选择(遗传算法)
生命历程法
学历
选择偏差
人口学
生命银行
遗传力
医学
心理学
生物
发展心理学
遗传学
病理
人工智能
计算机科学
社会学
经济
经济增长
作者
Shiro Furuya,Fengyi Zheng,Qiongshi Lu,Jason M. Fletcher
出处
期刊:Demography
[Duke University Press]
日期:2024-03-14
卷期号:61 (2): 363-392
标识
DOI:10.1215/00703370-11239766
摘要
Abstract Causal life course research examining consequences of early-life exposures has largely relied on associations between early-life environments and later-life outcomes using exogenous environmental shocks. Nonetheless, even with (quasi-)randomized early-life exposures, these associations may reflect not only causation (“scarring”) but also selection (i.e., which members are included in data assessing later life). Investigating this selection and its impacts on estimated effects of early-life conditions has, however, often been ignored because of a lack of pre-exposure data. This study proposes an approach for assessing and correcting selection, separately from scarring, using genetic measurements. Because genetic measurements are determined at the time of conception, any associations with early-life exposures should be interpreted as selection. Using data from the UK Biobank, we find that in utero exposure to a higher area-level infant mortality rate is associated with genetic predispositions correlated with better educational attainment and health. These findings point to the direction and magnitude of selection from this exposure. Corrections for this selection in examinations of effects of exposure on later educational attainment suggest underestimates of 26–74%; effects on other life course outcomes also vary across selection correction methods.
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