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如何在线自我报告的体重与图像捕获的体重相比? 一项比较性研究使用了年轻成年人在线纵向研究的数据
Megan C Whatnall1, Katerina Z Kolokotroni2, Therese E Fozard2
1School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, NSW, Australia; Food and Nutrition Program, Hunter Medical Research Institute, Newcastle, NSW, Australia.
The American journal of clinical nutrition
|May 28, 2023
概括
在线自我报告的体重与年轻成年人中图像捕获的体重密切匹配,显示出人口统计学之间的强烈相关性. 这验证了基于图像的方法,用于在数字健康研究中收集体重数据.
科学领域:
- 流行病学 流行病学
- 医疗信息学 医疗信息学
- 生物统计学 生物统计学
背景情况:
- 准确的人类测量测量对于流行病学研究和临床实践至关重要.
- 传统上,自我报告的体重是根据个人测量进行验证的.
- 在线数据收集为健康研究提供了一个可扩展的替代方案.
研究的目的:
- 为了比较在线自我报告的体重与年轻成年人体重图像的体重图像.
- 为了分析这些身体质量指数 (BMI),性别,国家和年龄的比较.
- 确定与提供体重图像相关的人口因素.
主要方法:
- 从一项为期12个月的纵向研究中对基线数据进行截面分析.
- 通过Prolific平台从澳大利亚和英国的年轻成年人收集的在线调查数据.
- 统计测试包括威尔科克森签名等级测试,皮尔森相关性和布兰德-阿尔特曼图表.
主要成果:
- 自我报告的体重和图像捕获的体重显著不同,但有很强的相关性 (r = 0.983).
- 在BMI,性别,国家和年龄组 (r > 0.870) 中保持了很高的相关性.
- 体重指数在30-39.9公斤/平方米之间的人不太可能提供体重图像.
结论:
- 基于图像的体重收集方法与在线研究环境中自我报告的体重一致.
- 这证实了数字健康研究中对体重数据的图像捕获的使用.
- 这些发现支持在线人类识别数据收集的可靠性.
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