Faculty of Medicine and Health, School of Psychology, University of Leeds, Leeds, UK.
Department of Psychology, Drexel University, Philadelphia, PA, USA.
Int J Obes (Lond). 2021 Mar;45(3):525-534. doi: 10.1038/s41366-020-00706-0. Epub 2020 Nov 3.
Weight-loss programmes often achieve short-term success though subsequent weight regain is common. The ability to identify predictive factors of regain early in the weight maintenance phase is crucial.
To investigate the associations between short-term weight variability and long-term weight outcomes in individuals engaged in a weight-loss maintenance intervention.
The study was a secondary analysis from The NoHoW trial, an 18-month weight maintenance intervention in individuals who recently lost ≥5% body weight. Eligible participants (n = 715, 64% women, BMI = 29.2 (SD 5.0) kg/m, age = 45.8 (SD 11.5) years) provided body-weight data by smart scale (Fitbit Aria 2) over 18 months. Variability in body weight was calculated by linear and non-linear methods over the first 6, 9 and 12 weeks. These estimates were used to predict percentage weight change at 6, 12, and 18 months using both crude and adjusted multiple linear regression models.
Greater non-linear weight variability over the first 6, 9 and 12 weeks was associated with increased subsequent weight in all comparisons; as was greater linear weight variability measured over 12 weeks (up to AdjR = 4.7%). Following adjustment, 6-week weight variability did not predict weight change in any model, though greater 9-week weight variability by non-linear methods was associated with increased body-weight change at 12 (∆AdjR = 1.2%) and 18 months (∆AdjR = 1.3%) and by linear methods at 18 months (∆AdjR = 1.1%). Greater non-linear weight variability measured over 12 weeks was associated with increased weight at 12 (∆AdjR = 1.4%) and 18 (∆AdjR = 2.2%) months; and 12-week linear variability was associated with increased weight at 12 (∆AdjR = 2.1%) and 18 (∆AdjR = 3.6%) months.
Body-weight variability over the first 9 and 12 weeks of a weight-loss maintenance intervention weakly predicted increased weight at 12 and 18 months. These results suggest a potentially important role in continuously measuring body weight and estimating weight variability.
减肥计划通常能在短期内取得成功,但随后的体重反弹是很常见的。因此,能够在体重维持阶段早期识别出反弹的预测因素至关重要。
研究短期体重变化与参与减肥维持干预的个体长期体重结果之间的关联。
该研究是 NoHoW 试验的二次分析,这是一项为期 18 个月的体重维持干预研究,对象是最近体重减轻≥5%的个体。符合条件的参与者(n=715,64%为女性,BMI=29.2(SD 5.0)kg/m,年龄=45.8(SD 11.5)岁)在 18 个月内通过智能秤(Fitbit Aria 2)提供体重数据。通过线性和非线性方法在前 6、9 和 12 周计算体重变化的变异性。使用未经调整和调整后的多元线性回归模型,根据这些估计值预测 6、12 和 18 个月时的体重百分比变化。
在前 6、9 和 12 周时,非直线体重变异性越大,所有比较中随后的体重增加越多;线性体重变异性越大,在 12 周时测量(最多调整后的 R2=4.7%)也是如此。在调整后,任何模型中 6 周的体重变异性都不能预测体重变化,而通过非线性方法测量的 9 周体重变异性与 12 个月(增量调整后的 R2=1.2%)和 18 个月(增量调整后的 R2=1.3%)的体重变化有关,以及通过线性方法与 18 个月(增量调整后的 R2=1.1%)的体重变化有关。在 12 周时,通过非线性方法测量的更大的非直线体重变异性与 12 个月(增量调整后的 R2=1.4%)和 18 个月(增量调整后的 R2=2.2%)的体重增加有关;而在 12 周时的线性变异性与 12 个月(增量调整后的 R2=2.1%)和 18 个月(增量调整后的 R2=3.6%)的体重增加有关。
减肥维持干预的前 9 和 12 周体重变化可微弱预测 12 个月和 18 个月时体重的增加。这些结果表明,连续测量体重和估计体重变异性可能具有重要作用。