1. TEMPLATE DESIGN © 2008 www.PosterPresentations.com Toxocara Infection in the United States: The Relevance of Poverty, Geography and Demography as Risk Factors and Implications for Estimating County Prevalence Human toxocariasis is a zoonotic helminth infection caused by parasitic roundworms, Toxocara canis and Toxocara cati, which are transmitted from dogs and cats, respectively. Infection by Toxocara spp. is usually under diagnosed since infection is generally asymptomatic, yet it may lead to severe manifestations of infection over time. To understand areas and communities at high risk and in need of prevention measures, an estimation of infection by Toxocara spp. at a disaggregated area scale is warranted. Incorporating individual and family risk factors as well as geographic context to examine burden of infection from Toxocara spp. in the U.S. population provides a unique approach to estimate Toxocara spp. seroprevalence in the U.S. and evaluating the effect of these factors on infection. Taken in concert with the poverty effect, the indication is that rural poverty in particular is associated with a high Toxocara spp. seropositivity. Areas with high rural poverty may benefit from health education messages to further reduce morbidity of associated with Toxocara infection. Data from 20,396 participants with complete or partly missing data for the above variables (9,876 males; 10,520 females) were included in this analysis. Large differences in Toxocara spp. seropositivity by region, county and metropolitan status were obtained from the survey regression model, showing that genuine geographic (contextual) effects remain after controlling for population composition effects linked to age, ethnicity or poverty status ( Figure 1 ). The relative risk of infection comparing individuals below the poverty line vs. those at or above the poverty line varied greatly by region within non-metropolitan areas ( Figure 2 ); region-specific RR in non- metropolitan areas ranged from 1.5-3.4 in males, and 0.5 – 1.9 for females. Living below the poverty line (PIR<1) was associated with a higher risk of infection among all race/ethnic groups; these differences were largest among White non-Hispanics ( Figure 3 ), while the prevalence of seropositivity was highest among Black non-Hispanic and Other race/ethnic groups. BACKGROUND Peter Congdon 1, Patsy Lloyd 2,3 1 Department of Geography and Center for Statistics, Queen Mary University of London, UK; 2 George Washington University School of Public Health and Health Services, Department of Epidemiology and Biostatistics, Washington, DC; 3 National Minority Quality Forum, Washington, DC METHODS Data Sources Data from National Health and Nutrition Examination Survey III (NHANES III) were used. Data were collected between 1988 and 1994, and Mexican-Americans and Blacks were oversampled to ensure adequate representation from these populations (1). Surplus sera were collected from a sample of participants, ages 6 and older, and tested for antibodies to Toxocara spp. in an indirect immunoassay with an antigen of Toxocara canis (2). Variables in analysis Predictors: Age; Race/ethnicity; U.S Region of residence (Northeast, Midwest, South, West); Residence in metropolitan area; Poverty Income Ratio (PIR); Response: Presence of antibodies for Toxocara spp. Outcome Measures County level estimates of Toxocara spp. seroprevalence are the primary outcome measures of this analysis. Secondary outcomes include relative risks (RR) of Toxocara spp. infection by a binary measure of poverty status (PIR < 1 vs. PIR ≥ 1). CONCLUSIONS REFERENCES RESULTS Figure 2 Relative Risk of Toxocara spp. Seroprevalence (Poverty vs. not in Poverty) by Metropolitan area, Region, and Gender The objective of this analysis was to estimate the prevalence of Toxocara spp. seropositivity in counties of the United States by applying regression models and geographic information systems (GIS) to socio-demographic, geographic and serological data from the National Health and Nutrition Examination Survey III (NHANES III). A binary regression model using geographic and individual level predictors was created for males and females, separately. The age- ethnic Toxocara spp. seropositivity rate for each county was determined as a weighted average according to the poverty composition in each county. U.S. county-level maps were prepared for males and females. PURPOSE Regression Model A gender specific binary regression model under a log link is used to estimate the presence of Toxocara spp. antibody using geographic, family and person level predictors. Let A i and E i denote age and ethnic categories of subject i, M i and R i denote the metro status and region of their place of residence, and S i denotes poverty status (S i =1 for people in poverty). M i =1 for metro places. Main effects are taken in these variables, with an ethnic specific poverty effect. Interactions between ethnicity, region and metro status, u 1 (E i,R i,M i ), and interactions between age, region, and metro status, u 2 (A i,R i,M i ), were also examined. For subject i the probability p i of infection is estimated from a log link regression: log(p i )=  +  (A i )+  (E i )+  (R i )+ M i +  Ei S i + u 1 (E i,R i,M i ) + u 2 (A i,R i,M i ). The next step is to translate individual subject regressions to county prevalence rate estimates. For a given gender in the j -th county, age and ethnic specific rates P j (A,E) are derived using two sets of rates. One set is for people in each county in poverty, whose estimated infection rate includes the poverty effect (specific to ethnicity E),  E : P P j (A,E)=exp[  +  (A)+  1 (E)+  2 (R)+  3 (M j )+  E +u 1 (E,R j,M j )+ u 2 (A,R j,M j )] where R j and M j are the region and metro status of county j. The other set of rates is for the remaining portion of each county’s population, those not in poverty, so that the poverty effect,  E, is not included, namely: P N j (A,E)=exp[  +  (A)+  1 (E)+  2 (R)+  3 (M j )+u 1 (E,R j,M j )+ u 2 (A,R j,M j )] The age-ethnic infection rate for each county is obtained as a weighted average according to county poverty composition: P j (A,E)=S j P P j (A,E)+(1-S j )P N j (A,E) where S j is the county poverty rate. To form overall county rates for each ethnic group, age weights w A from the US 2000 population may be used: P j (E)=Σ A w A P j (A,E). To derive overall rates for each county regardless of ethnic group, ethnic weights w E from the US 2000 population are used, so that P j =Σ w E P j (E). Geographic Information Systems (GIS) ArcView 9.2 was used to map gender-specific county-level estimates of Toxocara spp. seroprevalence. Legend boundaries were created using Natural Breaks (Jenks’ Method) (3). p p Figure 1. Estimated Seroprevalence of Toxocara spp. in the United States between 1988-1994, by County; (a) Females, (b) Males Figure 3 Toxocara spp. Seroprevalence and Relative Risk of Infection (Poverty vs. not in Poverty) by Race/Ethnicity, and Gender a b 1. U.S. Department of Health and Human Services (DHHS), National Center for Health Statistics (NCHS). Third national health and nutrition examination survey, 1988-1994, NHANES III laboratory data file (CD- ROM). public use data file documentation number 76200. Hyattsville, MD: Centers for disease control and prevention, 1996. 2. U.S. Department of Health and Human Services (DHHS). National Center for Health Statistics. Documentation, codebook, and frequencies; surplus sera laboratory component: Antibody to Toxocara larva migrans. January 2007. 3. ArcView 9.2 software. Environmental Systems Research Institute, Redlands, California, 2006.