International Journal of Public Health

, Volume 56, Issue 1, pp 15–24

Toxocara infection in the United States: the relevance of poverty, geography and demography as risk factors, and implications for estimating county prevalence

Original Article

DOI: 10.1007/s00038-010-0143-6

Cite this article as:
Congdon, P. & Lloyd, P. Int J Public Health (2011) 56: 15. doi:10.1007/s00038-010-0143-6

Abstract

Objective

To estimate Toxocara infection rates by age, gender and ethnicity for US counties using data from the National Health and Nutrition Examination Survey (NHANES).

Methods

After initial analysis to account for missing data, a binary regression model is applied to obtain relative risks of Toxocara infection for 20,396 survey subjects. The regression incorporates interplay between demographic attributes (age, ethnicity and gender), family poverty and geographic context (region, metropolitan status). Prevalence estimates for counties are then made, distinguishing between subpopulations in poverty and not in poverty.

Results

Even after allowing for elevated infection risk associated with poverty, seropositivity is elevated among Black non-Hispanics and other ethnic groups. There are also distinct effects of region. When regression results are translated into county prevalence estimates, the main influences on variation in county rates are percentages of non-Hispanic Blacks and county poverty.

Conclusions

For targeting prevention it is important to assess implications of national survey data for small area prevalence. Using data from NHANES, the study confirms that both individual level risk factors and geographic contextual factors affect chances of Toxocara infection.

Keywords

Toxocara infectionPovertyEthnicityGeographic prevalenceBayesian

Copyright information

© Swiss School of Public Health 2010

Authors and Affiliations

  1. 1.Department of Geography, Center for StatisticsQueen Mary University of LondonLondonUK
  2. 2.National Minority Quality ForumWashington, DCUSA
  3. 3.Department of Epidemiology and Biostatistics, School of Public Health and Health ServicesGeorge Washington UniversityWashington, DCUSA