title: Age and sex patterns of drug prescribing in a defined American population.
abstract: OBJECTIVE
  To describe the age and sex patterns of drug prescribing in Olmsted County, Minnesota.
  
  
  METHODS
  Population-based drug prescription records for the Olmsted County population in 2009 were obtained using the Rochester Epidemiology Project medical records linkage system (n=142,377). Drug prescriptions were classified using RxNorm codes and were grouped using the National Drug File-Reference Terminology.
  
  
  RESULTS
  Overall, 68.1% of the population (n=96,953) received a prescription from at least 1 drug group, 51.6% (n=73,501) received prescriptions from 2 or more groups, and 21.2% (n=30,218) received prescriptions from 5 or more groups. The most commonly prescribed drug groups in the entire population were penicillins and β-lactam antimicrobials (17%; n=23,734), antidepressants (13%; n=18,028), opioid analgesics (12%; n=16,954), antilipemic agents (11%; n=16,082), and vaccines/toxoids (11%; n=15,918). However, prescribing patterns differed by age and sex. Vaccines/toxoids, penicillins and β-lactam antimicrobials, and antiasthmatic drugs were most commonly prescribed in persons younger than 19 years. Antidepressants and opioid analgesics were most commonly prescribed in young and middle-aged adults. Cardiovascular drugs were most commonly prescribed in older adults. Women received more prescriptions than men for several drug groups, in particular for antidepressants. For several drug groups, use increased with advancing age.
  
  
  CONCLUSIONS
  This study provides valuable baseline information for future studies of drug utilization and drug-related outcomes in this population.
authors.affiliation: Division of Epidemiology, Mayo Clinic, Rochester, MN.
authors.forename: Wenjun
authors.initials: W
authors.lastname: Zhong
authors.forename: Hilal
authors.initials: H
authors.lastname: Maradit-Kremers
authors.forename: Jennifer L
authors.initials: JL
authors.lastname: St Sauver
authors.forename: Barbara P
authors.initials: BP
authors.lastname: Yawn
authors.forename: Jon O
authors.initials: JO
authors.lastname: Ebbert
authors.forename: Véronique L
authors.initials: VL
authors.lastname: Roger
authors.forename: Debra J
authors.initials: DJ
authors.lastname: Jacobson
authors.forename: Michaela E
authors.initials: ME
authors.lastname: McGree
authors.forename: Scott M
authors.initials: SM
authors.lastname: Brue
authors.forename: Walter A
authors.initials: WA
authors.lastname: Rocca
mesh_terms: D000328:Adult; D017677:Age Distribution; D000368:Aged; D000553:Ambulatory Care / Q000706:statistics & numerical data; D000701:Analgesics, Opioid / Q000627:therapeutic use*; D000890:Anti-Infective Agents / Q000627:therapeutic use*; D002317:Cardiovascular Agents / Q000627:therapeutic use*; D017723:Drug Utilization Review; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D010045:Outpatients / Q000706:statistics & numerical data; D010818:Practice Patterns, Physicians' / Q000706:statistics & numerical data*; D063487:Prescription Drug Misuse / Q000706:statistics & numerical data; D055553:Prescription Drugs / Q000145:classification / Q000627:therapeutic use*; D015995:Prevalence; D011320:Primary Health Care; D017678:Sex Distribution; D014481:United States / Q000453:epidemiology; D055815:Young Adult
chemical_list: D000701:Analgesics, Opioid; D000890:Anti-Infective Agents; D002317:Cardiovascular Agents; D055553:Prescription Drugs