NutriNet-巴西队列数据进行横截面研究.
- 基于简短的3分钟问卷 (Nova24hScreener) 开发两个分数 (Nova-WPF和Nova-UPF).
- 用得分推导的饮食摄入量与详细的24小时饮食回忆进行比较,以验证.
主要成果:
- 诺瓦-WPF和诺瓦-UPF的分数都与相应的饮食能量摄入量 (p < 0.001) 有直接的线性关系.
- 在得分间隔和实际饮食摄入量之间观察到实质性的一致性 (Nova-WPF PABAK=0.72; Nova-UPF PABAK=0.79).
- 高可靠性表明得分准确地代表了饮食模式.
结论:
- 开发的Nova-WPF和Nova-UPF评分是评估巴西饮食质量的有效工具.
- 这些分数表明,在反映未经加工/最小加工的全植物食品和超加工食品的摄入量方面表现良好.
- 这些分数适合在人口层面评估和监测饮食质量.
相关概念视频
Expected Frequencies in Goodness-of-Fit Tests
2.5K
A goodness-of-fit test is conducted to determine whether the observed frequency values are statistically similar to the frequencies expected for the dataset. Suppose the expected frequencies for a dataset are equal such as when predicting the frequency of any number appearing when casting a die. In that case, the expected frequency is the ratio of the total number of observations (n) to the number of categories (k).
2.5K
Classification of Systems-II
134
Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
134
Goodness-of-Fit Test
3.3K
The goodness-of-fit test is a type of hypothesis test which determines whether the data "fits" a particular distribution. For example, one may suspect that some anonymous data may fit a binomial distribution. A chi-square test (meaning the distribution for the hypothesis test is chi-square) can be used to determine if there is a fit. The null and alternative hypotheses may be written in sentences or stated as equations or inequalities. The test statistic for a goodness-of-fit test is given as...
3.3K
Assessment of the Gastrointestinal System II: Health Perception Pattern
76
Assessing the gastrointestinal (GI) system is a complex process that begins with collecting subjective data. This data, collected through patient interviews, provides crucial insights into the patient's health history, perception patterns, and lifestyle habits, all contributing significantly to GI health.
Health Perception Patterns
Health perception patterns offer valuable insights into a patient's lifestyle habits and how they may impact their GI health. These patterns include:
Health Perception Patterns
Health perception patterns offer valuable insights into a patient's lifestyle habits and how they may impact their GI health. These patterns include:
76
Review and Preview
6.9K
In statistics, several tools are used to interpret the data. Measures of central tendency represent the characteristics of the data, such as mean, median, and mode. Additionally, measures of variance like standard deviation and range are used to find the spread of data from the mean. Relative standing measures the distance between data locations. Commonly used measures of relative standings are percentile, z score, and quartiles.
Percentiles are a type of fractile that partition data into...
Percentiles are a type of fractile that partition data into...
6.9K
Nominal Level of Measurement
27.8K
The way a set of data is measured is called its level of measurement. Correct statistical procedures depend on a researcher being familiar with levels of measurement. Not every statistical operation can be used with every set of data. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
The data that cannot be measured but can be grouped into categories fall under the nominal level of measurement. Data that is measured using a nominal...
The data that cannot be measured but can be grouped into categories fall under the nominal level of measurement. Data that is measured using a nominal...
27.8K


