Predicting the Population Health Impacts of Community Interventions: The Case of Alcohol Outlets and Binge Drinking

被引:22
作者
Ahern, Jennifer [1 ]
Colson, K. Ellicott [1 ]
Margerson-Zilko, Claire [2 ]
Hubbard, Alan [3 ]
Galea, Sandro [4 ]
机构
[1] Univ Calif Berkeley, Sch Publ Hlth, Div Epidemiol, Berkeley, CA 94720 USA
[2] Michigan State Univ, Coll Human Med, Dept Epidemiol & Biostat, E Lansing, MI 48824 USA
[3] Univ Calif Berkeley, Sch Publ Hlth, Div Biostat, Berkeley, CA 94720 USA
[4] Boston Univ, Sch Publ Hlth, Boston, MA USA
基金
美国国家卫生研究院;
关键词
CAUSAL INFERENCE; COLLECTIVE EFFICACY; EPIDEMIOLOGY; NEIGHBORHOODS; ORGANIZATION; VERSION; MODELS; NORMS;
D O I
10.2105/AJPH.2016.303425
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
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.
引用
收藏
页码:1938 / 1943
页数:6
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