A new, developmentally-sensitive measure of weight suppression.

A new, developmentally-sensitive measure of weight suppression.
复制标题

一种新的、对发育敏感的体重抑制措施。

DOI:
10.1016/j.appet.2021.105231
复制
发表时间:
2021-08-01
期刊:
影响因子:
5.4
通讯作者:
Lowe MR
Lowe MR
中科院分区:
医学2区
文献类型:
--
作者:
Singh S;Apple DE;Zhang F;Niu X;Lowe MR

文献摘要

被引文献

相似文献

体重抑制(WS)已被证明与饮食行为、精神病理和饮食失调预后的许多指标相关。然而,由于WS的测量传统上是简单地用成人身高时的过去最高体重减去当前体重,这种计算对于大多数饮食失调患者来说是有问题的,他们通常在青春期达到过去的最高体重。在这里,我们提出了一种新的计算WS的方法来解决这一缺点,称为“发育体重抑制”(DWS),并提供了一个基于web的计算工具。DWS计算为一个人的最高发病前z-BMI(即BMI z-score)与当前z-BMI之间的差值。根据疾病控制中心(2010年)公开提供的LMS参数,使用Cole的λ -mu-sigma (LMS)方法计算z- bmi。一个基于网络的用户界面可在https://niuxin.shinyapps.io/devws/上获得,使其计算更容易,研究人员更容易采用。通过使用z- bmi代替体重,DWS对年龄、身高和性别等发育相关因素更加敏感。初步研究结果表明,与传统计算的WS相比,DWS与饮食病理和体重减轻的生物反应的关系更密切,尽管需要更多的研究来验证这一假设。
Weight suppression (WS) has demonstrated associations with numerous indices of eating behavior, psychopathology and eating disorder prognosis. However, because WS has traditionally been measured as a simple subtraction of current weight from highest past weight at adult height, this calculation is problematic for most individuals with disordered eating, who usually reach their highest past weight during adolescence. Here we propose a new method for computing WS to address this shortcoming, termed “developmental weight suppression” (DWS), and provide a web-based tool for ease of calculation. DWS is calculated as the difference between one’s highest premorbid z-BMI (i.e., BMI z-score), and current z-BMI. z-BMIs were calculated using Cole’s lambda-mu-sigma (LMS) approach, in accordance with LMS parameters publicly available from the Center for Disease Control (2010). A web-based user interface is available at https://niuxin.shinyapps.io/devws/, making its computation easier and its adoption by researchers simpler. By using z-BMIs in place of weights, DWS is more sensitive to the developmentally-relevant factors of age, height, and sex. Preliminary findings suggest that DWS is more strongly related to measures of eating pathology and biological reactions to weight loss than traditionally-computed WS, although more research is needed to test this hypothesis.