title: Holistic model-based monitoring of the human health status in an urban environment system: pilot study in Verona city, Italy.
abstract: BACKGROUND
  In recent decades the global health paradigm gained an increasing systemic characterization. The ecosystem health theory states that a healthy ecosystem, whether natural or artificial, significantly contributes to the good health status of the human population.
  
  
  METHODS
  The present study describes an interdisciplinary monitoring model that retrospectively analyzes the intersection between the urban environment and citizens. The model analyzes both the biophysical and the anthropic subsystems through the application of landscape ecology and environmental quality indexes along with human health indicators. Particularly, ecological quality of landscape pattern, atmospheric pollution, outdoor noise levels and local health indicators were assessed. Verona municipality was chosen as study area to test the preliminary efficiency of the model. Territory was split into two superimposed layers of land units, which were further geo-referentiated with Geographical Information System (GIS) technology. Interdependence of any of the analyzed traits was further investigated with Fisher exact test.
  
  
  RESULTS
  Landscape composition was assessed and an Average Ecological Quality (AEQ) score assigned to each land unit. A direct proportionality emerged for concentrations of considered air pollutants and traffic levels: a spatial model for the atmospheric pollution was drawn. A map depicting the distribution of traffic-related noise levels was also drawn. From chosen indicators, a quality class score was assigned to every minor and major land unit. Age-standardised rates about hospitalizations for the municipal population and specific rates for the over-65s/1000 inhabitants were calculated. Quality class assignement for each health indicator was graphically rendered. After direct standardisation of rates for the population sample, data were compared with two reference populations, the Regional population and the Local Socio-sanitary Unit (ULSS20) population. Standardised hospitalization rates for the whole municipal population always resulted lower than the ULSS20 rates, except for auditory pathologies. It was notable that rates of hospitalizations for cancerous diseases for Verona municipal population were four times and two times lower than the ULSS20 and the Regional population ones, respectively. Contingency table were made for the health main indicator (specific rates for the over-65s/1000 inhabitants) and the environmental quality key factors of landscape ecological quality, outdoor noise level and air pollution. H0 of independence was rejected for respiratory pathologies and air pollution and for the triad cardiocirculatory pathologies, air pollution and landscape ecological quality at (a = 0.05). Fisher exact test confirmed the non-independence of cardiocirculatory diseases and biophysical environment and the analogous association for respiratory pathologies when comparison was made with global environmental quality index.
  
  
  CONCLUSIONS
  The first testing of the model suggests some possible elements of implementation and integration which could further enhance it. Among them, the subjective investigation of the health status assumes a primary role. On the whole the monitoring model seems to effectively represent the real complexity of the urban environment systems and should be regarded as an important contribution to the new way of health research.
authors.affiliation: Department of Environmental Medicine and Public Health, Hygiene Office, University of Padua, Italy.
authors.forename: S
authors.initials: S
authors.lastname: Tarocco
authors.forename: I
authors.initials: I
authors.lastname: Amoruso
authors.forename: G
authors.initials: G
authors.lastname: Caravello
mesh_terms: D001294:Attitude to Health; D003627:Data Interpretation, Statistical; D004779:Environment Design; D006304:Health Status; D006694:Holistic Health; D006801:Humans; D007558:Italy / Q000453:epidemiology; D015233:Models, Statistical; D010865:Pilot Projects; D011157:Population Dynamics; D012111:Residence Characteristics; D014504:Urban Health; D014505:Urban Population / Q000706:statistics & numerical data*