Report comment

Report comment

As for safety: remember the lower rate of birth defects with sperm donors. That implies limits on how much damage freezing could do.

Report comment

The researchers ran regressions where they effectively compared children born to the same father at different times in his life, and they reported enormous changes in psychiatric problems. They found big effects on autism: Children born to men over 45 were 3.5 times as likely to be diagnosed with autism as those born to men aged 20 to 24.

…But let’s look a little more closely at the data and statistics here. The authors actually ran three analyses. First, they looked at the raw data and asked, on average, are children born to older fathers more likely to have ADHD? Second, they controlled for some demographics, such as education and income, and maternal age. And finally, they ran their “sibling fixed effects” regression. They reported their results in helpful graphs, and below we’ve replicated the one for ADHD. http://espnfivethirtyeight.files.wordpress.com/2014/04/oster-bad-sperm-adhd.png In the first analysis using raw data, older men do not appear to be more likely to have children with ADHD. In the second analysis, when the researchers’ adjusted for some characteristics of the father, mother, and so on, we see that the children of older fathers are less likely to be diagnosed with ADHD. It’s only when we move to the siblings analysis that we see a huge positive effect of paternal age on a child’s likelihood of an ADHD diagnosis.

One theory for this gap in results is, of course, that the final analysis is the most accurate because it examines children under near ideal conditions: They were born to the same father at different times in his life. But when there is such a big difference in findings across analyses, it’s worth asking if something odd is going on. To answer this, we need to be clear on what this “sibling fixed effects” analysis really does. Consider a dad with two children, born four years apart. A basic fixed-effects model would ask whether the older child is less likely to have ADHD than the younger, and then attribute any observed difference to paternal age.

Running this basic analysis would have the same problem with maternal age that we discussed earlier. Because mothers often age along with fathers within a family, if we analyzed sibling pairs with the same mother and the same father, it would be impossible to separate the effects of maternal and paternal age. This paper does claim to separate these effects. How? The data includes half-siblings — children who share a father but not a mother.1 The authors can infer the effects of the father’s age separately from the mother’s age by looking within groups of siblings who share a father but not a mother. That means the huge positive effect seen in the chart above essentially tells us that a later-born child of a father who has multiple kids with multiple partners is more likely to be diagnosed with ADHD. In the paper, this difference is attributed to paternal age.

Why push so deeply into the statistics here? Seeing what the data is really saying lets us think a little more about what else might be happening. Now that we know the effects are driven by differences across half-siblings, we can start asking what else — beyond paternal age — might be driving the difference. Most obviously, we may wonder whether being a child in a fluid family situation could itself have an impact on ADHD risk (as other studies have found). Another, if more mundane, explanation for the big effect that paternal age appears to have on a child’s ADHD risk is that by striving so hard to isolate the effect of paternal age, the paper’s authors ended up studying a small number of individuals. And this makes it more likely that the results they saw were just due to chance.

Report comment

Report comment

Wat. Genetic load doesn’t work like that. If there were enough mutations in a single generation to be significantly noticeable, the species would be utterly unmaintainable without seriously strong eugenics.

As it is, the ratio between background mutational load and the amount generated every generation is probably around 10-30 times at least. That is, we all have the equivalent of at least 10-30 generations of mutational load, with variance between people probably on the order of 5-10 generations at least, so the effect of an additional generation is probably not so significant.

It would be good to do real calculation with real numbers, or even find some data, but I don’t buy it for now.

That said, this is all assuming we don’t control for the genetic load of the parents. If we did control for the genetic load of the parents, we could measure the generational mutations.

Report comment

Report comment

@moridinamael Say that to porn industry, they must have gotten something seriously wrong.

Report comment

Report comment

Report comment