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The role of neighborhood level socioeconomic characteristics in Salmonella infections in Michigan (1997–2007): Assessment using geographic information system

BACKGROUND: The majority of U.S. disease surveillance systems contain incomplete information regarding socioeconomic status (SES) indicators like household or family income and educational attainment in case reports, which reduces the usefulness of surveillance data for these parameters. We investig...

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Autores principales: Younus, Muhammad, Hartwick, Edward, Siddiqi, Azfar A, Wilkins, Melinda, Davies, Herbert D, Rahbar, Mohammad, Funk, Julie, Saeed, Mahdi
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2267442/
https://www.ncbi.nlm.nih.gov/pubmed/18093323
http://dx.doi.org/10.1186/1476-072X-6-56
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author Younus, Muhammad
Hartwick, Edward
Siddiqi, Azfar A
Wilkins, Melinda
Davies, Herbert D
Rahbar, Mohammad
Funk, Julie
Saeed, Mahdi
author_facet Younus, Muhammad
Hartwick, Edward
Siddiqi, Azfar A
Wilkins, Melinda
Davies, Herbert D
Rahbar, Mohammad
Funk, Julie
Saeed, Mahdi
author_sort Younus, Muhammad
collection PubMed
description BACKGROUND: The majority of U.S. disease surveillance systems contain incomplete information regarding socioeconomic status (SES) indicators like household or family income and educational attainment in case reports, which reduces the usefulness of surveillance data for these parameters. We investigated the association between select SES attributes at the neighborhood level and Salmonella infections in the three most populated counties in Michigan using a geographic information system. METHODS: We obtained data on income, education, and race from the 2000 U.S. Census, and the aggregate number of laboratory-confirmed cases of salmonellosis (1997–2006) at the block group level from the Michigan Department of Community Health. We used ArcGIS to visualize the distribution, and Poisson regression analysis to study associations between potential predictor variables and Salmonella infections. RESULTS: Based on data from 3,419 block groups, our final multivariate model revealed that block groups with lower educational attainment were less commonly represented among cases than their counterparts with higher education levels (< high school degree vs. ≥ college degree: rate ratio (RR) = 0.79, 95% confidence interval (CI):0.63, 0.99; ≥ and high school degree, but no college degree vs. ≥ college degree: RR = 0.84, 95% CI: 0.76, 0.92). Levels of education also showed a dose-response relation with the outcome variable, i.e., decreasing years of education was associated with a decrease in Salmonella infections incidence at the block group level. CONCLUSION: Education plays a significant role in health-seeking behavior at the population level. It is conceivable that a reporting bias may exist due to a greater detection of Salmonella infections among high education block groups compared to low education block groups resulting from differential access to healthcare. In addition, individuals of higher education block groups who also have greater discretionary income may eat outside the home frequently and be more likely to own pets considered reservoirs of Salmonella, which increase the likelihood of contracting Salmonella infections compared to their counterparts with lower levels of education. Public health authorities should focus on improving the level of disease detection and reporting among communities with lower income and education and further evaluate the role of higher educational attainment in the predisposition for salmonellosis.
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spelling pubmed-22674422008-03-14 The role of neighborhood level socioeconomic characteristics in Salmonella infections in Michigan (1997–2007): Assessment using geographic information system Younus, Muhammad Hartwick, Edward Siddiqi, Azfar A Wilkins, Melinda Davies, Herbert D Rahbar, Mohammad Funk, Julie Saeed, Mahdi Int J Health Geogr Research BACKGROUND: The majority of U.S. disease surveillance systems contain incomplete information regarding socioeconomic status (SES) indicators like household or family income and educational attainment in case reports, which reduces the usefulness of surveillance data for these parameters. We investigated the association between select SES attributes at the neighborhood level and Salmonella infections in the three most populated counties in Michigan using a geographic information system. METHODS: We obtained data on income, education, and race from the 2000 U.S. Census, and the aggregate number of laboratory-confirmed cases of salmonellosis (1997–2006) at the block group level from the Michigan Department of Community Health. We used ArcGIS to visualize the distribution, and Poisson regression analysis to study associations between potential predictor variables and Salmonella infections. RESULTS: Based on data from 3,419 block groups, our final multivariate model revealed that block groups with lower educational attainment were less commonly represented among cases than their counterparts with higher education levels (< high school degree vs. ≥ college degree: rate ratio (RR) = 0.79, 95% confidence interval (CI):0.63, 0.99; ≥ and high school degree, but no college degree vs. ≥ college degree: RR = 0.84, 95% CI: 0.76, 0.92). Levels of education also showed a dose-response relation with the outcome variable, i.e., decreasing years of education was associated with a decrease in Salmonella infections incidence at the block group level. CONCLUSION: Education plays a significant role in health-seeking behavior at the population level. It is conceivable that a reporting bias may exist due to a greater detection of Salmonella infections among high education block groups compared to low education block groups resulting from differential access to healthcare. In addition, individuals of higher education block groups who also have greater discretionary income may eat outside the home frequently and be more likely to own pets considered reservoirs of Salmonella, which increase the likelihood of contracting Salmonella infections compared to their counterparts with lower levels of education. Public health authorities should focus on improving the level of disease detection and reporting among communities with lower income and education and further evaluate the role of higher educational attainment in the predisposition for salmonellosis. BioMed Central 2007-12-19 /pmc/articles/PMC2267442/ /pubmed/18093323 http://dx.doi.org/10.1186/1476-072X-6-56 Text en Copyright © 2007 Younus et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Younus, Muhammad
Hartwick, Edward
Siddiqi, Azfar A
Wilkins, Melinda
Davies, Herbert D
Rahbar, Mohammad
Funk, Julie
Saeed, Mahdi
The role of neighborhood level socioeconomic characteristics in Salmonella infections in Michigan (1997–2007): Assessment using geographic information system
title The role of neighborhood level socioeconomic characteristics in Salmonella infections in Michigan (1997–2007): Assessment using geographic information system
title_full The role of neighborhood level socioeconomic characteristics in Salmonella infections in Michigan (1997–2007): Assessment using geographic information system
title_fullStr The role of neighborhood level socioeconomic characteristics in Salmonella infections in Michigan (1997–2007): Assessment using geographic information system
title_full_unstemmed The role of neighborhood level socioeconomic characteristics in Salmonella infections in Michigan (1997–2007): Assessment using geographic information system
title_short The role of neighborhood level socioeconomic characteristics in Salmonella infections in Michigan (1997–2007): Assessment using geographic information system
title_sort role of neighborhood level socioeconomic characteristics in salmonella infections in michigan (1997–2007): assessment using geographic information system
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2267442/
https://www.ncbi.nlm.nih.gov/pubmed/18093323
http://dx.doi.org/10.1186/1476-072X-6-56
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