title: Tackling the growth of the obesity literature: obesity evidence spreads across many journals.
abstract: OBJECTIVE
  This study identified the journals with the highest yield of clinical obesity research articles and surveyed the scatter of such studies across journals. The study exemplifies an approach to establish a journal collection that is likely to contain most new knowledge about a field.
  
  
  METHODS
  All original studies that were cited in 40 systematic reviews about obesity topics ('included studies') were compiled and journal titles in which they were published were extracted. The journals were ranked by the number of included studies. The highest-yielding journals for clinical obesity and the scatter across journal titles were determined. A subset of these journals was created in MEDLINE (PubMed) to test search recall and precision for high-quality studies of obesity treatment (that is, articles that pass predetermined methodology criteria, including random allocation of participants to comparison groups, assessment of clinical outcomes, and at least 80% follow-up).
  
  
  RESULTS
  Articles in 252 journals were cited in the systematic reviews. The three highest-yielding journals specialized in obesity, but they published only 19.2% of the research, leaving 80.8% scattered across 249 non-obesity journals. The MEDLINE journal subset comprised 241 journals (11 journals were not indexed in MEDLINE) and included 82% of the clinical obesity research articles retrieved by a search for high-quality treatment studies ('recall' of 82%). Of the articles retrieved, 11% were about clinical obesity care ('precision' of 11%), compared with precision of 6% for obesity treatment studies in the full MEDLINE database.
  
  
  CONCLUSIONS
  Obesity journals captured only a small proportion of the literature on clinical obesity care. Those wishing to keep up in this field will need to develop more inclusive strategies than reading these specialty journals. A journal subset based on these findings may be useful when searching large electronic databases to increase search precision.
authors.affiliation: Health Information Research Unit, Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada.
authors.forename: L A
authors.initials: LA
authors.lastname: Baier
authors.forename: N L
authors.initials: NL
authors.lastname: Wilczynski
authors.forename: R B
authors.initials: RB
authors.lastname: Haynes
mesh_terms: D015706:Bibliometrics; D004059:Diffusion of Innovation; D019317:Evidence-Based Medicine / Q000706:statistics & numerical data*; D006801:Humans; D009765:Obesity; D010506:Periodicals as Topic / Q000706:statistics & numerical data*; D012106:Research / Q000706:statistics & numerical data