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J-shapedness: an often missed, often miscalculated relation: the example of weight and mortality
  1. Sissi Cao1,
  2. Rahim Moineddin2,
  3. Marcelo L Urquia3,
  4. Fahad Razak4,5,6,7,
  5. Joel G Ray8
  1. 1Schulich School of Medicine and Dentistry, University of Western Ontario, London, Ontario, Canada
  2. 2Department of Family and Community Medicine and Institute for Clinical Evaluative Sciences, University of Toronto, Toronto, Canada
  3. 3Li Ka Shing Knowledge Institute, St. Michael's Hospital, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
  4. 4Division of General Internal Medicine, St. Michael's Hospital
  5. 5Scientist in the Keenan Research Centre, Li Ka Shing Knowledge Institute, St. Michael's Hospital
  6. 6Department of Medicine, University of Toronto
  7. 7Bell Fellow, Harvard Center for Population and Development Studies
  8. 8Departments of Medicine, Obstetrics & Gynecology and Health Policy Management & Evaluation, St. Michael's Hospital, University of Toronto, Toronto, Ontario, Canada
  1. Correspondence to Dr Joel G Ray, Department of Medicine, St. Michael's Hospital, 30 Bond Street, Toronto, Ontario, Canada M5B 1W8; rayj{at}


We present three considerations in analysing the association between weight and mortality, as well as other relations that might be non-linear in nature. First, authors must graphically plot their independent and dependent variables in a continuous manner. Second, authors should assess the shape of that relation, and note its shape. If it is non-linear, and specifically, J-shaped or U-shaped, careful consideration should be given to using the ‘best’ statistical model, of which multivariate fractional polynomial regression is a reasonable choice. Authors should also refrain from truncating their data to avoid dealing with non-linear relations.

  • Perinatal Epidemiology
  • Birth Weight
  • Clinical epidemiology
  • Epidemiology
  • Obesity

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