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The impact of education on dental health — Ways to measure causal effects
Author(s) -
Grytten Jostein
Publication year - 2017
Publication title -
community dentistry and oral epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.061
H-Index - 101
eISSN - 1600-0528
pISSN - 0301-5661
DOI - 10.1111/cdoe.12319
Subject(s) - causality (physics) , medicine , instrumental variable , observational study , regression discontinuity design , causal inference , dental health , causal model , regression analysis , health education , measure (data warehouse) , econometrics , dentistry , statistics , public health , nursing , data mining , physics , mathematics , pathology , quantum mechanics , computer science , economics
Abstract To our knowledge, there are no studies in which a possible causal effect of education on dental health has been examined. Such studies are needed to predict whether more schooling for people with poor dental health improves their dental health. Within social science, and in economics in particular, several methods have been developed to make causal inferences of the relationship between education and general health. These methods, which are based on observational data, are relevant to use for estimating a possible causal effect of education on dental health. This commentary provides an overview of the state of the art of the following methods: the use of instrumental variables, twin studies and a regression discontinuity design. Using these methods, reversed causality and the omission of a third variable that influences both education and dental health can be controlled for. In that way, an unbiased estimate of the effect of education on dental health can be obtained. To implement each of the methods correctly, several criteria have to be fulfilled. These criteria are outlined and discussed below.