Universidade Federal do Rio Grande do Norte. Programa de Pós-Graduação em Saúde Coletiva. Natal, RN, Brasil.
Universidade Federal do Rio Grande do Norte. Departamento de Odontologia. Natal, RN, Brasil.
Rev Saude Publica. 2024 Jul 26;58:28. doi: 10.11606/s1518-8787.2024058005505. eCollection 2024.
The aim of this study was to analyze the validity of self-reported anthropometric measurements (weight and height) for classifying the nutritional status of Brazilian adults and elderly people using data from the 2019 National Health Survey (PNS). The PNS sample is made up of permanent private households from all of Brazil's federative units and this is a cross-sectional study in which 6,571 records were identified with measured and reported data, with no missing data for one variable being identified when in the presence of another. Validation was carried out with 6,381 data after removing atypical data. The variables used for stratification were: gender, age, race/color, schooling, and income, and the weighted Kappa Coefficient and the Intraclass Correlation Coefficient (ICC) were used to analyze agreement between the nutritional status categories. Accuracy was analyzed based on sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). For construct validity, a Poisson regression was performed for each outcome (measured and self-reported), with the independent variables "gender", "color/race", "schooling", and "family income". All the analyses showed positive results for validation. There was greater reproducibility among adults (18 to 59 years old) compared to the elderly and among men compared to women. This validation indicates a concrete possibility of carrying out an association of observational studies using reported nutritional status as the outcome variable, as an efficient strategy which could minimize the operational difficulties often encountered.
本研究旨在分析巴西成年人和老年人自我报告的人体测量学数据（体重和身高）的有效性，这些数据用于使用 2019 年国家健康调查（PNS）的数据对营养状况进行分类。PNS 样本由巴西所有联邦单位的私人常住家庭组成，这是一项横断面研究，共确定了 6571 条具有测量和报告数据的记录，当存在其他变量时，没有一条记录缺失一个变量。在去除非典型数据后，对 6381 条数据进行了验证。用于分层的变量包括：性别、年龄、种族/肤色、教育程度和收入，加权 Kappa 系数和组内相关系数（ICC）用于分析营养状况分类之间的一致性。根据敏感性、特异性、阳性预测值（PPV）和阴性预测值（NPV）分析准确性。对于构效关系，对每个结果（测量和自我报告）进行泊松回归，自变量为“性别”、“肤色/种族”、“教育程度”和“家庭收入”。所有分析均表明验证结果为阳性。成年人（18 至 59 岁）的重现性高于老年人，男性高于女性。该验证表明，使用报告的营养状况作为因变量进行观察性研究的关联具有具体的可能性，这是一种有效的策略，可以最大限度地减少经常遇到的操作困难。
