title: Factors influencing the use of bed nets in Mbarara municipality of Uganda.
abstract: In order to identify independent predictors for bed net use, respondents from 643 households selected randomly from 21 clusters were interviewed in Mbarara municipality, Uganda. Respondents answered questions about demographic characteristics, social economic conditions, causes and transmission of malaria, beliefs about severity and complications of malaria, malaria morbidity and health care-seeking behavior, perceived control of malaria prevention, beliefs about utility of bed nets, perceived susceptibility to malaria, and whether they use bed nets or not. Univariate and multivariate logistic regression analyses were used to identify predictors for bed net use. Fifty-five percent (356 of 643) of the households had bed net users. The independent factors that favored bed net use were as follows: 1) age < 30 years, 2) ownership of a television, 3) having mosquito nets in ventilators of the house, 4) being a skilled worker or a professional, or owning a major business, 5) living in a permanent house, 6) believing that bed nets prevent malaria, 7) believing that bed nets are worth their cost, 8) not believing that convulsions cannot be cured by modern medicine, and 9) believing that bed nets are not expensive. The strongest predictors of bed net use are living in a permanent house and agreeing that bed nets are worth their cost, with adjusted odds ratios of 4.29 (95% confidence interval, 2.76-6.71) and 3.93 (95% confidence interval, 2.5-26.13), respectively. These data suggest that in order to increase the use of bed nets, the price of bed nets needs to be reduced and educational messages that stress the favorable use of bed nets need to be increased.
authors.affiliation: Health Services Sector, Bushenyi Local Government, Uganda.
authors.forename: F
authors.initials: F
authors.lastname: Nuwaha
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000818:Animals; D001294:Attitude to Health; D001512:Bedding and Linens / Q000706:statistics & numerical data; D002648:Child; D002675:Child, Preschool; D003430:Cross-Sectional Studies; D009033:Culicidae; D005260:Female; D006801:Humans; D007223:Infant; D007303:Insect Vectors; D007306:Insecticides; D008288:Malaria / Q000453:epidemiology / Q000517:prevention & control*; D008297:Male; D008875:Middle Aged; D009032:Mosquito Control / Q000191:economics / Q000295:instrumentation* / Q000379:methods; D010342:Patient Acceptance of Health Care / Q000706:statistics & numerical data; D011247:Pregnancy; D011251:Pregnancy Complications, Infectious / Q000517:prevention & control; D015995:Prevalence; D012044:Regression Analysis; D011795:Surveys and Questionnaires; D014454:Uganda / Q000453:epidemiology
chemical_list: D007306:Insecticides