Background:
Characterizing the contribution of socioeconomic factors to racial/ethnic disparities in STD rates is complicated by the paucity of socioeconomic data in most public health surveillance systems. Area-based-socioeconomic-measures, collected through the U.S. Census, offer a means to gain insights into these inequalities through association of community-level socioeconomic measures with case-based surveillance data.

Objective:
To quantify the relationship between STD infection rates and community poverty levels, and characterize how that relationship varies among racial/ethnic groups.

Method:
Gonorrhea cases reported in California (2004 through 2006) were geocoded and associated with census tracts. Using census data, tracts were categorized into one of four poverty categories based on the percentage of residents living below the federal poverty line. Weighted infection rates for each poverty category were calculated for each of four racial/ethnic groups. Race/poverty rate profiles were generated for the entire state and for individual counties, and cases were mapped to identify patterns of spatial clustering. Detailed maps will be presented.

Result:
Of 58,394 total Gonorrhea cases, 43,830 (75%) were successfully geocoded. Infection rates and poverty levels were positively correlated in each racial/ethnic group, but rates among blacks were at least 4-times higher than among Asians, Hispanics, and whites in every poverty category. This racial differential eclipsed increases associated with poverty: rates among blacks in the lowest poverty category were 2.5-times higher than the highest rate among Asians, Hispanics, and whites in the highest poverty category. Among black cases, 28% (n=2,571) resided in the highest poverty census tracts; these cases were concentrated in only 3.4% (n=242) of the state's census tracts.

Conclusion:
Gonorrhea infection rates consistently increased with increasing poverty levels, but the influence of this trend was overshadowed by striking racial/ethnic disparities in infection.

Implications:
These findings will allow public health practitioners to design intervention programs that more effectively target disparities at a focused geographic level.