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Ecological Fallacy and Aggregated Data: A Case Study of Fried Chicken Restaurants, Obesity and Lyme Disease.
Salkeld, Daniel J; Antolin, Michael F.
Affiliation
  • Salkeld DJ; Department of Biology, Colorado State University, Fort Collins, CO, 80523, USA. dan.salkeld@colostate.edu.
  • Antolin MF; Department of Biology, Colorado State University, Fort Collins, CO, 80523, USA.
Ecohealth ; 17(1): 4-12, 2020 03.
Article in En | MEDLINE | ID: mdl-32026056
ABSTRACT
Interdisciplinary approaches are merited when attempting to understand the complex and idiosyncratic processes driving the spillover of pathogens from wildlife and vector species to human populations. Public health data are often available for zoonotic pathogens but can lead to erroneous conclusions if the data have been spatially or temporally aggregated. As an illustration, we use human Lyme disease incidence data as a case study to examine correlations between mammalian biodiversity, fried chicken restaurants and obesity rates on human disease incidence. We demonstrate that Lyme disease incidence is negatively correlated with mammalian biodiversity, the abundance of fried chicken restaurants and obesity rates. We argue, however, that these correlations are spurious, representing both an 'ecologic fallacy' and Simpson's paradox, and are generated by the use of aggregated data. We argue that correlations based on aggregated data across large spatial scales must be rigorously examined before being invoked as proof of disease ecology theory or as a rationale for public health policy.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Lyme Disease / Bias / Fast Foods / Obesity Type of study: Incidence_studies / Prognostic_studies Limits: Animals / Humans Language: En Journal: Ecohealth Year: 2020 Document type: Article Affiliation country: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Lyme Disease / Bias / Fast Foods / Obesity Type of study: Incidence_studies / Prognostic_studies Limits: Animals / Humans Language: En Journal: Ecohealth Year: 2020 Document type: Article Affiliation country: United States