title: Socioeconomic variation in asthma hospitalization: excess utilization or greater need?
abstract: OBJECTIVE
  To assess the hypothesis that higher incidence of severe acute asthma exacerbation, not lower severity threshold for admission, explains the difference between the asthma hospitalization rates of inner-city and suburban children.
  
  
  METHODS
  All 2028 asthma hospitalizations between 1991 and 1995 for children (aged >1 month and <19 years) dwelling in Rochester, New York, were analyzed. ZIP codes defined residences as inner-city, other urban, or suburban. Based principally on the worst oxygen saturation (SaO2) during the first 24 hours of hospitalization, severity was examined by hospital record review (n = 443) of random samples of inner-city, other urban, and suburban asthma admissions.
  
  
  RESULTS
  Large inner-city/suburban differences were noted in many sociodemographic attributes, and there was also a distinct, stepwise gradient in risk factors in moving from the suburbs to other urban areas and to the inner city. Racial and economic segregation was particularly striking. Black individuals accounted for 62% of inner-city births versus <3% in the suburbs. Medicaid covered 65% of inner-city births, whereas Medicaid covered only 6% of suburban births. The overall asthma hospitalization rate was 2.04 admissions/1000 child-years. Children <24 months old, those most commonly hospitalized for asthma, were fourfold more likely to be hospitalized (OR: 3.97, 95% CI: 3. 44-4.57) than children between the ages of 13 and 18 years. The hospitalization rate of asthma in boys was almost twice the rate of asthma in girls. The greatest gender difference was observed among children who were <24 months old. For these children, the rate for boys was 6.10/1000 child-years compared with 2.65/1000 child-years for girls (OR: 2.31, 95% CI: 1.95-3.03). This gender difference diminished gradually in older age groups to the extent that there was no difference among girls and boys between the ages of 13 and 18 years (males, 1.12/1000 child-years vs females, 1.09/1000 child-years). Based on worst SaO2 values, mild (worst SaO2 >/=95%), moderate (90%-94%), and severe (<90%) admissions constituted 10.3%, 41.9%, and 47.7% of all hospitalizations, respectively. Although rates within the community followed a distinct geographic pattern of suburban (1.05/1000 child-years) < other urban (2.99/1000 child-years) < inner-city (5.21/1000 child-years), the proportions of admissions with low severity did not vary among areas. Likewise, the proportions of admissions that were severe (SaO2 <90%) were not significantly different (44.8, 45.7, and 52.1% for suburban, other urban, and inner-city areas, respectively). The distributions of asthma severity, measured by the duration of frequent nebulized bronchodilator treatments and the length of hospital stay, were also similar among children from different socioeconomic areas.
  
  
  CONCLUSIONS
  The marked socioeconomic and racial disparity in Rochester's asthma hospitalization rates is largely attributable to higher incidence of severe acute asthma exacerbations among inner-city children; it signals greater need, not excess utilization. Both adverse environmental conditions and lower quality primary care might explain the higher incidence. Interventions directed at the environment offer the possibility of primary prevention, whereas primary care directed at asthma is focused on secondary prevention, principally on improved medication use. Higher hospitalization rates cannot be assumed to identify opportunities for cost reduction. The extent to which our observations about asthma hold true under other conditions and in other communities warrants systematic attention. Knowledge of when higher rates signal excess utilization and when, instead, they signify greater needs should guide equitable national health policy.
authors.affiliation: Department of Pediatrics, University of Rochester School of Medicine, Rochester, NY 14642, USA. ken_mcconnochie@urmc.rochester.edu
authors.forename: K M
authors.initials: KM
authors.lastname: McConnochie
authors.forename: M J
authors.initials: MJ
authors.lastname: Russo
authors.forename: J T
authors.initials: JT
authors.lastname: McBride
authors.forename: P G
authors.initials: PG
authors.lastname: Szilagyi
authors.forename: A M
authors.initials: AM
authors.lastname: Brooks
authors.forename: K J
authors.initials: KJ
authors.lastname: Roghmann
mesh_terms: D000293:Adolescent; D001249:Asthma / Q000145:classification / Q000191:economics / Q000453:epidemiology* / Q000208:ethnology; D002648:Child; D002675:Child, Preschool; D005260:Female; D006760:Hospitalization / Q000191:economics / Q000706:statistics & numerical data*; D006801:Humans; D015994:Incidence; D007223:Infant; D008297:Male; D009518:New York / Q000453:epidemiology; D012720:Severity of Illness Index; D012737:Sex Factors; D012959:Socioeconomic Factors; D013224:Status Asthmaticus / Q000191:economics / Q000208:ethnology; D018881:Suburban Health; D019036:Suburban Health Services / Q000191:economics / Q000706:statistics & numerical data; D014504:Urban Health; D019037:Urban Health Services / Q000191:economics / Q000706:statistics & numerical data