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Objective

Analysis of Salmonella Data for Health Disparities by Socioeconomic Status, King County, WA, 2000 and 2010 Atar Baer 1,2 , Jenny Lloyd 1 , Jeffrey S. Duchin 1,2 1 Public Health — Seattle & King County, 2 University of Washington. Objective. Results.

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Objective

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  1. Analysis of Salmonella Data for Health Disparities by Socioeconomic Status, King County, WA, 2000 and 2010 Atar Baer1,2,Jenny Lloyd1, Jeffrey S. Duchin1,21 Public Health — Seattle & King County, 2 University of Washington Objective Results Use a standardized method to examine health disparities among salmonellosis cases in King County. In 2000, the highest proportion of salmonellosis cases occurred among census tracts at the lowest poverty level, whereas in 2010, the proportion was highest among impoverished areas. Age-standardized rates of salmonellosis by poverty did not differ significantly between 2000 and 2010. In both 2000 and 2010, age-standardized rates were highest in census tracts with >10% poverty (rate=10.1 per 100,000 and 11.3 per 100,000, respectively) relative to census tracts with lower poverty levels, though differences were not significant. Among children < 5 years, among whom rates of salmonellosis were highest, rates decreased with increasing poverty in 2000, but increased with increasing poverty in 2010. There was a U-shaped trend in rates of salmonellosis by poverty among Whites in both years, as well as among non-Whites in 2010; in 2000, rates of salmonellosis among non-Whites decreased with increasing poverty. Background In 2011, a report by the CDC highlighted national disparities in access to healthcare, environmental hazards, morbidity, and mortality. Public Health – Seattle & King County participated in a CSTE-organized pilot project to analyze salmonellosis data in 2000 and 2010 for disparities by age, race and poverty level, using the methodology established by the Harvard University Public Health Disparities Geocoding Project. Salmonellosis Rates by Race and Poverty Level per 100,000 Population Methods There were 205 and 229 cases of salmonellosis among King County residents in 2000 and 2010, respectively. Over 98% of cases were successfully geocoded for each year. Complete data were available for 82% of cases in 2000 and 95% of cases in 2010 for race, and 100% by age. King County population counts for 2000 and 2010 were obtained from the U.S. Census Bureau and stratified by age (<5 years, 5-18 years, 19 to 44 years, and 45+ years) and by race (White and non-White). The percent of persons living below poverty level by census tract in King County was obtained from the 2000 decennial census and the 2005-2009 American Community Survey 5-year population estimates and grouped as under 5%, 5.0-9.9%, and >10.0. The geocoded cases were aggregated by age and race, and linked to population and poverty level data for 2000 and 2010. We calculated race- and age-specific as well as age-standardized rates of salmonellosis among impoverished census tracts. Conclusions We did not find consistent disparities in salmonellosis by poverty level over time. Possible explanations for observed disparities include differences in exposures to risk factors (e.g., travel, restaurants, dietary factors) associated with socioeconomic status, or in access to care; further study is needed. References Public Health Disparities Geocoding Project. http://www.hsph.harvard.edu/thegeocodingproject/ Contact: atar.baer@kingcounty.gov

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