title: Antibiotic consumption in relation to socio-demographic factors, co-morbidity, and accessibility of primary health care.
abstract: BACKGROUND
  Differences in antibiotic consumption between individuals are not only due to differences in primary infection morbidity, other non-medical factors are important. Our objective was to investigate how socio-demographic factors, co-morbidity, and access to primary care affect antibiotic prescribing.
  
  
  METHODS
  The study population included all 2 078 481 persons in Sweden who received at least one antibiotic prescription during 2010, and an unmatched control population of 788 580 individuals. We used record linkage to obtain data on co-morbidity, various socio-demographic variables, and waiting times for doctor appointments in primary care. We used logistic regression to estimate odds ratios (ORs) for antibiotic prescription.
  
  
  RESULTS
  The results showed that over 20% of the population were prescribed antibiotics during 2010. Children aged 0-5 years, persons ≥ 75 years of age, those living in urban areas, and women compared with men, received many prescriptions. Co-morbidity was a strong factor that determined the number of antibiotic prescriptions: those with Charlson's index ≥ 3 had an OR of 3.03 (95% CI: 3.00-3.07) to obtain antibiotics in the adjusted analysis, compared with individuals without co-morbidity (Charlson's index 0). Short waiting times for a doctor's visit in primary care were associated with a higher number of antibiotic prescriptions. Individuals born in Sweden were prescribed more antibiotics compared with those born in another country. Specifically, persons born in any of the 27 EU countries (excluding Scandinavia) had an OR of antibiotic prescription of 0.78 (95% CI: 0.77-0.78) compared with native-born individuals.
  
  
  CONCLUSIONS
  We conclude that non-medical factors strongly influence antibiotic prescriptions.
authors.affiliation: From the Public Health Agency of Sweden.
authors.forename: Anders
authors.initials: A
authors.lastname: Ternhag
authors.forename: Maria
authors.initials: M
authors.lastname: Grünewald
authors.forename: Pontus
authors.initials: P
authors.lastname: Nauclér
authors.forename: Karin Tegmark
authors.initials: KT
authors.lastname: Wisell
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000900:Anti-Bacterial Agents / Q000627:therapeutic use*; D002648:Child; D002675:Child, Preschool; D015897:Comorbidity; D003710:Demography; D011307:Drug Prescriptions; D004363:Drug Utilization / Q000706:statistics & numerical data*; D005260:Female; D006297:Health Services Accessibility / Q000706:statistics & numerical data*; D006801:Humans; D007223:Infant; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D011320:Primary Health Care / Q000706:statistics & numerical data*; D012141:Respiratory Tract Infections / Q000188:drug therapy* / Q000453:epidemiology; D012959:Socioeconomic Factors; D013548:Sweden / Q000453:epidemiology; D055815:Young Adult
chemical_list: D000900:Anti-Bacterial Agents
keywords: Antibiotic use; antibacterials; prescriptions; socio-economic