title: International differences in self-reported health measures in 33 major metropolitan areas in Europe.
abstract: BACKGROUND
  The increasing concentration of populations into large conurbations in recent decades has not been matched by international health assessments, which remain largely focused at the country level. We aimed to demonstrate the use of routine survey data to compare the health of large metropolitan centres across Europe and determine the extent to which differences are due to socio-economic factors.
  
  
  METHODS
  Multilevel modelling of health survey data on 126,853 individuals from 33 metropolitan areas in the UK, Republic of Ireland, Sweden, Norway, Finland, Spain, Belgium and Germany compared general health, longstanding illness, acute sickness, psychological distress and obesity with the average for all areas, accounting for education and social class.
  
  
  RESULTS
  We found some areas (Greater Glasgow; Greater Manchester, Cheshire and Merseyside; Northumberland, Tyne and Wear and South Yorkshire) had significantly higher levels of poor health. Other areas (West Flanders and Antwerp) had better than average health. Differences in individual socio-economic circumstances did not explain findings. With a few exceptions, acute sickness levels did not vary.
  
  
  CONCLUSIONS
  Health tended to be worse in metropolitan areas in the north and west of the UK and the central belt and south east of Germany, and more favourable in Sweden and north west Belgium, even accounting for socio-economic composition of local populations. This study demonstrated that combining national health survey data covering different areas is viable but not without technical difficulties. Future comparisons between European regions should be made using standardized sampling, recruitment and data collection protocols, allowing proper monitoring of health inequalities.
authors.affiliation: MRC/CSO Social and Public Health Sciences Unit, Glasgow, UK. l.gray@sphsu.mrc.ac.uk
authors.forename: Linsay
authors.initials: L
authors.lastname: Gray
authors.forename: Juan
authors.initials: J
authors.lastname: Merlo
authors.forename: Jennifer
authors.initials: J
authors.lastname: Mindell
authors.forename: Johan
authors.initials: J
authors.lastname: Hallqvist
authors.forename: Jean
authors.initials: J
authors.lastname: Tafforeau
authors.forename: Dermot
authors.initials: D
authors.lastname: O'Reilly
authors.forename: Enrique
authors.initials: E
authors.lastname: Regidor
authors.forename: Øyvind
authors.initials: Ø
authors.lastname: Næss
authors.forename: Cecily
authors.initials: C
authors.lastname: Kelleher
authors.forename: Satu
authors.initials: S
authors.lastname: Helakorpi
authors.forename: Cornelia
authors.initials: C
authors.lastname: Lange
authors.forename: Alastair H
authors.initials: AH
authors.lastname: Leyland
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002947:Cities / Q000453:epidemiology*; D005060:Europe / Q000453:epidemiology; D005260:Female; D006305:Health Status Indicators; D006306:Health Surveys; D006801:Humans; D008297:Male; D008875:Middle Aged; D055815:Young Adult