Kroke A, Liese A D, Schulz M, Bergmann M M, Klipstein-Grobusch K, Hoffmann K, Boeing H
German Institute of Human Nutrition, Department of Epidemiology, Potsdam-Rehbruecke, Germany.
Int J Obes Relat Metab Disord. 2002 Mar;26(3):403-9. doi: 10.1038/sj.ijo.0801920.
To evaluate the influence of recent weight changes (weight gain, loss and cycling) on subsequent weight changes.
Prospective cohort study with 2 y of follow-up. Data analysis with a polytomous logistic regression model.
A total of 18 001 non-smoking subjects, 6689 men and 11 312 women, from the general population.
Body height and weight measurements and interview data on lifestyle habits and medical history at baseline. For follow-up, self-administered questionnaires for assessment of body weight and incident diseases.
Recent changes in body weight, that is weight gain, weight loss and weight cycling, were significant predictors of subsequent weight changes in both men and women after controlling for age, baseline BMI and several lifestyle and behavioural characteristics as potential confounding factors. Weight cycling before baseline was the strongest predictor of subsequent large weight gain (> or =2 kg) with an odds ratio (OR) of 4.84 (95% confidence interval (CI) 3.34-7.02) in men. In women, prior weight loss was the strongest predictor of subsequent large weight gain (OR 4.77; 95% CI 3.63-6.03), followed by weight cycling (OR 3.02; 95% CI 2.15-4.25).
These data indicate the need for thorough weight history assessment to identify those who are most likely to gain weight. Effective weight control before the development of obesity or after intentional weight loss due to obesity should be a primary goal in the management of obesity.
评估近期体重变化（体重增加、减少及波动）对后续体重变化的影响。
随访2年的前瞻性队列研究。采用多分类逻辑回归模型进行数据分析。
来自普通人群的18001名非吸烟受试者，其中男性6689名，女性11312名。
在基线时测量身高和体重，并收集有关生活方式习惯和病史的访谈数据。随访时，通过自行填写问卷评估体重和新发疾病。
在将年龄、基线体重指数以及一些生活方式和行为特征作为潜在混杂因素进行控制后，近期体重变化，即体重增加、体重减少和体重波动，是男性和女性后续体重变化的显著预测因素。基线前的体重波动是男性后续大幅体重增加（≥2千克）的最强预测因素，优势比（OR）为4.84（95%置信区间（CI）3.34 - 7.02）。在女性中，先前体重减轻是后续大幅体重增加的最强预测因素（OR 4.77；95% CI 3.63 - 6.03），其次是体重波动（OR 3.02；95% CI 2.15 - 4.25）。
这些数据表明需要全面评估体重史，以识别那些最有可能体重增加的人。在肥胖发生之前或因肥胖导致有意减重后进行有效的体重控制，应成为肥胖管理的首要目标。
