Citation

Ahern J, Colson KE, Margerson-Zilko C, Hubbard A, Galea S. Am. J. Public Health 2016; 106(11): 1938-1943.

Affiliation

Jennifer Ahern and K. Ellicott Colson are with the Division of Epidemiology, School of Public Health, University of California, Berkeley. Claire Margerison-Zilko is with the Department of Epidemiology and Biostatistics, College of Human Medicine, Michigan State University, East Lansing. Alan Hubbard is with the Division of Biostatistics, School of Public Health, University of California, Berkeley. Sandro Galea is with the School of Public Health, Boston University, Boston, MA.

Copyright

(Copyright © 2016, American Public Health Association)

DOI

10.2105/AJPH.2016.303425

PMID

27631757

Abstract

A substitution estimator can be used to predict how shifts in population exposures might change health. We illustrated this method by estimating how an upper limit on alcohol outlet density might alter binge drinking in the New York Social Environment Study (n = 4000), and provided statistical code and sample data. The largest differences in binge drinking were for an upper limit of 70 outlets per square mile; there was a -0.7% difference in binge drinking prevalence for New York City overall (95% confidence interval [CI] = -0.2%, -1.3%) and a -2.4% difference in binge drinking prevalence for the subset of communities the intervention modified (95% CI = -0.5%, -4.0%). A substitution estimator is a flexible tool for estimating population intervention parameters and improving the translation of public health research results to practitioners. (Am J Public Health. Published online ahead of print September 15, 2016: e1-e6. doi:10.2105/AJPH.2016.303425).

Language: en