| 1. |
- Sujan, Ayesha C., et al.
(författare)
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A Genetically Informed Study of the Associations Between Maternal Age at Childbearing and Adverse Perinatal Outcomes
- 2016
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Ingår i: Behavior Genetics. - New York, USA : Springer. - 0001-8244 .- 1573-3297. ; 46:3, s. 431-456
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Tidskriftsartikel (refereegranskat)abstract
- We examined associations of maternal age at childbearing (MAC) with gestational age and fetal growth (i.e., birth weight adjusting for gestational age), using two genetically informed designs (cousin and sibling comparisons) and data from two cohorts, a population-based Swedish sample and a nationally representative United States sample. We also conducted sensitivity analyses to test limitations of the designs. The findings were consistent across samples and suggested that, associations observed in the population between younger MAC and shorter gestational age were confounded by shared familial factors; however, associations of advanced MAC with shorter gestational age remained robust after accounting for shared familial factors. In contrast to the gestational age findings, neither early nor advanced MAC was associated with lower fetal growth after accounting for shared familial factors. Given certain assumptions, these findings provide support for a causal association between advanced MAC and shorter gestational age. The results also suggest that there are not causal associations between early MAC and shorter gestational age, between early MAC and lower fetal growth, and between advanced MAC and lower fetal growth.
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| 2. |
- D'Onofrio, Brian M., et al.
(författare)
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Translational Epidemiologic Approaches to Understanding the Consequences of Early-Life Exposures
- 2016
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Ingår i: Behavior Genetics. - New York, USA : Springer. - 0001-8244 .- 1573-3297. ; 46:3, s. 315-328
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Forskningsöversikt (refereegranskat)abstract
- Prominent developmental theories posit a causal link between early-life exposures and later functioning. Yet, observed associations with early exposures may not reflect causal effects because of genetic and environmental confounding. The current manuscript describes how a systematic series of epidemiologic analyses that combine several genetically-informative designs and statistical approaches can help distinguish between competing theories. In particular, the manuscript details how combining the use of measured covariates with sibling-comparisons, cousin-comparisons, and additional designs can help elucidate the sources of covariation between early-life exposures and later outcomes, including the roles of (a) factors that are not shared in families, including a potential causal effect of the exposure; (b) carryover effects from the exposure of one child to the next; and (c) familial confounding. We also describe key assumptions and how they can be critically evaluated. Furthermore, we outline how subsequent analyses, including effect decomposition with respect to measured, plausible mediators, and quantitative genetic models can help further specify the underlying processes that account for the associations between early-life exposures and offspring outcomes.
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