Estimating global mortality from potentially foodborne diseases: an analysis using vital registration data.

ABSTRACT:

Background

Foodborne diseases (FBD) comprise a large part of the global mortality burden, yet the true extent of their impact remains unknown. The present study utilizes multiple regression with the first attempt to use nonhealth variables to predict potentially FBD mortality at the country level.

Methods

Vital registration (VR) data were used to build a multiple regression model incorporating nonhealth variables in addition to traditionally used health indicators. This model was subsequently used to predict FBD mortality rates for all countries of the World Health Organization classifications AmrA, AmrB, EurA, and EurB.

Results

Statistical modeling strongly supported the inclusion of nonhealth variables in a multiple regression model as predictors of potentially FBD

SUBMITTER: Hanson LA 

PROVIDER: S-EPMC3341201 | biostudies-literature | 2012 Mar

REPOSITORIES: biostudies-literature