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成功的肥胖症登记处的基本数据集特征:一项系统评价。

Essential dataset features in a successful obesity registry: a systematic review.

作者信息

Nosrati Mina, Seifi Najmeh, Hosseini Nafiseh, Ferns Gordon A, Kimiafar Khalil, Ghayour-Mobarhan Majid

机构信息

International UNESCO Center for Health-Related Basic Sciences and Human Nutrition, Mashhad University of Medical Sciences, Mashhad, Iran.

Department of Nutrition, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.

出版信息

Int Health. 2025 Jan 3;17(1):8-22. doi: 10.1093/inthealth/ihae017.

Abstract

BACKGROUND

The prevalence of obesity and the diversity of available treatments makes the development of a national obesity registry desirable. To do this, it is essential to design a minimal dataset to meet the needs of a registry. This review aims to identify the essential elements of a successful obesity registry.

METHODS

We conducted a systematic literature review adhering to the Preferred Reporting Items for Systematic Review and Meta-Analysis recommendations. Google Scholar, Scopus and PubMed databases and Google sites were searched to identify articles containing obesity or overweight registries or datasets of obesity. We included English articles up to January 2023.

RESULTS

A total of 82 articles were identified. Data collection of all registries was carried out via a web-based system. According to the included datasets, the important features were as follows: demographics, anthropometrics, medical history, lifestyle assessment, nutritional assessment, weight history, clinical information, medication history, family medical history, prenatal history, quality-of-life assessment and eating disorders.

CONCLUSIONS

In this study, the essential features in the obesity registry dataset were demographics, anthropometrics, medical history, lifestyle assessment, nutritional assessment, weight history and clinical analysis items.

摘要

背景

肥胖的患病率以及现有治疗方法的多样性使得建立一个全国性肥胖登记系统成为必要。要做到这一点,设计一个满足登记系统需求的最小数据集至关重要。本综述旨在确定成功的肥胖登记系统的基本要素。

方法

我们按照系统评价和Meta分析的首选报告项目建议进行了系统的文献综述。检索了谷歌学术、Scopus和PubMed数据库以及谷歌网站,以识别包含肥胖或超重登记系统或肥胖数据集的文章。我们纳入了截至2023年1月的英文文章。

结果

共识别出82篇文章。所有登记系统的数据收集均通过基于网络的系统进行。根据纳入的数据集,重要特征如下:人口统计学、人体测量学、病史、生活方式评估、营养评估、体重史、临床信息、用药史、家族病史、产前史、生活质量评估和饮食失调。

结论

在本研究中,肥胖登记系统数据集中的基本特征是人口统计学、人体测量学、病史、生活方式评估、营养评估、体重史和临床分析项目。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4bef/11697092/bc390dea8684/ihae017fig1.jpg

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