2019
DOI: 10.1111/rssa.12543
|View full text |Cite
|
Sign up to set email alerts
|

Can Genetics Reveal the Causes and Consequences of Educational Attainment?

Abstract: Summary There is an extensive literature on the causes of educational inequalities, and the life course consequences of educational attainment. Mendelian randomization, where genetic variants associated with exposures of interest are used as proxies for those exposures, often within an instrumental variables framework, has proven highly effective at elucidating the causal effects of several risk factors in the biomedical sciences. We discuss the potential for this approach to be used in the context of social a… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2

Citation Types

0
2
0

Year Published

2023
2023
2024
2024

Publication Types

Select...
3
1
1

Relationship

0
5

Authors

Journals

citations
Cited by 5 publications
(2 citation statements)
references
References 56 publications
0
2
0
Order By: Relevance
“…MR’s core assumptions are: (1) some variants are associated with the exposure (EA), (2) these variants are related to mental health only via their effect on educational success, and (3) these variants do not correlate with any confounders of the relationship between education and mental health 10 . When assumptions are met, MR estimates the causal effect of education on mental health, even in presence of confounding and measurement error 11 . Reverse causation can be empirically evaluated by running two sets of MR analyses: one with variants related to EA as exposure and variants related to psychiatric diagnoses as outcome, and the reverse analysis.…”
Section: Introductionmentioning
confidence: 99%
“…MR’s core assumptions are: (1) some variants are associated with the exposure (EA), (2) these variants are related to mental health only via their effect on educational success, and (3) these variants do not correlate with any confounders of the relationship between education and mental health 10 . When assumptions are met, MR estimates the causal effect of education on mental health, even in presence of confounding and measurement error 11 . Reverse causation can be empirically evaluated by running two sets of MR analyses: one with variants related to EA as exposure and variants related to psychiatric diagnoses as outcome, and the reverse analysis.…”
Section: Introductionmentioning
confidence: 99%
“…MR's core assumptions are: (1) some variants are associated with the exposure (EA), (2) these variants are related to mental health only via their effect on educational success, and (3) these variants do not correlate with any confounders of the relationship between education and mental health 223 . When assumptions are met, MR estimates the causal effect of education on mental health, even in presence of confounding and measurement error 224 . Reverse causation can be empirically evaluated by running two sets of MR analyses: one with variants related to EA as exposure and variants related to psychiatric diagnoses as outcome, and the reverse analysis.…”
Section: Introductionmentioning
confidence: 99%