title: Predictors of antibiotic use in African communities: evidence from medicines household surveys in five countries.
abstract: OBJECTIVE
  To investigate antibiotic use in five national household surveys conducted with the WHO methodology to identify key determinants of antibiotic use in the community.
  
  
  METHODS
  Data from The Gambia, Ghana, Kenya, Nigeria and Uganda surveys were combined. We used logistic regression models that accounted for the clustered survey design to identify the determinants of care seeking outside the home and antibiotic use for 2914 cases of recent acute illness.
  
  
  RESULTS
  Overall, 95% of individuals with acute illness took medicines, 90% sought care outside their homes and 36% took antibiotics. In multivariate analyses, illness severity was a strong predictor of seeking care outside the home. Among those who sought outside care, the strongest predictor of antibiotic use was the presence of upper respiratory symptoms (OR: 3.02, CI: 2.36-3.86, P<0.001), followed by gastrointestinal symptoms or difficulty breathing, and antibiotics use was less likely if they had fever. The odds of receiving antibiotics were higher when visiting a public hospital or more than one healthcare facility.
  
  
  CONCLUSIONS
  The nature and severity of symptoms and patterns of care seeking had the greatest influence on decisions to take antibiotics. Antibiotics were widely available and inappropriately used in all settings. Policies to regulate antibiotics distribution as well as interventions to educate prescribers, dispensers and consumers are needed to improve antibiotic use.
authors: Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA.
authors: C E
authors: CE
authors: Vialle-Valentin
authors: R F
authors: RF
authors: Lecates
authors: F
authors: F
authors: Zhang
authors: A T
authors: AT
authors: Desta
authors: D
authors: D
authors: Ross-Degnan
mesh_terms: D000208:Acute Disease; D000293:Adolescent; D000328:Adult; D000349:Africa; D000900:Anti-Bacterial Agents / Q000627:therapeutic use*; D002648:Child; D002675:Child, Preschool; D016000:Cluster Analysis; D016001:Confidence Intervals; D005191:Family Characteristics; D005260:Female; D005334:Fever / Q000188:drug therapy; D005767:Gastrointestinal Diseases / Q000188:drug therapy*; D019538:Health Care Surveys; D006296:Health Services; D006761:Hospitals; D006801:Humans; D007223:Infant; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D016017:Odds Ratio; D010342:Patient Acceptance of Health Care / Q000706:statistics & numerical data*; D017150:Public Sector; D012119:Respiration; D012140:Respiratory Tract Diseases / Q000188:drug therapy*; D012720:Severity of Illness Index; D014944:World Health Organization; D055815:Young Adult
chemical_list: D000900:Anti-Bacterial Agents