Section of Ecology, Department of Biology, University of Turku, Turku 20014, Finland
Proc Biol Sci. 2017 Dec 13;284(1868). doi: 10.1098/rspb.2017.2104.
A shorter lifespan as a potential cost of high reproductive effort in humans has intrigued researchers for more than a century. However, the results have been inconclusive so far and despite strong theoretical expectations we do not currently have compelling evidence for the longevity costs of reproduction. Using Monte Carlo simulation, it is shown here that a common practice in human reproduction-longevity studies using historical data (the most relevant data sources for this question), the omission of women who died prior to menopausal age from the analysis, results in severe underestimation of the potential underlying trade-off between reproduction and lifespan. In other words, assuming that such a trade-off is expressed also during reproductive years, the strength of the trade-off between reproduction and lifespan is progressively weakened when women dying during reproductive ages are sequentially and non-randomly excluded from the analysis. In cases of small sample sizes (e.g. few hundreds of observations), this selection bias by reducing statistical power may even partly explain the null results commonly found in this field. Future studies in this field should thus apply statistical approaches that account for or avoid selection bias in order to recover reliable effect size estimates between reproduction and longevity.
高繁殖努力可能导致人类寿命缩短，这一潜在代价引起了研究人员一个多世纪的兴趣。然而，到目前为止，研究结果尚无定论，尽管理论上有强烈的预期，但我们目前并没有令人信服的证据表明繁殖会带来寿命成本。本文通过蒙特卡罗模拟表明，在使用历史数据（针对该问题最相关的数据源）进行人类生殖-寿命研究的常见做法中，将绝经前死亡的女性从分析中排除，会严重低估繁殖和寿命之间潜在的权衡关系。换句话说，如果这种权衡关系也在生殖期表达，那么随着在生殖期死亡的女性被依次、非随机地从分析中排除，繁殖和寿命之间的权衡关系的强度会逐渐减弱。在样本量较小的情况下（例如只有几百个观察值），这种选择偏差可能会通过降低统计能力来部分解释该领域中常见的无效结果。因此，该领域的未来研究应采用能够解释或避免选择偏差的统计方法，以恢复繁殖和寿命之间可靠的效应大小估计值。
