title: Birthweight Related Factors in Northwestern Iran: Using Quantile Regression Method.
abstract: BACKGROUND
  Birthweight is one of the most important predicting indicators of the health status in adulthood. Having a balanced birthweight is one of the priorities of the health system in most of the industrial and developed countries. This indicator is used to assess the growth and health status of the infants. The aim of this study was to assess the birthweight of the neonates by using quantile regression in Zanjan province.
  
  
  METHODS
  This analytical descriptive study was carried out using pre-registered (March 2010 - March 2012) data of neonates in urban/rural health centers of Zanjan province using multiple-stage cluster sampling. Data were analyzed using multiple linear regressions andquantile regression method and SAS 9.2 statistical software.
  
  
  RESULTS
  From 8456 newborn baby, 4146 (49%) were female. The mean age of the mothers was 27.1±5.4 years. The mean birthweight of the neonates was 3104 ± 431 grams. Five hundred and seventy-three patients (6.8%) of the neonates were less than 2500 grams. In all quantiles, gestational age of neonates (p<0.05), weight and educational level of the mothers (p<0.05) showed a linear significant relationship with the i of the neonates. However, sex and birth rank of the neonates, mothers age, place of residence (urban/rural) and career were not significant in all quantiles (p>0.05).
  
  
  CONCLUSIONS
  This study revealed the results of multiple linear regression and quantile regression were not identical. We strictly recommend the use of quantile regression when an asymmetric response variable or data with outliers is available.
authors.affiliation: . r.fallahvalamdehi@modares.ac.ir.
authors.forename: Ramazan
authors.initials: R
authors.lastname: Fallah
authors.forename: Anoshirvan
authors.initials: A
authors.lastname: Kazemnejad
authors.forename: Farid
authors.initials: F
authors.lastname: Zayeri
authors.forename: Alireza
authors.initials: A
authors.lastname: Shoghli
mesh_terms: D000328:Adult; D001724:Birth Weight; D003430:Cross-Sectional Studies; D005260:Female; D005865:Gestational Age; D006801:Humans; D007231:Infant, Newborn; D007492:Iran; D008297:Male; D008423:Maternal Age; D012111:Residence Characteristics