Department of Community Health, Federal University of Ceará, Rua Prof. Costa Mendes, Fortaleza, CE, BR.
Christus Univesity Center, R. João Adolfo Gurgel, Cocó, Fortaleza, CE, BR.
Ann Glob Health. 2019 Mar 4;85(1):24. doi: 10.5334/aogh.2299.
Cross-sectional studies are fundamental studies in the practice of epidemiological science. This article aims to present in detail the methodology for conducting a series of cross-sectional studies, as well as the analysis of data through pooled data.
The series of studies are population cross-sectional studies, with statewide coverage, searching for representative sample of reproductive aged women and pre-school children in Ceará, Brazil. The sampling plan followed simple random, stratified, systematic and by conglomerates, in sequence. About 300 variables were collected. For each of the individual studies, multivariate data analysis was used to verify associations between dependent variables. For all the studies together, techniques used were trend chi-squared and pooled data analysis using linear mixed modeling procedures.
There were 6 studies in sequence, for 30 years. Among other findings, the variables income, maternal education and breastfeeding time proved to be associated with the reduction of malnutrition in children considering all the period (p values 0.013, 0.033 and 0.037, respectively).
Cross-sectional studies can be replicated at regular time series following the methodology exposed in this, even for locations with limited resources, ensuring adequate management of decisions of using federal funding aimed at achieving targeted programs to maximize the results obtained with the public resource available.
横断面研究是流行病学实践中的基础研究。本文旨在详细介绍一系列横断面研究的方法学,以及通过汇总数据进行数据分析。
该系列研究是全国性的横断面研究,对巴西塞阿拉州的育龄妇女和学龄前儿童进行了代表性抽样。抽样计划依次采用简单随机、分层、系统和聚类。共收集了约 300 个变量。对于每一项个体研究,采用多变量数据分析来检验因变量之间的关联。对于所有研究,采用趋势卡方检验和汇总数据线性混合模型程序进行分析。
共进行了 6 项研究,历时 30 年。其他发现包括,收入、母亲教育程度和母乳喂养时间等变量与儿童营养不良的减少呈正相关,考虑到整个时期(p 值分别为 0.013、0.033 和 0.037)。
即使在资源有限的地区,也可以按照本研究中阐述的方法定期复制横断面研究,以确保联邦资金决策的合理管理,这些资金旨在实现针对特定项目的目标,以最大限度地利用现有公共资源获得的结果。