title: Cluster analysis of behavioural weight management strategies and associations with weight change in young women: a longitudinal analysis.
abstract: OBJECTIVE
  Maintaining a healthy weight is important for the prevention of many chronic diseases. Little is known about the strategies used by young women to manage their weight, or the effectiveness of these in preventing weight gain. We aimed to identify clusters of weight control strategies used by women and to determine the average annual weight change among women in each cluster from 2000 to 2009.
  
  
  METHODS
  Latent cluster analysis of weight control strategies reported by 8125 participants in the Australian Longitudinal Study of Women's Health. Analyses were performed in March-November 2014.
  
  
  RESULTS
  Weight control strategies were used by 79% of the women, and four unique clusters were found. The largest cluster group (39.7%) was named dieters as 90% had been on a diet in the past year, and half of these women had lost 5 kg on purpose. Women cut down on size of meals, fats and sugars and took part in vigorous physical activity. Additionally 20% had used a commercial programme. The next largest cluster (30.2%) was the healthy living group who followed the public health messages of 'eat less and move more'. The do nothing group (20%) did not actively control their weight whereas the perpetual dieters group (10.7%) used all strategies, including unhealthy behaviours. On average women gained 700 g per year (over 9 years); however, the perpetual dieters group gained significantly more weight (210 g) than the do nothing group (P<0.001).
  
  
  CONCLUSIONS
  Most women are actively trying to control their weight. The most successful approach was to follow the public health guidelines on health eating and physical activity.
authors.affiliation: Department of Primary Care Clinical Sciences, School of Health and Population Sciences, University of Birmingham, Birmingham, UK.
authors.forename: C D
authors.initials: CD
authors.lastname: Madigan
authors.affiliation: Department of Primary Care Clinical Sciences, School of Health and Population Sciences, University of Birmingham, Birmingham, UK.
authors.forename: A J
authors.initials: AJ
authors.lastname: Daley
authors.affiliation: School of Agricultural, Computational and Environmental Sciences, University of Southern Queensland, Darling Heights, Queensland, Australia.|School of Human Movement and Nutrition Sciences, University of Queensland, St Lucia, Queensland, Australia.
authors.forename: E
authors.initials: E
authors.lastname: Kabir
authors.affiliation: Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
authors.forename: P
authors.initials: P
authors.lastname: Aveyard
authors.affiliation: School of Human Movement and Nutrition Sciences, University of Queensland, St Lucia, Queensland, Australia.
authors.forename: W
authors.initials: W
authors.lastname: Brown
mesh_terms: D001315:Australia / Q000453:epidemiology; D016000:Cluster Analysis; D004032:Diet; D002149:Energy Intake; D004734:Energy Metabolism; D015444:Exercise; D005260:Female; D015438:Health Behavior; D007722:Health Knowledge, Attitudes, Practice; D006801:Humans; D008137:Longitudinal Studies; D009765:Obesity / Q000517:prevention & control / Q000523:psychology*; D010349:Patient Compliance; D011634:Public Health; D015430:Weight Gain; D016387:Women's Health; D055815:Young Adult