OBJECTIVE: To evaluate the influence of recent weight changes (weight gain, loss and cycling) on subsequent weight changes. DESIGN: Prospective cohort study with 2 y of follow-up. Data analysis with a polytomous logistic regression model. SUBJECTS: A total of 18 001 non-smoking subjects, 6689 men and 11 312 women, from the general population. MEASUREMENTS: 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. RESULTS: 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). CONCLUSION: 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.
OBJECTIVE: To evaluate the influence of recent weight changes (weight gain, loss and cycling) on subsequent weight changes. DESIGN: Prospective cohort study with 2 y of follow-up. Data analysis with a polytomous logistic regression model. SUBJECTS: A total of 18 001 non-smoking subjects, 6689 men and 11 312 women, from the general population. MEASUREMENTS: 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. RESULTS: 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). CONCLUSION: 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.
Authors: A J Søgaard; H E Meyer; L A Ahmed; L Jørgensen; A Bjørnerem; R M Joakimsen; N Emaus Journal: Osteoporos Int Date: 2012-02-07 Impact factor: 4.507
Authors: Merja Kataja-Tuomola; Jari Sundell; Satu Männistö; Mikko J Virtanen; Jukka Kontto; Demetrius Albanes; Jarmo Virtamo Journal: Eur J Epidemiol Date: 2010-03-30 Impact factor: 8.082
Authors: Daniel L Riddle; Jasvinder A Singh; William S Harmsen; Cathy D Schleck; David G Lewallen Journal: Arthritis Care Res (Hoboken) Date: 2013-05 Impact factor: 4.794