title: Prevalence and determinants of declining versus stable hemoglobin levels in whole blood donors.
abstract: BACKGROUND
  A too short recovery time after blood donation results in a gradual depletion of iron stores and a subsequent decline in hemoglobin (Hb) levels over time. This decline in Hb levels may depend on individual, unobserved characteristics of the donor.
  
  
  METHODS
  We used a data set of 5388 Dutch blood donors from the Donor InSight study. The statistical analysis is based on a Bayesian growth mixture model, which assumes that each donor belongs to one of several groups. Each group implies a different Hb trajectory, and donors with similar longitudinal trajectories belong to the same group. Analyses were performed for male and female donors separately.
  
  
  RESULTS
  For both sexes the model identified four groups of donors. Stable Hb trajectories were found among 14% of male donors and 15% of female donors; declining Hb trajectories were observed in the remaining groups of donors. The percentage of donor deferrals differed strongly between groups.
  
  
  CONCLUSIONS
  The model can be used to predict to which group a donor belongs, and this prediction can be updated after each donation. This is of high practical importance because early identification of donors with declining Hb levels could help to tailor donation intervals and to prevent iron deficiency and donor deferrals.
authors.affiliation: Department of Biostatistics, Erasmus MC, Rotterdam, the Netherlands.
authors.forename: Kazem
authors.initials: K
authors.lastname: Nasserinejad
authors.affiliation: Department of Biostatistics, Erasmus MC, Rotterdam, the Netherlands.
authors.forename: Joost
authors.initials: J
authors.lastname: van Rosmalen
authors.affiliation: Department of Donor Studies, Sanquin Research, Amsterdam, the Netherlands.
authors.forename: Katja
authors.initials: K
authors.lastname: van den Hurk
authors.affiliation: Department of Donor Studies, Sanquin Research, Amsterdam, the Netherlands.
authors.forename: Mireille
authors.initials: M
authors.lastname: Baart
authors.affiliation: Department of Epidemiology and Biostatistics and the EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands.|Department of Health Sciences, Faculty of Earth and Life Sciences, VU University, Amsterdam, the Netherlands.
authors.forename: Trynke
authors.initials: T
authors.lastname: Hoekstra
authors.affiliation: Department of Biostatistics, Erasmus MC, Rotterdam, the Netherlands.
authors.forename: Dimitris
authors.initials: D
authors.lastname: Rizopoulos
authors.affiliation: Department of Biostatistics, Erasmus MC, Rotterdam, the Netherlands.|L-Biostat, KU Leuven, Leuven, Belgium.
authors.forename: Emmanuel
authors.initials: E
authors.lastname: Lesaffre
authors.affiliation: Department of Donor Studies, Sanquin Research, Amsterdam, the Netherlands.|Department of Public Health, Academic Medical Center, Amsterdam, the Netherlands.
authors.forename: Wim
authors.initials: W
authors.lastname: de Kort
mesh_terms: D000328:Adult; D001499:Bayes Theorem; D001782:Blood Donors / Q000145:classification; D046148:Donor Selection; D005260:Female; D006454:Hemoglobins / Q000032:analysis* / Q000096:biosynthesis; D006801:Humans; D007501:Iron / Q000097:blood; D053208:Kaplan-Meier Estimate; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D009010:Monte Carlo Method; D010949:Plasma; D015995:Prevalence; D012621:Seasons; D013997:Time Factors; D055815:Young Adult
chemical_list: D006454:Hemoglobins; D007501:Iron