title: Exploring the association between resistance and outpatient antibiotic use expressed as DDDs or packages.
abstract: OBJECTIVE
  The objective of this study was to explore the association between resistance and outpatient antibiotic use, expressed as either DDDs per 1000 inhabitants per day (DID) or packages per 1000 inhabitants per day (PID).
  
  
  METHODS
  IMS Health data on outpatient penicillin and cephalosporin (β-lactam) and tetracycline, macrolide, lincosamide and streptogramin (TMLS) use, aggregated at the level of the active substance (WHO version 2011) expressed as DID and PID (2000-07) were linked to European Antimicrobial Resistance Surveillance System (EARSS) data on proportions of penicillin-non-susceptible Streptococcus pneumoniae (PNSP) and erythromycin-non-susceptible S. pneumoniae (ENSP) (2000-09). Combined data for 27 European countries were analysed with a generalized linear mixed model. Model fit for use in DID, PID or both and 0, 1 or 2 year time lags between use and resistance was assessed and predictions of resistance were made for decreasing use expressed as DID, PID or both.
  
  
  RESULTS
  When exploring the association between β-lactam use and PNSP, the best model fit was obtained for use in PID without time lag. For the association between TMLS use and ENSP, the best model fit was obtained for use in both PID and DID with a 1 year time lag. PNSP and ENSP are predicted to decrease when use decreases in PID, but not when use decreases in DID.
  
  
  CONCLUSIONS
  Associations between outpatient antibiotic use and resistance and predictions of resistance were inconsistent whether expressing antibiotic use as DID or PID. We recommend that data on antibiotic use be expressed as PID and that time lags between use and resistance be considered when exploring these associations.
authors.affiliation: Interuniversity Institute for Biostatistics and statistical Bioinformatics (I-BIOSTAT), Hasselt University, Hasselt, Belgium robin.bruyndonckx@uhasselt.be.
authors.forename: Robin
authors.initials: R
authors.lastname: Bruyndonckx
authors.affiliation: Interuniversity Institute for Biostatistics and statistical Bioinformatics (I-BIOSTAT), Hasselt University, Hasselt, Belgium Centre for Health Economic Research and Modelling Infectious Diseases (CHERMID), Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium.
authors.forename: Niel
authors.initials: N
authors.lastname: Hens
authors.affiliation: Interuniversity Institute for Biostatistics and statistical Bioinformatics (I-BIOSTAT), Hasselt University, Hasselt, Belgium.
authors.forename: Marc
authors.initials: M
authors.lastname: Aerts
authors.affiliation: Laboratory of Medical Microbiology, Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium.
authors.forename: Herman
authors.initials: H
authors.lastname: Goossens
authors.affiliation: European Food Safety Authority, Parma, Italy.
authors.forename: José
authors.initials: J
authors.lastname: Cortiñas Abrahantes
authors.affiliation: Laboratory of Medical Microbiology, Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium Centre for General Practice, Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium.
authors.forename: Samuel
authors.initials: S
authors.lastname: Coenen
mesh_terms: D000900:Anti-Bacterial Agents / Q000627:therapeutic use*; D024881:Drug Resistance, Bacterial; D004363:Drug Utilization; D004812:Epidemiologic Methods; D005060:Europe / Q000453:epidemiology; D006801:Humans; D010045:Outpatients; D011008:Pneumococcal Infections / Q000188:drug therapy* / Q000453:epidemiology / Q000382:microbiology*; D013296:Streptococcus pneumoniae / Q000187:drug effects*
chemical_list: D000900:Anti-Bacterial Agents
keywords: antibiotic resistance; generalized linear mixed model; predictions of resistance