title: Examining the determinants of mosquito-avoidance practices in two Kenyan cities.
abstract: BACKGROUND
  This study assesses the behavioural and socio-economic factors associated with avoiding mosquitoes and preventing malaria in urban environments in Kenya.
  
  
  METHODS
  Data from two cities in Kenya were gathered using a household survey and a two-stage cluster sample design. The cities were stratified based on planning and drainage observed across the urban areas. This helped control for the strong environmental and topographical variation that we assumed influences mosquito ecology. Individual interviews given to each household included questions on socio-economic status, education, housing type, water source, rubbish disposal, mosquito-prevention practices and knowledge of mosquitoes. In multivariate regression, factors measuring wealth, education level, and the communities' level of planning and drainage were used to estimate the probability that a household engages in multiple mosquito-avoidance activities, or has all members sleeping under a bed net.
  
  
  RESULTS
  Our analysis shows that people from wealthier, more educated households were more likely to sleep under a net, in Kisumu (OR = 6.88; 95% CI = 2.56,18.49) and Malindi (OR = 3.80; 95% CI = 1.91,7.55). Similarly, the probability that households use several mosquito-prevention activities was highest among the wealthiest, best-educated households in Kisumu (OR = 5.15; 95% CI = 2.04,12.98), while in Malindi household wealth alone is the major determinant.
  
  
  CONCLUSIONS
  We demonstrate the importance of examining human-mosquito interaction in terms of how access to resources may enhance human activities. The findings illustrate that the poorest segments of society are already doing many things to protect themselves from being bitten, but they are doing less than their richer neighbours.
authors.affiliation: Department of International Health and Development, School of Public Health and Tropical Medicine, Tulane University, Suite 2200, 1440 Canal St., New Orleans, LA 70112, USA. kmacint@tulane.edu
authors.forename: Kate
authors.initials: K
authors.lastname: Macintyre
authors.forename: Joseph
authors.initials: J
authors.lastname: Keating
authors.forename: Stephen
authors.initials: S
authors.lastname: Sosler
authors.forename: Lydiah
authors.initials: L
authors.lastname: Kibe
authors.forename: Charles M
authors.initials: CM
authors.lastname: Mbogo
authors.forename: Andrew K
authors.initials: AK
authors.lastname: Githeko
authors.forename: John C
authors.initials: JC
authors.lastname: Beier
mesh_terms: D000818:Animals; D000852:Anopheles; D001512:Bedding and Linens / Q000706:statistics & numerical data; D002958:City Planning / Q000706:statistics & numerical data; D003625:Data Collection; D007722:Health Knowledge, Attitudes, Practice; D006798:Housing / Q000706:statistics & numerical data; D006801:Humans; D007303:Insect Vectors; D007306:Insecticides; D007630:Kenya / Q000453:epidemiology; D008288:Malaria / Q000191:economics / Q000453:epidemiology / Q000517:prevention & control*; D009032:Mosquito Control / Q000191:economics / Q000379:methods*; D011203:Poverty; D012959:Socioeconomic Factors; D014504:Urban Health; D018505:Waste Management / Q000191:economics / Q000379:methods; D014881:Water Supply
chemical_list: D007306:Insecticides