共 82 条
What matters most: quantifying an epidemiology of consequence
被引:58
作者:

Keyes, Katherine
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机构:
Columbia Univ, Dept Epidemiol, New York, NY USA Columbia Univ, Dept Epidemiol, New York, NY USA

Galea, Sandro
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h-index: 0
机构:
Boston Univ, Sch Publ Hlth, Dept Epidemiol, Boston, MA 02118 USA Columbia Univ, Dept Epidemiol, New York, NY USA
机构:
[1] Columbia Univ, Dept Epidemiol, New York, NY USA
[2] Boston Univ, Sch Publ Hlth, Dept Epidemiol, Boston, MA 02118 USA
关键词:
Causal inference;
Consequentialism;
Consequentialist epidemiology;
Causes;
Interaction;
Prevalence;
CAUSAL INFERENCE;
SOCIOECONOMIC-STATUS;
MENTAL-ILLNESS;
FATTY-ACIDS;
RISK;
HEALTH;
MORTALITY;
INTELLIGENCE;
ASSOCIATION;
YOUNG;
D O I:
10.1016/j.annepidem.2015.01.016
中图分类号:
R1 [预防医学、卫生学];
学科分类号:
1004 ;
120402 ;
摘要:
Risk factor epidemiology has contributed to substantial public health success. In this essay, we argue, however, that the focus on risk factor epidemiology has led epidemiology to ever increasing focus on the estimation of precise causal effects of exposures on an outcome at the expense of engagement with the broader causal architecture that produces population health. To conduct an epidemiology of consequence, a systematic effort is needed to engage our science in a critical reflection both about how well and under what conditions or assumptions we can assess causal effects and also on what will truly matter most for changing population health. Such an approach changes the priorities and values of the discipline and requires reorientation of how we structure the questions we ask and the methods we use, as well as how we teach epidemiology to our emerging scholars. (C) 2015 Elsevier Inc. All rights reserved.
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页码:305 / 311
页数:7
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