Meaning of "shared familial confounding" in a study

Question

From a news report:

Using population-based, longitudinal cohort study data from Sweden, researchers examined the relationship of infection during childhood with IQ and adult nonaffective psychosis. They also assessed whether shared familial confounding explains the infection-nonaffective psychosis and IQ-nonaffective psychosis relationships, and whether IQ alters the childhood infection-psychosis link. They included 647,515 Swedish men born between 1973 and 1992 in the analysis who were hospitalized with any infection from birth to age 13 years. They measured hospitalization for diagnosed nonaffective psychosis until the end of 2011, and IQ at age 18 years.

What is the meaning of shared familial confounding in this text? I'm trying to understand it "from the context" and can't. I'm now googling for "familial confounding" and trying to understand what that means, but thus far I found no clear definition, only studies that use this term, and it's a bit hard to understand.

P.S. I cross-posted the question on Stats SE.

Answer 1

If A and B occur together more than would be expected, most people assume that A causes B or B causes A. Confounding refers to the case where something else affects both of them, making them appear more directly related than they truly are.

For example, say I do a study and discover that most Olympic athletes come from wealthy families, at a rate far more than everyone else. I find a correlation between wealth and Olympic success. Some people might say "that makes sense, they get put into expensive sports when they're young, their families can buy equipment and pay coaches, and they can concentrate on their sport instead of having to work at a job in their teens and twenties." But someone else might point out that tall people are generally richer than short people -- more successful, get more promotions, etc, and for most sports, taller people do better. Or is it that rich people, who eat better and have less stress, grow up taller than poor people? Anyway, maybe their tallness is causing their sports excellence and is correlated with their wealth. Height becomes a confounding factor. Does it explain all the wealth/Olympic correlation? Or most of it? Or just a little bit of it?

Shared familial confounding refers to things like "if your parents are tall, you'll probably also be tall and so will your siblings." It could also refer to "if your parents had a lot of success in sports, they will encourage you to do it too" -- and whatever factors led them to their success in sports may or may not still exist for you.

You can try to separate the confounding in the athlete study by looking at sports in which being taller isn't an advantage, or sports that don't require years of expensive training, equipment, memberships, vacation trips to ski resorts etc. You can also look at adopted children, who don't share genes with their parents, to try to reduce some of the "tall child from a tall parent" aspect. It's hard.

In your study, you can imagine the question is "does getting a lot of childhood infections mean you're more likely to be psychotic?" and they I suppose I have to deal with "does being psychotic mean your children, who inherit your tendency to psychosis in their genes or by the way you raise them, are more likely to get a lot of infections?" as well as "is there something that runs in families that might make you psychotic and more likely to get a lot of childhood infections?" - either by having a weak immune system or by being exposed to some other agent or by being raised a certain way or having certain genes. Those are shared familial confounding,

Answer 2

Confounding:

In statistics, a confounder (also confounding variable or confounding factor) is a variable that influences both the dependent variable and independent variable causing a spurious association. Confounding is a causal concept, and as such, cannot be described in terms of correlations or associations.

That is: you see a correlation between two variables and try to understand the causality that might connect the two variables you look at. If there is a causal factor, but an indirect/external one concerning your two variables of interest then you only have confirmed the correlation, but are not much the wiser for the probable causal link connecting them. This is very often a problem if we like to hunt for monocausal explanations and in reality there are more factors than one influencing the outcome of any observation.

If variables A and B are correlated, that's interesting. If A causes B it's fantastic to know. But If C causes A and B, and you do not know about C, it's still a dark box. You want to get to know C and how much iz is causing anything on A and/or B. Sometimes it is not easy to manipulate C, then you must at least identify C and better yet try to control C.

The study mentioned in the news report is:

Association of Childhood Infection With IQ and Adult Nonaffective Psychosis in Swedish Men. A Population-Based Longitudinal Cohort and Co-relative Study

Second, is the association between childhood infection and adult psychotic disorders likely to be causal, or could this be explained by shared familial confounding? A 2015 study used co-relative control analyses to show that shared familial confounding is an unlikely explanation for the association between lower premorbid IQ and adult psychotic disorders. The IQ-psychosis association was similar in the general population and in cousin, half-sibling, and full-sibling pairs with differing IQs. If there were confounding by shared familial risk factors, the association would be expected to become progressively weaker in groups sharing increasing levels of genes and environment compared with the general population; this was not the case. These findings also suggest that unique (nonshared) environmental risk factors may contribute to lower premorbid IQ in individuals with schizophrenia. Childhood infection may be such an environmental factor not shared within families. To our knowledge, no study has examined the effect of shared familial confounding on the association between childhood infection and adult psychosis. We are not aware of any independent replication of the co-relative analyses of premorbid IQ and adult psychosis.

This is perhaps easier to understand if already explained in a headline:

Familial (shared environmental and genetic) factors and the foetal origins of cardiovascular diseases and type 2 diabetes: a review of the literature

In that article you have the following visual explanation:

Familial (socio-economic and genetic) confounding of the association between birth weight and risk of cardiovascular diseases and type 2 diabetes.

So, in your case, the study tries to determine whether childhood infections are the most important causal factor for explaining the observed correlation for adult psychotic disorders, or whether there are shared influences that might attribute their bit to an explanation. Among those familial variables in this study were:

Winter birth (December to May), migration status (either parent born outside Sweden), parental history of NAP (from NPR), household crowding (ie, when the number of livable rooms minus 1 is greater than the number of people living in the house), and parental highest socioeconomic status when the participant was aged 8 to 12 years were included as potential confounders.

That made them feel confident enough to reach the following conclusion:

We present evidence that early childhood is a sensitive period for the effects of infection on IQ and risk of NAP. The associations of adult NAP with early-childhood infection and adolescent IQ are not fully explained by shared familial factors and may be causal. Lower premorbid IQ in NAP arises from unique environmental factors, such as early-childhood infection or other factors intimately related to this. Childhood infection may increase risk of adult NAP by affecting neurodevelopment and by exaggerating the effects of cognitive vulnerability to psychosis.