title: Decomposing Kenyan socio-economic inequalities in skilled birth attendance and measles immunization.
abstract: BACKGROUND
  Skilled birth attendance (SBA) and measles immunization reflect two aspects of a health system. In Kenya, their national coverage gaps are substantial but could be largely improved if the total population had the same coverage as the wealthiest quintile. A decomposition analysis allows identifying the factors that influence these wealth-related inequalities in order to develop appropriate policy responses. The main objective of the study was to decompose wealth-related inequalities in SBA and measles immunization into their contributing factors.
  
  
  METHODS
  Data from the Kenyan Demographic and Health Survey 2008/09 were used. The study investigated the effects of socio-economic determinants on [1] coverage and [2] wealth-related inequalities of SBA utilization and measles immunization. Techniques used were multivariate logistic regression and decomposition of the concentration index (C).
  
  
  RESULTS
  SBA utilization and measles immunization coverage differed according to household wealth, parent's education, skilled antenatal care visits, birth order and father's occupation. SBA utilization further differed across provinces and ethnic groups. The overall C for SBA was 0.14 and was mostly explained by wealth (40%), parent's education (28%), antenatal care (9%), and province (6%). The overall C for measles immunization was 0.08 and was mostly explained by wealth (60%), birth order (33%), and parent's education (28%). Rural residence (-19%) reduced this inequality.
  
  
  CONCLUSIONS
  Both health care indicators require a broad strengthening of health systems with a special focus on disadvantaged sub-groups.
authors.affiliation: Institute of Health and Society, Université catholique de Louvain, Brussels, Belgium. carine.vanmalderen@uclouvain.be
authors.forename: Carine
authors.initials: C
authors.lastname: Van Malderen
authors.forename: Irene
authors.initials: I
authors.lastname: Ogali
authors.forename: Anne
authors.initials: A
authors.lastname: Khasakhala
authors.forename: Stephen N
authors.initials: SN
authors.lastname: Muchiri
authors.forename: Corey
authors.initials: C
authors.lastname: Sparks
authors.forename: Herman
authors.initials: H
authors.lastname: Van Oyen
authors.forename: Niko
authors.initials: N
authors.lastname: Speybroeck
mesh_terms: D000293:Adolescent; D000328:Adult; D004522:Educational Status; D005260:Female; D006297:Health Services Accessibility / Q000592:standards*; D054625:Healthcare Disparities / Q000191:economics / Q000639:trends; D006801:Humans; D007114:Immunization / Q000592:standards*; D007223:Infant; D007630:Kenya; D008297:Male; D008427:Maternal Health Services / Q000191:economics / Q000592:standards*; D008457:Measles / Q000517:prevention & control*; D008875:Middle Aged; D011314:Preventive Health Services / Q000592:standards; D012044:Regression Analysis; D012959:Socioeconomic Factors; D055815:Young Adult