Does population mixing measure infectious exposure in children at the community level?
Author(s) -
John Taylor,
Graham Law,
Paul J. Boyle,
Zhiqiang Feng,
Mark S. Gilthorpe,
Roger C Parslow,
Gavin Rudge,
Richard Feltbower
Publication year - 2008
Publication title -
european journal of epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.825
H-Index - 111
eISSN - 1573-7284
pISSN - 0393-2990
DOI - 10.1007/s10654-008-9272-0
Subject(s) - medicine , epidemiology , demography , population , census , infectious disease (medical specialty) , proxy (statistics) , incidence (geometry) , etiology , standardized rate , environmental health , public health , disease , statistics , pathology , physics , mathematics , sociology , optics
Epidemiological studies focusing on the etiology of childhood chronic diseases have used population mixing as a proxy for the level of infection circulating in a community. We compared different measures of population mixing (based on residential migration and commuting) and other demographic variables, derived from the United Kingdom Census, with hospital inpatient data on infections from two Government Office Regions in England (Eastern and the West Midlands) to inform the development of an infectious disease proxy for future epidemiological studies. The association between rates of infection and the population mixing measures was assessed, using incidence rate ratios across census areas, from negative binomial regression. Commuting distance demonstrated the most consistent association with admissions for infections across the two regions; areas with a higher median distance travelled by commuters leaving the area having a lower rate of hospital admissions for infections. Deprived areas and densely populated areas had a raised rate of admissions for infections. Assuming hospital admissions are a reliable indicator of common infection rates, the results from this study suggest that commuting distance is a consistent measure of population mixing in relation to infectious disease and deprivation and population density are reliable demographic proxies for infectious exposure. Areas that exhibit high levels of population mixing do not necessarily possess raised rates of hospital admissions for infectious disease.
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