title: Validation of self-reported weights and heights in the avoiding diabetes after pregnancy trial (ADAPT).
abstract: BACKGROUND
  Randomized controlled trials that test the effectiveness of mobile health-based weight loss programs are attractive to participants, funders, and researchers because of the low implementation cost, minimal participant burden, and the ability to recruit participants from longer distances. Collecting weight data from geographically dispersed participants is a challenge. Relying on participant self-report is one approach to data collection, but epidemiologic studies indicate that self-reported anthropometric data may be inaccurate.
  
  
  METHODS
  We provided women enrolled in a randomized controlled trial (RCT) of postpartum weight loss after gestational diabetes with a digital scale and training to collect and report weight via a web-based survey. To validate self-reported weights and heights, we visited 30 randomly selected women in their homes, with a reference scale and stadiometer, a mean of 34 days after the self-report. We ran linear regression models to identify characteristics that were associated with underreporting or overreporting of anthropometric measures.
  
  
  RESULTS
  Of the 30 women we visited, 11 women (37%) were assigned to the weight loss intervention group and 19 women (63%) were in the control group. Mean age was 38.5 years (SD 4.5). The overall mean difference between participants' self-reported weights and the weights obtained at their home visit was 0.70 kg (+1.92). Women assigned to the intervention group underreported their weight in comparison with the control group by 1.29 kg (95% CI -2.52, -0.06). The overall difference in collected to self-reported height was -0.56 cm (±1.91). No characteristics were associated with underreporting or overreporting of height.
  
  
  CONCLUSIONS
  Our research suggests that by providing a digital scale and developing a weight collection protocol, researchers can train women to collect and record their own study weights with reasonable validity. To achieve the level of validity required for clinical trials, researchers should consider additional strategies to assure the validity of the data.
  
  
  BACKGROUND
  NCT01923350.
authors.forename: Kathryn A
authors.initials: KA
authors.lastname: Paez
authors.affiliation: Social & Scientific Systems, Inc, Silver Spring, MD, USA. sgriffey@s-3.com.
authors.forename: Susan J
authors.initials: SJ
authors.lastname: Griffey
authors.forename: Jennifer
authors.initials: J
authors.lastname: Thompson
authors.forename: Matthew W
authors.initials: MW
authors.lastname: Gillman
mesh_terms: D000328:Adult; D001827:Body Height; D001835:Body Weight; D003625:Data Collection / Q000379:methods*; D016640:Diabetes, Gestational / Q000517:prevention & control*; D005260:Female; D006801:Humans; D011247:Pregnancy; D011897:Random Allocation; D057566:Self Report; D015431:Weight Loss