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首页> 外文会议>Australian National Health Informatics Conference >Validation of Anthropometric Measures Self-Reported in a Randomized Controlled Trial of a Web-Based Platform for Weight Loss
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Validation of Anthropometric Measures Self-Reported in a Randomized Controlled Trial of a Web-Based Platform for Weight Loss

机译：在基于Web的重量损失的基于Web的平台的随机对照试验中自我报告的人类测量措施验证

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Introduction: A great number of weight loss interventions have been delivered through digital solutions. Analysis of the effectiveness in terms of weight loss is fundamental to understand the real potential of digital technologies as tools for delivery of weight loss interventions. For this, we need accurate and reliable anthropometric data. For reasons of convenience, self-reported weight and height often replace actual measurements in these interventions. This might lead to misclassification of BMI status during selection of participants and to bias in the assessment of the outcomes. Therefore, it is fundamental to have validation studies of self-reported web-based data. Objectives: We aimed to validate online selfreported height, weight and BMI in a POEmaS trial subsample. Methods: We included 12.5% of the POEmaS' population (n=159). Anthropometric data reported on the web-platform were compared to measured data by paired T-tests. Agreement was assessed by Bland-Altman plots. Multinomial regression was used to investigate factors associated with self-reported weight validity. Results: There was no significant difference between reported and measured weight (0.4 kg, SD 1.7; p=0.13) and BMI (0.03 kg/m2, SD 0.87; p=0.06). Reported height was on average 0.4 cm (SD 1.2) higher than the measured ones (p<0.001). For all anthropometric data, >=95% of the cases were within the limits of agreement. Higher measured BMI was the only factor associated with low accuracy of weight report. Each unit increase in BMI increased the odds that the reported weight was lower than the one measured (OR 1.13; 95%CI 1.01-1.26). Discussion: Selfreported weight and BMI change showed good agreement with measured ones. Since these are the primary outcomes of the POEmaS trial, the findings of the validation study suggest that the outcomes’ accuracy is high and that it does not vary across gender, age, study group. These findings are relevant to digital health researchers and assessors and suggest that digital health interventions for weight loss might rely on self-reported assessment of outcomes. This might be particularly useful when other modes of assessment, such as anthropometry and e-scales, are not feasible or not available. However, we acknowledge that these results might not be applicable to low educated populations.
机译：简介：通过数字解决方案提供了大量的减肥干预措施。对减肥方面的有效性分析是了解数字技术的实际潜力作为交付减肥干预的工具的基础。为此，我们需要准确且可靠的人类测量数据。出于方便的原因，自我报告的体重和高度经常替代这些干预措施的实际测量。这可能导致在参与者选择期间对BMI状态进行错误分类，并在评估结果时偏见。因此，具有对自我报告的基于网络数据的验证研究是基础的。目标：我们的目标是在诗集试用子样本中验证在线Selfreworted高度，体重和BMI。方法：我们列入了12.5％的诗集（n = 159）。将网平台上报告的人体测量数据进行比较，通过配对的T检验进行测量数据。协议是由Bland-Altman Plots评估的。多项式回归用于调查与自我报告的重量有效性相关的因素。结果：报道和测量重量之间没有显着差异（0.4千克，SD 1.7; P = 0.13）和BMI（0.03kg / m 2，SD 0.87; p = 0.06）。报告的高度平均比测量值高0.4厘米（SD 1.2）（P <0.001）。对于所有人类测量数据，> = 95％的病例在协议的范围内。更高的测量BMI是与重量报告的低精度相关的唯一因素。 BMI的每个单位增加增加报告的重量低于测量的几率（或1.13; 95％CI 1.01-1.26）。讨论：自我重量和BMI变化显示与测量的重量良好。由于这些是POEMAS试验的主要结果，因此验证研究的结果表明，结果'准确性很高，并且它不会因性别，年龄，研究组而异。这些调查结果与数字健康研究人员和评估师有关，并表明减肥的数字健康干预可能依赖于自我报告的结果评估。当其他评估模式（例如人类测量法和电子尺度）不可行时，这可能特别有用。但是，我们承认这些结果可能不适用于低受过教育的人群。

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