title: The prevalence of low serum zinc and copper levels and dietary habits associated with serum zinc and copper in 12- to 36-month-old children from low-income families at risk for iron deficiency.
abstract: OBJECTIVE
  Iron and zinc share common food sources, and children at risk of iron deficiency may also develop zinc deficiency. We determined the prevalence of zinc and copper deficiency and examined factors associated with serum zinc and copper in young children from low-income families at risk of iron deficiency.
  
  
  METHODS
  A cross-sectional study design was used to assess serum zinc and copper, along with an interview-assisted survey to assess factors associated with serum zinc and copper in a convenience sample.
  
  
  METHODS
  Participants were 435 children aged 12 to 36 months recruited from select clinics of the Special Supplemental Nutrition Program for Women, Infants, and Children in Contra Costa and Tulare Counties, California.
  
  
  METHODS
  Frequencies were used to report prevalence. Multiple linear regressions were conducted to examine factors associated with serum zinc and copper, controlling for age, sex, and ethnicity.
  
  
  RESULTS
  The prevalence of low serum zinc level (<70 microg/dL [<10.7 micromol/L]) was 42.8%, and low serum copper level (<90 microg/dL [<14.2 micromol/L]) was <1%. Mean+/-standard deviation of serum copper was 150+/-22 microg/dL (23.6+/-3.5 micromol/L) and 140+/-24 microg/dL (22.1+/-3.8 micromol/L) for anemic and non-anemic children, respectively (t test, P=0.026). In multiple linear regression consumption of sweetened beverages was negatively associated with serum zinc level, and consumption of >15 g/day meat was positively associated with serum zinc level, whereas current consumption of breast milk and >15 g/day beans were positively associated with serum copper level.
  
  
  CONCLUSIONS
  The prevalence of low serum zinc concentration in the sample was high, and warrants further investigation amongst vulnerable populations.
authors.affiliation: Department of Nutrition, University of California, Davis, California, USA.
authors.forename: Julie M
authors.initials: JM
authors.lastname: Schneider
authors.forename: Mary L
authors.initials: ML
authors.lastname: Fujii
authors.forename: Catherine L
authors.initials: CL
authors.lastname: Lamp
authors.forename: Bo
authors.initials: B
authors.lastname: Lönnerdal
authors.forename: Sheri
authors.initials: S
authors.lastname: Zidenberg-Cherr
mesh_terms: D000367:Age Factors; D018798:Anemia, Iron-Deficiency / Q000097:blood* / Q000453:epidemiology; D001942:Breast Feeding; D002140:California / Q000453:epidemiology; D002675:Child, Preschool; D003300:Copper / Q000008:administration & dosage / Q000097:blood* / Q000172:deficiency; D003430:Cross-Sectional Studies; D005260:Female; D005522:Food Services; D006630:Hispanic or Latino / Q000706:statistics & numerical data; D006801:Humans; D007223:Infant; D007407:Interviews as Topic; D007501:Iron / Q000008:administration & dosage / Q000097:blood; D000090463:Iron Deficiencies; D016014:Linear Models; D008297:Male; D015596:Nutrition Assessment; D009752:Nutritional Status; D015995:Prevalence; D018570:Risk Assessment; D012307:Risk Factors; D012737:Sex Factors; D015032:Zinc / Q000008:administration & dosage / Q000097:blood* / Q000172:deficiency
chemical_list: D003300:Copper; D007501:Iron; D015032:Zinc