Division of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts, Amherst, MA 01003-9304,USA.
Paediatr Perinat Epidemiol. 2009 Sep;23(5):394-402. doi: 10.1111/j.1365-3016.2009.01053.x.
The 'birthweight paradox' describes the phenomenon whereby birthweight-specific mortality curves cross when stratified on other exposures, most notably cigarette smoking. The paradox has been noted widely in the literature and numerous explanations and corrections have been suggested. Recently, causal diagrams have been used to illustrate the possibility for collider-stratification bias in models adjusting for birthweight. When two variables share a common effect, stratification on the variable representing that effect induces a statistical relation between otherwise independent factors. This bias has been proposed to explain the birthweight paradox. Causal diagrams may illustrate sources of bias, but are limited to describing qualitative effects. In this paper, we provide causal diagrams that illustrate the birthweight paradox and use a simulation study to quantify the collider-stratification bias under a range of circumstances. Considered circumstances include exposures with and without direct effects on neonatal mortality, as well as with and without indirect effects acting through birthweight on neonatal mortality. The results of these simulations illustrate that when the birthweight-mortality relation is subject to substantial uncontrolled confounding, the bias on estimates of effect adjusted for birthweight may be sufficient to yield opposite causal conclusions, i.e. a factor that poses increased risk appears protective. Effects on stratum-specific birthweight-mortality curves were considered to illustrate the connection between collider-stratification bias and the crossing of the curves. The simulations demonstrate the conditions necessary to give rise to empirical evidence of the paradox.
“出生体重悖论”描述了这样一种现象，即在按其他暴露因素（尤其是吸烟）分层后，出生体重特异性死亡率曲线会相交。这一悖论在文献中被广泛注意到，并且已经提出了许多解释和纠正方法。最近，因果关系图已被用于说明在调整出生体重的模型中存在混杂分层偏倚的可能性。当两个变量具有共同的效应时，按表示该效应的变量分层会在其他独立因素之间产生统计关系。这种偏倚被认为可以解释出生体重悖论。因果关系图可以说明偏倚的来源，但仅限于描述定性影响。在本文中，我们提供了说明出生体重悖论的因果关系图，并使用模拟研究在一系列情况下量化了混杂分层偏倚。所考虑的情况包括对新生儿死亡率有直接影响和没有直接影响的暴露因素，以及通过出生体重对新生儿死亡率有间接影响和没有间接影响的暴露因素。这些模拟的结果表明，当出生体重与死亡率的关系受到大量未被控制的混杂因素的影响时，对出生体重进行调整后的效应估计的偏倚可能足以产生相反的因果结论，即增加风险的因素似乎具有保护作用。还考虑了对特定于层的出生体重-死亡率曲线的影响，以说明混杂分层偏倚与曲线相交之间的联系。模拟结果表明了产生悖论经验证据的必要条件。
