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- Title
Effect of Race/Ethnicity and Socioeconomic Status on Pandemic H1N1-Related Outcomes in Massachusetts.
- Authors
Placzek, Hilary; Madoff, Lawrence
- Abstract
Objectives. We linked hospital discharge and American Community Survey and US Census data to investigate 2009 H1N1 influenza (H1N1)-related outcomes by racial/ethnic groups and socioeconomic status (SES). Methods. We examined the population discharged from any acute care hospital in Massachusetts and calculated rates of intensive care unit (ICU) stay by racial/ethnic and SES groups between April 26 and September 30, 2009. We used logistic regression models to identify predictors of ICU stay. Results. Of 4874 H1N1-related hospitalizations, 526 (11%) were admitted to the ICU. Those in less affluent SES groups had lower risk of ICU stay than the most affluent SES group. Compared with Whites, Hispanics had significantly lower risk of 2009 H1N1-related ICU stay (odds ratio = 0.52; 95% confidence interval = 0.32, 0.86). Only 13% of Whites admitted to the ICU were in the lowest SES group, compared with 63% of Hispanics and 43% of Blacks. Conclusions. To our knowledge, this is the first statewide description of 2009 H1N1 influenza-related ICU stays according to racial/ethnic group and SES in the United States. Future work should investigate evidence related to social determinants of health among racial/ethnic groups to reduce disparities in relation to pandemic influenza.
- Subjects
MASSACHUSETTS; RACE &; social status; ANALYSIS of variance; CATASTROPHIC illness; CENSUS; CHI-squared test; CLUSTER analysis (Statistics); COMPARATIVE studies; CONFIDENCE intervals; STATISTICAL correlation; EPIDEMIOLOGY; ETHNIC groups; HEALTH services accessibility; HISPANIC Americans; INTENSIVE care units; EVALUATION of medical care; MEDICAL record linkage; RACE; WHITE people; LOGISTIC regression analysis; DATA analysis; RESIDENTIAL patterns; SOCIOECONOMIC factors; DISCHARGE planning; PREDICTIVE validity; RETROSPECTIVE studies; H1N1 influenza; HEALTH &; social status; STATISTICAL models; DESCRIPTIVE statistics
- Publication
American Journal of Public Health, 2014, Vol 104, Issue 1, pe31
- ISSN
0090-0036
- Publication type
Article
- DOI
10.2105/AJPH.2013.301626