Balloon

I seem to remember reading somewhere that Jean Piaget once investigated his infant’s motor abilities by tying a string to the infant’s hand. By pulling the string, the infant could cause a pleasant sound to be made. The infant soon learned this action-outcome contingency, apparently demonstrating a capacity to hold an internal representation of his own action and its relationship to a desired outcome.

In the same spirit, I want to see how easily Dahlia can learn that she has the capacity to control the movement of a balloon of which the string is attached to her wrist. At 20 days, it looks to me as though she already understands something:

 

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Dahlia vs. Mirror

 

Mirrors provide a lot of useful information about the nature of an organism’s self-perception.[1] The ability to recognise one’s mirror image as belonging to oneself indicates an awareness of the fact that one’s own consciousness resides within a body that resembles those with which one frequently interacts. This realisation is only a few steps away from the recognition that others, who possess bodies similar to that of oneself, also have thoughts and feelings just like oneself. This latter stage of understanding is known as “theory of mind”. Accordingly, a number of developmental theorists link children’s attainment of the self-awareness that is necessary for self-recognition in a mirror to the emergence of theory of mind.[2]

However, children typically take about two years to recognise themselves in the mirror.[3] Amsterdam (1972) describes the developmental changes observed in mirror-viewing infants as follows:

the first prolonged and repeated reaction of an infant to his mirror image is that of a sociable “playmate” from about 6 through 12 months of age. In the second year of life wariness and withdrawal appeared; self‐admiring and embarrassed behaviour accompanied those avoidance behaviours starting at 14 months, and was shown by 75% of the subjects after 20 months of age. During the last part of the second year of life, from 20 to 24 months of age, 65% of the subjects demonstrated recognition of their mirror images.”

But research also indicates that past experience with mirrors is helpful in learning to recognise one’s image therein.[4] I therefore thought it would be useful to record Dahlia’s behaviour in front of a mirror over her first years of life. Here are some videos that I have already recorded – I intend to continually add to this collection until Dahlia has ambiguously achieved self-recognition. Along the way, look out for interesting behaviours such as experimental/investigative movements (i.e. movements that appear to be designed to test the extent to which one’s own actions are imitated by the body observed in the mirror) and/or anything else that you think indicates some interesting cognitive goings-on.

Experimenters often focus on cues such as performing self-directed actions guided by visual input from the mirror (e.g. trying to rub away a dirty mark from one’s face that can only be seen in the mirror) or performing actions that appear intended to test the hypothesis that one’s own behaviour is immediately mimicked by the image in the mirror.

Personally, I am interested to see whether Dahlia’s repeated exposure to mirrors helps her to understand what she is seeing at an earlier-than-typical age. Given that this kind of self-understanding is important for other-understanding (Flavell, 1999), I hope that her repeated mirror exposure will facilitate the acquisition of skills related to theory of mind.

 

 

 

[1] Amsterdam, 1972; Anderson, 1984; Roma et al., 2007

[2] Gallup, 1998; Perner, 1991

[3] Amsterdam, 1984. Mirror self-recognition in infants and humans is usually assessed by observing the extent to which an individual utilises information attained from the mirror to act upon their own body. Specifically, a mark is placed on an area (usually the forehead) that can only be seen in the mirror. If, upon seeing their reflection, the individual touches the area of the forehead on which the mark has been placed, then self-recognition can be inferred. For more details and additional methodological considerations, see Chang et al., 2015.

[4] Chang et al., 2015

 

 

 

 

References

Amsterdam Mirror self-image reactions before age two Dev. Psychobiol., 5 (1972), pp. 297–305

Anderson, J. R. (1984). Monkeys with mirrors: Some questions for primate psychology. International Journal of Primatology5(1), 81-98.

Chang, L., Fang, Q., Zhang, S., Poo, M. M., & Gong, N. (2015). Mirror-induced self-directed behaviors in rhesus monkeys after visual-somatosensory training. Current Biology25(2), 212-217

Flavell, J. H. (1999). Cognitive development: Children’s knowledge about the mind. Annual review of psychology, 50(1), 21-45.

Gallup, G. G., Jr. (1998). Self-awareness and the evolution of social intelligence. Behavioural Processes, 42, 239–247.

Perner, J. (1991). Understanding the representational mind. Cambridge, MA: MIT Press.

Roma, P. G., Silberberg, A., Huntsberry, M. E., Christensen, C. J., Ruggiero, A. M., & Suomi, S. J. (2007). Mark Tests for mirror self‐recognition in capuchin monkeys (Cebus apella) trained to touch marks. American Journal of Primatology69(9), 989-1000.

Breastfeeding

Across the world, healthcare professionals seem to have reached an overwhelming consensus on the value and importance of breastfeeding. UNICEF, the World Health Organisation and numerous National Health bodies expend vast resources promoting the huge developmental benefits ascribed to breastfeeding.[1] For the baby, these benefits include increased cognitive ability,[2] improved mental health in adolescence[3] and reduced risk of respiratory tract infections, diarrhea, asthma, food allergies, celiac disease, type 1 diabetes, obesity, infections, sudden infant death syndrome, cardiovascular disease and leukemia.[4] For the mother, purported benefits include reduced risk of breast cancer, ovarian cancer, osteoporosis, cardiovascular disease and obesity.[5]

On the basis of these claimed effects, parents can expect to receive regular reminders, often very forcefully worded, of the importance of breastfeeding. Marsha Walker, Executive Director of the National Alliance for Breastfeeding Advocacy, writes that even a single bottle feed before six months will cause irreparable harm to a baby,[6] an assertion that has been parroted by a number of influential writers and bloggers.[7] The argument underlying this rather bold claim relates to the effects of breast and bottle feeding on the bacterial content of the infant’s gut. The adult gut, and indeed the entire adult body, is filled with a delightful array of bacteria, fungi, and archaea (known collectively as the microbiota), without which many of the ordinary biological functions that keep us ticking would be impossible.[8] Some of these microorganisms are “good” (their presence generally contributes positively to human health), whilst other are classified as “bad” (their presence may harm human health).

In contrast, the gut of a neonate is sterile, meaning that it is devoid of the bacteria typically found in the adult gut.[9] As such, early events in the infant’s life, such as the type of birth (Caesarean or vaginal) that they experience, can have a long-lasting influence on the characteristics of their microbiota. The neonate’s gut is also “open”, which means that the small gaps (known as tight junctions) between the enterocytes (a type of epithelial cell) of the intestinal lining are larger than in adults. However, intestinal permeability (the extent to which the tight junctions are “open”) drops rapidly in the first week of life before undergoing a more gradual decline thereafter.[10]

According to some breastfeeding advocates, the high intestinal permeability of the infant gut means that harmful bacteria and/or substances that stimulate the growth thereof can pass through to the bloodstream when the infant consumes formula milk. Breast milk, on the other hand, has been evolutionarily endowed with the perfect mixture of enzymes, antibodies and nutrients to cultivate the most awesome microbiota you could ever imagine. So nothing in breast milk would be expected to cause problems in the context of high intestinal permeability. [11]

It is claimed that the undesirable bacteria that formula milk allows to grow within the infant’s gut lead to a long-lasting change in the constituency of their microbiota, resulting in a variety of problems that would not arise in the presence of an optimally cultivated (through exclusive breastfeeding) microbiota.[12] Hence, it is concluded that even a single bottle feed will cause lasting harm to an infant.

Neglected Issues

As you might have guessed, I am a little bit sceptical of the remarkable properties ascribed to breast milk. But before considering the evidence for the above claims, it is important to clarify a few issues that are often neglected or assigned insufficient attention in the breastfeeding literature.

First, and most obviously, the “correlation does not equal causation” principle is extremely pertinent when evaluating claims made about the incredible powers of breast milk. Almost all of the health benefits ascribed to breastfeeding have been inferred on the basis of correlational data – there are very, very few randomised control trials in which breastfeeding status has been experimentally manipulated. This is clearly problematic – correlations between breastfeeding and, for example, child leukaemia[13] do not necessarily imply a causal influence of breastfeeding on leukaemia risk. It may be that factors correlated with breastfeeding, such as maternal education,[14] have a causal impact on leukaemia risk, with no causal role played by breastfeeding itself.

This is particularly important given that there are number of factors that are linked to breastfeeding and that are very likely to have a significant impact on the health of the mother and the child. These include maternal socio-economic status,[15] maternal age,[16] maternal education14 immigrant status[17] single parent status[18] and maternal smoking behaviour.[19] Associations found between breastfeeding and any given outcome could therefore plausibly reflect the causal influence of any of these factors, which can therefore be labelled “confounding variables”.

Researchers sometimes attempt to account the effects of confounding variables by measuring them and statistically controlling for their impact. For instance, if you have a rough of idea the impact of maternal smoking on child IQ, you could assess maternal smoking behaviour and then control for its impact on IQ in a given sample of children. In other words, after measuring each child’s IQ, you would use your knowledge of the statistical association between maternal smoking and IQ to estimate how your sample of children would vary in terms of IQ if their mothers all had equivalent smoking behaviour. If the estimates of each child’s IQ derived thusly still correlated with breastfeeding status, then it could be inferred that the correlation between IQ and breastfeeding in your sample cannot be attributed to the confound between breastfeeding and maternal smoking.

However, even when researchers take care to control for the effects of numerous confounding variables in this way, inference of causality on the basis of correlational data is still problematic for a number of reasons:

  • There may be additional confounding factors for which the researchers were unable to control.
  • It may be difficult to measure the confounding factors precisely, making it impossible to fully control for their impact on any observed correlations.
  • Controlling for a given confounding variable requires estimating the effect of said variable on the outcome variable (e.g. IQ). If this estimate is not perfectly accurate (which it never can be), then the statistical control procedure will not completely account for the confound.

Hence, a major issue in the interpretation of research pertaining to the benefits of breastfeeding is the “correlation does not equal causation” principle: the presence of a correlation between breastfeeding and a particular outcome cannot be used to infer a causal influence of breastfeeding on the outcome in question.

A second issue is the fact that evidence for a plausible mechanism does not constitute evidence for an effect. Permit me to explain this principle with an example. Zhang et al. (2012) cultivated samples of different types of bacteria in breast milk, formula milk and bovine (cow) milk. Simply put, they found that the bacteria in the breast milk grew in a manner that would be more conducive to infant health relative to the bacteria in the other milk solutions. Essentially, the bacteria in the breast milk clustered together to form a biofilm that would serve as a barrier against infection; the bacteria in the other milk solutions failed to do so or did it so a lesser extent.

Some people have taken this finding as evidence that breastfeeding promotes resistance to infection. But herein lies “evidence for a mechanism does not constitute evidence for an effect” issue. The fact that breastmilk is shown to have a particular biological property in the laboratory does not necessarily guarantee that it will have corresponding effects in the body. The human body is extremely complex and reacts to incoming substances in a sophisticated and often unexpected manner. It may compensate for the absence of a particular nutrient by synthesising more of said nutrient by itself; it may break down incoming substances before they reach the region where they would be able to exert any effect; it may be able to initiate certain processes by itself when nutritional inputs fail to do so. There are feedback mechanisms and downstream effects, and the capacity to effect a change in one part of a biological process may be constrained by the factors that appear to be totally unrelated thereto. Moreover, a given substance may have numerous different effects across the body, meaning that isolating a single effect of a substance in a petri dish may not give an accurate understanding of its total impact on human health.

Take the example of anti-oxidants. It is well established that anti-oxidants reduce the activity of free-radicals, which are atoms or molecules that can impair cell-functioning. It follows that dietary supplementation with anti-oxidants should reduce improve cell functioning by removing free-radicals, whereas research shows that this is not in fact the case.[20] Thus, the actual effect of a particular substance may not conform with what would be expected on the basis of the known biological function and laboratory behaviour of the substance.

Therefore, the effects of breast milk on human health cannot be discerned on the basis of studies that examine potential mechanisms for its biological impact.[21] For instance, to determine the effect of breastfeeding on IQ, it is not sufficient to conduct laboratory studies in which the impact of substances contained in breastmilk on biological functions known to be related to IQ are investigated. The only definitive way to address the question is to measure IQ in samples of infants who are randomly assigned to receive more or less breastfeeding.[22] We cannot determine the impact of breastfeeding on susceptibility to infection by examining the behaviour of breast milk in the laboratory. Likewise, we cannot draw conclusions about the impact of breastfeeding on Leukaemia, infection, cardiovascular disease or mental health simply by assessing the influence of breastfeeding on biological processes that are related to these disorders. Breastfeeding status must be manipulated, and the effect of the manipulation on the outcome variable of interest must be observed. Any study that focuses solely on biological markers or laboratory findings that are believed to be important for an outcome variable of interest cannot provide a definitive understanding of the health properties of breast milk.

The Evidence

Having established two pitfalls that need to be avoided when interpreting evidence relating to the effects of breastfeeding, we can now explore the relevant evidence. There is of course extensive correlational evidence linking breastfeeding to all of the aforementioned beneficial medical outcomes, and then some.[23] However, as noted above, the utility of this research is limited given the fundamental “correlation does not necessarily imply causation” problem. Nevertheless, researchers have employed a variety of strategies to circumvent this problem in their attempts to ascertain the causal influence of breastfeeding on the outcome variables that it is commonly purported to affect.

Brion et al., 2011

Brion et al. (2011) examined correlations between receipt of breastfeeding, Body Mass Index (BMI), Blood Pressure (BP) and IQ in samples of participants taken from high and middle income countries. The confounding structures of these two types of countries differ – in other words, the variables that correlate with breastfeeding and that could plausibly give rise to the effects typically attributed thereto are different in high and middle income countries. For instance, Brion et al. (2011) breastfeeding is strongly correlated with socio-economic status in Britain, but not in Brazil. Brion et al. (2011) reasoned that any causal effects of breastfeeding on BMI, BP or IQ would be expected to give rise to consistent correlations between breastfeeding and the outcome in question across countries of various income levels. Conversely, any correlations between breastfeeding and a given outcome variable that were due to confounding factors would only be expected to emerge in the countries in which the relevant confounding structure was present.

Brion et al. (2011) found that IQ was consistently correlated with receipt of breastfeeding across countries of different income levels, but that BP and BMI were only correlated with IQ in high income countries. This is the pattern that would be expected given a causal effect of breastfeeding on IQ and a breastfeeding-BMI and breastfeeding-BP correlation attributable to confounding with socio-economic status. Thus, Brion et al.’s (2011) results indicated that breastfeeding has a causal role in enhancing IQ, but has no effect on BMI or BP.

Caspi et al. (2007)

Caspi et al. (2007) assessed the extent to which the relationship between breastfeeding and IQ varies as a function of a person’s genetic characteristics. They examined a single nucleotide polymorphism (a single DNA unit in the genome of which the molecular identity varies across people) on a gene called FADS2. FASD2 codes for a protein that is involved in the metabolism of fatty acids. Since breast milk contains a number of fatty acids that are absent in formula milk and that are believed to be important for neurocognitive development,[24] Caspi et al. (2007) deemed the possibility of this gene’s modulation of the link between breastfeeding and IQ to be worthy of investigation. Specifically, they examined the IQ difference between breastfed and non-breastfed individuals for three different genetic variants of the SNP of interest on the FASD2 gene. They found that the relationship between breastfeeding and IQ differed depending on the version of the FASD2 SNP that a person had. For most of their sample, breastfeeding was associated with a significantly higher IQ. However, among people with a specific variant of the SNP under investigation, there was no relationship between breastfeeding and IQ.

This finding supports the presence of a causal link between breastfeeding and IQ because it reveals the existence of a statistical interaction that is consistent with a likely plausible mechanism of this effect. If the commonly observed IQ – breastfeeding correlation is simply due to some form of confounding, then there would be no reason to expect the magnitude thereof to vary as a function of genotype. However, if receipt breastfeeding influences IQ via the delivery of fatty acids, then it would make sense that genes involved in the metabolism of fatty acids would modulate the effects of breastfeeding on IQ. Thus, although Caspi et al.’s (2007) result do not definitively confirm the they existence of a causal link between breastfeeding and IQ, they do suggest that such a link is likely to be present.

Randomised Control Trials

Randomised Control Trials represent the Gold Standard for assessing the presence of a causal relationship between two variables. It is therefore surprising that the number of RCTs addressing a practice as highly promoted as breastfeeding is less than a handful (for a comparable example, see the case of flossing[25]). The most highly cited of these was conducted by Kramer et al. (2001), who studied mothers attending 31 maternal hospitals and their polyclinics in the Republic of Belarus. Each site was randomly assigned to receive a breastfeeding promotion or to continue with their existing breastfeeding communication practices. The authors then compared mothers who had been seen at the sites with breastfeeding campaigns to the mothers at the sites wherein there had been no additional breastfeeding promotion.[26] As would be expected, there was clear evidence that the breastfeeding promotion campaign had been successful: mothers attending the sites with breastfeeding promotion campaigns were significantly more likely to breastfeed – and did so for longer – than mothers attending the control sites.

Kramer et al. (2001) found that performance on IQ tests and teachers’ reports of academic performance at 6.5 years of age were significantly higher for children whose mothers had attended the sites with breastfeeding promotion compared to the children of mothers who had attended the control sites. This is the strongest piece of evidence for the beneficial effects of breastfeeding on IQ that anyone has heretofore produced.

Other studies taking measurements from the same participants have found breastfeeding to have a positive effect on attitudes towards food and healthy eating,[27] but no effect was observed on cariometabolic risk factors such as blood pressure and obesity.[28]

However, a separate RCT on a different sample found that preterm infants who were fed banked breast milk developed more favourable cholesterol profiles as adolescents relative to infants who were fed banked formula milk.[29]

There have also been two RCTs in Honduras comparing infants who were exclusively breastfeed for 4 – 6 months with infants who were not exclusively breast fed.[30] These studies did not find any particularly noteworthy differences between the two conditions.[31]

Finally, an RCT conducted by Lindfors and Enocksson (1988) found that exposure to a small amount of formula milk prior to initiation of breastfeeding reduced the risk of subsequent allergy development relative to a control group of exclusively breastfed infants. This clearly contradicts the “even a single bottle feed will permanently harm your baby” claim, although it does not provide a clear indication of the effects of long term exposure to formula milk. Moreover, it should be noted that an RCT conducted by De Jong et al. (2002) found no significant effects in an attempted replication of Lindfors and Enocksson (1998).

Intra-sibling pair comparison

A number of studies have sought to disentangle the effects of breastfeeding from the effects of the numerous variables confounded therewith by examining sibling pairs who were discordant in their receipt of breastfeeding. This involves identifying sibling pairs in which one sibling was breastfed whilst the other was not. Since both siblings have the same parents and family background, any differences between them cannot be attributed thereto. For instance, the IQ – breastfeeding correlation is often suspected of being due to confounding with maternal IQ, since more intelligent mothers are more likely to breast feed.[32] Comparing siblings discordant for breastfeeding eliminates this possibility, because a difference between children of the same mother clearly cannot be due to the differences in maternal characteristics.

Using this model, Metzger and McDade (2010) found that bottle fed members of siblings pairs were at significantly greater risk of obesity in adolescence than their breastfed siblings. However, other studies have found null effects using this design for a range of variables, including asthma, hyperactivity, attachment, compliance, academic achievement[33] and IQ.[34]

Nevertheless, it is important to note that a straight-forward interpretation of sibling comparisons may be problematic. It is possible that mothers worry more about infants that show initial signs of developmental problems (e.g. low birthweight; unstable temperament etc.) and are consequently more motivated to breastfeed such infants in order to compensate for their apparent difficulties. Such a selection effect would mask the beneficial effects of breastfeeding, because it would mean that breastfed infants within sibling pairs would start at a higher level of developmental risk relative to their bottle fed sibling.

It is also possible that mothers who do not breastfeed all of their infants are not representative of the general breastfeeding population. It may be that such mothers are relatively under-motivated to breastfeed relative to other breastfeeding mothers (hence their decision to bottle feed their other child), and they may consequently fail to develop the ability to breastfeed as effectively as more motivated mothers.[35] The effects of effective, “textbook” breastfeeding may therefore be underestimated by examining the offspring of these mothers, who could have been breastfed in a relatively “ineffective” manner. Thus, null effects observed in sibling studies cannot be taken as definitive evidence for the absence of a beneficial causal effect of breastfeeding on child development.

Conclusion

The existing body of literature presents quite a mix message about the effects of breastfeeding, and it is difficult to summarise the overall gist of this research in simple terms. My interpretation is that breastfeeding is very likely to have a small beneficial effect on some developmental outcomes, and is very, very unlikely to have a negative effect relative to bottle feeding.

 

References

American Academy of Pediatrics Section on Breastfeeding. (March 2012). “Breastfeeding and the use of human milk”Pediatrics129 (3): 827–841.

Bartels, M., Van Beijsterveldt, C. E. M., & Boomsma, D. I. (2009). Breastfeeding, maternal education and cognitive function: a prospective study in twins. Behavior genetics39(6), 616-622.

Brion, M. J. A., Lawlor, D. A., Matijasevich, A., Horta, B., Anselmi, L., Araújo, C. L., … & Smith, G. D. (2011). What are the causal effects of breastfeeding on IQ, obesity and blood pressure? Evidence from comparing high-income with middle-income cohorts. International Journal of Epidemiology, dyr020

Catassi, C., Bonucci, A., Coppa, G. V., Carlucci, A. & Giorgi, P. L. Intestinal permeability changes during the first month: effect of natural versus artificial feeding. J. Pediatr. Gastroenterol. Nutr. 21, 383–386 (1995).

 

Colen, C. G., & Ramey, D. M. (2014). Is breast truly best? Estimating the effects of breastfeeding on long-term child health and wellbeing in the United States using sibling comparisons. Social Science & Medicine109, 55-65

 

De Jong, M. H., Scharp-Van Der Linden, V. T. M., Aalberse, R., Heymans, H. S. A., & Brunekreef, B. (2002). The effect of brief neonatal exposure to cows’ milk on atopic symptoms up to age 5. Archives of disease in childhood86(5), 365-369.

 

Der, G., Batty, G. D., & Deary, I. J. (2006). Effect of breast feeding on intelligence in children: prospective study, sibling pairs analysis, and meta-analysis. Bmj333(7575), 945.

 

Donath, S., & Amir, L. H. (2000). Rates of breastfeeding in Australia by State and socio‐economic status: Evidence from the 1995 National Health Survey. Journal of Paediatrics and Child Health36(2), 164-168.

Duan, X., Wang, J., & Jiang, X. (2016). A meta-analysis of breastfeeding and osteoporotic fracture risk in the females. Osteoporosis International, 1-9.

 

Dubois, L., & Girard, M. (2003). Social determinants of initiation, duration and exclusivity of breastfeeding at the population level: the results of the Longitudinal Study of Child Development in Quebec (ELDEQ 1998-2002). Canadian Journal of Public Health/Revue Canadienne de Sante’e Publique, 300-305.

 

Goldacre, B. (2014). Bad pharma: how drug companies mislead doctors and harm patients. Macmillan.

 

Henderson, J., & Redshaw, M. (2011). Midwifery factors associated with successful breastfeeding. Child: care, health and development37(5), 744-753.

 

Jiménez, E., Marín, M. L., Martín, R., Odriozola, J. M., Olivares, M., Xaus, J., … & Rodríguez, J. M. (2008). Is meconium from healthy newborns actually sterile?. Research in microbiology159(3), 187-193.

Kalach, N., Rocchiccioli, F., Boissieu, D., Benhamou, P.-H. & Dupont, C. Intestinal permeability in children: variation with age and reliability in the diagnosis of cow’s milk allergy. Acta Paediatr. 90, 499–504 (2001).

 

Kramer, M. S., Chalmers, B., Hodnett, E. D., Sevkovskaya, Z., Dzikovich, I., Shapiro, S., … & Shishko, G. (2001). Promotion of Breastfeeding Intervention Trial (PROBIT): a randomized trial in the Republic of Belarus. Jama285(4), 413-420.

 

Kramer, M. S., & Kakuma, R. (2012). Optimal duration of exclusive breastfeeding. The Cochrane Library.

 

Kwan, M. L., Buffler, P. A., Abrams, B., & Kiley, V. A. (2004). Breastfeeding and the risk of childhood leukemia: a meta-analysis. Public health reports119(6), 521.

 

Lamberti, L. M., Zakarija-Grković, I., Walker, C. L. F., Theodoratou, E., Nair, H., Campbell, H., & Black, R. E. (2013). Breastfeeding for reducing the risk of pneumonia morbidity and mortality in children under two: a systematic literature review and meta-analysis. BMC public health13(3), 1.

Lesa, G. M., Palfreyman, M., Hall, D. H., Clandinin, M. T., Rudolph, C., Jorgensen, E. M., & Schiavo, G. (2003). Long chain polyunsaturated fatty acids are required for efficient neurotransmission in C. elegans. Journal of cell science116(24), 4965-4975.

Lindfors, A., & Enocksson, E. (1988). Development of atopic disease after early administration of cow milk formula. Allergy43(1), 11-16.

Marchesi, J. R. (2010). “Prokaryotic and Eukaryotic Diversity of the Human Gut”. Advances in Applied Microbiology Volume 72. Advances in Applied Microbiology. 72. pp. 43–62.

Marques, T. M., Wall, R., Ross, R. P., Fitzgerald, G. F., Ryan, C. A., & Stanton, C. (2010). Programming infant gut microbiota: influence of dietary and environmental factors. Current opinion in biotechnology21(2), 149-156.

Martin, R. M., Patel, R., Kramer, M. S., Vilchuck, K., Bogdanovich, N., Sergeichick, N., … & Gillman, M. W. (2013). Effects of promoting longer term and exclusive breastfeeding on cardiometabolic risk factors at age 11.5 years: a cluster-randomized, controlled trial. Circulation, CIRCULATIONAHA-113.

Metzger, M. W., & McDade, T. W. (2010). Breastfeeding as obesity prevention in the United States: a sibling difference model. American journal of human biology22(3), 291-296.

Najdawi, F., & Faouri, M. (1999). Maternal smoking and breastfeeding.

Noone, C., Menzies, I. S., Banatvala, J. E. & Scopes, J. W. Intestinal permeability and lactose hydrolysis in human rotaviral gastroenteritis assessed simultaneously by non-invasive differential sugar permeation. Eur. J. Clin. Invest. 16, 217–225 (1986).

Oddy, W. H., Kendall, G. E., Li, J., Jacoby, P., Robinson, M., de Klerk, N. H., … & Stanley, F. J. (2010). The long-term effects of breastfeeding on child and adolescent mental health: a pregnancy cohort study followed for 14 years. The Journal of pediatrics156(4), 568-574.

Quinn, P. J., O’Callaghan, M., Williams, G. M., Najman, J. M., Andersen, M. J., & Bor, W. (2001). The effect of breastfeeding on child development at 5 years: a cohort study. Journal of paediatrics and child health37(5), 465-469.

Rittershaus, L., & Halling, T. (2013). “Breast is best”—Infant-feeding, infant mortality and infant welfare in Germany during the late nineteenth and twentieth centuries. Health2013.

Singh, G. K., Kogan, M. D., & Dee, D. L. (2007). Nativity/immigrant status, race/ethnicity, and socioeconomic determinants of breastfeeding initiation and duration in the United States, 2003. Pediatrics119(Supplement 1), S38-S46.

Singhal, A., Cole, T. J., Fewtrell, M., & Lucas, A. (2004). Breastmilk feeding and lipoprotein profile in adolescents born preterm: follow-up of a prospective randomised study. The Lancet363(9421), 1571-1578

Skugarevsky, O., Wade, K. H., Richmond, R. C., Martin, R. M., Tilling, K., Patel, R., … & Gillman, M. W. (2014). Effects of promoting longer-term and exclusive breastfeeding on childhood eating attitudes: a cluster-randomized trial. International journal of epidemiology, dyu072

Vallès, Y., Gosalbes, M. J., de Vries, L. E., Abellán, J. J., & Francino, M. P. (2012). Metagenomics and development of the gut microbiota in infants. Clinical Microbiology and Infection18(s4), 21-26.

Walker, M. (2004). “Just One Bottle Won’t Hurt”–or Will It?. Supplementation of the breastfed baby. Accessed online at http://www. health-e-learning. com/articles/JustOneBottle. pdf.

Q Zhang, A., Y Ryan Lee, S., Truneh, M., L Everett, M., & Parker, W. (2012). Human whey promotes sessile bacterial growth, whereas alternative sources of infant nutrition promote planktonic growth. Current Nutrition & Food Science8(3), 168-176.

[1] Rittershaus & Halling, 2013

[2] Quinn et al., 2001

[3] Oddy et al., 2010

[4] American Academy of Pediatrics Section on Breastfeeding, 2012;
NHS choices http://www.nhs.uk/conditions/pregnancy-and-baby/Pages/benefits-breastfeeding.aspx

[5] NHS choices

[6] Walker, 2004

[7] E.g. https://www.hyperbiotics.com/blogs/recent-articles/109024966-the-importance-of-a-virgin-gut-breastfeeding-is-more-essential-than-we-thought

[8] Marchesi, 2010

[9] Recently, it has been found that the infant gut is not totally sterile – some bacteria transfer from the mother to the foetus in utero (Jimenes et al., 2008). However, the constituency of the neonate microbiota is markedly different from that of an adult, and only reaches an adult-like composition at around 12 months of age (Valles et al., 2012).

[10] Catassi et al., 1995; Noone et al., 1986; Kalach et al., 2001. The Alpha Parent blog, in referring to the “open gut” concept to justify the superiority of breastfeeding, mistakenly claims that the gut closure occurs at 6 months: http://www.thealphaparent.com/2011/07/virgin-gut-note-for-parents.html
Science of Mom directly addresses error: https://scienceofmom.com/2016/05/03/whats-up-with-the-virgin-gut-do-babies-really-have-an-open-gut-until-6-months-of-age/

[11] Marques et al., 2010

[12] http://www.thealphaparent.com/2011/07/virgin-gut-note-for-parents.html

[13] Kwan et al., 2004

[14] Bartels, 2009

[15] Donath & Amir, 2000

[16] Dubois & Girard, 2003

[17] Singh et al., 2007

[18] Henderson & Redshaw, 2011

[19] Najdawi & Faouri, 1999

[20] Goldacre, 2014

[21] Such studies may certainly be useful, but in isolation they cannot provide a complete picture of the health consequences of breastfeeding on mother and infant health.

[22] Given that depriving an infant of breast milk may be harmful, ethical constraints demand that such studies are conducted by randomly assigning infants to intervention conditions (wherein mothers are actively encouraged to breastfeed to a greater extent than usual) or control conditions (wherein the researchers make no attempts to sway mothers’ breastfeeding decisions). Studies that have used this strategy are discussed below.

[23] Duang, Wang and Jiang, 2016; Lamberti et al., 2013

[24] Lesa et al., 2003

[25] http://www.nytimes.com/2016/08/03/health/flossing-teeth-cavities.html

[26] This design is known as “cluster randomisation” – rather than assigning individual babies to be breast fed or bottle fed, the researchers assigned large groups of mothers to be exposed or to not be exposed to a breastfeeding intervention. This avoided the obvious ethical issues that would be involved in assigning a child to be bottle fed. Note that it would not have been sufficient to run a breastfeeding promotion at one site and compare it to one other control site, because doing so would mean that any observed differences between the sites could be attributable to the features of the individual sites themselves, rather than to the breastfeeding promotion.

[27] Skugarevsky et al. (2014)

[28] Martin et al. (2013)

[29] Singhal et al. (2005)

[30] Cohen (1994); Dewey (1999)

[31] For a good summary of their findings, see Kramer and Kakuma (2012).

[32] Caspi et al. (2007)

[33] Colen and Ramey (2014)

[34] Der et al. (2006)

[35] For anyone who is not aware: breastfeeding is not easy.

Your parenting efforts are futile, fool!

Before setting out on a project to supply one’s unborn child with an awesome developmental environment, it is pertinent to ask the following question:

What’s the point?

“What a dumb question!” the affronted reader scoffed at his/her computer screen. “If we can take for granted the assumption that we want our children to grow into happy, competent and well-adjusted adults, then how can anyone question the ‘point’ of trying to be a good parent?!?”

Well, dear reader, even if one accepts (which I do) that parents have a duty to create the best future that they can for their children, it is nevertheless perfectly reasonable to question whether parents have the ability to influence their children’s development. How do we know that parents have any effect at all on the lives that their children will lead 10, 20, 30 or 60 years down the line? How do I know, in other words, that all of my (planned[1]) effort to give Dahlia a bright future will not be entirely futile?

I don’t mean this in an esoteric/fatalistic “it’s all in the hands of fate” way. I’m alluding to a number of prominent developmental researchers who genuinely believe that the role of parents and their choices in influencing children’s development is pretty close to zero. And these guys aren’t just nutters on the outer fringes of Developmental Psychology – they are respected academics with plenty of empirical evidence from which to draw support. But before I introduce you to these lovely people, a little (actually, a lot of) background is required. Please be warned – major digression is up ahead.

A few decades ago, it was very trendy for social science researchers to use correlational research to study of variables that were often claimed to play causal roles in driving important developmental outcomes[2]. The research literature sagged with the weight of study after study documenting statistical relationships between a range of environmental factors and child characteristics. Parental involvement in criminal activities, it was found, correlates with offspring criminal behaviour[3]; over-controlling parents are more likely to have depressed children[4]; family social status correlates with children’s agreeableness (a personality trait)[5]; children who grow up in houses with more books develop into more proficient readers[6]; right wing and racist parents tend to have kids that are more right wing and racist than average[7] – the list is endless.

Many researchers[8] and some lay-people[9] took the view that these intergenerational correlations were attributable to the influence of parents’ behaviour on the development of their children. Criminal parents are generally abusive and violent, so their kids, being more messed-up than average as a consequence, go on to commit more crimes. Over-controlling parents prevent their children from seeking rewarding experiences, thereby inducing a state of helplessness that heightens their sensitivity to depression for life. Etcetera Etcetera. You, I, or uncle Bob could speculate about hundreds of plausible causal pathways from parenting styles to child outcomes covering each of the aforementioned correlations. The problem is that, as anyone with at least half a neuron’s worth of statistical knowledge[10] will be aware, causation cannot necessarily be inferred from causation.

Consider some examples. Ice cream sales and homicide rates correlate – peaks in purchases of ice creams tend to co-occur with increased activity among the homicidal maniac community. This is not because the taste of deliciousness makes people murderously angry. Nor is it because murderous anger makes people want to taste something delicious. It is because heat makes people murderously angry, and it also causes them to want ice-cream.[11] In other words, ice-cream consumption and murder have no causal connection to each other;[12] rather, a third factor (heat) has a simultaneous causal influence on both, leading to their statistical covariation in the absence of a direct causal link.

As such, correlational findings can rarely be taken as definitive evidence for a proposed causal relationship. If variable A correlates with variable B, then it could be that A causally influences B – but it could also be the case that B causally influences A, or that variable C has a causal influence on both A and B. Correlational information alone is insufficient to disambiguate between these alternatives.

In the case of intergenerational correlations like those described above, there are likewise a number of possible explanations, only some of which involve causal relationships. You might think that criminal parents abuse their children more and thereby cultivate little versions of their criminal selves. But it might equally be the case that criminal parents tend to live in poor neighbourhoods, and that growing up in such neighbourhoods causes their children to become involved in crime. It may be that some criminal behaviour is influenced by genetic factors, in which case the children of criminal parents would be expected to inherit a genetic profile that disposes them towards crime. Similarly, you might think that children who grow up in houses with plenty of books develop greater reading proficiency for an obvious reason: they have more exposure to engaging written material. But again, there are plenty of other plausible explanations for the “number of books in house – child reading proficiency” correlation. Parents with genes that confer reading ability would be expected to both purchase more books and to pass their genes on to their children. Well-read children and book abundance would then co-occur without having influenced one another.

To facilitate causal inferences about the factors that affect development, correlational designs that simply measure different variables are therefore insufficient. When it comes to assessing the causal influence of an environmental factor, randomised control trials are the gold standard. These essentially involve assembling a sample of children and randomly assigning some to a treatment condition (in which the child’s environment is altered in a way that is expected to be beneficial) or a control condition (in which the child’s environment is not altered). For instance, a sample of 100 children who attend normal day-care centres could be recruited, and 50 of them could be randomly transferred to a day-care centre of higher quality (treatment condition) whilst the others remain in their current day-care centre (control condition).[13] In this case, day-care quality would be called the independent variable – the variable whose causal impact is being tested. The researchers would then measure other variables of interest (e.g. IQ) from all of the children in the two conditions. These would be dependent variables – variables whose capacity to be causally influenced by the independent variable is being tested. Note that since each child receives either a beneficial intervention or no intervention at all, no harm will be caused to any of the participants as a consequence of the research.[14]

The beauty of randomised control trials is that they allow inferences to be made about the causal impact of the independent variable on the dependent variable(s). A significant difference between, for example, the mean IQ scores of the children in the treatment and control conditions could be used to infer (with high confidence) a causal influence of day-care quality on IQ. Since children were assigned randomly to the treatment and control conditions, there is a limit to how much we would expect children in the two conditions to differ purely as a result of chance. It would be unlikely for any two groups of children to be identical in terms of mean IQ, but it would also be unlikely for them to differ substantially in terms of mean IQ unless there is something causing them to differ. A significant mean IQ difference between the treatment and control groups would therefore allow us to infer that the factor that defines the two conditions (in this case day-care quality) had a causal influence on the children’s IQ.

Importantly, no ambiguities arise with regard to the direction of causality. The assignment to treatment or control condition was determined entirely by the researchers (who made their allocation based on chance), and we can therefore be absolutely sure that no other variables were responsible for determining the quality of day-care that the children received. Thus, the statistical relationship between day-care quality and IQ cannot be attributed to the fact that high IQ children are more likely to be assigned to receive higher-quality day-care, because the assignment was based on chance alone (not on IQ or anything else). Likewise, there can be no third variable affecting both day-care quality condition and IQ, because we know that the former was entirely determined by the researchers and not by any other variables. Thus, randomised control trials permit the evaluation of the causal influence of environmental factors (e.g. day-care quality) on important developmental outcomes (e.g. IQ).

Unfortunately, randomised control trials are expensive, impractical and often impossible to implement within the constraints of a civilised ethical system – for instance, you can’t randomly assign some children to be abused and some to be free from abuse in order to determine the consequences of abuse. Moreover, one of the most important influences on development – a person’s genes – cannot be randomly manipulated by researchers; a person’s genes are established before conception and remain stable throughout their life. Fortunately, people have come up with some pretty clever methods for assessing the extent to which a given trait or behaviour is subject to genetic influence. I’m going to briefly explain the two most common methods (the ones that you’ll find in any bog standard behavioural genetics textbook), but there are loads.

Before I do, however, it is probably important to clarify what is meant by the term “genetic influence” and “individual variation”. Individual variation refers to the extent to which individuals within a given population differ in terms of their score on a particular trait. For example, if everybody in a particular population is between 1.71m and 1.72m in height, the individual variation in height would be less compared to a situation in which people’s heights vary massively from 0.5m to 2.5m.

Genetic influence refers to the extent to which individual variation in a given trait or behaviour is caused by genetic variation. For instance, if I say that 50% of individual variation in IQ is attributable to genetic variation, this means that the total variation in IQ observed between different individuals would be 50% less if, hypothetically, we all had the same genes. In other words, the fact that we all have different genes (some of which push IQs up and some of which push IQs down) causes our IQs to vary by twice as much as they otherwise would.

This is an important point to note because it differs from lay people’s instinctive understanding of what is meant by “genetic influence”. Lay people typically assume that if a trait is subject to genetic influence, then it follows that there exist specific genetic variants that can cause people to be high or low on the trait (such as a “gay gene” or a “crime gene”). This is inaccurate for two main reasons. First, it is very rare for variants of a single gene to exert a large effect on traits or behaviour. Rather, it is almost always the case that many, many different genetic variants all exert very small individual effects, with the result that the cumulative effect of all the numerous different genes that influence a trait may be very high. Secondly, whilst genetic factors can increase the likelihood of certain developmental outcomes, they cannot guarantee a particular developmental outcome. For instance, a child with numerous genetic variants that confer high IQ will be more likely to actually develop an above-average IQ than a randomly selected member of the population. However, the child’s genes do not guarantee that this will happen, because it will always be possible for an environmental factor to prevent the development of a high IQ. For example, if the child is hit by an inter-continental ballistic missile (an environmental factor), he or she is unlikely to develop a high IQ on account of being dead. Thus, genetic influence should be thought of as a process that increases the likelihood of certain outcomes as a function of a person’s genetic profile, not as a process that guarantees that certain developmental outcomes will transpire.

Having clarified (I hope) what is meant by “genetic influence”, we can now explore the two principle techniques that are used in behavioural genetics to facilitate the estimate thereof for traits and behaviours of interest.

The twin method

The twin method involves recruiting samples of identical (Monozygotic, or MZ) and non-identical (Dizygotic, or DZ) twins. MZ twins share 100% of their DNA, whereas DZ twins share, on average, only 50% of their DNA[15]. By examining the degree of similarity observed within MZ and DZ twin pairs for a particular trait or behaviour, it is possible to make inferences about the effect of genetic factors

Let’s say you want to assess the extent to which genetic factors influence a person’s IQ. You would find 20 MZ twin pairs and 20 DZ twin pairs (the numbers here are purely for explanatory purposes and have no methodical relevance). Within each pair, you randomly assign one twin the label “twin 1” and the other the label “twin 2”, and you measure each twin’s IQ (giving you 80 different IQ scores). Making separate calculations for the MZ and DZ subsamples, you assess the correlation between the IQs of the twin 1s and their corresponding twin 2s. [16] Let’s say that you find a pattern looking something like the one depicted in these graphs:

MZDZ.png

In these graphs, each dot represents a single pair of twins. The dot’s position on the X axis denotes the IQ of twin 1 within the pair, and the dots position on the Y axis denotes the IQ of twin 2 within the pair. For example, the red dot on the MZ graph represents a twin pair in which twin 1 has an IQ of 112.5 and twin 2 has an IQ of 114. As can be seen, the IQs of the twin pairs in both the MZ and DZ groups are correlated, but the correlation is stronger for the MZ twins – knowing the IQ of twin 1 would enable us to make a better guess of twin 2’s IQ if we were looking at the MZ sample as opposed to the DZ sample.

The fact that the correlation is higher in the MZ sample allows us to infer a genetic influence on IQ. Since the members of both MZ twin pairs and DZ twin pairs grow up in the same household as their co-twin, greater similarity within MZ pairs relative to DZ pairs cannot be attributed to the impact of the family environment. Rather, the only potential causal factor that is shared to a greater extent within MZ twin pairs relative to DZ twin pairs is genes – MZ twin pairs share 100% of their genes whilst DZ twin pairs share, on average, 50% of their genes. As such, the fact that MZ twin pairs are more similar to each other in terms of IQ than DZ twin pairs can only be due to the increased genetic relatedness of the former. In this way, the collection of data from samples of MZ and DZ twins can enable to formulation of estimates about extent to which a given trait or behaviour is subject to genetic influence.

Twin studies can also allow us to make inferences about the impact of the shared-family environment (i.e. environmental factors that make children growing up in the same house more similar) on development. It is best to avoid too much statistical detail here – suffice to say that a causal role in shaping the development of a given trait can be ascribed to the shared family environment when the correlation among DZ twin pairs is more than half of the corresponding correlation among MZ twin pairs.

In the real world, studies like the one described above have indeed been conducted and generally indicate that about 70% of the variability in IQ between individuals can be attributed to genetic factors. In other words, if we lived in a hypothetical universe where everybody had the same genes, then the extent to which IQ would vary across individuals would be 70% less than in the current universe (Plomin & Spinath, 2004). Whoa!

Before I move on to describing a second method for assessing genetic and environmental influences on traits and behaviour, a few points must be noted with regard to the twin method in order to avoid giving a deceptively rosy picture of their capacity to adjudicate the intellectual arena between nature and nurture.
A.) Parents may instinctively treat MZ twin pairs in a more similar manner to DZ twin pairs, meaning that increased similarity among the former could be due to environmental, rather than genetic factors
B.) MZ twins are not actually 100% genetically identical – the genome of each twin within an MZ pair will contain a few novel mutations unique to that individual, which calls into question one of the key assumptions of the twin method.
C.) People often conform to the opinions and behaviour of others, particularly others who share their physical and dispositional characteristics. This could mean that members of MZ twin pairs mimic the behaviour and personality of their co-twin to a greater extent than members of DZ twin pairs, which could cause correlations among MZ twin pairs to increase in the absence of any genetic influence on the trait or behaviour under investigation.
D.) Twins in general may not be representative of the single-birth population. As such, estimates of the genetic and environmental contributions to traits and behaviours in twin samples may not be applicable to everyone else.
E.) MZ twins may share a more similar pre-natal environment than DZ twins. This could mean that greater MZ vs. DZ similarity could be attributable to pre-natal, not genetic, factors.
F.) Etcetera etcetera.

And now, we can talk about the adoption method.

The Adoption Method

The adoption method involves recruiting samples of children who were adopted into families to which they are not biologically related. Any similarity between the child and their adoptive family can only be attributed to the influence of the family environment, because the child has no genetic relationship with their adopted family. For instance, if children adopted into wealthy families develop higher IQs than children adopted into poorer families, we can infer that family wealth has a causal impact on the child’s IQ. In a typical family, it might be possible to argue that common genetic factors are responsible for conferring high IQ and high earning capacity, such that parents who are genetically disposed to be wealthy pass on IQ-enhancing genes to their children. However, such an explanation can be ruled out in the case of adoptive families, because in these families there is no biological relationship between children and parents and, thus, no mechanism for the transfer of IQ-enhancing genes. Thus, similarities between adopted children

Conversely, any similarity between the adopted child and their biological family can be attributed to the influence of genetic factors. Since the child never has contact with their biological family, the only thing capable of exerting a common influence on both the child and his/her biological relatives is shared genetic material. Thus, by examining the degree of similarity between adopted children and their biological and adopted families, it is possible to obtain evidence pertaining to the role of genetic and environmental factors in influencing a particular trait or behaviour.

So what?

By now, I would imagine that anyone who has bothered to read this far down is probably thinking something along the lines of “get to the point, please”. Well, I’m nearly there. You see, studies that have employed the adoption and twin methods describe above present what might be interpreted as a rather bleak and pessimistic view of parents’ capacity to alter the course of their children’s development. Basically, the existing body of evidence from twin and adoption suggests that, overall, the shared family environment has little to no influence on a wide range of important developmental outcomes. This would seem to suggest that parents have very little influence on their children’s futures.

For instance, consider the various studies that have examined used the adoption and twin methods to investigate the genetic and environmental influences on personality development. According to the most widely accepted model of personality, there are five distinct personality traits that define an individual’s idiosyncratic behavioural tendencies, namely openness to experience, extraversion, neuroticism, agreeableness and conscientiousness. Twin studies examining these “Big 5” personality traits indicate that about 45% of the individual variation therein is attributable to genetic variation,[17] with virtually no role played by the shared family environment. In other words, siblings from the same family would generally be more similar to each other in terms of personality that two randomly selected members of the population, but only because of their genetic relatedness and not because of the similar rearing environment that they would both have experienced.[18] Studies using the adoption method reveal similar findings: adopted children have similar personalities to their biological parents, but their similarity to their adoptive relatives is no greater than their mean similarity to a random member of the population.[19]

The story is similar for behavioural genetic studies of schizophrenia,[20] anxiety disorders,[21] cognitive ability in adulthood,[22] susceptibility to addiction,[23] likelihood of falling victim to school bullying,[24] obesity,[25] divorce[26] and plenty of other things. Even a trait like religiosity, which you would think should be almost entirely determined by the religious practices of your parents, is also subject to substantial genetic influence[27]. There are some exceptions: shared environmental factors have been found to exert a substantial influence on people’s tendencies towards criminal behaviour,[28] and twin (but not adoption) studies indicate that the shared family environment influences the risk of falling victim to depression[29].

What’s more, some intergenerational correlations that were once attributed to the effects of parents on their children have now been shown to be largely due to genetic confounds. For instance, take the finding that children whose parents frequently interact with them in a coercive manner are more likely to display anti-social behaviour[30]. This was once taken to indicate that coercive parenting causes children to behave antisocially. However, a rather famous adoption study casts doubt on this explanation. It was found that adopted children whose biological parents had an elaborate criminal history received more coercive parenting from their adoptive parents compared to other adopted children. Think about that for a moment – the criminal history of the adopted child’s biological parents correlated with the tendency of their adopted parents to behave in a coercive manner. Since the biological parents had no contact with their children, the only way that they could influence these children’s lives was through the genes transmitted to them. In other words, biological parents with criminal histories transmitted genes to their children that enhanced the children’s tendency to engage in aggressive and defiant behaviour; these aggressive and defiant behaviours then evoked hostile reactions from the adopted parents, leading to a correlation between biological parent criminal history and adoptive parent hostility.[31]

The remarkable thing about this finding is that it reveals that variables typically assumed to be causes of developmental outcomes may in fact be consequences of genetically-conferred tendencies that are more common in children who are already prone to develop in a certain way. In other words, children are not merely recipients of the causal inputs provided by their environments; they shape their environments through their own behaviour, which is often under genetic influence.[32]

Some researchers have interpreted these findings as evidence that the influence of parents on children’s development has been heavily overestimated. For instance, in her book “the nurture assumption”, Judith Harris argues that genetic influences on development far outweigh the impact of any factors over which parents are likely to have significant control. She also proposes that children’s peers have more influence on their development than their parents.[33] One example that she uses is language development – the children of immigrant parents learn the new language of their host culture easily from their peers; instead of mimicking their parents’ accents they adopt the (correct) pronunciations that they hear from same-age others.[34]

Personally, I think there is a lot of truth to what Harris says. Evidence for powerful genetic influences on a range of developmental outcomes is very, very strong.[35] Conversely, to my knowledge there is no comparable evidence for the causal role of parenting behaviours in development. As I will show below, there is evidence that parents have some effect on their children’s development across various domains, but data from twin, adoption and other genetically informative studies indicate that this environmental influence is highly unlikely to be greater than the impact of genetic factors.

Moreover, I think Harris is spot on when in pointing to the impact of peer influence on children’s development. Experiments using random assignment demonstrate that children’s aggression[36] smoking,[37] risk-taking[38] and wellbeing[39] is strongly influenced by the behaviour of their peers. Moreover, the fact that adolescent’s rate peer relationships as among their highest concerns in life[40] strongly suggests that they would be highly susceptible to peer pressure. Studies of “peer contagion” reveal that adolescence is a stage in life at which people are particularly prone to the influence of same-age others[41]. When people reach university age, studies examining random assignments to dormitory partners show that people tend to align their alcohol consumption and academic habits to those of their new room-mates[42], again highlighting the impact of peer influence on important developmental outcomes. Likewise, children’s computer-aided learning has been found to be influenced by the characteristics of the same-age learning partners that they are assigned.[43] More generally, children have been found to mimic the behaviours and problem solving strategies of other children around them from a very young age.[44]

Further evidence for the importance of peers in driving important developmental outcomes comes from studies of bullying in schools. A wide variety of evidence, some of which comes from randomised control trials, shows that being subject to bullying has a highly detrimental impact on children’s development.[45]

So, all in all, there is pretty good evidence that for the roles of both genes and peers in influencing development. Doesn’t this mean, then, that there simply isn’t much influence left for parents to exert?

I’m going to try to make the case below that the answer to this question is “no”. Peers and genes aside, I think there is good reason to believe that the choices the typical parent exerts a strong influence on their children’s development.

I have the power!

First, let me make a point about the evidence from twin studies mentioned above, which indicates that important variables such as personality are subject to little to no influence from the “shared family environment”. What this means is that there are no environmental factors causing children raised in the same household to be more similar to each other – the only reason siblings are more similar to each other than two random members of the population is because of their genetic relatedness. One might be tempted to infer that this means that parents have no impact on their children’s personality or susceptibility to mental illness. If parents’ behaviour did have an effect on their children’s development, then we would expect children of the same family (who are presumably exposed to the same parenting behaviour) to be similar to each other for reasons other than genetic relatedness.

However, the “presumably” of the previous sentence is in fact a very tenuous one, because evidence indicates that parents often treat their different children in very different ways.[46] So the presence of a significant effect of parenting behaviour would not necessarily function to make siblings within the same household more similar to each other. As such, evidence from twin studies indicating that the shared family environment explain a negligible portion of the individual variation in many important traits should not be taken as evidence that parents don’t matter.

Moreover, when it comes to adoption studies, there is evidence that environmental factors linked to the family have an important impact on development. For instance, Wicks et al. (2010) found that children adopted into families that had higher socio-economic status (SES) were at less risk of later developing schizophrenia compared to children adopted into low SES families. Wicks et al. (2010) also found that the effect of adoptive family SES was greatest for children who had a schizophrenic biological parent – in other words, the increase in risk faced by children adopted into low (vs. high) SES families was particularly great for children who had a biological parent with schizophrenia. This is an example of gene-environment interaction, which refers to the process whereby the effect of an environmental variable (in this case family SES) on a dependent variable (child risk of schizophrenia) depends on a genetic variable (child’s genetic disposition to experience schizophrenia, as indexed by status of biological parent). The key point, however, is that Wicks et al.’s (2010) data clearly showed that the characteristics of the adoptive environment were important for children’s later development. Likewise, Duyme et al. (1999) found that children adopted into high SES families grew to have higher IQs relative to children adopted into low SES families.

Further evidence for the importance of the family environment in development comes from a range of randomised control trials examining the impact of interventions aimed at improving parents’ interactions with their children. One study of which I am particularly fond randomly assigned parents to either watch several episodes of the parenting show “families” (which depicts the implementation of desirable parenting practices) or to a “waiting list” control condition.[47] Children of the parents in the “families” condition exhibited a significant decline in behavioural problems, indicating that the parenting practices taught by the television series had a beneficial impact on the children. A wide range of other parenting interventions have also been shown to have beneficial consequences for the children involved.[48] There is therefore good evidence that the ways in which parents interact with their children can have important effects of the way those children develop.

It’s worth mentioning the work of Michael Rutter at this point. Rutter is among many researchers analysing data from samples of Romanian adoptees who were adopted shortly after the fall of the tyrannical (and Western-backed) Ceausescu regime in 1989. As infants, these children were raised in orphanages under conditions of horrific deprivation: numerous babies were placed in single cots with no access to toys and rare attention from adults. Malnourishment was common and in some instances there may have been as many as 50 or 60 children per adult caregiver.  Rutter et al. have published several studies over the years comparing UK-born adoptees to people who grew up in these Romanian orphanages before being adopted in the UK.

A number of interesting findings have emerged over the years. First, a large improvement in the Romanian group in terms of body weight, head circumference and IQ was observed shortly after adoption in the UK, indicating that part of the effects of early deprivation were amenable to recovery.[49] Secondly, a range of social, cognitive and neurobiological impairments have been found to persist among the Romanian group, who have now entered adulthood.[50] Thirdly, Romanian-born individuals who were adopted before reaching 6 months of age do not differ significantly in their cognitive, emotional or biological profiles from UK-born adoptees, indicating that the detrimental effects of severe early deprivation only persist in the long term if the deprivation lasts for more than 6 months.[51] Fourthly, many of the individuals who spent the longest amount of time (more than 24 months) in the Romanian orphanages have grown into healthy, happy and well-functioning adults, indicating that even severe, prolonged childhood deprivation does not make subsequent developmental problems inevitable. [52]

There are few key points here, particularly from the point of view of an aspiring parent. It’s quite remarkable that the Romanian orphans who were adopted before 6 months displayed no observable long term impairments as a consequence of their severe early deprivation. My wife and I recently read a parenting book written very stern paediatrician, who informed us in no uncertain terms that breast feeding is an absolute must up until 6 months of age (no exceptions!) and that even a single bottle feed would risk irreparably and permanently harming our baby. The fact that 5 months of exposure to the horrific conditions of a Romanian orphanage (which certainly did not come with a readily available supply of breast milk) was not sufficient to generate permanent impairment makes me very sceptical about the paediatrician’s claims.[53]

Of course, there are some caveats that need to be noted in the interpretation of the above findings. The Romanian adoptees were compared to UK-born adoptees, so this was not a randomised control experiment. That is, children were not randomly assigned to either experience or to not experience severe deprivation before adoption. Rather, their experience of severe deprivation was determined by their pre-existing life circumstances: their country of birth and the circumstances of their parents. This means that there may have been factors that varied systematically between Romanian and UK born adoptees (aside from severe deprivation) that generated or masked differences between them. For instance, the hardships of communist Romania forced many children from “typical” families into orphanages (Beckett et al., 2006), whereas in the UK, adopted children tend to come from families who are particularly disadvantaged (Plomin et al., 2013). The UK-born adoptees, having been born to particularly disadvantaged parents, may therefore have been at greater genetic risk for various developmental problems relative to the Romanian-born adoptees. This could have masked some of the detrimental effects of early deprivation in the Romanian sample, because it would have meant that they were compared with an artificially low standard. As such, the absence of significant developmental differences between UK adoptees and Romanian orphans who were adopted into the UK before 6 months of age does not necessarily permit the inference that early deprivation is developmentally inconsequential when remedied prior to 6 months.

Nevertheless, data from the Romanian adoptees has clearly demonstrated that early deprivation or receipt of inadequate adult care is detrimental to later development. For instance, Almas et al. (2016) found that orphans who were randomly selected to be taken out of their existing childcare institution and placed in the care of a foster family developed higher IQs relative to their peers who remained in institutional care. Because this study randomly selected children to be taken out of foster care, its results permit causal inference with respect to the causal impact of institutional vs. foster care on IQ.

So, all in all, there is pretty good evidence that parenting has at least some causal impact on children’s development. The surprising lack of impairment among Romanian adoptees who were adopted prior to six months of age notwithstanding, this seems to indicate that parenting is not, in fact, futile.

A Non-Linear relationship?

I should note one important fact that is often overlooked in the debate surrounding the importance of parenting practices on child development, namely the fact that much of the hard evidence for the causal influence of parenting comes from studies that have used samples of atypically disadvantaged children.[54] Understandably, researchers tend to be more interested in finding ways to improve outcomes for children growing up in very difficult circumstances rather than children who already have quite bright prospects.[55] Thus, much of the existing research that has employed randomised control trials to assess causal influences on child development has tended to focus on the capacity of a factor or factors of interest to improve outcomes for children in high-risk groups. For instance, there have been plenty of randomised control trials examining interventions aimed at the parents of young people at high risk of behavioural[56] emotional,[57] cognitive[58] and social[59] problems. However, relatively few studies involve interventions designed to improve developmental outcomes for children who are already at relatively low risk.[60]

This raises the possibility that the relationship between parenting quality[61] and child outcomes may be non-linear. It may be that improvements in parenting quality confer benefits to children only up to a point; past this point, the impact of additional improvements in parenting quality may confer diminishing benefits to the child. In other words, having OK parents may be much, much better than having awful parents, but having amazing parents may only be slightly better than having OK parents (see figure 2 for a graphical representation of this statistical relationship). For example, let’s say that parenting quality can be quantified in terms of how frequently a parent reads to their child, and that the quality of a child’s development outcomes can be quantified in terms of their reading ability. It may be that reading to one’s child for 1 hour a week dramatically improves their reading ability relative to 0 hours per week of reading. But reading to them for 2 hours a week may only slightly increase their reading ability relative to 1 hour of reading per week, the benefit of 3 hours of parental reading relative to 2 hours may be even less. For every additional hour of parental reading per week, the benefit in terms of the child’s reading ability may continuously diminish (i.e. there may be diminishing returns to parents’ investment in their children).

 

Figure 2

non_linear

If this was the case, then a literature bias in favour of utilising disadvantaged samples in RCT studies would lead to an overly optimistic impression of the extent to which parents can influence the ways in which their children develop. For instance, if an RCT reveals that, among disadvantaged families, reading to one’s children improves their literacy abilities, we cannot necessarily assume that the result will extrapolate to non-disadvantaged families. In non-disadvantaged families, children are likely to be read to more regularly than in disadvantaged families, even in the absence of any interventions designed to encourage parental reading. As such, according to the above conjecture, the benefit conferred on these children by any further increases in parental reading may be minimal. Their parents may already read to them so frequently that further increases in reading time yield little to no additional benefit. Thus, the magnitude of the effect of parental reading estimated on the basis of studies using disadvantaged samples would not extrapolate to advantaged families.

There is some evidence that this “diminishing returns” principle is indeed applicable to many aspects of child development. For instance, in their review of a wide range of family-based interventions, Engle et al. (2011) concluded that interventions tend to be more effective when directed at the most disadvantaged children. Using samples of twins from high and low socio-economic status families, Turkeimer et al. (2003) found that the family environment has a significant impact on IQ for poorer children, but that variation in IQ across wealthy children is largely attributable to genetic factors. This indicates that improvements in the family environment may be capable of improving IQ in children who are disadvantaged, but that wealthier children tend to already have highly cognitively stimulating home environments, such that further improvements therein would have no impact on their IQ. Furthermore, a number of studies have shown that the relationship between parental wealth and child educational attainment is non-linear, with increases in parental wealth associated with greater increases in child educational attainment at lower regions of the wealth distribution.[62] The same non-linear relationship has been found between parent and child education in developing countries.[63]

Research on Romanian adoptees also appears to support the diminishing returns principle. Adoptees who were taken from the extreme deprivation of Romanian orphanages to well-functioning UK families experienced a drastic improving in cognitive, emotional and physical functioning.[64] However, Beckett et al. (2006) failed to find an effect of adopted parent educational level on any of the developmental outcomes measured for the Romanian adoptees. This suggests that being raised in a typical UK home is much better than being raised in a Romanian orphanage under Ceausescu, but that once you make it into a UK home, you have already reached an upper region of the parenting quality distribution wherein further increases in parenting quality (as indexed by parental education[65]) have minimal impact. In other words, the effect of improvements in a child’s rearing environment may diminish as the rearing environment increases in quality.

Perhaps this provides room for a mid-way position with regard to the importance of parents as causal contributors to development: parenting is not futile, in the sense that abusing or neglecting one’s children will be extremely likely to cause them permanent harm. But once you have already reached the stage of being an adequate parent, then making an effort to further improve your parenting practices may be of minimal benefit to your children.

However, I would not have started this blog if I believed this to be true. Whilst it is almost certainly the case that variation in parenting practices makes more of a difference at the lower end of the parenting quality distribution,[66] this does not mean that parenting becomes inconsequential once you reach the upper portions of the distribution. There are plenty of RCTs showing that improvements in parenting practices can be of benefit to children who are likely to already be receiving high quality parenting.[67]Moreover, parenting is a multifaceted process that comprises many different domains of activity (e.g. discipline, provision of nutritious food, guidance in mastering important cognitive milestones etc.). For many of these domains, there is no evidence that the relationship between parenting practices and child outcomes is non-linear,[68] and there is even evidence that the effects of improvements in care-giving are more pronounced at the upper portions of the caregiving quality distribution.[69]

Furthermore, it is important to note that interventions targeting disadvantaged children have an obvious advantage, which I call the “low-hanging fruit” advantage. For instance, consider the issue of malnutrition, which can be devastating for those that it affects. In a developed country, one generally has to be a pretty awful parent to allow one’s children to suffer from malnutrition (although in some instances parents obviously cannot be blamed for such things). So simply by providing one’s children with a basic level of nutrition, one can avoid the serious issues that would be expected to affect the children of highly neglectful parents. Thus, by moving from “extremely neglectful” to “quite neglectful (but not neglectful enough to induce malnutrition)”, a parent can confer a huge benefit to their child. Better still, a parent might not only try to ensure that their child is not malnourished, but they may even encourage their children to eat healthy foods whilst avoiding unhealthy foods. But this would be more challenging – children generally favour sweet, fatty and unhealthy foods over broccoli and cabbage, and it therefore takes a great deal of effort, commitment and skill on the part of parents to raise a healthy eater. Moreover, the increased parental effort that is required yields a diminished return: the health gap between unhealthy eaters and malnourished eaters is much wider than the gap between unhealthy eaters and healthy eaters.

In other words, avoiding malnutrition can be classified as a goal that is analogous to low-hanging fruit: you have to be a pretty bad parent (or a pretty bad fruit-picker) not to attain it. But you have to be a much more committed parent (or be prepared to climb much higher) to obtain to the high-hanging fruit, namely a child who is a healthy eater. Moreover, the low-hanging fruit are the juiciest – the most serious problem is the one that is easiest and cheapest to prevent. As one ascends the fruit tree, the additional gains afforded by the extra fruit diminish. Of course, anyone who reaches the upper levels of the fruit tree will already have picked the lower-hanging fruit, so it is always better to be higher up. The point remains, however, that the gain achieved by additional ascent reduces as one’s starting height increases.

This is true in many other areas of child-development as well. It’s easy to give your infant some form of pleasant human contact some of the time, but providing highly stimulating and engaging interactions a lot of the time is much more difficult. Meanwhile, the devastating effects of severe social deprivation relative to mere social impoverishment are much greater than the effects of social impoverishment relative to social enrichment. Thus, the low-hanging fruit (providing some social contact) are much juicier than the high-hanging fruit (providing optimal social contact). The same is true of many aspects of parenting.

Children who have highly motivated parents are therefore only likely to have small problems that are very difficult to ameliorate, whereas children with less motivated parents are likely to have more serious problems that are easier to ameliorate. Thus, interventions aimed at children whose parents have been less successful in creating favourable rearing environments can target the low-hanging fruit. They can tackle the easily-resolved-but-serious problems, achieving high gain at relatively low cost. Conversely, an intervention aimed at children raised in more favourable environments will have to target the high-hanging fruit. These children’s parents are likely to have solved most of the serious, easily-resolved problems that their children face, meaning that any intervention will have to expend relatively more resources resolving relatively less serious problems in order to be of benefit these children. Consequently, interventions targeting disadvantaged children are likely to generate higher effect sizes than interventions targeting non-disadvantaged children.

Whilst this explains why the effectiveness of family interventions varies as a function of social (dis)advantage, it does not mean that the high-hanging fruit are not worth the effort involved in their attainment. They may be more difficult to reach, but they still confer benefits on one’s children. So, as far as I am concerned, trying to improve one’s parenting is worth the effort at all regions of the parenting quality distribution.

 

 

 

 

 

[1] Permit me to present an early qualification to avoid sounding horrendously arrogant from hereon in: when I criticise or praise certain parenting practices, and when I outline my intention to follow parenting practices that I deem to be “awesome”, I do not seek to convey any value judgements about myself or others. My comments about the favourability or lack thereof of certain parenting characteristics refer to the empirically documented impact of the characteristics themselves, not to the parents who possess them. I recognise that many parental characteristics that influence a child’s development are impossible or very difficult for parents to control (e.g. parent socio-economic status; parental divorce; parental death; parental exposure to disease). When it comes to comments about my own plans to provide a favourable rearing environment for Dahlia, I speak of nothing more than intentions. Dahlia is yet to be born and, as such, I have no idea how successful these intentions will be. In short, I don’t mean anything I write to sound judgemental.

[2] Moffitt, 2005

[3] Butterfield, 1996; 2002

[4] Parker, 1983

[5] Furnham & Cheng, 2015

[6] Payne, Whitehurst and Angel, 1994

[7] Not that all forms of right wing ideology involve racism; Duriez and Soenens, 2009

[8] Thornberry, 1996

[9] Parrot, Silk and Conduit, 2003

[10] This phrase assumes far too much functional specificity within the human brain, but I think it sounds nice. Also, half a neuron is a dead neuron.

[11] http://science.howstuffworks.com/innovation/science-questions/10-correlations-that-are-not-causations.htm

[12]  Aside from the fact that the deceptive marketing of ice cream to children to the extreme detriment of their health is, arguably, murder – but that is for another post.

[13] See Mota et al., 2006 for example of something like this

[14] Unless, of course, the environmental alteration that is applied transpires to be unintentionally harmful (e.g. the “higher-quality day-care centres turn out to be not so high quality after all). The risk of such an eventuality must be assessed by an ethics committee – if the risk of any participants being harmed is deemed to be unacceptably high, then the research will be unlikely to receive ethical approval and will therefore be prevented from taking place.

[15] Strictly this is not actually true. All humans are almost entirely genetically identical – 99.9% of the DNA of one human will be identical to that of any other human. When we say that DZ twins share 50% of their DNA, we mean that even if you zoom in to focus only on the 0.1% of sites on the human genome where any two given people can differ, then the two members of a given DZ twin pair will have the identical DNA at 50% of these sites (this is an average – some DZ twin pairs may be more genetically similar; others may be less genetically similar). MZ twins have the same DNA at 100% of these sites (although, as we shall see later, even MZ twins are not totally genetically identical to each other).

[16] Statistical correlation and its application to twin research is a bit too complicated to explain fully in the current post, but for anyone interested see here.

[17] Remember, this means that if we had a magic button that would make everybody’s genes the same, the amount of individual variation in each of the big 5 personality traits would be reduced by 45%.

[18] Vernon, Villani, Vickers and Harris, 2008; Jang, Livesley and Vernon, 1996; Plomin and Caspi, 1990; Johnson, Vernon & Feiler, 2008; Krueger and Johnson, 2008

[19] Vukasovic and Bratko, 2015

[20] Tienari et al., 2003; Wicks, Hjern and Dalman, 2010

[21] Ask,  Torgersen, Seglem and Waaktaar, 2014; Rapee, Schniering and Hudson, 2009

[22] Bergen, Gardner and Kendler, 2007; Haworth et al., 2010; Briley and Tucker-Drob, 2013

[23] Agrawal & Lynskey, 2013

[24] Ball et al., 2008

[25] Silventoinen et al., 2010

[26] McGue and Lykken, 1996

[27] D’Onfrio et al., 1999

[28] Frisell, Pawitan, Langstrom & Lichtenstein, 2012; Rhee and Waldman, 2002

[29] Rice, 2009; McAdams et al.,  2015

[30] Brannigan et al., 2002

[31] O’Conner et al., 1998

[32] Moffitt, 2005

[33] Harris, 1998

[34] Johnson and Newport, 1989

[35] Turkheimer, 2016

[36] Dishion et al., 1999; Bandura, Ross and Ross, 1963

[37] Thomas et al., 2013

[38] Gardner & Steinberg, 2005

[39] Witvliet et al., 2009

[40] Westenberg et al., 2004

[41] Dishion and Tipsord, 2011

[42] Zimmerman, 2003; Kermer and Levy, 2002

[43] Fafchamps & Mo, 2015

[44] Haun et al., 2013

[45] Clarkson et al., 2016; Espelage et al., 2015; Olweus & Limber, 2007

[46] Caspi et al., 2004

[47] Sanders et al., 2000; see also Sanders et al., 2008

[48] Calam et al., 2008; Carta et al., 2013; Guttentag et al., 2014

[49] Rutter et al., 1999

[50] Kennedy et al., 2016

[51] Kumsta et al., 2016

[52] Beckett et al., 2006

[53] FYI, my wife and are planning on breastfeeding, but we are doubtful of all the weird and wonderful claims about its benefits. Based on the available evidence (which, surprisingly, is extremely scarce when it comes to randomised control trials), we think that breastfeeding probably has mild benefits relative to bottle feeding. I’ll discuss this more in a later post.

[54] Diamond & Lee, 2011

[55] Sheldon & King, 2001

[56] Hutchings et al., 2007

[57] Perry, 2014

[58] Keen et al., 2010

[59] Cates et al., 2016

[60] Diamond & Lee, 2011

[61] By parenting quality, I mean an aggregate of all the parenting variables that impact children in ways that are generally considered to be important.

[62] Karagiannaki, 2012

[63] Blunch, 2012

[64] Rutter et al., 1999; Beckett et al., 2006

[65] I’m assuming that more educated parents are generally “better” parents in the sense that they provide a more developmentally beneficial rearing environment; this is a fair assumption to make (Lundberg et al., 2014).

[66] Engle et al., 2011

[67] Lakes et al., 2004; Morawska & Sander, 2009

[68] Beijersbergen et al., 2012

[69] Finch et al., 2015

 

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What’s it all about?

What’s it all about?

Simply put, this The Chronicles of Dahlia is about the life and development of my unborn daughter Dhalia, who is currently an 8.5 month old foetus residing in the obliging womb of my dear wife.

But by means of introduction, I think it is useful to tell a story that demonstrates very well what The Chronicles of Dahlia is not about.

The story begins at an ante-natal class at the Royal Free Hospital, London. My 8-month-pregnant wife and I joined a large group of other 8-month-pregnant people and their partners to learn about how not to ruin our imminently arriving babies. In the middle of the class, the midwife asked a question about sleeping positions: “what do people [i.e. you bunch of pregnant women et al.] think are the most important things to consider when putting baby to sleep?”

The room fell awkwardly silent. Presumably, most people try to quietly blend into their background in these sort of situations, hoping not to be called upon to provide an answer. Also presumably, a minority of people try to subtly draw attention to themselves, hoping for the opportunity to display their knowledge without seeming to care about displaying their knowledge. In this case, however, there was someone whose eagerness to voice her fascinating opinions took priority over standard question-answering etiquette.

“I just think-”, she burst out, drawing the eyes of her relieved classmates “-that the most important thing is for people to do what they feel comfortable with. If you feel like the best thing for your baby is to have him next to your bed, or to swaddle, or to have him in a different room, then that’s what you should do. I really feel that it’s so important for mummies and daddies to find their own style and their own way of doing things, and just do whatever feels right to you.”

She managed to keep talking for a good few minutes without communicating much more than the above. I don’t remember the exact wording, but it could be summarised as “good parenting = parenting based on intuitive parental judgement”.

As I hope to demonstrate in forthcoming posts, an apt metaphor for this statement would be a tiny granule of truth buried amidst a steaming heap of garbage. The tiny granule corresponds to the fact that yes, parents’ sense of childrearing autonomy is important[1] and that parental intuitions about what is best for baby may sometimes be a reliable (or at least better-than-nothing)[2] source of information. The steaming heap of garbage corresponds to the fact that there are often far more reliable sources of information about the likely effects of parenting behaviours on children than parental intuition. Parents often make intuitive judgements that are demonstrably false and that, if acted upon, would cause harm to their child. If a parent “feels” that their child would benefit from being denied vaccination or passed through fire in honour of the god Molech, then their feelings should be ignored. Stating that respect for parental comfort in decision making outweighs all other considerations is therefore nonsensical, at least if we assume any parental responsibility to cultivate the health and happiness of their children.

Apparently, the midwife at Royal Free’s ante-natal class disagreed. She saw a tiny granule of truth surrounded by millions of other grains of truth in a veritable heap of truth-gems, glistening beneath a glorious, truth-filled sun powered by the fusion of truth atoms at 111 Truth Street, Truthville, Truthistan, TRU 7H. I exaggerate – but she did ask the “I love parental intuition” lady to stand in front of everyone and repeat what she had already needlessly taken 5 minutes to say.

Fortunately, the midwife then completely contradicted the ILPI lady by describing a number of strict, empirically informed rules relating to baby sleep practices. There was a little room for parental judgement, but some practices were categorically (and correctly) defined as unsafe and unacceptable, regardless of whether they “feel right”.

This captivating tale reveals a tendency that exists among many parents, namely the tendency to rely on intuition and gut feeling above all else, often to the detriment of their children[3]. Across the forums of mumsnet and the communities of baby center; in the playground, in parent support groups and ante-natal classes; in parental advice websites masquerading as respectable institutions whilst peddling pseudoscience and claptrap, the disturbing ideology abounds: trust your gut and nothing else.

In later posts, I’m going to discuss at length the various problems associated with this perspective. But for now, suffice to say that it constitutes the near anti-thesis[4] of what The Chronicles of Dahlia is about. The aim of TCOD is to emphasise the role of science in informing parenting decisions. To be sure, there are websites that already do this[5], probably with much greater comprehensiveness and clarity than I will be able to achieve here. TCOD will (hopefully) be unique, however, in seeking to show empirically informed parenting principles in action over the course of the development of a real, genuine human.

The primary intended purpose of TCOD is to document the attempts of my wife and I to raise our child in the manner that, based on the available evidence and given various practical constraints, will be most beneficial to her. I aim to justify our parenting decisions and to elaborate on the research underlying them.

Note that the first sentence of the above paragraph is worded with a number of caveats. We will attempt to raise Dahlia in the manner dictated by evidence as most conducive to her wellbeing; this is an extremely difficult task, and we may not succeed – but we will try. Our parenting decisions will be based on the available evidence. I will discuss in later posts what exactly I mean by “evidence” (mainly, but not exclusively, data published in peer-reviewed journals). By “available” I do not mean evidence that is technically accessible; I mean evidence that is accessible to my wife and I and that we have the mental capacity and time resources to comprehend and evaluate. And I will set out in later posts what I mean by Dahlia’s “wellbeing”. “Practical constraints” refer to practical factors that may preclude the course of parenting action that is most beneficial to our daughter – it would be great to send her to the most awesome school in the world, for instance, but financial considerations may not be permitting.

Finally, the above is the primary purpose of TCOD, but not the sole purpose. Hopefully, it will be interesting and/or informative for some of the myriads of people on the internet.

So there you go – that’s basically what TCOD is. I might occasionally stray from this theme to write about general issues of relevance to parents or people involved with childcare in some way.

 

 

[1] A sense of autonomy and control over one’s life is central to personal wellbeing, and parental wellbeing is central to the parent-baby bond (O’Donnell et al., 2013; Parfitt et al., 2013).

[2] Intuition is generally a more helpful than harmful guide to accurate judgement (Dane & Pratt, 2007; Dunn et al., 2010). Some maternal and paternal instincts have evolutionary roots, having been genetically transmitted across generations by virtue of their capacity to enhance the likelihood of the child’s successful development (Feldman, 2015). This being the case, we can infer that a parent acting on instinct would be more likely to raise a healthy, happy child than a parent making random parenting decisions.

[3] For instance, parents who rely more on their intuition are less likely to vaccinate (Anderson, 2016).

[4] I say near antithesis in recognition of that tiny little truth granule beneath the steaming heap of garbage.

[5] The best such blog of which I am aware is parentingscience.com

 

 

 

References

Anderson, D. A. (2016). Analytic Thinking Predicts Vaccine Endorsement: Linking Cognitive Style and Affective Orientation Toward Childhood Vaccination.

Dane, E., & Pratt, M. G. (2007). Exploring intuition and its role in managerial decision making. Academy of management review32(1), 33-54.

Dunn, B. D., Galton, H. C., Morgan, R., Evans, D., Oliver, C., Meyer, M., … & Dalgleish, T. (2010). Listening to your heart how interoception shapes emotion experience and intuitive decision making. Psychological science.

Feldman, R. (2015). The adaptive human parental brain: implications for children’s social development. Trends in Neurosciences38(6), 387-399.

O’Donnell, S., Chang, K., & Miller, K. (2013). Relations among autonomy, attribution style, and happiness in college students. College Student Journal47(1), 228-234

Parfitt, Y., Pike, A., & Ayers, S. (2013). The impact of parents’ mental health on parent–baby interaction: A prospective study. Infant Behavior and Development36(4), 599-608.